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Journal of Management Policy and Practice

North American Business Press Atlanta – Seattle – South Florida - Toronto

Journal of Management Policy and Practice

Editor Dr. Daniel Goldsmith

Founding Editor

Dr. William Johnson

Editor-In-Chief Dr. David Smith

NABP EDITORIAL ADVISORY BOARD

Dr. Andy Bertsch - MINOT STATE UNIVERSITY Dr. Jacob Bikker - UTRECHT UNIVERSITY, NETHERLANDS Dr. Bill Bommer - CALIFORNIA STATE UNIVERSITY, FRESNO Dr. Michael Bond - UNIVERSITY OF ARIZONA Dr. Charles Butler - COLORADO STATE UNIVERSITY Dr. Jon Carrick - STETSON UNIVERSITY Dr. Mondher Cherif - REIMS, FRANCE Dr. Daniel Condon - DOMINICAN UNIVERSITY, CHICAGO Dr. Bahram Dadgostar - LAKEHEAD UNIVERSITY, CANADA Dr. Deborah Erdos-Knapp - KENT STATE UNIVERSITY Dr. Bruce Forster - UNIVERSITY OF NEBRASKA, KEARNEY Dr. Nancy Furlow - MARYMOUNT UNIVERSITY Dr. Mark Gershon - TEMPLE UNIVERSITY Dr. Philippe Gregoire - UNIVERSITY OF LAVAL, CANADA Dr. Donald Grunewald - IONA COLLEGE Dr. Samanthala Hettihewa - UNIVERSITY OF BALLARAT, AUSTRALIA Dr. Russell Kashian - UNIVERSITY OF WISCONSIN, WHITEWATER Dr. Jeffrey Kennedy - PALM BEACH ATLANTIC UNIVERSITY Dr. Jerry Knutson - AG EDWARDS Dr. Dean Koutramanis - UNIVERSITY OF TAMPA Dr. Malek Lashgari - UNIVERSITY OF HARTFORD Dr. Priscilla Liang - CALIFORNIA STATE UNIVERSITY, CHANNEL ISLANDS Dr. Tony Matias - MATIAS AND ASSOCIATES Dr. Patti Meglich - UNIVERSITY OF NEBRASKA, OMAHA Dr. Robert Metts - UNIVERSITY OF NEVADA, RENO Dr. Adil Mouhammed - UNIVERSITY OF ILLINOIS, SPRINGFIELD Dr. Roy Pearson - COLLEGE OF WILLIAM AND MARY Dr. Sergiy Rakhmayil - RYERSON UNIVERSITY, CANADA Dr. Robert Scherer - CLEVELAND STATE UNIVERSITY Dr. Ira Sohn - MONTCLAIR STATE UNIVERSITY Dr. Reginal Sheppard - UNIVERSITY OF NEW BRUNSWICK, CANADA Dr. Carlos Spaht - LOUISIANA STATE UNIVERSITY, SHREVEPORT Dr. Walter Amedzro ST-Hilaire - HEC, MONTREAL, CANADA Dr. Ken Thorpe - EMORY UNIVERSITY Dr. Robert Tian - MEDIALLE COLLEGE Dr. Calin Valsan - BISHOP'S UNIVERSITY, CANADA Dr. Anne Walsh - LA SALLE UNIVERSITY Dr. Thomas Verney - SHIPPENSBURG STATE UNIVERSITY Dr. Christopher Wright - UNIVERSITY OF ADELAIDE, AUSTRALIA

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This Issue Trade, the Environment, and Impacts on State Agricultural Exports ................................................ 11 David Karemera, Won Koo, Louis Whitesides International trade theory predicts that the relative level of a country’s resource endowments, trade policy, environmental regulations, and level of technology would jointly determine production specialization and trade pattern of the country. This study develops state export share and alternative environmental risk models to evaluate the effects of resource endowments, prices, and environmental risk factors on agricultural exports and environment. A simultaneous system of the environmental risk and export share models was estimated by using the nonlinear estimation method outlined in RATS (2009). The results reveal that crop prices, state GDP, state farm GDP and technological changes were found to be major determinants of the state export shares. The results also suggest that NAFTA had no negative effect on the environment. The study found that the European Union (EU) and expansion of its membership led to significant reduction in state agricultural exports due mainly to the effect of trade diversion in the EU expansion. The Impact of Physician Job Satisfaction on the Sustained Competitive Advantage of Health Care Organizations ............................................................................................... 21 Olena Mazurenko, Stephen J O’Connor This paper employs the resource-based theory of the firm to explain the influence of human resources on the sustained competitive advantage of an organization. Based on previous conceptual and empirical literature, we posit that the presence of a high potential employee workforce, coupled with adequate human resource management policies, can result in improved profit generating potential. We developed a conceptual framework with several propositions that illustrate the associations between job satisfaction and organizational productivity. We apply this concept in the health care field, suggesting that the satisfaction of physicians’ needs leads to greater organizational productivity and sustained competitive advantage. Union Participation: A Social Exchange Perspective ............................................................................ 35 Ray Gibney, Marick F. Masters, Thomas J. Zagenczyk, Thomas Amlie, Stephen Brady We introduce the concept of perceived union obstruction (PUO), which expands the union-member social exchange relationship literature to include negative relationships. In addition, we assess cross foci-target perceptions and behaviors by testing hypotheses regarding the effects of perceived treatment by the organization and union on commitment to the union and participation in union activities. Hypotheses are tested using a sample of 168 public sector union members. Regression results provided mixed results for hypotheses. Generally, negative exchange relationships had a greater impact on attitudes and behaviors. Implications for theory and practice are discussed. The Impact of Exit Decisions on Successful R&D Alliances ................................................................. 50 David Epstein, Robert T. Keller In this paper, we focus on the impact of exit decisions on successful R&D alliances. Specifically, we investigate how product exit choices influence the firm’s entry into successful strategic alliances. This longitudinal study examines 10 years of product development in the pharmaceutical industry over a sample of 87 firms. Our findings reveal that firms exiting declining research fields are more likely to form successful R&D alliances than firms expanding into these declining fields.

Concentration and Consolidation as Determinants of External Competitiveness of Enterprises in Food Industry .................................................................................. 61 Grażyna Michalczuk, Urszula Widelska The aim of this paper is to present the level of concentration and consolidation processes in the food industry in Podlaskie Voivodship as a determinant of external competitiveness. The analysis was conducted on the basis of the results of research carried out within the analysis of key sectors of Podlaskie Voivodship. The external competitiveness is related to the adjustment of an enterprise to changes in the environment, taking into consideration cooperation conditions and becoming open to external markets in particular. A Post-Mortem on Long-Term Projections of Global Food Requirements ........................................ 67 Ira Sohn World population grew from 3.7bn in 1970 to almost 7bn in 2010 and, by 2050, is projected to increase to over 9bn. Because of growing scarcities of essential agricultural inputs, which can take decades to mobilize in sufficient quantities, long-term projections of global food requirements are critical if the “ghost of Malthus” is to be kept at bay. This paper examines long-term, i.e. 30-year, global production and consumption projections of four major agricultural sectors. These projections, whose terminal year was 2000, are then assessed against observed data from the UN’s Food and Agriculture Organization’s Food Balance Sheets. Risk and Precautionary Approaches to Climate Change: Conceptual and Empirical Lessons from the Insurance Industry...................................................................................................... 88 Patrick G. Welle The concept of option value provides insight in weighing the countervailing risks of doing “Too Much Too Soon” or “Too Little Too Late” in addressing climate change. Option value represents profit potential to the insurance industry when it is positive, which occurs if people’s willingness to pay exceeds expected actuarial losses. Climate change could increase both the mean and the variability of actuarial losses. This paper reviews literature relating climate change to the insurance industry and summarizes empirical estimates of damage payments by private insurers. Public data on long-term trends in weather-related disaster and emergency relief payments are cited. A Study of Original Equipment Manufacturing in China: Current and Future Trends ................................................................................................................... 102 Min Z. Carter, Hank Findley This study examines issues faced by Chinese original equipment manufacturing firms (OEMs) and explores OEM future development. Qualitative data, consisting of responses from 32 managers in 16 OEMs, were content analyzed. Results reveal various threats to OEM development and numerous opportunities that have yet to be fully explored by OEMs, as well as OEMs strengths and strategic and managerial challenges. Further, this study interprets the future OEM trends, particularly the shift from an OEM business model to the original design manufacturer (ODM) and original brand manufacturer (OBM) models, as well as, the development of long-term relationships with their clients.

Enotourism as a Form of Activating Rural Areas (On the Basis of the Province of Podkarpackie) ................................................................................... 117 Wiesława Kuźniar This study encompasses selected issues connected with the development of wine tourism in the province of Podkarpackie. Its development is based on wine production which has been of greater and greater importance in Poland. Wine tourism defined as enotourism provides the opportunities of local development, especially for the areas of natural predispositions to wine making. The example of such a region is the province of Podkarpackie, which has been playing a significant role in the revival of Polish contemporary wine making. In recent years, many initiatives been observed, including marketing ones, stimulating development of enotourism in the studied region. En Route to a Typology of the Female Entrepreneur? Similarities and Differences Among Self-Employed Women .............................................................................................................. 121 Paul J. Davis, Fatima Abdiyeva This paper explores the extent to which women entrepreneurs and their businesses share a set of common characteristics and/or experiences internationally and introduces new research on women entrepreneurs in Kazakhstan. It finds that while women entrepreneurs around the world share many common characteristics, there exist sufficient exceptions or insufficient evidence to validate any unifying typology. Further, that the experiences of women entrepreneurs and the women themselves are not homogenous and that formulation of a typology would be simplistic and, in itself, sexist. The Kazakhstani research introduced suggests the experience of women entrepreneurs there is similar to that of women entrepreneurs in many other countries.

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Trade, the Environment, and Impacts on State Agricultural Exports

David Karemera South Carolina State University

Won Koo

North Dakota State University

Louis Whitesides South Carolina State University

International trade theory predicts that the relative level of a country’s resource endowments, trade policy, environmental regulations, and level of technology would jointly determine production specialization and trade pattern of the country. This study develops state export share and alternative environmental risk models to evaluate the effects of resource endowments, prices, and environmental risk factors on agricultural exports and environment. A simultaneous system of the environmental risk and export share models was estimated by using the nonlinear estimation method outlined in RATS (2009). The results reveal that crop prices, state GDP, state farm GDP and technological changes were found to be major determinants of the state export shares. The results also suggest that NAFTA had no negative effect on the environment. The study found that the European Union (EU) and expansion of its membership led to significant reduction in state agricultural exports due mainly to the effect of trade diversion in the EU expansion. INTRODUCTION

The impact of environmental policy on international trade continues to generate a great deal of attention among both academicians and policy makers. The relationship between trade and environmental standards is increasingly a hotly debated issue. Environmental concerns are routinely brought to the negotiation table during free trade negotiations.

The main concern of the environmental group is that any free trade agreement reduces tariff and/or non-tariff trade barriers among member countries and increases environmental risk through overuse off fertilizers and chemicals to maximize productivity.

For example, under the North American Free Trade Agreement (NAFTA), tariffs and non-tariff barriers were gradually eliminated on goods traded among the United States, Canada and Mexico which resulted in increases in trade volume among these countries through trade creation and diversion effects. The increases in tradeflows are due to increased productivity through production specialization and the substantial use of production resources. Natural resources could be overused and/or depleted, leading to environmental quality degradation. On the other hand, the trade advocacy group supporting free trade claims that open trade would lead to innovation in technology that is environmentally friendly and could

Journal of Management Policy and Practice vol. 13(4) 2012 11

increase productivity. However, enforcing abatement technology to meet environmental standards may impute costs to producers and result in comparative disadvantage to the producers and exporters. This study examined the relationship between trade and environmental factors and analyzed the environmental consequences of free trade. The study used selected environmental factors and analyzed the impact of free trade agreements, such as NAFTA, on the environment and identified the effects of the environmental factors on state agricultural production and exports.

Previous studies on the subject have addressed trade and environmental issues through use of aggregate data in general good trade (Harrigan, 1997; Baek & Koo, 2009) or semi aggregate data in agricultural trade (Managi & Karemera, 2005). The impact of state productivity was discussed in previous studies by Ball, Gollup, Kelly-Hawke, and Swinland (1999), Ball, Butault and Nehring, (2001), and Caves, Christensen and Diewert (1982a, 1982b). The current study expanded previous literature by increasing the period of study and introducing specific environmental factors. A system of structural equations was specified and estimated for this study. Furthermore, technical advances in agricultural as well as efficiency changes arising from agricultural production and trade activities were derived and incorporated into the model. Thus, it was hypothesized that technologies, prices, and factor endowments, including environmental factors, are significant determinants of agricultural exports.

Environmental factors considered in this study represented the level of pollution and degradation from pesticides and chemicals used to increase agricultural productivity. Published indexes of ground water pollution in agricultural farm land and levels of CO2 were used to estimate the environmental damage model. This study addressed the risk to human health and fish life from chemical and pesticide runoffs and leaching. The study examined whether NAFTA is good or bad for state agricultural trade and environment. The impact of another major free trade agreement such as the European Union (EU) on state agricultural trade was also evaluated within the framework of international trade (Leamer & Levinsohn, 1995). The findings will contribute to the wealth of literature on environmental and trade policy study and could be an instrument of trade negotiators and policy makers in trading countries.

A system of structural and reduced form equations of agricultural export shares and environmental risk models were specified following Harrigan (1997) and Antweiler and Trefler (2001). The system was estimated by a nonlinear system estimation method outlined in Regression Analysis of Time Series, commonly known as RATS (2009). METHODOLOGY

This study used state-level data to examine the relationship between trade and environment, mainly the impact of trade openness on state environmental quality. The model developed for this study was based on the framework developed by Antweiler and Trefler (2001) to account for environmental performance under NAFTA and EU (Grossman & Krueger, 1993) and applied the methodology of Harrigan (1997) to examine the relationships between trade and environmental standards. Harrigan specified the export shares as a function of factor endowments including environmental stringency and technology. Van Beers and Van den Bergh (1997) suggested that environmental regulations influence trade patterns. This study estimated the impact of endowment and factor supplies, prices, and environmental risk factors on exports and the impact of free trade on environmental risk factors in Harrigan’s (1997) framework. Based on the previous studies, we specified two models: export share model and environmental model based on environmental risk factors. Development of the Export Share Models

The export share model was specified on the basis of the modified Heckscher-Ohlin and Ricardian model (Harrigan, 1997). Consider the small open economy model characterized by fixed factor supplies, constant returns to scale (CRS), and perfect competition. The general equilibrium of this economy is to maximize the value of final output. A common formulation of this maximization problem was given by

12 Journal of Management Policy and Practice vol. 13(4) 2012

( , , )( ), , ,

=

∈ ∈ ∈

r p v p yy v p y vn m

Maxsubject to Y

θ θ

R R (1)

where r (p, v, and θ) is the revenue function, y is the final good vector, p is the vector of final goods price, Y (v) is convex production set for endowments v, and θ is the level of productivity relative to some base periods. The gradient of r(p, v, θ) with respect to p yields the vector of net output supplies y(p, v, θ) as long as the revenue function r(p, v, θ) is twice continuously differentiable, which requires smooth substitutability among factors and at least as many factors as goods (m≥ n). Following Harrigan (1997) and Redding and Vera-Martin (2001), we specified the export share equation based on equation 1, as a function of output prices, variables representing natural resource endowments, technical progress (TC) and efficiency change (EC) as follows;

sjt = f(pit, vit, tcit, ecit eit) (2) where i is an index for individual state and t is an index for time, p and v represents vectors of output prices and resource endowments, respectively. TC and EC represent technical progress and efficiency changes, respectively. The term e is an independently and identically distributed error term. An empirical export model for individual states should include additional economic variables affecting exports directly or indirectly. The variables are state per capita GDP (PGDP) to represent income level in the state, agricultural GDP to represent total agricultural production in the state, and regional free trade agreements such as NAFTA and EU. Thus, equation 2 in state i and time t is re-specified under a double-log functional form as;

InSit = β0 + β1lnPit + β2lnFGDPit + β3lnPGDPit + β4NAFTAt + β5EUt + β6PIit + β7ECit + β8TCit + lneit, (3)

where Sit represents the share of state i’s agricultural export to its GDP in time t, Pit represents average export price, FGDP represents state farm income representing production and export capacity of the state, PGDP is per capita GDP, representing personal income and living standard in state i, NAFTA and EU are dummy variables representing the North American Free Trade Agreement and European Union, respectively; PI represents pollution index in each state, EC represents changes in production efficiency and TC denotes technical progress in crop production.

It was hypothesized that increased farm exports come from increased domestic production and may possibly have affected environmental policy to control pollution intensity. Prices of agricultural commodities were expected to be positively related to export share since increases in commodity prices stimulate agricultural production. It was assumed that state PGDP is negatively related to export share mainly because an increase in personal income tends to increase domestic consumption and adversely affect export. Technical changes and efficiency changes were used to present the impact of productivity on trade and were expected to have positive impact on export share. Environmental Damage Model

It is important to notice the relationship between export share and variables representing pollution. Regulations on pollution affect production and consequently export. On the other hand, export share also affects the level of pollution in a state. To investigate how does export promotion under globalization affect environmental degradation in each state, this study used state ground water pollution from chemical and pesticide contents and air pollution as measured by CO2 and SO2 levels. The impact on risk to human health and fish life of chemical and pesticide runoffs and leaching, as indicated by respective indexes, was assessed. Harris, Konya, and Matyas (2002) analyzed the environmental consequences of free trade. Antweiler et al., (2001) used a general equilibrium framework of world trade to determine how


elimination of trade barriers affect pollution levels in trading countries. They assumed that pollution is proportional to output and derived a pollution emission model as follows:

1 2 3 4 5

6 7 8 9 10

ln ln ln ln ln lnln ln ln

kt kt kt kt kt ekt

kt kt kt z k t t kt

Z S r mw I s D D

α α κ α α α θ

α α α α α ε

= + + + +

+ + + + + +∑ ∑ (4)

where Z represents an index of pollution level, S is industry scale, k is capital/labor, r is land/labor, m is intermediate input/labor, w is water/pesticide pollution abatement expenditure as a proxy for pollution abatement effort, I represents income, s is trade intensity defined by (export + import)/GDP, Dk and Dt are dummy variables for state k and year t, respectively. This study used capital/labor, intermediate input/labor and land/labor as factor abundance1. All other variables have been previously defined. Formal mathematical derivations are explained by Antweiler et al., (2001), and Ball et al., (2001) with additional applications available in Managi and Karemera (2005).

It was assumed that the amount of pollution increased with expanded economic activity if the nature of the economic activity remained unchanged. Grossman and Krueger (1993), Copeland and Taylor (1994, 1995), and Antweiler et al., (2001) proposed the decomposition of trade’s effect into scale, composition, and technique effects that have been useful for the study of trade and environment (Färe et al., 1994). The scale effect explained the negative environmental consequences of scalar in economic activity. The composition effect explained how trade-induced changes in the composition of output affect pollution concentrations. Trade liberalization will lead countries to shift resources into the sectors that make intensive use of its abundant factors. The technique effect explained the positive environmental consequences of increases in income that call for cleaner production methods.

Antweiler et al., (2001) employed GDP as a proxy for technique effect since rising incomes were associated with cleaner production methods and brought about positive environmental outputs. Thus, real income gain indirectly created the technique effect. Technical impact was composed of three effects: environmental effect, eθ , pollution abatement effort, w , and income effects, I. Antweiler et al., (2001) used trade intensity to represent degree of globalization. However, this study used export share, s, as a proxy for trade openness2 since import data was not available for each state. In addition, the trade intensity variable only captured the partial effects of trade liberalization or trade openness on environmental outputs. This was because decreases in trade restrictions alter the scale of output, composition, and income per capita.

Agricultural exports played an important role in U.S. trade, providing 18% of all 2006 total income from exports (USDA, 2008; Council of Economic Advisers, 2003). Pesticides and chemicals are widely used in the agricultural sector and contribute to agricultural production. Pesticides and chemicals, however, pose potential risk to human health and the environment. The risks include contaminated surface water and groundwater through pesticide runoff and leaching. Furthermore, pesticides affect the quality of water available for public use, consumption of drinking water, and water use for recreational purposes. In addition, chemical use affects the CO2 and SO2 concentration in the environment. Chemicals also affect human and fish life through chemical and pesticide runoffs and leaching in addition to abatement costs (Paul et al., 2002). Thus, this study assessed the impact of risk to human health and fish life as indicated by the respective indexes. If environmental regulations are effective, environmental damage or risks decrease consequently. Ground water pollution index (GWP), including the index of risk to human health from exposure to pesticide runoff (HFR) or the index of risk to human health from exposure to pesticide leaching (HFL), and indexes of threats to fish life from runoffs (FFR) and leaching (FFL)3 were included in the impact analysis. In addition, the amount of ccarbon dioxide (CO2) and sulfate dioxide (SO2) were used as indications of air pollution and environmental damage. Consequently, the environmental pollution model was specified as:


PIit = β0 + β1 lnSit + β2lnFGDPit + β3lnPGDPit + β4OAit + β5CAit + β6NAFTAt + β7EUt + β8Pit + lnUit, (5)

where PI represents pollution level in each of the categories mentioned above, and OA and CA represent operational and capital abatement, respectively. Other variables were defined previously.

The system of equations (3) and (5) was estimated by using a nonlinear estimation method provided in RATS (2009). The system is a simultaneous system representing the export share model and pollution models with the implied assumption of cross correlations through error terms. Additionally, to further address the issues of endogeneity of pollution indicators we estimated two-equation systems of the export share model and each of the pollution models by using the same nonlinear estimation method. EMPIRICAL RESULTS

Data on export share were collected from the Economic Research Service (ERS) of the United States and from the Department of Agriculture in various issues. Export values for each state by commodity were based primarily on a state’s share of production of the exported commodities. Export share is a ratio of value of total state export to total state farm cash receipts. All environmental pollution indices were collected from Kellogg et al., (2000).

Environmental risks are constructed from exposure to pesticide runoff into surface water and pesticide leaching into groundwater (Kellogg et al., 2000). The assessment of risk was based on the extent to which the concentration of a specific pesticide out of approximately 200 pesticides exceeding a water quality threshold. The variable, HFR was defined as a risk to human health from exposure to pesticide runoff; the variable HFL was defined as a risk to human health from exposure to pesticide leaching; while the variables FFR and FFL were defined as a risk to fish life from exposure to pesticide runoff and leaching respectively. The data were obtained from Kellogg et al., (2000). Additional data collected by the authors included amount of pesticides/chemicals in ground water and air CO2 and SO2 as indications of air quality.

The data on prices, farm GDP and PGDP were available in various publications of ERS and state websites. The environmental data set, including data for FFL, FFR HHL and HHR, was available from 1973 to 1996, while data for export shares, CO2, pesticide and financial variables were available to 2004.

Table 1 presents estimated coefficients of the simultaneous system of export share and alternative pollution equations, while table 2 presents estimated coefficients of export share equation and each of the alternative pollution models. The estimated parameters appeared to be stable, indicating that overall fit of the models was good. In the estimated models, most coefficients were significantly different from zero and have right sign on the basis of economic theory. The results from the two different estimations presented in Tables 1 and 2 were similar. Thus, we mainly used the results presented in table 1 for analysis of the estimated results and interpretation/implications. Export, Agricultural GDP and GDP Impacts on Pollution

Special attention was paid to separate the effects of the farm GDP and the PGDP on pollution measures. The findings suggested that the effect of the farm GDP was positive and significant at the 1.0% level, implying that pollution, as expressed by the included pollution indicators, increased with augmented agricultural production (table 1). However, the results seem to suggest that in increases in personal income (PDGP) are associated with reduction in environmental pollution as expressed by environmental risk factors. The finding is consistent with traditional view that increases in the level of development lead to clear environment. The estimated coefficients can be interpreted as elasticity since the models were estimated in a double-log functional form. The elasticities were, in absolute values, less than 1.00 for farm income, implying that pollution is not sensitive to changes in agricultural production (PGDP) in most cases. The results show that increases in export shares leads to increased pollution associated with chemical leaching into ground water threatening fish life, but reduces chemical runoff threatening human life and carbon level.


Environmental Risk Factors and Economic Variables Impacts on Agricultural Exports Economic factors were included in the export share model to examine the state’s production and

export capacity on its export. The economic factors were statistically significant at the 5% level with positive signs, clearly indicating a strong impact on the export share. Increases in farm GDP and higher crop prices were clearly associated with higher levels of export shares. Total factor productivity and efficiency change were significant at the 5% level and had positive sign, indicating that efficiency improvements in the U.S. agricultural sector have spurred agricultural exports. Increases in crop prices were associated with increased export share as producers responded positively to higher export prices.

The environmental impact on exports is factor-specific. Most environmental variables are significant at the 5% level in the export equation. The impact of regulating pollution on exports varies by type of pollution. The results suggested that CO2, FFR, HFR and HFL weree statistically significant and positively associated with the state export share, while FFL was significant but negatively associated with the export share. This finding, in general, supported the hypothesis that regulating pollution leads to an increase in production costs and consequently causes a comparative disadvantage in exporting agricultural commodities. This result was consistent with previous studies (Pethig, 1976; McGuire, 1982; Baumol & Oates, 1988; Carraro & Siniscalco, 1992; Copeland & Taylor, 2003). States may lose a comparative advantage from significant amounts of costs incurred to state agricultural producers to conform with environmental regulations and/or to make product/output cost adjustments or resource relocation to meet it. However, most environment risk elasticities were less than 1.0, suggesting that export shares are not sensitive to changes in the environmental risk factors. Both operational and capital abatement were significant at the 5% level and had positive sign, indicating that reducing pollution levels was positively associated with export share in each state.

The NAFTA variable was not statistically significant for both export share and pollution equations, indicating that NAFTA has limited impacts on each state agricultural export shares and environment. However, the impacts of the EU on state export shares were strikingly significant for both state export share as well as environment risk equations, mainly FFL and HFL. The EU and expansion of its membership led to significantly reduced US agricultural export shares. This was due mainly to the EU internal agricultural policy and results of significant trade diversion. In general, the impact of the EU on environment was significant and led to reduce FFL and HFL. CONCLUSIONS

The impact of environmental policy on international exports has received a great deal of attention among both academicians and policy makers. A system of export share and environmental risk models were estimated using the nonlinear least squares method described in RATS (2009). Also, a system of export share model and each of the environmental risk models were estimated using the same estimation method. The two methods provided nearly identical results. The results showed that economic variables, environmental factors, and relative prices were major determinants of agricultural export shares.

The estimated results suggested that higher farm GDP led to increased levels of pollution and export in most states in the U.S. Most environmental variables are positively related to state export of agricultural commodities, indicating that regulating pollution causes a comparative disadvantage in exporting agricultural commodities. The expansion of the EU had a negative effect on state export of agricultural commodities due mainly to trade diversion effects of the expansion. The EU diverts its imports from the US to its new member countries. NAFTA was not statistically significant in state export share equation mainly because Mexico and Canada are not major destinations of U.S. agricultural exports. The FTAs do not lead to environmental degradation as measured by the included environmental factors. ENDNOTES

1. Theoretical model in Antweiler et al., (2001) included only capital/labor as factor abundance since there was little reason to believe that other endowment factors had an independent effect on either the demand


for a clean environment or the derived demand for pollution emissions. In the empirical model, Antweiler et al., (2001) included several factors abundance for sensitivity analysis.

2. Aggregated national level of import and summation of import and export trend is similar for 1975-2002. The simple correlation between export and import is 0.97 (Council of Economic Advisers, 2003).

3. Environmental pollution was considered as additional factor components following usual convention in environmental economics of treating pollution emissions as an input to production (i.e., Baumol & Oates, 1988).

REFERENCES Antweiler, W., Trefler, D. (2002). Increasing returns and all that: A view from trade, American Economic Review, 92(1), 93-119. Ball, V.E., Gollop, F.M., Kelly-Hawke, A. & Swinland, G.P. (1999). Patterns of state productivity growth in the U.S. farm sector: Linking state and aggregate models, American Journal of Agricultural Economics, 81(1), 164-79. Ball, V.E., Butault, J-P., & Nehring, R. (2001). U.S. Agriculture, 1960-96: A Multilateral Comparison of Total Factor Productivity. Working Paper, Economic Research Service, US Department of Agriculture, ERS Technical Bulletin No. 1895. Washington, DC. Baumol, W.J., & Oates, W.E. (1988). The Theory of Environmental Policy (2nd ed.), Cambridge: Cambridge University Press. Carraro, C., & Siniscalco, D. (1992). The international dimension of environmental policy. European Economic Review, 36(2-3), 379-87. Caves, D.W., Christensen, L.R., & Diewert, W.E. (1982a). Multilateral comparisons of output, input and productivity using superlative index numbers. Economic Journal, 92(365), 73-86. Caves, D.W., Christensen, L.R., & Diewert, W.E. (1982b). The economic theory of index numbers and the measurement of input, output and productivity. Econometrica, 50(6), 1393-1414. Copeland, B., & Scott, T. (2003). Trade, Growth and the Environment, mimeo. University of British Columbia. Färe, R., Grosskopf, S., & Knox Lovell, C.A. (1985). The Measurement of Efficiency of Production. Boston: Kluwer-Nijhoff. Färe, R., Grosskopf, S., Norris, M., & Zhang, Z. (1994). Productivity growth, technical progress, and efficiency change in industrialized countries. American Economic Review, 84(1), 66–83. Grossman, G.M., & Helpman, E. (1991). Innovation and Growth in the Global Economy. Cambridge, Mass. and London: MIT Press. Grossman, G.M., & Krueger, A.B. (1993). Environmental Impacts of a North American Free Trade Agreement in P. Garber (ed.): The U.S.-Mexico Free Trade Agreement. Cambridge, MA: MIT Press. Harrigan, J. (1997). Technology, factor supplies, and international specialization: Estimating the neoclassical model. American Economic Review, 87(4), 475-94.


Harris, M.N., Konya, L. & Matyas, L. (2002). Modeling the impact of environmental regulations on bilateral trade flows: OECD, 1990-96. World Economy, 25(3), 387-405. Kellogg, R.L., Nehring, R., Grube, A., Goss, D.W., & Plotkin, S. (2000). Environmental Indicators of Pesticide Leaching and Runoff from Farm Fields. Working Paper, Natural Resources Conservation Service, U.S. Department of Agriculture, Washington, DC, USA. Leamer, E.E., & Levinsohn, J. (1995). International Trade Theory: The Evidence. In Gene M. Grossman and Kenneth Rogoff (eds), Handbook of International Economics, Vol. III, 1339-96. Amsterdam: Elsevier. Managi, S., & Karemera, D. (2005). Trade and environmental damage in U.S. agriculture. The World Review of Science, Technology and Sustainable Development, 2(2), 400-425. North Holland. McGuire, M.C. (1982). Regulation, factor rewards, and international trade. Journal of Public Economics, 17(3), 335-354. Paul, C.J.M., Ball,V.E., Felthoven, R.G., Grube, A., & Nehring, R.F. (2002). Effective costs and chemical use in united states agricultural production: Using the environment as a "free" input. American Journal of Agricultural Economics, 84(4), 902-15. Pethig, R. (1976). Pollution, welfare, and environmental policy in the theory of comparative advantage. Journal of Environmental Economics and Management, 2, 160-169. Redding, S. and Vera-Martin, M. (2001). Factor Endowments and Production in European Regions. mimeo, London School of Economics. Van Beers, C., & Van den Bergh, J.C.J.M. (1997). An empirical multi-country analysis of the impact of environmental regulations on foreign trade flows. Kyklos, 50(1), 29-46. United States Department of Agriculture (2008). U.S. Agricultural Trade Boots Overall Economy, FAU-124 Economic Research Service3/USDA. The authors wish to thank participants at the 9th Biannual Pacific Rim Conference organized by the Western Economic Association International in Brisbane, Australia, in April, 2011. Kermit Rose provided valuable computer programming assistance. Environmental data used in the study came from Shunsuke Managi. Additional state data were collected by Daniel Malonza of South Carolina Department of Environment. Pamela Laursen provided editorial assistance. Financial support from the CSREES Grant no5114 is gratefully acknowledged. The usual disclaimer applies.

TABLE 1 NONLINEAR SYSTEM ESTIMATION OF EXPORT SHARE AND POLLUTION RISK

MODELS UNDER ALTERNATIVE RISK MODEL SPECIFICATION

Export Share FFL FFR HFL HFR Carbon Dioxide

Constant -7.995a 4.932a -0.289 -1.544b -0.778 -0.008

(-7.13) (4.82) (-0.33) (-2.01) (-1.31) (-0.04)

Export Share 0.227a 0.066a -0.097a -0.001 0.002

(7.77) (2.42) (-4.27) (-0.05) (0.33)


Carbon Dioxide t-1 0.062 0.992

a

(1.6) (117.04)

FFL t-1 -0.149a 0.905a

(-6.62) (7.1)

FFR t-1 0.143a 0.938a

(9.07) (75.49)

HFL t-1 0.121a 0.944a

(5.62) (98.01)

HFR t-1 0.022 0.979

a

(1.44) (129.84)

Capital Abatement

0.117 a 0.067b 0.016 0.016 0.012 -0.002

(3.48) (2.02) (0.56) (0.63) (0.61) (-0.22)

Operational Abatement

-0.192 a -0.011 -0.031 0.005 -0.011 -0.001

(-4.92) (-0.3) (-1.05) (0.19) (-0.55) (-0.06)

Farm GDP 0.325a -0.063 c 0.098 a 0.103a 0.031 -0.000

(8.89) (-1.94) (3.21) (4.14) (1.52) (-0.04)

GDP per Capita 0.014 -0.388a -0.166c -0.081 0.021 0.008

(0.12) (-3.96) (-1.86) (-01.07) (0.36) (0.35)

Crop Price 1.544a

(9.38)

Live Stock Price 0.055

(0.35)

Productivity 0.097b

(1.93)

Effective Change 2.079a

(5.31)

NAFTA -0.128 -0.105 0.063 0.235a 0.067 0.067

(-1.14) (-0.96) (0.66) (2.81) (1.03) (1.03)

European Union -0.379a 0.057 0.082c -0.029 -0.013 -0.013

(-7.36) (1.15) (1.89) (-0.78) (-0.45) (-0.45)

Iterations Count 79 79 79 79 79 79

N 903 903 903 903 903 903

Objective Function Value SEE

5418 5418 5418 5418 5418 5418

0.61 0.613 0.539 0.468 0.463 0.138 Numbers in ( ) are the t-statistics of the corresponding variables. a:indicates significance at 1%; b: indicates significance at 5%; and c: indicates significance at 10%

TABLE 2

PAIRWISE NONLINEAR SYSTEM ESTIMATION OF EXPORT SHARE MODEL AND EACH POLLUTION RISK MODEL UNDER ALTERNATIVE RISK MODEL SPECIFICATION

Export

Share FFL Export Share FFR Export

Share HFL Export Share HFR Export

Share Carbon Dioxide

Constant -8.089 4.637a -8.079a -0.978 -7.88a -1.495c -7.967a -1.442b -7.843a 0.048

(-7.15) (4.56) (-7.09) (-1.06) (-6.82) (-1.93) (-6.85) (-2.24) (-6.71) (0.22)


Export Share 0.194a 0.011 -0.097a -0.038c 0.006

(6.63) (0.38) (-4.32) (-1.94) (0.9)

FFL t-1 -0.135a 0.913a -0.1a -0.101a -0.092a -0.092a

(-5.82) (70.9) (-4.42) (-4.43) (-3.99) (-3.95)

FFR t-1 0.14a 0.134a 0.955a 0.139a 0.133a 0.137a

(8.61) (8.32) (71.94) (8.64) (8.23) (8.46)

HFL t-1 0.104a 0.066a 0.064a 0.953a 0.057b

(4.68) (2.98) (2.88) (96.24) (2.51)

HFR t-1 0.031b 0.037b 0.033b 0.989a 0.038b

(1.98) (2.33) (2.05) (118.52) (2.36)

Carbon Dioxidet-1

0.049 0.045 0.048 0.051 0.992a

(1.23) (1.1) (1.17) (1.22) (119.31)

GDP per Capita

0.04 -0.383a 0.033 -0.134 0.019 -0.071 0.023 0.058 0.Q18 0.007

(0.34) (-3.94) (0.28) (-1.43) (0.16) (-0.93) (0.19) (0.89) (0.15) (0.31)

Farm GDP 0.316a -0.052 0.318a O.l13a 0.312a 0.098a 0.315a 0.047b 0.31a -0.002

(8.55) (-1.59) (8.53) (3.5) (8.3) (3.93) (8.31) (2.1) (8.14) (-0.36)

Crop Price 1.589a 1.609a 1.597a 1.569a

(9.33) (9.35) (9.22) (8.9)

Live Stock Price

-0.05 -0.128 -0.085 -0.076

(-0.31) (-0.78) (-0.51) (-0.45)

Productivity 0.073 0.088c 0.109b 0.083

(1.4) (1.67) (2.05) (1.54)

Operational Abatement

-0.18a -0.02 -0.165a -0.041 -0.167a 0 -0.158a -0.013 -0.167a 0

(-4.58) (-0.57) (-4.19) (-1.31) (-4.17) (-0.01) (-3.93) (-0.59) (-4.14) (0.01)

Capital Abatement

0.118a 0.072b 0.119a 0.028 0.119a 0.018 0.117a 0.015 0.122a -0.002

(3.51) (2.18) (3.55) (0.9) (3.49) (0.7) (3.42) (0.7) (3.56) (-0.29)

Effective Change

1.973a 2.089a 2.01a 1.984a

(4.86) (5.05) (4.83) (4.67)

NAFTA -0.117 -0.1 -0.08 0.044 -0.086 0.242a -0.072 0.098 -0.069 0.012

(-1.05) (-0.92) (-0.72) (0.45) (-0.77) (2.93) (-0.64) (1.41) (-0.61) (0.52)

EU -0.375a 0.053 -0.378a 0.052 -0.363a -0.038 -0.366a -0.051 -0.361a -0.001

(-7.25) (1.08) (-7.31) (1.15) (-6.91) (-1.02) (-6.94) (-1.6) (-6.82) (-0.12) Iteration count 57 57 77 77 52 52 52 52 43 43

N 903 903 914 914 917 917 919 919 920 920 Objective function value

1806 1806 1828 1828 1834 1834 1838 1838 1840 1840

Standard Error of Estimate

0.609 0.608 0.611 0.571 0.62 0.473 0.623 0.398 0.626 0.137

Numbers in parentheses are the t-statistics of the corresponding variables. a: Indicates significance at 1%;b:indicates significance at 5%; and c: indicates significance at10%.


The Impact of Physician Job Satisfaction on the Sustained Competitive Advantage of Health Care Organizations

Olena Mazurenko

University of Alabama at Birmingham

Stephen J O’Connor University of Alabama at Birmingham

This paper employs the resource-based theory of the firm to explain the influence of human resources on the sustained competitive advantage of an organization. Based on previous conceptual and empirical literature, we posit that the presence of a high potential employee workforce, coupled with adequate human resource management policies, can result in improved profit generating potential. We developed a conceptual framework with several propositions that illustrate the associations between job satisfaction and organizational productivity. We apply this concept in the health care field, suggesting that the satisfaction of physicians’ needs leads to greater organizational productivity and sustained competitive advantage. INTRODUCTION

The health care system consists of a variety of actors and organizations connected through complex and evolving relationships. Despite this, physicians remain the key stakeholders within the system, delivering care to patients. Therefore, physicians’ satisfaction with their daily work is critical to the successful operation of the whole system.

Recent literature has documented declines in job satisfaction among physicians (Skolnik, 1993; Adams, 2002; Williams, 2003). Skolnik et al. (1993) revealed that only 65% of family practitioners were satisfied with their jobs. This finding was reinforced by the results of a recent Kaiser Family Foundation poll, in which 58% of physicians surveyed reported a decline in their enthusiasm for the practice of medicine over the last five years (Adams, 2002). The potential impact of this decline has an effect on physicians themselves, on patients and on health care organizations. Evidence shows that increased job dissatisfaction among physicians leads to higher levels of burnout, mental problems and even suicide (Williams, 2003). From the patient’s perspective, increased physician dissatisfaction has resulted in lower levels of compliance with medical treatment, increased medical errors and patient dissatisfaction (DiMatteo et al., 1993). Health care organizations experience economic consequences of increased job dissatisfaction in terms of higher turnover rates. Even though it is difficult to estimate actual costs of turnover, Buchbinder et al. (1999) projected that the cost to replace a single primary care physician averaged $250,000. Waldman and colleagues (2004) argued that this amount could be doubled in cases of recruiting a senior physician (chair or chief), reaching $500,000 per person.


From a theoretical point of view, job satisfaction has been correlated with higher productivity and organizational performance (Judge et al., 2001). Therefore, health care organizations should bolster employees’ satisfaction through appropriate human resource management policies. Satisfied employees are more likely to become strong human assets, resulting in greater profit - generating potential. Furthermore, according to the resource-based theory of the firm, employees could contribute to a sustained competitive advantage for the organization (Barney, 1991).

The purpose of this paper is to assess the impact of physician job satisfaction on the sustained competitive advantage of health care organizations. This is achieved through a conceptual framework based upon the resource-based theory of the firm as well as evidence from scholarly literature. Propositions developed using the conceptual framework posit positive correlations between physician job satisfaction and organizational productivity. Moreover, assumptions regarding reciprocal relationships between job satisfaction and organizational productivity are presented. The exploration of the roles of these findings is discussed for future research and managerial implications. Theoretical Background Job Satisfaction

As ordinarily understood, job satisfaction encompasses people’s feelings about their jobs. The classical explanation of job satisfaction is provided by Locke (1976), who defines it as “a pleasurable or positive emotional state resulting from the appraisal of one’s job or job experiences”. Accordingly, job dissatisfaction is the unpleasurable emotional state resulting from appraisal of one’s job as frustrating or blocking the attainment of one’s values (Locke, 1976). Subsequent research has identified various antecedents and facets of job satisfaction that influence an individual’s expectations, needs (physical and psychological) and values (Price et al., 1981).

Numerous theories have been employed to explain job satisfaction. Fundamental contributions to our understanding of the job satisfaction phenomenon were obtained from Hackman and Oldham’s (1980) job characteristic theory. Additional theoretical approaches have been developed to investigate job satisfaction (Price & Muller, 1981; Miner, 1992; Eagly & Chaiken, 1993; Weiss, 2002). These approaches differ in perception of job satisfaction as an affect, attitude or behavior.

Despite the differences discussed above, most research has treated job satisfaction similarly. Job satisfaction has been measured as a global concept referring to overall satisfaction and as a facet-specific concept, referring to various aspects of a job (Nagy, 2002). Various scales have been used to measure facets of job satisfaction. The most widely used scales are: Job Satisfaction Survey (Spector, 1985), Job Descriptive Index (JDI) (Smith et al., 1969) and the Job Diagnostic Survey (Hackman & Oldham, 1980). The two most widely accepted job satisfaction instruments are the Job in General Scale (Ironson et al., 1989) and the Michigan Organizational Assessment Questionnaire Satisfaction Subscale (Camman, 1979). These instruments have been widely used and were adapted according to the needs of each industry (Spector, 1997). Most of these instruments assess similar components of job satisfaction. For instance, the Job Satisfaction Survey contains the following items: pay, promotion, supervision, fringe benefits, contingent rewards, operating conditions, coworkers, nature of work and communication. This scale uses a summated rating scale format (Spector, 1997).

The theoretical and measurement approaches discussed above have been used in the health care field, including nurse turnover research (Price & Muller, 1981; Mobley, 1982; Parasuraman, 1989). However, certain researchers have expressed skepticism about the applicability of occupational and organizational psychology approaches to measuring job satisfaction among medical staff (Godfrey, 1978; Schrader, 1981; Light et al., 1988). Despite this criticism, an extensive review of the literature has revealed few attempts to design individualized methodological approaches measuring job satisfaction in the health care field. However, it is worth noting the input of Williams and colleagues (1999), who designed a multidimensional satisfaction instrument and tested it on a nationally representative sample of primary care physicians in the United States (Williams et al., 1999). They identified the following relevant components of job satisfaction: autonomy, relationships with colleagues, relationships with patients, relationships with staff, personal time, community, pay, administration and resources. Other researchers


included in their models the impact of practice setting (Garcia-Pena et al., 2000), full-time versus part-time status, and time pressure during office visits (Linzer, 2000). A systematic review of the physician satisfaction literature reported by Scheurer et al. (2009) shows a variety of approaches and instruments for studying this construct. Certain antecedents yielded controversial relationships with job satisfaction. For instance, objective workload (actual number of visits per week) was not associated with satisfaction, whereas subjective evaluation of workload yielded significant relationship. Therefore, additional research is needed to identify the key determinants of physicians’ job satisfaction in order to design appropriate working conditions.

There are relatively few studies identifying relevant determinants of physician job satisfaction. Despite this, research has shown a consistent and significant association between physician job satisfaction and intention to leave and turnover (Locke, 1983; Baker, 1993; Wright et al., 2000). Physician turnover has multiple consequences for health care organizations, impacting both the effectiveness and productivity of care delivery. Additionally, health care organizations that are affected by high turnover incur significant financial expenses (Berger et al., 1992). It is worth mentioning that these estimates include only the direct cost of turnover, such as hiring and recruitment expenses and costs of new employee training. However, researchers argue that direct costs account for only 15 to 30 percent of the total turnover costs (Razc, 2000; Schloss et al., 2009). A major portion of total turnover costs are indirect costs associated with the inefficiency of former employees leaving positions, new employees working without experience and the general impact of coworker loss on remaining employees (Schloss et al., 2009). These elements are difficult to quantify and to incorporate into turnover calculations.

One could argue that, in a highly changing and uncertain environment, the consequences of physician turnover might undermine the survival of a health care organization. Therefore, physicians’ job satisfaction as an identified and predominant antecedent of turnover should be appropriately addressed in any organizational strategy. It is worth noting that employees’ job satisfaction plays a great role not only in organizational survival but also in gaining the market advantage. Therefore, meeting physicians’ needs could improve organizational performance for health care institutions. These relationships are reflected in the Resource-Based View (RBV) theory of the firm. This theory emphasizes the long-term effect of human resources on improving organizational performance and productivity. Without a doubt, any organization would prefer to have a strategy that improves productivity and creates a competitive advantage for a longer period of time. Health care organizations are not exempt from this rule; therefore, RBV theory could be applied to this industry as well. The following section briefly describes RBV theory with empirical evidence from various settings. Resource-Based View of the Firm

Strategic management highlights the role of resources as important antecedents of firm performance (Priem, 2001). Therefore, researchers attempt to identify the characteristics of firm resources that could provide a unique advantage over competitors. The importance of firm resources in improving organizational performance is reflected in resource-based view (RBV) theory of the firm (Barney, 1991).

According to this theory, resources are defined as “all assets, capabilities, organizational processes, firm attributes, information, knowledge, etc. controlled by a firm that enable the firm to conceive and implement strategies that improve its efficiency and effectiveness” (Barney, 1991, p. 231). Accordingly, resources fall into three categories: 1) physical capital resources (plant, equipment), 2) human capital resources (human capital pool, human resource practices) and 3) organizational capital resources (firm’s structure, planning, controlling, coordinating systems). Barney argued that not all resources will contribute to conceiving and implementing valuable strategies to improve a firm’s performance. However, RBV theory attempts to identify the attributes of the firm’s resources that will lead to improving efficiency and effectiveness and provide a sustained competitive advantage for the firm.

Barney (1991) presented two basic assumptions for identifying a firm’s valuable resources. First, resources are distributed heterogeneously across firms. Second, these productive resources cannot be transferred from firm to firm without cost (Barney, 1991). Given these assumptions, he formulated two fundamental arguments about firm resources. First, resources that are both rare and valuable can produce


a competitive advantage. Valuable resources are defined as ones that contribute to firm efficiency and effectiveness. Second, resources must have certain characteristics in order to produce a long-lasting advantage. These resources should be difficult to imitate, substitute and transfer from one organization to another.

Subsequent research has demonstrated that firms can achieve a sustainable competitive advantage from such sources as information technology (Powell, 1997), strategic planning (Michalisin et al., 1997), organizational alignment (Powell, 1992), trust (Barney & Hadsen, 1994) and others. Among other resources, the role of human resources has yielded considerable controversy (Boudreau, 1991; Jones & Wright, 1992; Huselid, 1995). In general, organizations turn their attention to human resource interventions primarily when they have excess profit. During economic declines, the importance/ relevance of employee and human resource practices are abandoned (Boudreau, 1991).

The application of RBV theory to human resources has created a debate over the specific human resource elements that serve as a source of sustained competitive advantage (Capelli, Singh, 1992; Wright, 1994). Capelli et al. (1992) proposed that certain human resource policies have the potential for improving a firm’s effectiveness. However, Wright et al. (1994) were highly critical of this view, indicating that human resource policy could be imitated by competitors. Rather, they proposed that human capital, if highly skilled and motivated, has greater potential for the creation of sustained competitive advantage (Wright et al., 1994). These researchers applied Barney’s (1991) core arguments to human capital. They argued that employees can provide a source of sustained competitive advantage when the following requirements are met. According to Barney (1991), resources must add value to the firm’s production processes; therefore, levels of employee performance must matter. Resources must be rare; therefore, the employees’ skills must be rare as well. Barney’s argument about difficulty in imitability could also be applicable to human capital, because the firm is able to qualitatively differentiate its employees from those of its competitors. Furthermore, a firm’s human resources must not be replaceable by technological advances or other substitutes. This requirement is subject to certain limitations depending on the firm’s environment and specifics of the industry. For example, labor-intensive industries have higher potential for substituting technologies for human capital, whereas knowledge-intensive industries have less flexibility in this matter.

Following this debate, a more comprehensive view on human resources was proposed (Boxall, 1998). According to Boxall, the superiority of one firm’s human resources over another’s depends on two elements: human capital advantage (employees with potential for productive possibilities) and human process advantage (adequate human resource policies). Therefore, firms should satisfy employees’ interests to create a committed workforce. Following this, appropriate human resource management (HRM) policies should be adopted in order to align human capital with a firm’s overall strategy (Boxall, 1998). Empirical Applications of Resource-Based View Theory

RBV concepts have been used to analyze relationships within human resource management in various settings. One of the early applications of RBV is found in a study by Huselid (1995). The author proposed that HRM practices could indeed create a source of sustained competitive advantage. Moreover, he revealed a relationship between HRM practices (High Performance Work Systems) and employee turnover and gross rate of return on assets (Huselid, 1995). This study provided evidence of the potential impact of HRM practices on financial and market-based performance of organizations.

Applying RBV concepts to samples of business units yielded similar results (Koch et al., 1996). The authors argued that specific HRM policies are able to acquire a unique stock of human capital that is hard for competitors to imitate and will increase labor productivity. They argued that “a highly productive workforce is likely to have attributes that make it a particularly valuable strategic asset” (p. 335). They found that “setting-specific” HRM practices that are able to attract and retain employees are positively associated with labor productivity. This relationship appeared to be stronger in capital-intensive organizations.


RBV logic has been used to assess the impact of racial diversity on firm performance. Richard (2001) analyzed a sample of banks and found that racial diversity provides value by ensuring a variety of perspectives. Therefore, socially complex dynamics inherent in diversity lead to its inimitability. Results of the research revealed that diversity was positively related to productivity, return on equity and market performance.

It is worth mentioning that empirical applications of RBV concepts take a variety of forms. However, they all follow a common underlying logic: human resource activities lead to the creation of a skilled workforce, which will engage in the functional behavior of the firm, resulting in higher productivity and performance. Human Resources in Health Care

In health care, human resources are comprised of human capital (clinical, administrative and other staff) and various HRM policies that are implemented in the organizations. In this field, the value of human capital cannot be underestimated. Despite modern technological innovations, only individuals with appropriate knowledge and skills are able to provide care to patients. Among clinical staff, physicians are viewed as prominent stakeholders who are responsible for providing services to clients, i.e. patients. According to RBV theory, physicians can be viewed as a source of sustained competitive advantage. This proposition can be supported by the following arguments. Physicians possess unique knowledge and skills that are rare and difficult to acquire. Moreover, combined physician capital is relatively difficult to imitate within other health care organizations, because each physician possesses a distinct array of knowledge and skills. Finally, it is problematic to substitute technology for a physician in the process of care delivery to patients. Therefore, it could be argued that physicians are a source of sustained competitive advantage that contributes to organizational productivity and performance.

There is growing interest in exploring the role of human resources in health care organizational performance. Recent research has focused on the links between staffing levels, staffing mix and outcomes (Sovie et. al., 2001; Aiken et al., 2002). Findings from these studies demonstrate that higher staffing levels and/or staffing mix are related to “better” patient outcomes (lower mortality rates, needle stick injuries, or infections; higher patient satisfaction) (Sovie et. al., 2001; Aiken et al., 2002). These studies shed light on the role of HRM in health care; however, due to methodological limitations (small sample size, cross-sectional design), they were not able to reveal the relative importance of human resources in health care. Moreover, previous research has not attempted to apply concepts of RBV theory in examining the relationship between human resources and organizational productivity. As was mentioned earlier, RBV theory was successfully employed to investigate the role of human resources in other industries (Huselid, 1995; Koch et al., 1996; Richard, 2001). Presently, research has focused on discrete human resource components, such as determinants of job satisfaction among different medical staff members (Williams et al., 1999; Garcia-Pena et al., 2000; Linzer, 2000) or the link between HRM and patient care quality (Eaton, 2000; Kochan, 1994). However, no attempts have been made to bridge distinct elements of human resources to assess the potential for creating a sustained competitive advantage for organizations in health care.

As was emphasized earlier, human capital itself does not ensure higher performance (Boxall, 1998). Therefore, health care organizations should design appropriate, setting-specific HRM policies that satisfy employees’ needs and motivate them toward higher productivity. According to RBV theory, this approach should create a relative productivity advantage and improve organizational efficiency and effectiveness (Barney, 1991). Supportive evidence in health care was found in nursing (Kramer et al., 1991). Several hospitals were able to successfully recruit and retain professional nurses during a national nursing shortage in the early 1980s (Brady-Schwartz, 2005). These organizations were labeled as “magnet hospitals”. These institutions were able to design HRM policies that attracted and retained well-qualified nurses and therefore consistently provided quality care. The key characteristics of HRM policies employed in magnet hospitals are: clinical career opportunities, planned orientation of staff, and emphasis on in-service/continuing education. These HRM policies contribute to decreases in nurse turnover and increases in nurse job satisfaction (Kramer et al., 1991). Moreover, Aiken et al. (1994) revealed that


magnet hospitals have lower mortality rates for Medicare patients in comparison with matched hospitals without the above-mentioned HRM policies in place (Aiken et al., 1994). The main message from this example is that “magnetism” (setting-specific HR policies) appears to be related to “better” staffing indicators and improved quality of care.

Thus, the theoretical literature suggests that the behavior of employees within an organization has important implications for a firm’s performance (Barney, 1991; Wright et al., 1994). Empirical research provided support for these relationships, revealing that motivated and satisfied employees have higher productivity (Huselid, 1995; Koch et al., 1996; Richard, 2001).Therefore, it could be argued that the design and implementation of HRM interventions that fit with employees’ needs and demands will enhance an organization’s human asset complement and create sustained competitive advantage. Evidence from “magnet” organizations supports the relationship between employee job satisfaction and better hospital performance. Therefore, one could argue that this logic could be applied to investigate the role of physician job satisfaction on organizational productivity and performance. What follows is a conceptual framework of research propositions. Conceptual Framework

The theoretical foundations of RBV theory (Barney, 1991) and empirical research (Huselid, 1995) identified relationships between a firm’s human resources and performance. However, no previous attempts were made to formally apply RBV concepts in health care. Therefore, the proposed framework expands on earlier work by suggesting a relationship between employee satisfaction and the sustained competitive advantage of the health care organization (see Figure 1). It has been shown that satisfaction with one’s job can be achieved by instituting corresponding HRM policies (Buchan, 2004). This HRM policy-employee satisfaction “fit” enables effective deployment of high levels of skills and increases in

FIGURE 1 CONCEPTUAL FRAMEWORK

organizational productivity. Among health care employees, physicians possess such extensive qualifications that they are considered key organizational stakeholders. This important position within the


health care system dictates that their needs and demands be met to the extent possible. Therefore, identifying aspects of physician job satisfaction can facilitate the development of HRM policies that create “policy-physician satisfaction fit” in health care organizations.

The propositions presented in this model posit that employee job satisfaction is important for creating and sustaining a firm’s performance advantage in the market. Based on a comprehensive literature review and empirical results from other fields, the propositions specifically address physicians’ job satisfaction. This framework may be useful for developing and implementing physician-specific HRM policies in health care organizations. Group-Specific HRM Policies and Job Satisfaction

Existing empirical research on job satisfaction reveals differences between employees’ needs and demands depending on the industry and profession (Williams et al., 1999; Garcia-Pena et al., 2000; Linzer, 2000). Therefore, analysis of the elements of job satisfaction, specific to the target group of employees, should be included in the organizational HRM strategy.

A growing body of literature on the physician workforce presents a number of intrinsic and extrinsic factors that attempt to explain variation in physician satisfaction rates (Smith, 2001; Edwards et al., 2002; Janus, 2010). Strongly criticizing predominant emphases on monetary incentives (pay for performance programs) embedded in health care HRM practices, researchers are advocating for the inclusion of individual intrinsic needs (Janus, 2010). For instance, physicians should have the opportunity to shape organizational goals, participate in resource allocation and obtain continuous training and technical support (Edwards et al., 2002). However, much of the literature is normative in nature, lacking empirical support for such propositions. This may be due to the complexity of interaction between independently practicing physicians and health care organizations. One could argue that HRM policies would be easier to apply to hospital employees, like nurses. Supportive evidence can be found in “magnet” institutions that were able to identify nurse-specific needs and design appropriate group-specific HRM policies. These policies contributed to documented increases in nurses’ job satisfaction (Kramer et al., 1991; Aiken et al., 2002). The proven effectiveness of nurse-specific HRM policies could be used in other health care professions. For these reasons, the following proposition is suggested:

Proposition 1: Group-specific HRM policies designed to meet physician needs are associated with increased job satisfaction.

Job Satisfaction and Intention to Leave

The literature argues that job satisfaction is an essential factor in determining withdrawal from an organization (Price et al., 1981; Miner, 1992; Nagy, 2002). This relationship is applicable in the health care industry as well. Early supportive evidence was revealed with nurses’ job satisfaction and turnover rates (Price et al., 1981). Price et al. confirmed that increases in nurses’ job satisfaction lead to reduced turnover rates. Methodological challenges in measuring actual turnover forced researchers to develop a surrogate variable able to capture one’s intention to leave the organization and profession. The relationship between employee intention to leave a specific employment position and actual job turnover has been extensively studied (Tett and Meyer, 1993). However, only a handful of studies have attempted to validate this relationship in the physician workforce. Buchbinder and colleagues (1999) examined data from the AMA’s Young Physician Survey and found that the likelihood of leaving practice within the next two years was negatively correlated with several aspects of job satisfaction, such as rewards, autonomy, working conditions, etc. (Buchbinder et al., 1999). In a follow-up survey, they found that those primary care physicians who reported a low level of satisfaction were 2.38 times more likely to actually leave their practice (Buchbinder et al., 2001). Similarly, Linzer et al. (2000) examined data from the Physician Worklife Survey and found that physicians’ intention to leave was negatively correlated with job satisfaction (Linzer et al., 2000). This pattern of relationships was shown to be consistent within different physicians’ specialties (Gallery et al., 1992; Linzer et al., 2000; Pathman et al., 2002). From this, it is proposed that:


Proposition 2: Increased physician job satisfaction is associated with reduced intention to leave a health care organization.

Physician Job Satisfaction and Organizational Productivity

Most research on employee attitudes (e.g. job satisfaction) indicates that how employees experience their work is reflected in organizational effectiveness (Likert, 1961; Price et al., 1981; Denison, 1990). For instance, evidence from 34 publicly held firms found that organizations in which employees reported an emphasis on human resources tended to have superior short-term financial performance. These firms experienced steady growth in their financial performance relative to their competitors over 5 years (Denison, 1990).

In the health care field, examining the relationship between staffing and outcomes revealed a similar pattern (Sovie et al., 2001; Aiken et al., 2002). Research showed that higher nursing staffing levels and/or staffing mix was related to “better” outcomes. Better outcomes were defined either as reductions in the levels of specified “negative” outcomes (mortality rates, needlestick injuries, or infections) (Sovie et. al., 2001) or improvement in reported quality of care or patient satisfaction (Aiken et al., 2002). Improvement in quality of care and reduction in mortality rates are only a couple of the indicators that reflect health care organizational performance; however, they provide support for the suggested relationship.

A similar relationship was found among physicians. Empirical studies have identified associations between physician satisfaction and a variety of measures of quality of care (Williams et al., 2003). These include physicians’ prescribing behavior and referral, patient satisfaction and adherence to medications. For instance, patients of physicians with higher satisfaction reported better adherence to medication (DiMatteo et al., 1993). Moreover, patients of physicians who have higher professional satisfaction are themselves more satisfied with their care (Haas et al., 2000). More recently, Williams and colleagues (2007) provided evidence that higher physician job satisfaction is associated with lower likelihood of patient errors and better quality of patient care (Williams et al., 2007). Given the documented impact of physician job satisfaction on multiple aspects of health care delivery, the following proposition is suggested:

Proposition 3.1: Physician job satisfaction is positively related to organizational productivity.

Recently, there has been growing empirical evidence for an alternative relationship between

employee job satisfaction and organizational performance. Prior literature provided an implicit direction for the causal arrow from employee attitude to organizational performance (Price et al., 1981; Locke, 1983; Spector, 1997; Koys, 2001). For instance, Koys analyzed data from units of a regional restaurant chain and concluded that satisfied employees had a positive influence on business outcomes (profits after controllable expenses). Moreover, the author revealed that customer satisfaction is affected by different levels of employee satisfaction. However, Schneider et al. (2003) revealed reciprocal relationships between these variables. At the organizational level, they analyzed employee attitude data from 35 companies over an 8-year period against financial (return on asset [ROA]) and market performance (earnings per share [EPS]). This research indicated that overall job satisfaction was more strongly predicted by ROA and EPS than the reverse. It was argued that employees are attracted to successful organizations and are likely to remain with such organizations (Schneider et al., 2003). Evidence of this reciprocal relationship could be found in health care. Researchers argue that “magnet” hospitals are able to attract and retain nurses due to their high performance and popularity in the industry. However, no empirical research was done in the health care workforce to prove this assumption. Given the above reasons, an alternative proposition is suggested:

Proposition 3.2: Organizational productivity will have a direct positive influence on

physician job satisfaction.


Job Satisfaction and Sustained Competitive Advantage RBV theory stresses the comparative benefits that human resources provide to organizations in terms

of their skill mix, values and distinctive qualifications (Barney, 1991). In most industries, organizations use the same inputs, but may differ in the processes used to combine these inputs and transform them into products. While inputs and outputs could be replicated by competitors, competitive advantage could be provided by a unique mix of skills, knowledge and expertise possessed by staff. As mentioned earlier, group-specific HRM policies could assist in capturing this unique stock of talent, which will possess distinct characteristics. Moreover, these group-specific HRM policies could facilitate increases in employee motivation and improved job satisfaction. Evidence suggests that human resources, including employee skills and knowledge and group-specific HRM policies, can assist in creating a competitive advantage (Huselid, 1995; Koch et al., 1996). Hallowell (1996) analyzed the sources of competitive advantage at Southwest Airlines. The author argues that by creating satisfied employees it creates value and establishes a superior position in the market. Applying this logic to health care, one could argue that physicians can be viewed as a unique stock of talent. Therefore, appropriate group-specific HRM policies should increase physician motivation and job satisfaction. Satisfied physicians would be an integral part of a value-creating strategy that is not being implemented by current or potential competitors. Unfortunately, no empirical research has been done to test these assumptions. Based on this logic, the following proposition is made:

Proposition 4.1: Physician job satisfaction will have a direct positive influence on a health care organization’s sustained competitive advantage.

Organizational performance is an indicator of an organization’s position in the market/industry.

Better organizational performance can be interpreted as competitive advantage in the market. Academic researchers have consistently documented a positive relationship between employee attitude (e.g. job satisfaction) and organizational performance/firm’s position in the industry (Likert, 1961; Price et al., 1981; Denison, 1990). Evidence shows that this relationship runs from employees’ attitudes to organizational performance (Denison, 1990). However, recent research found support for the reverse direction of this relationship, from organizational performance to employees’ job satisfaction (Schneider et al., 2003). It can be argued that a firm’s position in the industry can be attractive to employees. Therefore, organizations that have advantageous positions in the market due to higher performance and productivity are viewed as more attractive places to work. Nurse “magnet” hospitals serve as an example of this assumption. They appeared to be attractive to nurses due to their high position in the industry. Moreover, evidence shows that nurses who work in these “magnet” institutions are satisfied with their working conditions (Schneider et al., 2003). Unfortunately, no empirical research has been done to test this assumption within the physician workforce. Based on this logic, the following proposition has been made:

Proposition 4.2: A health care organization’s sustained competitive advantage will have a direct positive influence on physician job satisfaction.

Summary and Directions for Future Research

Most organizations are searching for ways to improve their productivity and performance. This process could include analysis of the firm’s strengths and weaknesses, investigation of a firm’s internal resources and exploration of competitors’ profiles. The scholarly community argues that all of these approaches have their advantages and disadvantages in solving the productivity puzzle (Barney, 1991). Recently, the attention of researchers has been drawn to the link between a firm’s internal characteristics and performance. These ideas are reflected in RBV theory, whereby a firm’s internal resources can serve to create a source of sustained competitive advantage. Among other resources, human resources have a special position. They have the high potential for creating a source of sustained competitive advantage if appropriate HRM policies are in place (Wright, 2000).


The health care field is one of the most knowledge- and labor-intensive industries, where delivery of services (care to the patients), is impossible without skilled personnel. Therefore, the demands and needs of human capital should have high priority in the organization. Evidence suggests that fulfillment of employees’ needs has a positive effect on organizational performance and productivity (Price & Muller, 1981; Miner, 1992; Eagly & Chaiken, 1993; Weiss, 2002). Therefore, increases in physician job satisfaction should be positively correlated with improved performance and productivity of health care organizations. Unfortunately, theoretical assumptions of RBV theory have not been formally applied in the health care industry. The failure to utilize this theory is regretful, especially taking into account the importance of human resources in this industry. The treatment of human resources as a source of sustained competitive advantage could provide new insight into the development and implementation of a general strategy for health care organizations.

The aim of this paper has been to assist researchers and managers in understanding the overall relationship between physician job satisfaction and the opportunity to create a sustained competitive advantage by health care organizations. The proposed framework depicts a clear picture of the issues that should be addressed by HR managers to create and implement a sustained competitive advantage for the organization. One could theorize that there is a significant relationship between physician job satisfaction and sustained organizational competitive advantage. Thus, several important implications for managers emerge from the propositions of this framework. It was shown that fulfilling physicians’ specific demands and needs through the application of appropriate HRM policies could improve their job satisfaction and motivation. Increases in physician job satisfaction could lead to increased productivity and the creation of a competitive advantage in the market. Moreover, a reciprocal relationship between organizational productivity and physician job satisfaction is proposed. Therefore, managers should design HRM strategies to address physicians’ needs and demands. The effectiveness and utility of the model in the creation of sustained competitive advantage requires empirical research. In the meantime, this framework provides a workable theoretical foundation that may assist in developing tools for the analysis of human resources in health care. REFERENCES Adams, D. (2002). Physicians are working more, enjoying it less. Washington, DC: AMA News. Aiken, L., & Clarke, S. & Sloane, D. (2002). Hospital staffing organization, and quality of care: cross national findings. International Journal for Quality in Health Care, 14, 5-13. Aiken, L., & Smith, H. & Lake E. (1994). Lower Medicare mortality among a set of hospitals known for good nursing care. Medical Care, 32, 771-787. Aiken, L., & Clarke, S. & Sloane, D. (2002). Hospital staffing organization, and quality of care: cross-national findings. International Journal for Quality in Health Care, 14, 5-13. Bailey, T. (1993). Discretionary effort and the organization of work: Employee participation and work reform since Hawthorne. Working paper, Columbia University, New York. Baker, L.C., & Cantor, J.C. (1993). Physician satisfaction under managed care. Health Affairs, 23, 258 - 270. Barney, J.B. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17, 99-120. Barney, J.B., & Hansen, M.H. (1994). Trustworthiness as a source of sustained competitive advantage. Strategic Management Journal, 15, 175-190.


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Union Participation: A Social Exchange Perspective

Ray Gibney The Pennsylvania State University at Harrisburg

Marick F. Masters

Wayne State University

Thomas J. Zagenczyk Clemson University

Thomas Amlie

The Pennsylvania State University at Harrisburg

Stephen Brady Supply Chain Innovations Today

We introduce the concept of perceived union obstruction (PUO), which expands the union-member social exchange relationship literature to include negative relationships. In addition, we assess cross foci-target perceptions and behaviors by testing hypotheses regarding the effects of perceived treatment by the organization and union on commitment to the union and participation in union activities. Hypotheses are tested using a sample of 168 public sector union members. Regression results provided mixed results for hypotheses. Generally, negative exchange relationships had a greater impact on attitudes and behaviors. Implications for theory and practice are discussed. INTRODUCTION

The 2009 National Labor Relations Board’s Annual Report suggests a far more complex union-member exchange relationship than is captured by current theory. In addition to the nearly 700 requests for decertification elections and deauthorization polls, over 5,000 complaints were filed against unions for coercion of employees or illegal restraint and over 300 complaints of discrimination. Specifically, it seems that many union members may not only believe that their unions aren’t supportive, but actually make it more difficult for them to achieve their personal and professional goals. To address this trend in the union environment and advance the literature on union-member relations, we present the argument that a member’s perception that the union is coercive and limiting presents a much different relationship than one that is simply not perceived to be supportive.

Experts believe that changes in the legislative environment will make it easier for unions to organize. As a result, some speculate that the three-decade decline in union density may come to an end – and even


that union density may increase. However, existing literature suggests union members seek to help their unions realize their goals based upon their beliefs that the union is committed to its members (Tetrick, 1995). In short, members are committed to the union and subsequently help the union achieve its goals based upon their perception that the union is committed to its members. Although new political administrations may make the environment more conducive for organizing, these changes will not alter members’ perception of their relationship with the union and not lead to the expected gains in union density. Accordingly, we suggest developing a more nuanced understanding of union-member relationships is important.

To this end, scholars studying social exchange theories have argued and shown that such relationships have both positive and negative facets. To understand the totality of the relationship and successfully predict its outcomes, both positive and negative dimensions need to be captured (Gibney, Zagenczyk, & Masters, 2009). As Eby, Butts, Lockwood, and Simon (2004: 415) note “negative relational experiences should not be conceptualized simply as a deviation from the positive, but (rather) a phenomenon that also composes the totality of relational experience”. With this in mind, we look to expand the union-member social exchange relationship perspective to include both positive and negative components.

This objective is necessary given that the majority of union-member social exchange research focuses almost solely on perceived union support (PUS), defined as “members’ global beliefs concerning the extent to which the union values their contributions and cares about their well-being” (Shore, Tetrick, Sinclair & Newton, 1994, p. 971). While much of the union-member social exchange research has focused on PUS, other social exchange relationships between the union and the member likely exist (Tetrick, 1995). We expand the literature to account for this possibility by presenting a measure which captures the negative social exchange relationship between the union and its members.

Critical to our argument is the idea that the union-member social exchange relationship does not exist in a vacuum. Members have multiplex relationships, as they maintain memberships in both their organizations as well as in their unions. Employees also have positive and negative social exchange relationships with the organization (Eisenberger, Huntington, Hutchison, & Sowa, 1986; Gibney, et al. 2009; Rousseau, 1995). Eisenberger et al. (1986) defined perceived organizational support (POS) as an employee’s perception that the organization values his or her contribution and cares about his or her well-being. Gibney et al. (2009) provided initial evidence that employees develop negative perceptions of their social exchange relationship with the organization, as opposed to relationships which are supportive to nonsupportive, as captured by the POS construct. Gibney et al.’s (2009) research also indicated that employees’ perceptions of organizational obstruction (POO) are distinct from POS and psychological contract breach, employees’ beliefs that their organization has failed to fulfill promised obligations (Rousseau, 1995). In a similar fashion, we introduce the concept of perceived union obstruction (PUO) in order to fully explain the totality of a member’s social exchange relationship with the union. Perceived union obstruction is defined as a member’s belief that the union obstructs, hinders or interferes with the accomplishment of his or her goals and objectives and is a detriment to his or her well-being.

Perceived union obstruction is important because research has long since recognized that union members’ perceptions of their exchange relationships with their employers drive their union-related attitudes and behaviors (Iverson & Currivan, 2003; Snape & Redman, 2007). Recent research has begun to examine these cross-foci-target relationships in more detail (Snape & Redman, 2007). For example, do perceptions of organizational support reduce citizenship behaviors directed toward the union? We further expand this burgeoning research stream by including both positive and negative relationships with the organization and union directed behaviors.

While the inclusion of social exchange variables may be a recent addition to this research stream, a long history of dual commitment and allegiance research exists (Iverson & Currivan, 2003; Snape & Redman, 2007). This line of research posits that employees who are committed to the company will be less likely to aid the union through citizenship behaviors or participate in union activities. The same is thought to be true for union members who are committed to the union. Generally speaking, the results of such dual commitment and allegiance studies are equivocal (Snape & Redman, 2007): the inclusion of social exchange perceptions which are predicated on the norm of reciprocity (Gouldner, 1960) might


present a slightly different picture. A positive or negative social exchange relationship might directly influence behaviors directed toward other groups. The old adage which states that the enemy of my enemy is my friend or the friend of my friend is my friend might endear employees and members to help one foci or the other.

In this study, we expand the current literature devoted to union-member social exchange relationships by including relational aspects which are positive and negative. In addition, we test whether social exchange relationships with one organization have ramifications for relationships with other institutions. We begin by reviewing the social exchange literature and then develop hypotheses. These hypotheses are then tested using a sample of public sector union members. We conclude with a discussion of the practical and theoretical implications as well as the limitations of the study.

FIGURE 1 THEORETICAL MODEL

LITERATURE REVIEW Exchange Relationships

Social exchange theory is predicated on the idea that individual-collective relationships may be characterized as exchanges of mutual support that are socioemotional (as opposed to solely economic) in nature (Blau 1964; Eisenberger et al, 1986; Sinclair & Tetrick, 1995). Underlying the individual-collective social exchange is the assumption that individuals personify the collective, be it a union or employer, and attribute the agents’ actions to the intent of the collective itself (Eisenberger et al, 1986; Levinson, 1965; Sinclair & Tetrick, 1995). Thus, perceived treatment from representatives may be interpreted as signals of the collective’s valuation of the employee or member. The social exchange relationship model in organizations is one in which employers offer rewards and favorable job conditions in exchange for employee loyalty and work effort (Blau, 1964; Eisenberger et al, 1986; Levinson, 1965). However, these positive work conditions may be attributed to the union if members believe that the positive work conditions exist because of representational and collective bargaining efforts by the union (Sinclair & Tetrick, 1995).

Social exchange relationships are widely believed to be driven by the norm of reciprocity (e.g., Eisenberger et al., 1986). The negative norm of reciprocity obligates individuals to return harm with

Union Commitment

Perceived Organizational Obstruction Perceived Organizational Support

Union Participation

Perceived Union Support Perceived Union Obstruction


harm, whereas the positive reciprocity norm obligates individuals to help, or at a minimum not harm, others who help (Gouldner, 1960). If an individual perceived positive treatment from the collective, the positive reciprocity norm suggests the individual will repay the positive treatment by behaving in a manner that is beneficial, or at a minimum is benign to the organization or union. Support perceptions are fostered when employees receive positive treatment from the organization, including fairness perceptions, human resource practices, and supervisory relationships (for a meta-analysis, see Rhoades & Eisenberger, 2002), whereas perceptions of union support (PUS) are fostered by union instrumentality or the degree to which the union garners better working conditions for members (Snape & Redman, 2007; Tetrick et al., 2007). Consistent with reciprocity norm, research shows that POS and PUS positively relate to commitment and citizenship behavior and negatively to turnover and turnover intentions (Iverson & Currivan, 2003; Rhoades & Eisenberger, 2002; Snape & Redman, 2004; Snape & Redman, 2007; Tetrick et al., 2007). Extant research generally indicates that social exchange theory presents a useful lens through which to view individual-collective relationships.

Yet some important aspects of social exchange are neglected in the literature. Researchers have long recognized that organizations are an important source of material and socio-emotional support for employees (Mayo, 1945). While early views of the employee-organization relationship focused exclusively on economic exchanges, subsequent perspectives considered the organization to be an important source of socio-emotional resources for employees as well. Employees derive esteem from organizational membership to overcome anomie (Mayo, 1945), which often leads them to attribute human-like characteristics to organizations (Levinson, 1965). Eisenberger et al. (1986) advanced the literature by proposing that employees develop a belief regarding the extent to which the organization provides support for them. They argued that the positive reciprocity norm (Gouldner, 1960) obligated employees to support the organization and union in return for its commitment to them. Together, Levinson (1965) and Eisenberger et al. (1986) demonstrate that employees: (1) personify organizations, and (2) form global beliefs regarding the extent to which treatment received from the organization is perceived to be supportive.

Gibney et al. (2009) expanded the employer-employee social exchange relationship to include negative exchanges. They argued that Gouldner’s (1960) norm of reciprocity contains positive and negative elements. Negative elements are so salient that entire research streams are devoted to negative extra-role behaviors – known as organizational retaliatory behaviors. Based upon the foci-target argument inherent in the reciprocity norm, employees must perceive that the organization is a source of negative treatment if they are to retaliate against the organization. Following this logic, Skarlicki and Folger (2004) noted that “although many inanimate objects do not logically qualify as culpable actors, people nonetheless often treat personifications… as transgressors and deem them accountable for negative outcomes” (p. 375). It is noteworthy that Skarlicki and Folger do not in any way limit their reasoning to organizations, but instead consider inanimate objects in general.

Drawing on this logic, we believe that union members will hold unions responsible for negative treatment that they believe stems from the union (Bigoness & Tosi, 1984; Fiorito, Gallagher & Fukami, 1988). For example, unions have traditionally attempted to negotiate the highest wages possible for members. In some instances, such increased costs for employers may result in some members losing employment. Survivor members may hold the union responsible for negative treatment, such as increased workload and hours. Another possible situation may emerge as a result of the long-honored union clause of right of refusal. Right of refusal clauses require the most senior member of a union to refuse overtime before the overtime can be offered junior members. Traditionally, members with less seniority earn less and therefore may have a greater need for the more compensation. It is highly possible that these members could perceive the union as obstructing or interfering with their goals because they perceive that its policies are unfair.

While the research on negative social exchange relationships is fairly new, it is probable that the negative social exchange relationships will impact commitment to the organization or union. Research has consistently found that social exchange relationships correlate with commitment to the union or organization (Iverson & Currivan, 2003; Rhoades & Eisenberger, 2002; Snape & Redman, 2004; Snape &


Redman, 2007; Tetrick et al., 2007). The positive norm of reciprocity obligates individuals to repay commitment with commitment (Eisenberger et al, 1986; Shore et al., 1994). In a union context, this increased commitment is manifested behaviorally through increased participation or through union activities or citizenship behaviors directed at the union. HYPOTHESIS DEVELOPMENT Social Exchange with the Organization and Union Participation

Employees who perceived that the organization obstructed them were more likely to engage in voice behaviors (Gibney et al., 2009) and tended to disidentify with the organization (Gibney, Zagenczyk, Fuller, Hester, & Caner, 2011). Hirschman (1970) described voice behaviors as employee attempts to change a situation instead of leaving the situation. Voice was later expanded to include activities such as engaging supervisors and coworkers in discussions about problems in the workplace (Rusbult, Zembrodt & Gunn, 1982) and participation in union activities (Iverson & Currivan, 2003).

The argument for including union participation in voice behaviors is predicated on the employment situation being characterized as dissatisfaction and displeasure with the current work environment (Rusbult Farrell, Rogers & Mainous, 1988). After actively engaging in other voice behaviors such as complaining, employees who are still dissatisfied with the environment will seek the union’s help in addressing the hygiene factors causing displeasure (Freeman & Medoff, 1984; Parkes & Razavi, 2004). This argument suggests that employees participate in union activities to rectify poor working conditions. A rational employee would most likely consider a work environment which is perceived to be detrimental to one’s well-being as characteristic of poor working conditions. Thus, an obstructed employee will aid the union by participating in union organizing activities.

While members may seek assistance from a union to moderate the employee-employer relationship in negative work environments, employees have complex relationships with the organization. Employees can also categorize the employer-employee relationship as caring and supportive and identify with the organization (Eisenberger et al., 1986). When employees believe the organization supports and cares about them, they are more likely to identify with the organization (Gibney et al., 2011). They will perceive a oneness with the organization and may see the union as a threat to their personal identity. In such a manner they will not help the union because helping the union may ultimately lead to damaging themselves psychologically such that negative statements about the organization could be interpreted as negative statements about themselves.

In contrast to looking for help in rectifying a negative work relationship, employees perceiving a positive work relationship are unlikely to feel obligated to help the union. In contrast to obstructed employees, these employees will distance themselves from active participation in union activities in an effort to not adversely impact the positive work environment that already exists. Some researchers have argued that members are likely to go beyond not helping the union and in fact contribute to efforts aimed at actively attempting to decertify the union as working conditions become more positive (Bigoness & Tosi, 1984). Thus, we hypothesize:

Hypothesis 1: Perceptions of organizational obstruction are positively related participation in union activities.

Hypothesis 2: Perceived organizational support is negatively related to participation in

union activities. Social Exchange with the Union and Union Participation

Perceived union obstruction is defined as a member’s belief that the union obstructs, hinders or interferes with the accomplishment of his or her goals and objectives and is a detriment to his or her well-being. This perception will be fostered by treatment received from the union. To the extent that the membership believes that the union obstructs goal attainment and is detrimental to their well-being,


members will be less likely to participate in union events. Cognitive dissonance theory (Festinger, 1957) and the negative norm of reciprocity (Gouldner, 1960) provide the theoretical underpinning of this relationship.

For example, some scholars have argued that unionization reduces a member’s autonomy and as a result their ability to engage in discretionary behaviors (Troy, 2004). As is the case in employer-employee relationships, the union-member social exchange relationship may also be characterized as dissatisfying (Fiorito et al., 1988). Fiorito and colleagues argued and found support for the idea that members develop perceptions that the union may reduce the quality of the working environment. Consistent with research on cognitive dissonance (Festinger, 1957), when the union-member relationship takes a negative tone, members are likely to distance themselves from the union in much the same way that employees distance themselves from organizations that negatively affect employee self-concept (Gibney et al., 2011). This occurs because employees experience tension when they behave in a positive manner towards an organization that they regard negatively. According to the positive and negative norms of reciprocity, individuals do not help those that are perceived to be harming them, but are likely to help those who help them (Gouldner, 1960). Thus, members that perceive the union to be supportive and care about their well-being are more likely to reciprocate by supporting the union through engagement in union activities. A growing body of research consistently finds that members who believe that the union is supportive participate in union activities (Tetrick et al., 2007).

Hypothesis 3: Perceived union support is positively related participation in union activities.

Hypothesis 4: Perceptions of union obstruction are negatively related to participation in

union activities. Social Exchange with the Union and Union Participation

While the “cross-foci” commitment or dual commitment and allegiance research is equivocal (Bigoness & Tosi, 1984), the mediating role of union commitment is significantly clearer (Chan, Snape & Redman, 2004; Sinclair & Tetrick, 1995; Snape & Redman, 2004; Snape & Redman, 2007; Tetrick et al, 2007). The argument is similar to that proposed in the organizational literature: employees look to reciprocate positive treatment through increased commitment which manifests itself in aiding the provider of said treatment by going above and beyond job requirements (Organ, 1988). However, job requirements may not present the opportunity to repay the union for positive treatment. Accordingly, members who feel obligated will look for ways to assist the union in other ways. Such assistance may take various forms including helping other members, attending union meetings and generally speaking favorably when discussing the union with others.

Based upon the positive norm of reciprocity (Gouldner, 1960), members who perceive that the union is committed to them reciprocate with commitment to the union characteristic of a homogeneous exchange relationship. This attitudinal exchange is then manifested in behavior indicative of commitment such as participation and aid directed to the union.

Although these arguments are based on the positive norm of reciprocity, members may also have negative perceptions of their relationship with the union (Bigoness & Tosi, 1984; Fiorito et al., 1998). When members perceive that the union treats them in a negative manner, they are unlikely to be committed to the union’s goals. The reduced commitment will be manifested in reduced participation in union-sponsored activities. Accordingly, we hypothesize that:

Hypothesis 5: Commitment to the union mediates the positive relationship between perceived union support and union participation.

Hypothesis 6: Commitment to the union mediates the negative relationship between

perceived union obstruction and union participation.


METHODS Sample and Procedures

The leaders of a public sector labor union in the eastern United States agreed to participate in the survey, but declined identification of the union in any forthcoming publications. We collected 168 responses from union members. Responses were collected from a small mailing (n=94, response rate 11%) and from attendees at monthly meetings (n=74). The sample was 53% female with an average age of 53 and a mean tenure of approximately 17 years. Approximately 37% of the respondents had completed a college degree (associate, bachelor or graduate degree). Measures

The response format for the union-member and employer-employee social exchange relationships, as well as union commitment scales, was a 7-point Likert scale with endpoints of “Strongly Disagree” (1) to “Strongly Agree” (7) with a midpoint of “Neither Agree\Disagree” (4). The response format for the union participation scale was a four point scale with endpoints of “Very Often” (3) and “Never” (0). Perceived Organizational Obstruction

Gibney et al. (2009) developed the Perceived Organizational Obstruction scale. We selected three items from their scale which are listed in Table 2 due to space constraints imposed by the organization. The items were chosen to cover the main dimensions of the construct: obstruction of work performance, goal attainment and detriment to well-being. Cronbach’s alpha for perceived organizational obstruction in the current sample is .80. Perceived Organizational Support

With space considerations in mind again, we selected three items from the perceived organizational support scale (Eisenberger et al., 1986) that are listed in Table 2. The items were selected to capture the main tenets of the perceived organizational support construct, which purports that the organization values employees’ contributions and cares for employees’ well-being (Eisenberger, et al., 1986). The reliability measure of Cronbach’s alpha for the current sample was .91. Perceived Union Support

We selected three items (see Table 2) with the factor loadings above .71 from the Perceived Union Support scale (Shore et al., 1994). A factor loading of .71 suggests more of the variance in item scores is due to the underlying construct instead of error. Internal consistency for the scale, as measured by Cronbach’s alpha, was .94. Perceived Union Obstruction

We changed the referent of the three perceived organizational obstruction scale items from organization to union to create the perceived union obstruction scale. Cronbach’s alpha for this scale was .86. Union Commitment

We used four items from the loyalty subscale of the union commitment scale developed by Gordon, Philpot, Burt, Thompson, and Spiller (1980; see Table 2). We utilized the loyalty subscale since “most prior research has established loyalty as a primary antecedent” to union participation (Tetrick, Shore, McClurg & Vandenberg, 2007, p. 820). Sherer and Morishma (1989) reported a Cronbach’s alpha of .88 for their seven item scale, whereas Tetrick et al. reported an alpha of .91 for the full ten item loyalty subscale. The internal consistency of the measure we used in this study was .95.


Union Participation We used seven items from Fullagar, Gallagher, Gordon and Clark’s (1995) eleven-item union

participation scale. We modified the scale response format. Fullagar et al. (1995) asked respondents whether the respondent had engaged in the behavior during the past year, whereas respondents in this study were be asked to report whether they performed the behaviors very often, often, hardly ever or never. Cronbach’s alpha for the current sample was .88. Control Variables

We controlled for gender, tenure and age. Gender was coded as 1 for men and 0 for women. Tenure and age were measured in years. We controlled for gender because female members may actually be obstructed by practices such as the glass ceiling. Tenure was controlled since junior members may perceive higher levels of obstruction due to union clauses such right of first refusal. In addition, employees who perceive higher levels of support from the organization are more likely to remain with the organization. Gibney et al. (2009) concluded that treatment by the organization may be more salient to younger workers whereas older employees perceive that organizational events may not directed at them personally. Thus, we controlled for age. In addition, older employees may face some of the same negative treatment that women experience. RESULTS

TABLE 1 DESCRIPTIVE STATISTICS

Correlations Mean Std.

Dev. 1 2 3 4 5 6 7 8 9

Age 52.58 9.55 N\A Gender .42 .5 .00 N\A Tenure 16.74 10.12 .37*** .07 N\A POO 3.77 1.79 -.09 -.07 .14 (.80) POS 3.21 1.87 .27** -.08 .01 -.41*** (.91) PUS 4.44 1.76 -.06 -.13 .10 .01 .12 (.94) PUO 2.30 1.56 .04 .17 .02 .23* -.09 -.40*** (.86) Union Commitment

5.34 1.78 .00 -.02 .14 -.08 .11 .65*** -.60*** (.95)

Union Participation

1.72 .80 -.08 .12 .17 .34*** -.18 .30** -.26** .40*** (.88)

Notes: Cronbach’s Alpha reported on diagonal in parentheses, *** Correlation is significant at the 0.001 level, ** Correlation is significant at the 0.01 level, * Correlation is significant at the 0.05 level

The means, standard deviations and bivariate correlations were calculated and are presented in Table 1. All union social exchange variables were significantly correlated with union participation as well as perceived organizational obstruction, but perceived organizational support was not significantly correlated with union participation. We assessed the discriminant validity of the constructs using the bivariate correlations. We used Morrow’s bivariate correlation criterion of .8 for construct redundancy (Morrow, 1983). The results presented in Table 1 suggest that respondents distinguished between positive and negative social exchange perceptions with and between the union and employer.


Before proceeding with hypotheses testing, we chose to evaluate if respondents distinguished between social exchange perceptions with the union and the organization. That is, within each social exchange relationship, we included positive and negative social exchange perceptions. We included union commitment perceptions to aid in evaluation of the degree to which single source bias influenced our results.

Nunnally (1978) suggested a ten to one item-respondent ratio for factor analysis. Thus, our study meets this criterion and we continued with our analysis. The sixteen items included in the factor analysis are presented in Table 2.

TABLE 2 FACTOR ANALYSIS

Item Factor

Union Commitment

Perceived Union Support

Perceived Organizational Support

Perceived Union Obstruction

Perceived Organization Obstruction

My organization is a detriment to my well-being. .02 .01 -.27 .17 .75

The organization gets in the way of my performance.

-.02 -.01 -.14 .05 .88

My goal attainment is thwarted by the organization.

-.03 .03 -.11 .04 .91

My organization really cares about my well-being.

-.01 .05 .91 -.03 -.16

My organization values my contributions to its well-being.

.15 .02 .89 -.07 -.18

My organization strongly considers my goals and values.

-.05 .12 .90 .04 -.17

The union strongly considers my goals and values.

.35 .86 .02 -.09 -.06

My union considers my best interests when it makes decisions that affect me.

.40 .83 .14 -.13 .06

My union really cares about my well-being. .33 .86 .09 -.20 .06 My union is a detriment to my well-being. -.11 .00 -.05 .88 .09 The union gets in the way of my performance. -.33 -.28 .01 .79 .14 My goal attainment is thwarted by the union. -.36 -.19 -.02 .83 .08 There’s a lot to be gained by joining the union. .90 .30 .03 -.18 -.02 Deciding to join the union was a smart move on my part.

.85 .30 .01 -.26 .01

I feel a sense of pride in being part of the union. .82 .32 .02 -.28 .01 Based on what I know now, and what I believe I can expect in the future, I plan to be a member of the union for the rest of the time I work for the company.

.85 .24 .04 -.16 -.04


The factor analysis utilized an extraction method of five factors – as compared to eigenvalues greater than one- with varimax rotation. This methodology was chosen, instead of completely exploratory extraction, because theory would suggest the existence of five factors since the larger scales from which the items were selected have been validated in previous research, except for PUO. All items loaded on the appropriate construct with an item-factor correlation of at least .71. No item exceeded the cross-loading item-factor correlation criterion of .4. Thus, confirming our expectations based upon prior research and analysis. The scales exhibit acceptable degrees of internal consistency (see Table 1). From these results, all items were retained for further analysis. We therefore concluded that respondents distinguished between items and responded to similar items in a similar fashion. However, this does not mean that the two different sources of data were invariant in responding to the independent variables in question. We therefore compared the two groups before continuing with our analysis.

Before combining the data, we checked for item invariance across the subsamples on the sixteen survey items which comprised the independent variables. The respondents differed in their response pattern to two items, one perception of union support item (chi square 22.65, 6 df, p<.001) and one perception of union obstruction (chi square 18.22, 6 df, p<.01), of the sixteen items.

Due to these differences in the response patterns, we decided to evaluate whether differences in the mean levels of perceptions of support and obstruction existed. We therefore created an index variable for perceived union support and perceived organizational obstruction. The results of an ANOVA provided mixed results. We ran the regressions for each of the subsamples. The same hypotheses found support in each of the subsamples at the same level of significance. However, the beta values changed. The results of the ANOVA found that members attending the meeting perceived higher levels of support, but no there was no significant differences in the mean of perceptions of obstruction between these groups.

Based upon the results of our analyses, we decided to proceed with hypotheses testing by treating the subsamples as a single sample. All hypotheses were tested using hierarchical regression analysis using Baron and Kenny’s (1986) methodology for testing mediation. We utilized a three-step regression model. In the first step, we entered demographic variables of age, gender and organizational tenure. Hypotheses 1 through 4 were tested using the second step of the regression which when the social exchange variables were entered. The regression results are presented in Table 3.

TABLE 3 RESULTS OF REGRESSION ANALYSIS

Predictors Union Participation Union Commitment Step1: 1 2 3 1 2 Demographic Variables Age -.16 -.05 -.05 -.07 .01 Gender .11 .22* .18* -.03 .12 Tenure .22* .10 .08 .17 .08 Adjusted R2 .03* -.01 Step 2: Independent Variables Perceived Organizational Obstruction .39*** .38*** .04 Perceived Organizational Support -.04 -.06 .04 Perceived Union Support .19 .06 .47*** Perceived Union Obstruction -.32*** -.20 -.44*** R2 Change .26*** Step 3: Mediator Union Commitment .27* R2 Change .03* .56*** Notes: *** Correlation is significant at the 0.001 level, ** Correlation is significant at the 0.01 level, * Correlation is significant at the 0.05 level


We found mixed support for our hypotheses in the second step of our regression analysis. Hypothesis 1 stated that POO would positively predict participation in union events. We found support for this in the third step of the regression (β = .39, p ≤ .001). Hypothesis 2, which stated that POS would be negatively related to union participation, was not supported (β =-.04, p > .05). Union participation was positively and but not significantly related to perceived union support (β = .19, p > .05). Thus Hypothesis 3 was not supported. Perceived union obstruction was negatively related to union participation (β = -.32, p ≤ .001) in support of Hypothesis 4.

We used the criteria established by Baron and Kenny (1986) to determine if mediation effects existed: (a) a significant association between the independent variable and the mediator variable, (b) a significant association between the mediator variable and the dependent variable, (c) a significant association between the independent variable and the dependent variable, and (d) an insignificant (full mediation) or reduced effect (partial mediation) for the independent variable on the dependent variable when the mediator variable is held constant.

The first requirement for mediation was met for perceived union support and perceived union obstruction (see Table 3). Both perceived union support and perceived union obstruction were significantly associated to the mediator variable (union commitment (PUS: β = .47, p ≤ .001; PUO: β = -.44, p ≤ .001). The second requirement for mediation was also met, as union commitment was significantly related to union participation (β = .04, p ≤ .05). Support for the third requirement for mediation, a significant correlation between the independent variable and the dependent variable, was obtained for perceived union obstruction (Hypothesis 4), but not perceived union support (Hypothesis 3). The fourth step in the test for mediation, which requires that the independent variable not influence the dependent variable after the mediator is entered into the regression equation, was also met. When union commitment was entered in the equation in step 3, the PUO-union participation (β = -.20, p >.05.) became insignificant in the presence of union commitment. Thus, commitment to the union fully mediated the PUO-participation in support of hypothesis 6. Hypothesis 5 was not supported because Hypothesis 3 was not supported. DISCUSSION

The results of this study provide evidence which generally supports the notions that: (a) union members develop perceptions which capture negative aspects of the social exchange relationships that they maintain with their unions and these perceptions go beyond perceptions of support; (b) perceptions of the employer-employee social exchange relationship influence member’s behavior in union activities; and (3) negative relationships have a greater influence than positive relationships.

While in different directions, the negative perceptions of PUO and POO were the strongest predictors of union participation. Employees and members seem to respond more strongly to negative treatment from the organization and the union. The relatively modest response to positive encounters suggests that negative campaigning works. As such, union leaders should continually emphasize the negative treatment from the organization. While focusing on the negative treatment from the organization, it would also be wise to occasionally point out some of the supportive treatment that the union provides.

Interestingly, while it also wise for corporate management to point out negative treatment from the union, executives need not point out positive treatment from the organization. This would lead to negative campaigns against one another. While our results suggest this would be an effective strategy, it should be used judiciously. Voice is only one response to dissatisfying working conditions (Rusbult et al., 1988). The employee\member may perceive that the only recourse to escape negative treatment from the organization AND the union is leave the organization. By terminating employment, the employee\member ceases being treated negatively by both the union and the employing organization.

One might expect such a response based upon the negative norm of reciprocity (Gouldner, 1960) which posits that individuals return negative treatment with negative treatment. The voluntary termination from a union environment simultaneously causes a loss of dues and fees to the union and increased replacement costs to the organization. In comparison to other retaliatory behaviors such as deviant


behaviors (Skarlicki & Folger, 2004), the union and organization may well be better off if the employee\member terminates the working relationship. Future research should explore the relationship between retaliatory behaviors directed at the union and organization in response to perceived negative treatment.

Iverson and Currivan suggested that researchers “rethink the tenuous link that unions create job dissatisfaction” and “focus on within differences” on union members (2003:105). Our results suggest possible area for this research. The evaluation of employee and member social exchange relationships with the union and organization may provide fertile ground for understanding the mechanisms of union participation and voluntary termination in organizations.

Our findings support and expand the current model of social exchange relationships and behavior in the organization. Snape and Redman (2007) posited that a positive social exchange relationship with the organization would be related to positive, discretionary behavior directed at the union (union citizenship behaviors). They did not find support for this relationship. The results of the current study did not evidence a relationship between perception of the social exchange relationship with the organization and positive, discretionary behaviors directed at the union (union participation). Our results expand this research stream by indicating that a negative relationship with the organization is likely to motivate employees to help the union.

This study also provides support for the consistent finding that union commitment is an antecedent to union participation (Bamberger, Kluger & Suchard, 1999; Fuller & Hester, 2001; Snape & Redman, 2007; Tetrick et al., 2007). Tetrick et al. (2007) evaluated different union participation models regarding social exchange. These researchers concluded that union commitment and loyalty mediated the relationship between PUS and participation in union events. Our results support and extend their findings. First, we found that union commitment mediated the PUS-union participation relationship. Second, we expand their research findings by demonstrating the mediating effect of perceived union obstruction, a negative social exchange relationship with the union.

Interestingly, Gibney et al. (2009) found that POS was significantly correlated with loyalty behaviors in an organizational context, while Tetrick et al. (2007) found a similar relationship in a union context. However, POO was not significantly correlated with loyalty in an organizational context, but PUO was related to union commitment in the current study. This suggests that the social exchange relationship between union members and the union is more complex than anticipated. These seemingly counterintuitive findings may derive from the nature of the employer-employee relationship relative to the union-member relationship. First and foremost, employees are paid for participation in the employment relationship through salary and wages, whereas members pay for participation in union activities through dues and fees. This inherit difference could be at the root of the difference in results. In addition, members may have different expectations regarding the union-member relationship. One of the best predictors of unionization is employee dissatisfaction. The expectation is that unions will rectify the problems encountered by employees. When they fail to fulfill these obligations, members may react adversely by withholding commitment and participation from the union. Future research should include measures of the obligations that unions and members owe one another and the degree to which these mutual obligations are met (Rousseau, 1995; Tetrick 1995). Limitations and Future Research

The major limitation of this study is the cross-sectional research design that we employed. This design prohibits us from drawing causal inferences for the directionality of the relationships between variables. For example, it is possible that members who participate in union activities believe that the union supports them to avoid cognitive dissonance. Thus, future research should employ longitudinal designs to assess this and other possibilities.

Another potential source of concern with the present research might be the use of self-reports. Respondents might have stated that they engaged in support activities if they perceived the union supported them. On the other hand, in the obstruction condition, individuals may deny helping a union


that treats them negatively. Future research should collect union participation information from shop stewards or other union members.

Finally, the data were collected from members of a single union within the United States through a mailing and meeting attendance. The subsamples also indicated that respondents differed in the response pattern to two items of the sixteen items in the survey. However, post-hoc analysis confirmed the pattern of results across the samples, but the results of the ANOVA suggested differences in the response pattern could affect the data. Since some of the data were collected at meetings and some were collected through a mailing, the results of this study should be viewed with caution. These factors could limit the generalizability of the analysis. Future research should use members from multiple unions and members from outside of the United States to increase generalizability.

Our results suggest that future research regarding union commitment and union participation should include not only union instrumentality, but also the applicable social exchange variables. For example, social exchange studies of union commitment and participation should include both PUO and PUS. CONCLUSION

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The Impact of Exit Decisions on Successful R&D Alliances

David Epstein University of Houston Downtown

Robert T. Keller

University of Houston

In this paper, we focus on the impact of exit decisions on successful R&D alliances. Specifically, we investigate how product exit choices influence the firm’s entry into successful strategic alliances. This longitudinal study examines 10 years of product development in the pharmaceutical industry over a sample of 87 firms. Our findings reveal that firms exiting declining research fields are more likely to form successful R&D alliances than firms expanding into these declining fields. INTRODUCTION

Conditions of alliance success and failure have interested scholars for some time (Anand & Khanna, 2000; Kale & Singh, 2001; Kogut, 1988; Park & Ungson, 2001). Some causes of alliance success have included defining the scope of the alliance in advance, complementary assets, and co-opetitors capabilities (Afuah, 2000, Khanna, 1999; Rothaermel, 2001). Success in new product alliances has also been studied. Findings have included the benefit to small firms of engaging in R&D alliances, the importance of advocacy within the firm, and the type of innovation by first movers and followers in product markets (Green, Welsh, & Dehler, 2003; Kalaignanam, Shankar, &Varadarajan, 2007; Robinson & Chiang, 2002). While this research has examined some of the conditions for success in new product alliances, no research currently examines how the firm’s exit decisions enhance the likelihood of successful R&D alliances. The purpose of this study is to consider the impact of choices made within the firm with regard to research exit and how those decisions impact the firm’s entry into R&D alliances. As such, our understanding of alliances will be enhanced by considering how exit from a research area may actually be a positive factor in alliance success. This study also provides several methodological contributions. Measures are developed from patent data for exit decisions. Finally the paper uses a longitudinal dataset which creates a stronger foundation for causality. LITERATURE REVIEW

Alliances are voluntary arrangements between two or more firms, often with competing interests and multiple purposes, which involve sharing resources and knowledge with the purpose of developing products, processes, or services (Gulati, 1998; Sampson, 2005). In the context of the current study, patentable products are developed by the partners through cooperative research and represent R&D alliances.


Although alliances offer promise to businesses that use these arrangements, these alliances often fail (Kogut, 1998). In fact over 40 percent of alliance partners are dissatisfied with the result of their business arrangement (Bleeke & Ernst, 1993). Causes of this failure may include coordination challenges, governance issues, poorly defined scope and fundamental conflicts of interest (Kogut, 1998; Oxley & Sampson, 2004; Sampson, 2005).

Elements leading to alliance success have also been studied. Prior alliance experience with specific partners, general alliance experience with other partners, behavioral uncertainty, firm age of alliance participants and possession of complementary assets have all been related to alliance success (Anand & Khanna, 2000; Lai & Chang, 2010; Rothaermel, 2001; Rothaermel & Boeker; 2008, Sampson, 2005). In the following section we consider the impact of the firm’s order of entry on subsequent alliance success. THEORY AND HYPOTHESIS Product Development, Product Exit, and R&D Alliances

In this section we explore the relationship between exit from research in technological fields and the formation of R&D alliances. More specifically we address the question whether firms that exit from declining research areas are more likely to form successful R&D alliances. Dosi (1988) discusses several ways that organizations develop knowledge bases. The most common method to increase technological knowledge in the firm is through in house R&D. Firms develop products along a particular trajectory which is influenced by prior events. Development of products along a particular trajectory increases the organizations ability to innovate in that direction (Sydow, Schreyogg, & Koch, 2009).

Grant (1996) also observes that firms can coordinate knowledge more efficiently in many instances. She suggests that when firm’s product and knowledge bases are not well aligned, opportunities exist to exchange knowledge outside the firm.

Little research has explored factors influencing the firm’s exit in research fields; however some related research on product markets has been conducted. The following discussion and arguments are based on the fact that product development and exit involve various subcomponents. One example of this can be found in research activity that leads up to the actual product. Clearly there is not a one to one relationship between research activity and product development; however that activity is nevertheless indicative of the organizations technological trajectory and goals with regard to product development.

Green et al (2003) finds that products having greater levels of management advocacy are less likely to be terminated. Management advocacy is also influenced by resource investments and technical and business experience related to the product. De Figueiredo and Kyle (2006) observe that competition increases the likelihood of product exit. They further find that more innovative products have a lower exit rate. Competition may be fierce in high tech industries such as pharmaceuticals. This suggests that product exits will occur with relatively greater frequency. Counterbalancing this is that exit from more innovative products will occur more slowly. One response to competitive pressures within an industry is to form alliances (Gimeno, 2004). Additionally the need to develop new products should increase the value and likelihood of alliance formation (Gerwin & Ferris, 2004). If less innovative products are being dropped then it seems likely that firms will seek to develop more innovative products than the ones they discontinued. However the development of new products may require the change of the firm’s current technological trajectory and movement into new technological fields.

Uncertainty also influences alliance formation when technological uncertainty and government regulation is high (Lopez-Gamero, Molina-Azorin, & Claver-Cores; Tushman & Anderson, 1986). When firms exit product markets, their need to replace products introduces technological uncertainty. One option for addressing technological uncertainty is to share the risks of research with a partner. Thus the uncertainty arising from the firm’s movement out of familiar technological fields should encourage the firm to seek R&D alliances. Decentralization can further enhance innovation by engaging multiple sources of information and enhancing interaction (Damanpour, 1991). Decentralization may also enhance knowledge production within firms (Pertusa-Ortega, Zaragoza-Saez, & Claver-Cortes, 2010). Firms exiting product markets often need to produce new knowledge within the firm. Similarly, alliances can be


a productive form of decentralization. Taken together, the need to produce new knowledge within the firm as a result of product exits will enhance the need to decentralize through alliances.

More generally what do firms signal when they build on their existing technological base or exit from product markets? They might be signaling their satisfaction or dissatisfaction with the product development process. When innovation in a specific area increases, firms may be implying that they are satisfied with their expertise in that area and wish to continue development (Sydow et al, 2009). Conversely firms exiting product markets may be implying that they lack the expertise or resources to continue innovation in that area or simply their belief that exiting unproductive technological fields may free up resources for innovation in other areas.

Firms exiting existing product markets may free up resources to be used on other projects. The first place for firms to look would be in house R&D. However the needed knowledge and resources may be lacking within the firm. In these instances firms may have sufficient incentive to engage in R&D alliances in spite of the risks of knowledge appropriation by other firms. On the other hand, firms building on existing product knowledge possess fewer reasons to risk losing their valuable knowledge to potential partners.

Hypothesis 1: Firms exiting early from research in declining product development fields

in the pharmaceutical industry will form more successful R&D alliances than firms that exit research later from these fields.

METHODS Sample

The sample consists of publicly traded firms in the pharmaceutical industry (SIC codes 2833 and 2834). This industry is a subset of the industries used by Schilling and Phelps (2007) in their study of interfirm collaboration networks. They specifically chose firms from industries designated as high technology by the Bureau of Labor Statistics. These firms were chosen for two reasons. This study examines product exit choices; therefore choosing an industry that has a moderate to large amount of product development occurring is essential in order to examine its effect on alliance formation. Secondly, patent data are used to determine measures of product development. Therefore, it is essential that firms in the selected industry file patents so that other measures can be constructed from the patent data.

Companies were chosen that had data available in January 1997 on Mergent Online. Mergent Online provides a database of 15,000 U.S. companies listed on the NYSE, AMEX, and NASDAQ exchanges. This database consists of active and inactive firms. The list of firms chosen from Mergent was accessed by SIC code and year selections. Firms in this study were listed as United States businesses or businesses whose primary headquarters was located in the United States. The primary purpose in choosing firms based in the United States was to control for cultural differences across countries that might influence alliance formation. Dependent Variable

The dependent variable in this study is total partnerships formed. In this study partnerships represent R&D alliances that produced patents. As a result, this variable defines successful R&D alliances rather than R&D alliances in general since such alliances are not guaranteed to produce patentable results. The partnerships were obtained from the patents filed. When multiple company names appeared in the assignee field, these were treated as partners in that specific patent. In this study, the concern is with alliances formed outside of the company. Therefore, alliances formed between the company and its subsidiary or permanent joint ventures were not included in this measure. All partnerships consist of two or more companies that are separate entities. Partnerships are considered to be dyadic. Therefore, when these partnerships consist of more than two entities, all two party combinations are included in the partnership count. Thus a three party alliance contains three two party combinations.


Independent Variables The independent variable chosen for the study of R&D alliance formation is product exit. This

variable is measured using structural decomposition analysis (SDA). SDA is an econometric technique that is designed to isolate the elements of change. The development of these measures followed the work of Mendonca and Fai (2007). The authors measure technological change using patent data from high technology industries. In the original paper, these measures were constructed for industries, however in the current study; our measure of product exit replaces industry with firms. At the firm level, Mendonca and Fai’s variables can be used to examine product exit choices. The measure is calculated as follows:

t-1, t = subscripts for initial year and final year of the period under consideration Let p = a patent class (1….N) j = a firm (1…N) t = year (1…10) i = industry (1..3)

τ = technologies share of patents in the patent class. kp

=τ where k is the total of all patents.

φ = firm j’s share of all patents in a patent class. φ = pp j

The following equation defines the measure:

))(( 111

−−−−=∑ ptptptpt

N

pφφττ for a firm j in an industry i.

The measure for exit from a declining research field is represented by the extent to which firms have

lost total share of patents through movement out of the declining fields referred to as product exit. When the second term is negative, product exit is measured. The measure represents decreases in the patent share of a product class in the technological environment from the previous period. When the first term is also negative, the firm is decreasing their share of a patent class from the previous period. Taken together the equation represents the decline of the firm’s technology in a specific area when the share of patents in the in that technological area is decreasing. When both terms are negative, the firm is exiting from a declining technological field. However when the first term is positive, it shows that the firm is increasing their patent holdings in a declining technological field. When the number resulting from this equation is positive, firms are exiting from declining research fields.

Mendonca and Fai (2007) reduced the patent classes into 9 broader classes. However in the current study, the actual patent classes provided by the United States Patent and Trademark Office (USPTO) are used to avoid contamination of the measure by misclassification. The data for these measures is obtained from the USPTO. First total patents issued by year are obtained. Next, total patents per year for each class that any firm in the database filed is determined. Finally the total number of patents filed by each firm in each class in each year is obtained. From this data, exit is measured. Control Variables

Ahuja (2000) suggests a number of control variables that might affect alliance formation. Four of those variables are included in this study. Current ratio controls for financial liquidity and is the ratio of current assets to current liabilities. Ahuja suggests that the desire for liquidity might drive firms into partnerships. Return on assets (ROA) represents financial performance. Financial performance might influence firms to engage in partnership activity, either in order to improve that performance or perhaps as an indicator that the firm has the financial ability to follow through on partnership obligations. The third variable included is debt/equity ratio which measures the leverage characteristics of the firm. The


amount of leverage might affect partnerships linkages due to the need to spread commitment by engaging in partnerships. The fourth variable, solvency indicates long term commitments of the firm (Gulati, 1995). Businesses engaging in long term projects with uncertain returns, a common occurrence in the pharmaceutical industry, might engage in partnerships to reduce the risk associated with long term commitments and the uncertainty associated with those commitments. Financial data for current ratio, ROA, debt/equity and solvency are obtained from Mergent Online. In some instances data are unavailable for certain companies in a given year. In these instances, additional information about the indicators is obtained by calculating the ratios from balance sheet data supplied by Compustat. Calculated results are compared to Mergent Online results for the same indicators to ensure that the indicators are calculated consistently. Total patents are also used as a control variable in this study since patents are used to obtain information about partnerships, location, and prior experience. It seems reasonable that firms filing more patents will also have more partnerships and more prior partnerships.

Proximity to partners is also added as a control variable. Closer proximity also benefits those firms by lowering coordination costs such as travel by key employees and shipping needed supplies (Porter, 1998). The ability to work closely with suppliers and complementors lowers the need for vertical integration. Proximity may also lead to closer relationships through better communication. Rich communication channels resulting from face to face meetings could enhance information exchange Individuals in clusters additionally may interact with each other in social situations since they live in close proximity. Familiarity in multiple contexts with individuals from other firms may lead to trust. Trust in turn may increase the possibility that firms will form alliances with one another (Uzzi, 1996, 1997). Distance was measured two ways. First distance was measured as a dichotomous variable with 1 indicating the partner firms were within 50 miles of each other. Additionally, the actual distance was obtained from the website www.geobytes.com/citydistancetool.htm.

Finally, prior alliances are added as a control variable. Firms with prior experience in partnerships are more likely to have developed expertise in working with those partners (Li, Eden, Hitt, & Ireland, 2008). This expertise may take the form of routines or even tacit knowledge about how best to work with others to develop new products. Familiarity and expertise reduce uncertainty and make risk sharing with other firms more likely to succeed. In this study, the total number of prior alliances that were repeated in the current year was totaled for each year for each firm. Model and Estimation

The dependent variable in this study, total partnerships is a positive count variable with a mean of .77 and a variance of 2.4. OLS regression is generally considered inappropriate when the dependent variable exhibits overdispersion. Two alternatives to OLS are Poisson and negative binomial regression. Poisson regression assumes an equal variance and mean while negative binomial regression has been developed to handle forms of count data when the assumptions of Poisson regression are not met as in the current study (Greene, 1997). Negative binomial distribution takes the form: εβλ += ii x'ln . The disturbance term ε can reflect specification error or cross-sectional heterogeneity, iλ represents the mean and variance of the distribution, and ix is a vector of regressors.

In the context of panel analysis, another choice must be made between random and fixed effects. The general form of the panel regression equation is iiiit Xiy εβα ++= (Greene, 1997). The difference between fixed and random effects is determined by the approach taken to the term iα which represents the individual effect. In random effects models, α is a group specific disturbance in which a single draw enters the regression identically in each period. The random effect model preserves degrees of freedom but assumes that individual effects are uncorrelated with other regressors. Conversely, the fixed effects model assumes that the individual effects are unknown parameters that must be estimated. Fortunately, the Hausman test allows one to determine which model is more appropriate (Greene, 1997). The null hypothesis that random effects was appropriate was rejected (p=.0106). Therefore the model used in this analysis is a fixed effects negative binomial model. Finally, the model uses an unbalanced panel design.


In unbalanced designs, groups may be missing data and group sizes may vary. Stata 10 is used to conduct all statistical analysis and provides routines to conduct the model analyses. RESULTS Descriptive Statistics

Table 1 reports descriptive statistics for the study variables. Two of the product development variables, early movers and followers are significantly related to total patents which make sense given that patent data was used to generate these variables. However the other two product development variables product development and product exit are not significantly related to total patents. Among the control variables, current ratio, return on assets and total patents are significantly related to total partnerships. Current ratio is a measure of liquidity and suggests that lower liquidity may be associated with R&D partnership formation since the coefficient is negative. ROA is positively associated with total partnerships suggesting that the size of the firm in financial terms may promote R&D partnerships.

TABLE 1 DESCRIPTIVE STATISTICS AND CROSS-LEVEL CORRELATIONS A

Variable Mean s.d. 1 2 3 4 5 6 7 1. D/E .41 5.14 1 2. Solvency .38 .75 .07 1 3. CR 5.43 6.86 .01 0.16*** 1 4. ROA .03 .03 .06 1 5. Distance 1881 1833 -.06 .12 -.01 -.08 1 Location .353 .48 .04 -.10 -.01 .13 -.53*** 1 7. Prior .62 .49 -.11 -.05 .14 -.06 .04 -.08 1 8. Total Patents

13.65 38.12 .02 -.05 .14*** .12* -.13 .17 -.04

9. Product Exit

.00 .002 .00 -.01 -.07 .06 -.09 .03 -.04

10. Total partnerships

.77 2.39 .03 .03 -.07* .08* 0 -.02 .15

an=870 * p<.05 ** p<.01 ***p<.001

Variable 8 9 10 8. Total Patents

1

9. Product Exit

.20*** 1

10. Total partnerships

.23*** -0.03 1


TABLE 2A

NEGATIVE BINOMIAL MODELS WITH FIXED EFFECTS FOR R&D PARTNERSHIP CREATION

Variables Model 1 Model 2 Constant 16.43 548.76 17.24 994.28 Independent Product exit 50.23** 16.14 Control D/E 0.003 0.012 0.07** 0.01 Solvency -.025 .125 -.027 .125 CR -.006 .015 -.0008 .018 ROA .004 .003 .004 .003 Location .277* .134 .263† .134 Distance .000 .000 .000 .000 Prior .078*** .008 .092*** .010 Total Patents .001 .001 .001 .001 df 7 8 Log Likelihood -199.17 -185.12 Log-Likelihood ratio 28.1 Wald Χ2 110.42 113.00

n=119 † p<.10 * p<.05 ** p<.01 Regression Models

The results of the fixed effects negative binomial regression analysis are reported in Table 2. Model 1 is the controls only model while model 2 adds the product exit variable. Model fit is significantly improved when product exit is added to the control variables.

In both models, prior experience with alliance partners is significantly related to the likelihood that firm’s will have more total partnerships. In both models, location and prior experience are significantly related to total partnerships. Model 2 supports hypothesis 1 that exit from declining research fields is related to successful R&D partnerships (β=. 50.23 p< .01). The positive coefficient indicates that when firms are decreasing their holdings in a declining technological field, they form more R&D alliances that produce patents. DISCUSSION

In this study we enhance our understanding of strategic orientation, R&D alliances and innovation. The ability to exit from unproductive products increases the likelihood of entering successful R&D alliances. Firms that adapt to changing market conditions in the form of exiting unproductive fields may hold a competitive advantage over less nimble competitors within their industry due to their ability to form more productive R&D alliances. Alliances and networks provide instances where groups of firms work together for a common goal. Exiting declining technological fields makes firms into more attractive partners. For these firms, the awareness of the inadequacy of previous products produces a sufficient incentive to seek alliance partnerships.


Importantly, these firms are entering successful R&D alliances. Sampson (2005) observes that alliances may face considerable coordination challenges, uncertainty, and cultural differences. Thus the success of alliances in this study is all the more remarkable. It may be that the pressure of leaving familiar technological fields and using slack resources outweighs the problems typically associated with alliances.

Among control variables, prior experience with partners was a highly significant predictor of total partnerships. Two elements might cause this relationship to occur. First firms seem to find it easier and possibly safer to ally with known partners rather than to venture into new alliances. Familiarity breeds trust which increases alliance effectiveness making future alliances more sensible (Perry, Sengupta, & Krapfel, 2004). When these alliances occur repeatedly, they contribute to the total number of partnerships. Thus total partnerships represent a way of doing business for firms that repeat alliances with known partners. Secondly, it may be that managerial styles are represented by the use of prior partners such that these decision makers are more oriented to developing partners and sharing the glory and benefits of R&D discovery. Additionally firms that engage in frequent alliances may have a developed ability to handle alliances in terms of coordination and cultural issues. Some firms have a department dedicated to alliances for instance. Another interesting finding comes from the theory of clusters (Porter, 1998). In this study, actual distance was not related to alliances but the dichotomous variable that measured whether firms were within 50 miles of each other was significant. Normally a continuous variable provides more information than a dichotomous variable, however close proximity seems to be important here. Firms that were within 50 miles of each other formed more successful R&D alliances suggesting that physical proximity does benefit successful alliances since members of the firm can interact with each other more readily.

A limitation of the study is the somewhat small size of the sample that may have hindered the ability to find more significant relationships. Additionally, focusing on pharmaceuticals may fail to uncover important industry effects. Further, the firms used in this study had publicly available information. This precludes privately held firms. However it seems reasonable to believe that the publicly held firms filed more patents and engaged in more R&D partnerships which were the variable of interest in this study. We also incorporated product development variables at the firm level that in Mendonca and Fai’s (2007) study were previously incorporated as technological change variables at the industry level. It might be argued that the relationship between the industry and the firm level are quite different and that the product development construct might have a different meaning. Nevertheless, the product development variables measure changes in the patenting patterns within the firms studied and provides valuable information not previously available. It might be interesting to consider the broader technological change environment in concert with the product development construct. In this instance, multilevel models over time could produce important discoveries.

On the positive side, this study uses a longitudinal design that allows two elements in the chain of causality to be examined. First the study determines which items covary and the study also examines the change over time in those relationships. Secondly, the inclusion of a ten year period allows the pharmaceutical industry to experience more than one historical change or event reducing the possibility of historical bias which could result from a cross sectional study. Third, the element of product development order of entry and exit are added as possible antecedents to alliance formation. This is also the first time that product exit choices have been used in the context of R&D alliances. Finally, understanding the antecedents of successful R&D alliance formation may inform decision makers about the reasonableness of forming partnerships with other firms and entities. REFERENCES Afuah, A. (2000) How much do your co-opetitors’ capabilities matter in the face of technological change? Strategic Management Journal, 21, (3), 387-404. Ahuja G. (2000). The duality of collaboration: inducements and opportunities in the formation of interfirm linkages. Strategic Management Journal, 21, (3), 317–343.


Anand B, Khanna T. (2000). Do firms learn to create value? The case of alliances. Strategic Management Journal, 21, (3), 295–315. Bleeke, J., & Ernst, D. (1993). Sleeping with the enemy. Harvard International Review 15, (4), 12-15. Lopez-Gamero, M., Molina,-Azorin, J., & Claver-Cortes, E. (2011). Environmental uncertainty and environmental management perception: A multiple case study. Journal of Business Research, 64, (4), 427-435. Damanpour, F. Organizational innovation: A meta-analysis of effects of determinants and moderators. (1991). Academy of Management Journal, 34, (3), 820-842. Dosi, G. Sources, procedures, and microeconomic effects of innovation. (1988). Journal of Economic Literature 26, (3), 1120-1171. Gerwin, D., & Ferris, J. (2004). Organizing new product development projects in strategic alliances. Organization Science, 15, (1), 22-37. Gimeno, J. (2004). Competition within and between networks: The contingent effect of competitive embeddedness on alliance formation. Academy of Management Journal , 47, 820-842. Grant R. (1996). Toward a knowledge-based theory of the firm. Strategic Management Journal, 17, 109–122. Green, S., Welsh, A., & Dehler, G. (2003). Advocacy, performance, and threshold influences on decisions to terminate new product development. Academy of Management Journal , 46, (4), 419-434. Greene, W. H. (1997). Econometric analysis (5th Ed.). Upper Saddle River, NJ: Prentice Hall. Gulati, R. (1995). Social structure and alliance formation patterns: a longitudinal analysis. Administrative Science Quarterly, 40, (4), 619-652. Kale, J., & Singh, P. (2001). How to make strategic alliances work. MIT Sloan Management Review, 42, (4): 37-43. Kalaignanam, K., Shankar, V., and Varadarajan, R. (2007). Asymmetric new product development alliances: Win-win or win-lose partnerships? Management Science, 53, (3), 357-374. Khanna, T. The scope of alliances. (1998). Organization Science, 9, (3), 340-355. Kogut, B. (1988). Joint Ventures: Theoretical and empirical perspectives. Strategic Management Journal, 9, (4), 319-332. Lai, W., & Chang,P. (2010). Corporate motivation and performance in R&D alliances. Journal of Business Research, 63, (5), 490-496. Li, D., Eden, L., Hitt, M., & Ireland, D. (2008). Friends, acquaintances, or strangers? Partner selection in R&D alliances. Academy of Management Journal, 51, (2), 315-334.


Mendonca, S., & Fai, F. (2007). Decomposing technological change at the twilight of the twentieth century: evidence and lessons from the world’s largest innovating firms. Innovation Management, Policy and Practice 9, (3-4), 311–323. Oxley, J., & Sampson, R. (2004). The scope and governance of international R&D alliances. . Strategic Management Journal, 25, (8-9), 723-749. Park, S., & Ungson, G. (2001). Interfirm rivalry and managerial complexity: a conceptual framework of alliance failure. Organization Science, 12, (1), 1237-53. Perry, M., Sengupta, S., & Krapfel, R. (2004). Effectiveness of horizontal alliances in technologically uncertain environments: are trust and commitment enough? Journal of Business Research, 57, (9), 951-953. Pertusa-Ortega, E., Zaragosa-Saez, P., & Claver-Cortes, E. (2010). Can formalization, complexity, and centralization influence knowledge performance? Journal of Business Research, 63, (3), 310-320. Porter, M. (1998). Clusters and the new economics of competition. Harvard Business Review, 76, (6), 77-90. Rothaermel, F. (2001). Incumbent’s advantage through exploiting complementary assets via interfirm cooperation. Strategic Management Journal, 22, (6-7), 687-699. Rothaermel, F., & Boeker, W. (2008) Old technology meets new technology: complementaries, similarities, and alliance formation. Strategic Management Journal, 29, (1), 47-77. Sampson, R. (2005). Experience effects and collaborative returns in R&D alliances. Strategic Management Decision, 26, (11), 1009-1031. Schilling, M., & Phelps, C. (2007). Interfirm collaboration networks: The impact of large-scale network structure on firm innovation. Strategic Management Journal, 53, (7), 1113-1126. Sydow, J., Schreyogg, G., & Koch, J. (2009). Organizational path dependence: opening the black box. Academy of Management Review, 34, (4), 689-709. Tushman, M., & Anderson, P. (1997). Technological discontinuities and organizational environments. Administrative Science Quarterly 31, (3), 439-465. Uzzi, B. (1996). The sources and consequences of embeddedness for the economic performance of organizations: the network effect. American Sociological Review, 61, (4), 674-698. Uzzi, B. (1997) Social structure and competition in interfirm networks: the paradox of embeddedness. Administrative Science Quarterly, 42, (1), 35-67. Web Reference www.geobytes.com/citydistancetool.htm (Last accessed 11/16/10)


ABOUT THE AUTHORS David Epstein David Epstein is an assistant professor of management at the University of Houston Downtown. His primary research interests are R&D alliances, path dependence, corporate governance, agency and political circulation theory, and improving methodology to produce more valid results. Robert T. Keller Robert T. Keller is the Baker Hughes Professor of Business Administration at the University of Houston. Professor Keller has authored over 125 journal articles and professional papers. He is currently on the editorial boards of IEEE Transactions on Engineering Management (past department editor), Journal of High Technology Management Research, and The Leadership Quarterly, and he has twice been a member of the editorial review board of the Academy of Management Journal. He is Past Chair of the Technology and Innovation Management Division of the Academy of Management, a member of the Academy Council, and a charter member of the Academy of Management Journal's Hall of Fame.


Concentration and Consolidation as Determinants of External Competitiveness of Enterprises in Food Industry

Grażyna Michalczuk

University of Bialystok

Urszula Widelska University of Finance and Management, Bialystok

The aim of this paper is to present the level of concentration and consolidation processes in the food industry in Podlaskie Voivodship as a determinant of external competitiveness. The analysis was conducted on the basis of the results of research carried out within the analysis of key sectors of Podlaskie Voivodship. The external competitiveness is related to the adjustment of an enterprise to changes in the environment, taking into consideration cooperation conditions and becoming open to external markets in particular. INTRODUCTION

The external competitiveness is related to the adjustment of an enterprise to changes in the environment, taking into consideration cooperation conditions and becoming open to new markets in particular. In this aspect the greatest significance is attributed to:

concentration processes; consolidation processes.

The aim of this paper is to present the level of concentration and consolidation processes in the food industry in Podlaskie Voivodship as a determinant of external competitiveness. The analysis was conducted on the basis of the results of research carried out within the analysis of key sectors of Podlaskie Voivodship.1 The Essence of Concentration as a Factor of External Competitiveness

Concentration processes are characteristic for Polish food industry. They are a consequence of the transformation process, when significant structural changes take place (Kraciuk, 2007, p.54):

in the ownership structure private companies have dominated, they share increased from 10% to more than 95%;

in the assortment structure product diversity is dominant connected with the improvement of the quality of manufactured goods;

in the sector structure, at the expense of traditional companies, mainly sectors representing secondary food processing have started to develop.


They are also the result of the adjustment process to the EU standards, changes in the external environment, and increasing globalization. The processes of concentration are also determined by the necessity to introduce modern management systems, quality and the increasing intellectual potential.

As the main feature of the structural changes in the Polish food industry should be recognized by the increase in the share of production sold of large enterprises, while increasing their share in the structure of all companies, which is a premise for increasing the ability to compete in external markets. In 2009, these companies accounted for 1.8% of food industry companies and produced more than 53% of production sold 2

The changes in the business breakdown structure of food companies show significant liquidity and wide diversity. This indicates that economically weak, poorly managed companies, with the wrong structure of factors of production, and consequently characterized by low market competitiveness, leave the market.(Chechelski, Judzińska, 2011, p. 79).

The consequence of these changes in the food industry is getting closer to the structure characteristic for the countries of the EU-15. The level of concentration have been reached similar to that found in Germany, France and Spain. However, it is still lower than in Great Britain, the Benelux countries or Scandinavia. (Urban, 2010, p. 42-43)

Concentration processes are also observed among surveyed producers of food and beverages in Podlaskie Voivodship. The number of firms in the surveyed industries and across all industry is decreasing slightly but steadily. Enterprises strong economically are beginning to dominate, which build long-lasting competitive advantage due to high market share, marketing and investment activity. While in 2000 the number of entities employing more than 9 people was 215, in 2010 it decreased to the level of 180 (Figure 1).

FIGURE 1 THE NUMBER OF ENTERPRISES OF FOOD INDUSTRY IN PODLASKIE VOIVODSHIP IN

YEARS 2000-2010 AND FORECASTS FOR YEARS 2011-2014

Source: [5] and unpublished data of Statistical Office (WUS) in Bialystok

Forecasts for 2011-2014 indicate that this trend will continue in subsequent years. The strongest

concentration processes have taken place among beverage producers, where the number of entities decreased by as much as 60%. (Przygodzka, 2009)


Of course, it should be remembered that official statistics do not include micro-entities. It is likely therefore that the inclusion in the analysis of these entities also could change the view on the matter. (Michalczuk, Widelska, 2010, p.283) On the other hand, the observed mergers and acquisitions eliminate the market micro-entities, which may function primarily in niche areas. Also, micro entities realize only 5% of sales of production of food and beverages at approximately 60% share in the structure of all companies operating in this industry. Therefore, this does not distort the thesis on ongoing processes of concentration of production in the food industry, but rather confirms it.

The decrease in number of entities (primarily in the group of micro and small ones) and the strengthening position of large companies (they realize more than half of production sold at a gradual decline in their number), indicates gradual concentration processes occurring among surveyed food and beverage producers. These processes will proceed further and large companies will acquire more and more significance, which are characterized by a greater ability to overcome non-economic barriers to entry and participation in the European market. The Essence of Consolidation as a Factor of External Competitiveness

The consolidation processes are to create favourable conditions for increasing an ability to compete through creating cluster initiatives. Building such initiatives increases cooperative capabilities, allows to prepare a new offer as well as strengthens competitive position, particularly with reference to both domestic and international competition. Companies present in the structure of the cluster gain advantages known as agglomeration advantages that allow them to have access to certain resources, expertise and specialized services. The cooperation within the cluster initiative offers an opportunity to create an effective value chain and the use of economies of scale through joint marketing and implementation of joint research projects with research and development entities (Dzierzanowski, Rybacka, Szultka, 2011, p.6). Taking into consideration the aspect of external competitiveness, it should be emphasized that the region also obtains benefits from the presence of clusters. Three main groups of benefits associated with the presence of competitive clusters gained by a region are indicated: (Dzierzanowski, Rybacka, Szultka, 2011, p.28) Better conditions for development of enterprises, through strengthening cooperation ties and thus

competitiveness in terms of development of the region; The increase in innovation, particularly in the area of cooperation between science and practice; Faster economic growth contributing to faster development of the region. Strengthening the external competitiveness of enterprises through the development of cluster

structures is confirmed by the fact that the vast majority of clusters operating in Poland, that is 89%, have development strategies (although not always completely formalized). Missions of clusters which are the core of strategies concentrate on the following issues: The ability of cooperation between business and science; The increase in the capacity of companies of a cluster to compete with multinational enterprises; The development of innovation; Creating optimal conditions for the development of enterprises; Creating the conditions for the transfer of knowledge; Building a joint brand. Enterprises of the food industry in Podlasie show rather low awareness in the area of functions and

role which consolidation processes may perform in increasing the sector’s competitiveness. More than half of the enterprises (54%) declare the lack of cluster membership and at the same time demonstrate the lack of interest in becoming a member in such structure in future. Only 16% examined companies show interest in such form of cooperation. Little percentage of respondents (7%) are members of a cluster, however only 2% among them appraised this form of integration highly. A large number of companies (23%) have not form an opinion about this matter (Figure 2).


FIGURE 2 ASSESSMENT OF INTEGRATION POSSIBILITIES THOUGH MEMBERSHIP OF CLUSTERS

IN THE OPINION OF EXAMINED ENTERPRISES

Source: [5].

The results of conducted research show on the one hand a low level of knowledge of enterprises on cluster initiatives, and confirm at the same time an unsatisfactory degree of enterprises’ activity in a business-related sphere. On the other hand, this is a chance to create new clusters in the analysed sector. Another research in turn pays attention to other relations. It turns out that great significance in this field is attributed to a size of an enterprise, its experience, and also to the level of education of its owners or management.(Daniluk, Wasiluk, 2009, p. 153)

Openness to foreign markets is also an important determinant of the competitiveness of the analysed sector. The research results seem to confirm a low level of expansiveness of enterprises in Podlasie. More than 90% respondents do not also plan to increase their share in the market through taking over other companies. Only 5% respondents have considered such possibility, certainly bigger enterprises, whose position in the market is strong enough so a takeover would be possible to carry out.

A few examined enterprises plan to expand their activity to other segments of the market. Only 11% positive responses were obtained in this respect. There were 8% indecisive people, while convinced that nothing changes in this respect as much as 81%

Recent studies on cooperative abilities of enterprises of Podlaskie Voividship show that the attitude to cluster initiatives is changing. Representatives of key sectors of Podlaskie Voivodship, including food industry, are increasingly emphasizing the benefits resulting from the operation in the structure of the cluster. As particularly vital were indicated the following:

The opportunity to promote small businesses. Joint promotion. Lobbying interests relevant to all members of the cluster. The ability to create a joint offering. The exchange of knowledge and experience. Complementary offers 3.

Such research results are a consequence of the structure in examined enterprises, among which small

companies were dominant, to larger extent oriented on developing their position in local markets.(Michalczuk, Widelska, 2010) It may also result from enterprises’ experience in relation to accomplishment of their market activity within already known target markets.

Series1, An enterprise belongs to a cluster but the membership

does not affect its functioning, 5, 5%

Series1, An enterprise does not belong to a cluster but is interested in such form of

cooperation, 16, 16%

Series1, I do not have an opinion, 23, 23%

Series1, An enterprise belongs to a cluster and appraises this form

of integration highly, 2, 2%

Series1, An enterprise does not belong to a cluster and is not interested in membership, 54,

54%


SUMMARY

Concentration is not only a process vital from the point of view of large companies. It is also a challenge of modern market. It is as well a factor which determines marketing activity of small enterprises in food industry oriented on distinguishing themselves and strengthening unique characteristics. The research shows that consolidation processes are not advanced to such degree as concentration processes. Enterprises in Podlasie do not recognize benefits resulting from functioning within cluster initiatives and a chance to strengthen their competitive position. ENDNOTES 1. The aim of conducted research was detailed presentation of the role and importance of food industry

in Podlaskie Voivodship. The object of the research were enterprises of the following sectors: meat processing and preservation and production of meat products (PKD 2007 10.1), vegetable and fruit processing and preservation (PKD 2007 10.3), beverage production (PKD 2007 11). The report was prepared on the basis of already existing data and as well questionnaire surveys on the sample of 100 enterprises of the sector. The complete report on research results can be found in: [5]

2. For comparison, in 2006 they accounted for 1.6% in the quantitative structure of companies and realized about 49% of production sold. (For more on the processes of concentration and their causes and conditions [1, 79; 10, 30-31].

3. Good practices of innovation and technology transfer in key sectors of Podlaskie Voivodship. Innovation Strategy in Podlaskie Voivodship - Building System of Implementation. [4]

4. Dobre praktyki innowacji i transferu technologii w kluczowych branżach województwa podlaskiego. Podlaska Strategia Innowacji – Budowa Systemu Wdrażania. Raport z badań. (2011), IBiA VIVADE sp. z o.o., Białystok.

5. Przygodzka, R., Kozłowska-Burdziak, M., Dębkowska, K., Sadowski, A., Widelska, U. (2009), Analysis of Key Sectors Of Podlaskie Voivodship, Food Industry. Wyd. WUP in Białystok, Białystok.

REFERENCES Checkelski, P., Judzińska, A. (2011), Wpływ kryzysu na Polski przemysł spożywczy , Komunikaty Raporty Ekspertyzy nr 552, Wyd. IERiGŻ –PIB, Warszawa. Daniluk A., Wasiluk A. (2009), Klaster spożywczy województwa podlaskiego w świetle przeprowadzonych badań, Zeszyty naukowe Politechniki Białostockiej, 2009, nr 14. Dobre praktyki innowacji i transferu technologii w kluczowych branżach województwa podlaskiego. Podlaska Strategia Innowacji – Budowa Systemu Wdrażania. Raport z badań. (2011), IBiA VIVADE sp. z o.o., Białystok. Dzierżanowski M., Rybacka M., Szultka, S. (2011), Rola klastrów w budowaniu gospodarki opartej na wiedzy, Gdańsk, Szczecin. Kraciuk, J. (2007), Procesy koncentracji w polskim przemyśle spożywczym. Ekonomika i Organizacja Gospodarki Żywnościowej, nr 63. Michalczuk, G., Widelska, U. (2010), Relative Capital in Development of Food Industry on the Basis of Podlskie Voivodoship in Poland. Hospodraska Politika v Clenskich Zemich Evropeskie Unie, Fakulty v Karvinie, Horni Lomna, Czech Republic.


Michalczuk, G., Widelska, U. (2010), Marketing Determinants of Small Enterprises Competitiveness in Beverage Sector, (in:) Strategie zarządzania małym przedsiębiorstwem, Uniwersytet Szczeciński, Szczecin. Michaeczuk, G., Widelska, U. (2010), Relative Capital in Development of Food Industry on the Basis of Podlskie Voivodoship and Poland, Hospodraska Politika v Clenskich Zemich Evropeskie Unie, Fakulty v Karvinie, Horni Lomna, Czechy. Przygodzka, R., Kozłowska-Burdziak, M., Dębkowska, K., Sadowski, A., Widelska, U. (2009), Analysis of Key Sectors Of Podlaskie Voivodship, Food Industry. Wyd. WUP in Białystok, Białystok. Przemysł spożywczy w Polsce, (2008), ING, Warszawa. Urban, R. (2010), Przemiany strukturalne przemysłu spożywczego, w: R. Urban, I. Sczepaniak, M. Mroczek, Polski sektor żywnościowy w pierwszych latach członkostwa (Synteza), seria „Program Wieloletni 2005-2009, Raport nr 177, IER iGŻ _PIB, Warszawa.


A Post-Mortem on Long-Term Projections of Global Food Requirements

Ira Sohn Montclair State University

World population grew from 3.7bn in 1970 to almost 7bn in 2010 and, by 2050, is projected to increase to over 9bn. Because of growing scarcities of essential agricultural inputs, which can take decades to mobilize in sufficient quantities, long-term projections of global food requirements are critical if the “ghost of Malthus” is to be kept at bay. This paper examines long-term, i.e. 30-year, global production and consumption projections of four major agricultural sectors. These projections, whose terminal year was 2000, are then assessed against observed data from the UN’s Food and Agriculture Organization’s Food Balance Sheets. INTRODUCTION: THE MAJOR ISSUES FACING GLOBAL AGRICULTURE IN THE 21ST CENTURY

The 2004 run-up of global food prices, reversing a three-decade old pattern of declining or stable prices, in conjunction with the increase in energy prices that began earlier in the decade, is causing concerns in developed and developing countries alike, as well as in international organizations such as the Paris-based International Energy Agency (IEA) at the Organization for Economic Cooperation and Development (OECD), the World Bank, and the Rome-based United Nations Food and Agriculture Organization (FAO). Higher prices for food and energy -- the two principal components of economic wellbeing -- are putting at risk the availability, affordability, and reliability of these two critical resources for hundreds of millions of the world’s most vulnerable people. In fact, some of the gains made over the last decade or two in reducing the number of people living in poverty worldwide have already been lost to the sharp increases in food and energy prices. Even though the FAO’s global food price index at the beginning of 2012 has receded modestly from its peak in 2010-11, currently, it is still 100% higher than it was in 2000 (Lucas and Fontanella-Khan, 2012).

Increasing geo-political tensions among the leading economic powers such as China, the European Union, Brazil, and the United States, who are trying to lock-in their resource supplies for decades to come, along with mounting scientific evidence of climate change due to the increasing emissions of greenhouse gases that is being attributed to the activities in the energy, manufacturing, transport, and agricultural sectors is painfully making it clear to political leaders and policy-makers that transforma-tional changes in the global energy, transport, manufacturing, and agricultural systems will be required if living standards for most of the world’s 7bn people are to increase over the next 40 years, when the world’s population is projected to reach more than 9bn people (Parker, 2011).

While policy-makers are still preoccupied with addressing fiscal imbalances, abnormally high – and persistent – unemployment rates, and sharply higher debt levels in the wake of the public and private spending excesses of the last two decades and the economic and financial meltdown in the United States


and Europe in 2008-2010, there is a critical need – because of the long lead-times to develop additional food and energy capacities – for long-term projections of global demand for these two indispensible resources if rising geo-political stress and domestic civil unrest are to be contained.

The Paris-based International Energy Agency and the Energy Information Administration, the statistical and analytical arm of the US Department of Energy, regularly publish long-term energy projections. Both of these agencies provide long-term projections, extending out 25 years or more, that are based on alternative – though reasonable – sets of assumptions (scenarios) regarding the major drivers of energy demand such as income and population growth, technological change, environmental policy, etc., in the major energy consuming (and often importing) countries, and projected supply conditions in the major energy producing (and often exporting) countries.

With regard to long-term projections of global food requirements, the US Department of Agriculture (USDA) publishes 10-year projections every year of commodities, trade, and prices based on projected US and world economic and population growth, agricultural policies, and other assumptions that affect the demand and supply conditions in the global agricultural sectors, such as increasing urbanization and changes in diets on the demand side, and estimated oil prices and productivity improvements in the farm sector on the supply side. The United Nations’ Rome-based Food and Agriculture Organization recently published long-term projections of global food and nutrition levels for 2050 that include the major commodity groups of cereals, livestock, oil crops, root crops, and sugar (Conforti, 2011). These projections, too, are based on reasonable assumptions regarding prospective per capita daily calorie and protein levels, income and population growth, and likely dietary changes, especially in China and India, who are likely to experience high income growth and high migration flows from the countryside to urban areas over the next 40 years.

Two other important organizations that develop long-term projections, that is, to 2050, of global food and agriculture requirements are the Washington-based International Food Policy Research Institute (IFPRI) that is supported by the Consultative Group on International Agricultural Research (CGIAR), an alliance of 64 governments, private foundations, and international and regional organizations, and the International Institute for Applied Systems Analysis (IIASA), headquartered in Laxenburg, Austria that was founded in 1972 and conducts policy-oriented research on problems that are both global and inter-disciplinary in nature such as energy and climate change, food and water, and poverty and equity. This organization is supported by 18 national member organizations such as the US National Academy of Sciences and the Russian Academy of Sciences. Their recent work on long-term projections of global agricultural requirements to 2050 appears in the FAO report, “ Looking Ahead in World Food and Agriculture: Perspectives to 2050” (Conforti, 2011).

Before turning to the subject of this paper - a post-mortem on global food projections carried out more than 30 years ago - it is useful to provide the context for writing it. In September 1981 a symposium, sponsored by the Norwegian Nobel Foundation (that I had the good fortune to participate in), was convened to “explore the long-term perspectives of world demographic and economic growth with particular emphasis on international differentials in demographic and economic characteristics, on resources and supplies, and on implications for emerging patterns of cooperation and conflict” (Faaland, 1982, p. vii). Because of the nature of the phenomena that were examined a 50-year time interval was not inappropriate, even though attempting to divine quantitative estimates of regional income growth or even population growth, not to mention regional cereal production or coal consumption 50 years into the future was then, and arguably is, even today, considered to be an exercise in futility. Nevertheless, after perusing the distinguished list of participants (Faaland, 1982; pp 254-5) in that three-day symposium, one would have to conclude that the papers presented and discussions that followed were “dead serious”, even though the quantitative results, with the benefit of hindsight, were almost always “dead wrong”. Please see Sohn (2005) and Sohn (2007) for the “errors” in the non-fuel minerals and energy minerals projections, respectively.

While the existential issue of unchecked population growth colliding with the capacity of the earth to feed itself was first raised more than 200 years ago by Thomas Malthus (1798), because of new constraints that have emerged over the years such as global warming and possible climate change on the


one hand, and the impressive array of scientific advances and technological breakthroughs on the other, this issue came to a head between the late 1960s and the early 1980s, with the famous debate between Paul Ehrlich (1968), a Stanford University biologist, and Julian Simon (1981), a University of Illinois economist, and the path-breaking studies sponsored by the Club of Rome and carried out by Jay Forrester (1971) and Dennis Meadows and his colleagues (1972). The latter studies, for the first time, elevated the vexing problem of pollution to “center stage” in the public-policy debate.

More recently, while not focusing specifically on the population growth-food supply dilemma, the report of the UN-sponsored Intergovernmental Panel on Climate Change (IPCC, 2007), followed in the same year by the Stern Report (2007) that was commissioned by the British government, strongly implied that fundamental changes will be needed in the global food, energy, and transport sectors if we are to achieve sustainable growth in material well-being in the 21st century in light of the projected growth in population and the mounting evidence of human-induced global warming. A BRIEF REVIEW OF RECENT LITERATURE ON LONG-TERM STUDIES ON AGRICULTURE, FOOD, AND NUTRITION

Two recent books published within a year of each other that focused on long-term trends provide the facts to support the view that without a successful global agricultural sector that incorporates production, transportation, distribution, changing consumption patterns, improved material well-being in the future - that is characterized by higher life expectancy, improved nutrition, higher incomes, and lower poverty rates - will not be possible.

The study by the 1993 Nobel laureate in economic science, Robert Fogel (2004), highlights, with particular emphasis on Europe and America, the remarkable extension of life expectancy in the 20th century and the decline in mortality rates which he attributes largely to growing (and improved) food supplies that provided increased caloric and nutritional requirements to support the higher energy levels needed for a growing work force that was sufficiently healthy, as a result of higher food intake levels and better nutrition, to fend off a long list of, often fatal, infectious diseases. Fogel makes the case, with the support of statistical data, that improvements in human nutrition contribute to economic growth and development and technological change, and vice versa. Without this synergy it is doubtful that mortality and morbidity rates would have declined sufficiently to achieve the remarkable average life expectancy levels that we are enjoying today in the developed countries, and increasingly in most of the developing countries. He highlights the interdependence of industrial progress and the importance of improvements in public health through advances in science and technological change in agriculture, manufacturing, and services.

Giovanni Federico (2005), a professor of economic history, reviewed the outstanding success of the agricultural sector over the last two centuries. Federico argues that the world agricultural system has successfully fed an ever-growing population with an increasing variety of products at falling prices, and, simultaneously over this 200 hundred-year period since Malthus’s hypothesis, it did this while releasing a growing number of workers from agricultural work to the rest of the economy. The author explains how the world was able to feed 6.5bn (in 2005), up from 1bn in 1800, as a result of steady progress in the “primary forces”: scientific advance, technological and institutional change, and globalization.

While the author concedes that because of the advances introduced into agriculture over the last 200 years the world should be able to provide the required caloric levels to sustain 7bn (reached in October 2011), but he questions whether the still growing population in the developing countries, which is expected to increase the world’s total above 9bn by mid-century, can be provided with the nutritional standards of the developed countries, that is, a changing composition of diets to reflect a much higher proportion of meat and dairy products that are, of course, much more land-intensive than a diet comprised primarily of cereals.

Another important issue that Federico raises is the front burner issue of the “sustainability of modern agriculture”, that is, how do we mitigate the environmental damage caused by the excessive use of fertilizers and pesticides, diminishing bio-diversity, increasing scarcities of water and land, and, of course,


increasing levels of green-house gas emissions, with the continuing improvement in the nutritional value of food in particular, and material wellbeing in general, in Asia and Africa in the 21st century?

Federico concludes his study with the assertion that in order to feed the (then) world population of 6.5bn in 2005 even with a traditional (and monotonous) cereal-only diet - using traditional techniques of production - would require the work of 75-80% of the world’s active population. As a result, living standards in some countries would be at best unchanged, or, more likely, would decline from those of two centuries ago!

While the run-up in global agricultural prices since 2004 that has spawned civil unrest in some 30 food-short developing countries in 2007-08 (Financial Times, 2012), can, in part, be attributed to production shortfalls caused by weather-related events such as floods and droughts in some of the major food producing and exporting countries such as Argentina, Australia, and Russia, the issue of “food security” is becoming as important as the issues of “energy security” and “climate change” in the international public policy debate.

In addition to the above mentioned full-fledged books and the periodic reports published by the FAO and USDA, these emerging issues have spawned an array of recent policy papers by government and academic experts (UK Government Office for Science, 2011; Godfray et al., 2010) and review articles appearing in the international press (Financial Times, 2011; Foley, 2011; Parker, 2011), on the challenges and opportunities for farming and food to the middle of the 21st century when the world’s population is projected to increase more than 30% above its current level of 7bn people.

The principal objective of this paper is much more narrow and modest than a comprehensive review of 200 years of agricultural history and increasing living standards, or a description of the complex set of challenges and opportunities that exist in order to feed a world population of more than 9bn people under conditions of declining growth yields of the main crops, higher energy prices, increasing scarcity of water and land (resulting, in part, from increasing urbanization in Africa and Asia), the increasing cost of fertilizers, increasing pressures on land-use and crop-use as a result of bio-fuel policies, and, not least, the increasing contribution that global agriculture is likely to make to the emissions of two toxic greenhouse gasses, methane and nitrous oxide, and the likely effect that climate change will have on the global agricultural system in general, and on cereal crops in particular. Needless to say many of these “negatives” will be cancelled out by scientific advances in genetic engineering, improved land and water management systems, a narrowing of the “yield gap” between the worst (and average) and best yields, in addition to increased output resulting from bringing more land under cultivation, etc.

This paper is primarily concerned with reviewing long-term global projections made more than 30 years ago of four major agricultural sectors: livestock products (including meat, eggs, and milk products); oil crops (which include oilseeds, peanuts, and soybean products, among other crops); grains (which include maize (corn), rice, wheat, barley, and oats, among others); and root crops (which include potatoes and cassava, among others, but not sugar crops), with the observed data from FAO’s detailed Food Balance Sheets (FAOSTATS). However, before examining the projections and the observed data it would be of interest to provide an overview of the model used at the end of the 1970s to make these projections, and a description of the representation of the agricultural sectors in that model. THE UNITED NATIONS WORLD INPUT - OUTPUT MODEL

In the early 1970s with the recognition of the increasingly adverse environmental effects caused by worldwide industrialization - the result, in part, of the increased use of fuel, non-fuel, and agricultural-based resources - and the first major oil crisis in the decade, the United Nations voiced its concerns regarding the growing gap in income, i.e., the standard of living, between the poor, less-developed countries of the world and the richer, highly industrialized ones. As a result, in 1973 the United Nations commissioned the construction of a general-purpose model of the world economy that would be able

“to investigate the interrelationships between future economic growth and prospective economic issues, including questions on the availability of natural resources,


the degree of pollution associated with the production of goods and services, and the economic impact of abatement policies. One question specifically asked by the study was whether the existing and other development targets were consistent with the availability and geographic distribution of resources” (Leontief et al., 1977).

In hindsight, writing at the beginning of 2012 - more than 35 years later - this modeling effort

should still be recognized as an intellectual “tour de force”. As far as the resource sectors were concerned, the model - which was constructed by a team of economists and computer programmers under the leadership of Professor Wassily Leontief, who was awarded the 1973 Nobel Memorial Prize in Economic Science - tracked three fuel minerals (oil, natural gas, and coal), six metallic minerals (aluminum, copper, iron, lead, nickel, and zinc), and four agricultural resources (livestock products, oil crops, grains, and root crops). Other agricultural- and food-related variables tracked by the model were irrigation investment, land development, cultivated land area, calories and proteins per day, and fish catch. The model also included 30 manufacturing and service sectors, as well as eight types of major pollutants, and five pollution abatement activities.

Economic activity was regionalized - the countries of the world were originally aggregated into 15 regional blocks - but were unified by export and import flows of goods and services, capital flows, aid transfers, and “cross border” payments of interest on borrowed capital. (Please see Table A.1 in the Appendix for the country aggregation scheme used in this study). An upgrade of the model around 1980 separated the two countries - Canada and the United States - included in the “North America” region, making a total of sixteen regions.

Once assembled, the model was designed to provide quantitative projections of regional and global resource requirements, pollution levels, cumulative resource use, and required inter-regional financial flows, etc., under varying assumptions regarding future income growth in the developed and developing countries with a view towards narrowing the income gap between the two groups of countries from 12:1 (in 1970) to 7:1 (by the year 2000) in accordance with the goal of UN General Assembly resolution 3201 (S-VI) of May 1, 1974 on the Establishment of a New International Economic Order. Curiously, according to the observed per capita GDP for the year 2000 used in the tables in this paper, the (per capita) income gap between the two groups of countries, in fact, declined from 12:1 in 1970 to 6.6:1 in 2000.

In 1977, with financial support from the US National Science Foundation (along with supplementary funding from the US Bureau of Mines), a team of investigators, again led by Professor Leontief, began a detailed study of the future demand for, and supply of, 26 non-fuel minerals for the US and world economy, embedding 20 “new” minerals into this recently completed World Input-Output Model. One of the principal issues examined in this study was the adequacy of these critical resources to meet national and global requirements to the year 2000 and beyond (Leontief et al., 1983a).

Since its completion in 1976, the World Input-Output Model was enlisted to examine a number of specialized issues ranging from the future of world ports to an expanded study of 20 other non-fuel minerals not included in the original project that was mentioned above (Leontief, Gray and Kleinberg, 1979; Leontief and Duchin, 1983; Leontief et al., 1983b), and the study presented at the symposium sponsored by the Norwegian Nobel Institute in September 1981 that was mentioned above (Leontief and Sohn, 1982). PROJECTED AND OBSERVED POPULATION AND INCOME GROWTH: THE MAIN DRIVERS OF GLOBAL FOOD REQUIREMENTS

This section presents the data that are among the principal long-term determinants of food consumption - population and income growth - on a regional and global level, for the 1970-2000 interval. Table 1 presents the developed and developing countries’ changing population levels and shares of the world total for 1970 and the projected and observed 2000 values.


TABLE 1 PROJECTED AND OBSERVED POPULATION LEVELS (IN BILLIONS)

AND SHARES (IN PERCENT), 1970-2000

1970 Base Year 2000 Projected 2000 Observed Region Level Share Level Share Level Share Developed Countries 1.0 0.3 1.4 0.2 1.4 0.2 Developing Countries 2.6 0.7 4.7 0.8 4.6 0.8 World 3.7 1.0 6.1 1.0 6.1 1.0

Note: For the country and regional aggregation schemes, please see Tables A.1 and A.2 in the Appendix. Sources: Leontief et al., 1977; World Bank, 2002

The population projections made in the mid-1970s for the year 2000 by the United Nations

Population Division, were insignificantly different from the observed global level for 2000, as can be observed in Table 1, above. As expected, the share of the developed countries in total world population declined from 30% to 23% over the interval, with more than three-quarters of the world’s population in 2000 residing in the developing countries, a trend that is likely to continue in the 21st century (Magnus, 2009).

Table 2, below, presents the projected and observed regional population, GDP, and GDP per capita growth rates for the projection interval. The lower observed population growth rates for most of the regions (with the exception of Africa, Asia, one European region, and the United States) as compared to the projections are consistent with long-term demographic trends. The demographic changes in two of the European regions WEH (western Europe, high income) and EEM (eastern Europe, medium income) are the result of the re-unification of Germany in the early 1990s and the migration of many eastern-Europeans and others to western-Europe, in part, as a result of the economic stress in the eastern countries in the wake of the collapse of the Soviet Empire in the 1980s. As for the US, the increase in the observed population growth rate in the 1970-2000 period compared with the projected rate for this interval is most likely explained by increased immigration from Central and South America, Asia, the Middle East, the former Soviet Union, and Africa during the last two decades. The observed growth rate for (non-Japan) Asia exceeded the projected rate by less than 10%, and the only substantial “error” appears to be Africa (AF), where the observed rate of population growth exceeded the projected rate by 0.5% per year.

Turning to GDP growth, observed world GDP growth was less than the rate projected by the World Model, despite the formidable growth rates achieved by China (ASC), and India and other Asian countries (ASL), from 1980 to the projection period’s terminal year, 2000. The observed lower growth rates in GDP relative to the projected rates over this interval in the middle-eastern oil-producing countries (OIL), Central and South America and the Caribbean (LA), South Africa (SAF), the Soviet Union (SU), and Eastern-Europe (EEM), and the lower observed growth in Japan and Western Europe (WEH), can be attributed to an array of well-known political, social, economic and financial problems that these regions (and countries) confronted during the 1980-2000 interval. These problems also explain, in part, the lower observed world GDP growth rate relative to the projected rate despite the successes in Asia.

The last two columns of Table 2 present projected and observed annual growth in GDP per capita over the projection interval. For economists, per capita GDP (whether calculated at current exchange rates or on a purchasing power parity basis) represents, an imperfect, though adequate statistic to measure relative “living standards” and their growth (or, as the case may be, their decline) over time. The observed changes in per capita GDP in China (ASC), India, South Korea, and Thailand (ASL), and the Soviet Union (SU) over the projection period reveal in the official data what is commonly perceived as the “conventional opinion” on the economic performance of these countries over the 1970-2000 interval.


TABLE 2 PROJECTED AND OBSERVED GROWTH IN POPULATION, GROSS DOMESTIC PRODUCT,

AND GROSS DOMESTIC PRODUCT PER CAPITA, 1970-2000 (ANNUAL PERCENTAGE CHANGE)

Population Gross Domestic

Product GDP per Capita

Region Projected

Observed Projected Observed Projected Observed AF* 2.3 2.8 2.9 3.7 0.6 0.9 ASC 1.4 1.5 4.3 8.9 2.9 7.3 ASL 2.0 2.2 3.6 5.4 1.6 3.1 CANADA 1.3 1.2 3.6 5.5 2.2 2.3 EEM*** 0.6 -0.2 4.4 2.6 3.8 2.8 JAPAN 0.7 0.6 5.3 3.5 4.6 2.9 LA** 2.3 2.0 6.0 3.6 3.6 1.6 OCH 1.3 1.3 3.8 3.4 2.5 2.1 OIL 3.2 2.9 12.0 2.7 8.5 -0.2 SU 0.8 0.6 3.2 0.0 2.4 -0.6 SAF 2.8 2.3 4.6 2.4 1.8 0.1 USA 0.9 1.1 2.8 3.3 2.3 2.2 WEH*** 0.2 0.4 3.3 2.5 3.1 2.1 WEM 1.3 1.2 2.4 3.1 1.0 1.9 WORLD 1.69 1.70 3.96 3.30 2.20 1.57

Notes: * Throughout this paper the region designated by AF combines the two regions, AAF and TAF, from the original regional representation in Appendix Table A.1. ** Throughout this paper the region designated by LA combines the two regions, LAL and LAM, from the original regional representation in Appendix Table A.1. *** Throughout this paper the data for 2000 are for a unified Germany that is part of the WEH region. Sources: Leontief and Sohn, 1982; Leontief et al., 1983b; World Bank, 2002

In addition to population and GDP growth, regional and global food requirements are also impacted

by a number of other important variables such as urbanization rates, which along with higher living standards (increased GDP per capita), result in changing diets such as, for example, a movement away from root crops to grains, and finally, to increased livestock products, characterized by more meat, eggs and cheese, in daily diets.

Despite not having access to the documentation regarding the technical relationships governing these regional changes in food diets from decade to decade over the projection interval when writing this paper, it is my understanding that because the World Model tracked both the changing regional urbanization rates and per capita GDP levels from decade to decade, the projections of the regional food requirements were, in part, determined by these factors that were modified region-by-region and decade-by-decade. GLOBAL AGRICULTURE, 1970-2000: THE PROJECTIONS AND THE OBSERVED DATA

This section presents a number of tables that provide an overview of the projections and observed data for the 30-year projection interval for the four broad-based agricultural sectors represented in the World Model - livestock products, oil crops, grains, and root crops - for the 15 regions (including the world) that are tracked in this study.


Some Caveats About the Data Before presenting these tables a few warnings are in order regarding some data problems I

encountered in order to make the World Model data and regional classification system compatible with the FAO’s database over the 30-year interval. Many, though not all, of the inconsistencies and anomalies have been mitigated (if not eliminated) by using annual or total growth rates over the reporting interval in place of reporting the levels of agricultural output and consumption for the projections and the observed data.

For example, in the 1970s the region EEM in the World Model represented all the central European countries in the then Soviet Union’s orbit (with the exception of Tito’s Yugoslavia). By the early 1990s and the unification of Germany, national accounts data (population and GDP growth statistics), as well as food production and consumption data, were no longer represented separately for East and West Germany, and, as a result, a “unified” Germany, for the observed, i.e., FAO, data in both 1970 and 2000, was included in the western Europe (high income) region.

Similarly in the case of the former Soviet Union, while the model’s projections for 2000 are for the (intact) Soviet Union, I was forced to reconstruct the “old” Soviet Union for the observed 2000 data since FAO’s database does not report data for the Soviet Union after 1991, following its dissolution. Some of the data problems I encountered could have been resolved in a more satisfactory way, but FAO staff was either unable or unwilling to respond to repeated requests to provide answers to my questions on these subjects.

Other political changes since 1970 proved more challenging in reconciling World Model regions with the FAO database. For example, in the closing years of the “Cold War”, circa 1974-76, when the World Model was constructed, South Vietnam and North Vietnam were assigned to different regions; the former to Asia Low Income (ASL) and the latter to Asia Centrally Planned (ASC). Since FAO’s database for 1970 does not track data for a divided Vietnam, therefore, the “unified” Vietnam was assigned to the Asia Centrally Planned region (ASC).

And then there is always the intractable problem of Taiwan. FAO, a United Nations organization, no longer recognizes Taiwan with country status, and therefore does not have a separate listing for it in its agricultural database. The World Model, constructed in the mid-1970s, included Taiwan in the ASL region, and Mainland China in the ASC region. Presumably, FAO’s data for China, both in 1970 and 2000, include both. But again, without more cooperation from FAO staff on these questions, I am unable to provide any further clarification on this issue.

In the original regional breakdown in the World Model, Latin America (including Mexico and the Caribbean) was divided into two regions (Latin America, low income and Latina America, medium income). In order to accommodate FAO’s regional breakdown - Central America (which includes Mexico), the Caribbean, and South America - these three FAO regions were aggregated into one, and the two World Model regions were combined into one, so there is now one “super” region in both sets of data for Latin America (LA). For Africa, a similar aggregation was performed: the World Model represented Africa with three regions - Arid Africa, South Africa, and Tropical Africa. The major oil-producing and -exporting countries in Africa, such as Algeria, Libya, and Nigeria, were consigned to the region designated by OIL that included countries such as Iran, Iraq, and Saudi Arabia. I aggregated the regions Arid Africa and Tropical Africa into one separate region, Africa (AF), while retaining South Africa as a “stand alone” region. This was done to facilitate the assembly of data from FAO’s database for 55 African countries that are represented in the World Model.

Other problems resulted from missing or incomplete documentation of technical information on the composition of the four broad-based groups of agricultural products tracked by the World Model. While the Model’s base-year is 1970, it is quite possible that the agricultural data may have been from an earlier year, and/or it is likely that revisions in subsequent years were made to the “1970” data by FAO as part of their normal data management procedures. As a result, the base-year 1970 World Model data can vary substantially from the 1970 observed data in the current FAO database. Fortunately utilizing annual and total growth rates over the 30-year interval in place of levels, as mentioned above, can address this problem.


A Comment on “Consumption” While the “production” of agricultural output is well defined in both the World Model and the FAO

database, regional “consumption” in the World Model is derived as a residual to regional production minus exports plus imports, and, as a result, I use the term “domestic supply” instead of “consumption”, a term that better aligns with the term used for this “equation” in FAO’s Food Balance Sheets. Needless to say, in the World Model projections, there are no increases or reductions in regional inventories or other “frictions” such as crops being used for feed or seed purposes. On the other hand, FAO’s Food Balance Sheets provide statistics for these “frictions”, and also provide a category for each crop that was used as “food”, which appears in some of the tables that follow in addition to “domestic supply”. Finally, while the “production” and “domestic supply” growth rates, both annual and total, will be equal for the world in 1970 and 2000 in the World Model projections (“rounding errors” notwithstanding), they need not be equal in the individual regions because of importing and exporting activities. On the other hand, FAO data may not balance even at the world level for 1970 and 2000 because of the other “frictions” mentioned above and/or errors on my part in recording the data flows as I reconstructed some of the “discontinued” regions, a problem that might have been avoided or, at least reduced, if FAO staff had been more cooperative. The Projections and the Observed Data Production and Domestic Supply

Tables 3 and 4, respectively, present the projected and observed annual growth rates in production and domestic supply (and, in the case of the observed data, food consumption) of the four broad-based agricultural sectors - livestock products, oil crops, grains, and root crops - for the 30-year projection interval.

TABLE 3 PROJECTED GROWTH RATES IN PRODUCTION AND DOMESTIC SUPPLY IN FOUR

AGRICULTURAL SECTORS, 1970-2000 (ANNUAL PERCENTAGE CHANGE)

Note: Domestic supply equals production plus net imports. Sources: Leontief and Sohn, 1982; Leontief et al., 1983b

At the global level the projected annual growth rates are remarkably close to the observed rates, save

oil crops, where the observed growth rate is almost 400% higher than the projected rate. Needless to say, this very large discrepancy relative to the other sectors warrants additional investigation in a planned future study. It would be reasonable to expect greater divergence at the regional (or country) level, not


only between the projected and observed values, but also even between the values for regional (country) production and domestic supply because of import, export (and, in the case of the observed growth rates, inventory adjustment) activities. This is, indeed, the case. The planned future study will focus on explaining the differences, at the regional level, between the projected and the observed growth rates employing the central explanatory variables - population, GDP, and GDP per capita growth - as the “primary suspects” in explaining away these discrepancies.

TABLE 4 OBSERVED GROWTH RATES IN PRODUCTION AND DOMESTIC SUPPLY IN FOUR

AGRICULTURAL SECTORS, 1970-2000 (ANNUAL PERCENTAGE CHANGE)

Livestock Products Oil Crops Grains Root Crops

Region Prod. Dom.

Supply Food Con. Prod.

Dom. Supply

Food Con. Prod.

Dom. Supply

Food Con. Prod.

Dom. Supply

Food Con.

AF 3.1 2.8 3.1 1.4 1.5 1.2 2.1 2.9 2.6 2.7 2.8 2.7 ASC 7.0 7.4 7.4 3.6 3.0 2.5 2.5 2.5 2.3 1.0 1.0 0.0 ASL 4.3 3.3 4.2 2.8 3.3 2.6 2.6 2.5 2.2 2.8 2.7 2.1 CAN 1.2 1.1 1.2 4.1 5.2 2.3 2.0 1.0 2.1 2.0 1.1 1.1 EEM -1.2 -1.3 -1.1 -0.8 -1.1 0.6 -1.7 -1.6 -2.0 -6.5 -3.3 -2.2 JAPAN 1.9 2.9 3.0 0.0 1.5 0.8 -1.0 0.9 0.0 -1.5 -0.7 0.8 LA 3.4 3.5 3.6 6.2 5.8 4.0 2.2 2.9 2.3 0.0 0.0 0.0 OCH 1.4 0.6 1.1 10.0 4.7 1.4 3.2 2.5 0.7 1.6 0.2 1.4 OIL 4.7 5.1 5.1 2.4 3.1 10.9 2.4 4.3 3.8 3.7 3.6 3.5 SU -0.8 -0.7 -0.7 0.0 -0.2 0.0 -1.1 -0.9 -0.9 -0.2 -1.1 -1.1 SAF 1.2 1.8 2.2 2.8 4.3 3.7 1.8 2.1 2.4 3.0 3.3 3.3 USA 1.6 1.4 1.4 2.9 2.4 1.4 2.0 1.5 2.3 1.4 1.2 1.5 WEH 1.0 0.7 -0.2 5.0 2.8 2.2 2.0 0.6 0.4 -1.1 -0.8 -0.2 WEM 2.0 1.9 2.9 2.9 3.2 5.0 1.8 1.5 0.9 0.0 1.5 1.0 WORLD 2.3 2.1 2.4 3.3 3.3 2.5 1.8 1.7 1.9 0.7 0.7 1.0

Note: Domestic supply equals production plus changes in inventories plus net imports. Source: FAOSTATS, (FAO)

At the global level, the observed growth rates of livestock products, oil crops and grains all exceeded

the rate of growth in population and per capita GDP, with only the rate of growth in production of root crops lagging population and per capita GDP growth, for reasons that are not obvious to me at this time. Regional (or Country) Dependence on Food Imports

Paralleling the growing concerns over “energy security” since the run-up in global food prices in 2004, “food security” has become an issue for countries who rely on food imports to bridge their shortfall between domestic production and food consumption. In addition, the FAO and other international organizations who track the adequacy of food supplies and nutrition levels in low-income countries, have elevated the issue of “food security’ to the highest level of public-policy debate.

The World Model tracked regional (and, in some cases, country) import and export activities. Therefore, it would be of interest to examine the changing position of regions (and, where possible, countries) over the 30-year interval of time with respect to their dependence on imports to supplement the domestic production of their food requirements.

Before presenting the projected and observed rates of import dependence in agriculture it is important to remind readers that the degree of import dependency of a region - or more specifically of a country - on energy or food is only one factor among others that comprise the more complex terms “energy security”


or “food security”. Some of these other factors include the sources of those imports, the availability of substitutes, the ease or difficulty of increasing efficiency in their use, etc.

TABLE 5

IMPORT DEPENDENCE IN AGRICULTURE, 1970 AND 2000: PROJECTED (WM) AND OBSERVED (FAO) RATIOS (IN PERCENT)

Note: An “import dependence” ratio is defined as net imports as a percentage of domestic supply. Sources: Leontief and Sohn, 1982; Leontief et al., 1983b; FAOSTATS, (FAO)

The changing rates of projected and observed dependency on agricultural imports are presented in

Table 5. While there are relatively large differences between the projected and observed data regarding the degree, i.e., the percent, of import dependency in 2000, generally speaking there is broad agreement between the projected and observed data regarding the regions (or countries) that are most dependent on imports to supplement their domestic production. The planned follow-up study will analyze these differences in conjunction with the differences already cited in population and GDP growth over the 30-year period.

Table 6 describes the changing role of world trade in agricultural commodities observed from 1970 - 2000. Since the proportion of world production of these agricultural products that were shipped across

TABLE 6 GLOBAL AGRICULTURE: THE CHANGING RATIOS OF WORLD IMPORTS TO WORLD

PRODUCTION, 1970 AND 2000 (IN PERCENT)

Source: FAOSTATS, (FAO)


regional (or country) borders increased for all four groups from 1970 to 2000, the annual rate of growth in world imports of these agricultural products exceeded the annual rate of growth in the world output of all four agricultural groups. Nevertheless, the liberalization of global agricultural trade over the 1970-2000 interval is progressing more slowly than total world merchandise imports, which grew by 10.6% per year according to the World Trade Organization (World Trade Organization). Per Capita “Consumption” of Livestock Products and Grains: The Projections and the Observed Values in 1970 and 2000

Table 7 presents the projected and observed annual per capita domestic supply (in kilograms) of two of the four agricultural sectors in this study: livestock products and grains. Grains were selected because grains was the largest commodity group (by far), in tonnage, of the four agricultural sectors included in the study, and livestock products were selected because increased per capita consumption of livestock products is closely associated with higher living standards. (Readers are reminded that “domestic supply” - domestic production and inventory changes plus net imports - is distributed to uses such as food, feed, seed, processing, etc).

At the global level the 2000 projections of per capita domestic supply was 17% above the observed FAO level, though most of the difference, 11%, is due to the higher base year level. For livestock products, the projected global level agrees well with the 2000 observed level, even though FAO’s base year level was 5% above the World Model 1970 level.

With a few exceptions - to be examined in the follow-up paper - generally speaking, per capita domestic supply of livestock products and grains increased in those regions where living standards advanced, in particular, in ASC (China) and ASL (India), and declined in those regions where living standards stagnated or fell (AF, EEM, and SU). These trends are more sharply discerned in Table 8, which presents only the observed changes in annual per capita consumption of livestock products and grains as food from 1970 to 2000.

TABLE 7 PROJECTED (WM) AND OBSERVED (FAO) ANNUAL PER CAPITA DOMESTIC SUPPLY OF

LIVESTOCK PRODUCTS AND GRAINS, 1970 AND 2000 (IN KILOGRAMS)

Notes: a. Domestic supply equals production plus net imports plus inventory changes. b. 1 kilogram equals approximately 2.2lbs. Sources: Leontief and Sohn 1982; Leontief et al., 1983; FAOSTATS, (FAO)


TABLE 8 OBSERVED (FAO) CHANGES IN ANNUAL PER CAPITA FOOD CONSUMPTION OF

LIVESTOCK PRODUCTS AND GRAINS, 1970 AND 2000 (IN KILOGRAMS)

Note: 1 kilogram equals approximately 2.2lbs. Source: FAOSTATS, (FAO)

Calories and Protein: The “Stuff” of Life

The ongoing global increase in daily calorie and protein levels and the decline in poverty rates, particularly in East Asia over the last two decades and more recently in Sub-Saharan Africa, is well documented (Perry, 2006). According to Fogel (2005), two critical “ingredients” - the total daily calorie level and the amount of daily protein intake - play a crucial role in improving labor productivity, both physical and mental, which, for economists, is the single most important factor responsible for raising the level of material well being.

Table 9 presents the projections and the observed levels of daily per capita calorie and protein levels for 1970 and 2000. For the world, the World Model projected (or targeted) only a very modest increase in the daily calorie level, from 2400 in 1970 to 2500 in 2000, an increase of only 4.2%, along with an increase of 12% in daily per capita protein levels over their 1970 levels. On the other hand, globally, the observed data indicate more impressive gains in both calorie and protein levels over the 30-year interval: a 13.6% increase in global daily per capita calories along with a 15% increase in daily per capita protein levels.

It is of interest to note the observed changes recorded over the projection interval in three key regions: ASC, which is dominated by China; North America, that incorporates both Canada and the United States; and the former Soviet Union. The observed changes in the first region attest to the well-documented improvement in material well being in China over the projection interval, the result of the widespread reform program that began in the late 1970s, including China’s re-engagement with the world economy. The changes in the second region provide some additional proof of the ongoing “obesity crisis” in North America with the large observed - though arguably unnecessary - increase in daily calorie levels in both Canada and the US from an already relatively elevated 1970 base year level. The changes in the former Soviet Union portray a region in crisis, with both daily per capita calorie and protein levels falling over the projection interval. In particular, readers will recall that the 1990s was a decade of enormous economic and political stress in the former Soviet Union, accompanied by falling living standards that is borne out in these data and the data on population and income growth (Table 2, above).


TABLE 9 PROJECTED (WM) AND OBSERVED (FAO) LEVELS OF DAILY PER CAPITA

CALORIES AND PROTEINS, 1970 AND 2000

Note: A “pint” (14oz or 414ml) of Häagen-Dazs ice cream contains 1050 calories. Sources: Leontief and Sohn, 1982; Leontief, 1983b; FAOSTATS, (FAO)

SUMMARY AND COMPLETING THE “UNFINISHED BUSINESS”

To sum up, at the global level the 30-year projected growth rates of three of the four agricultural sectors - oil crops notwithstanding - were surprisingly close to their observed rates from the FAO database. This is in contrast to the relatively large differences recorded between the projected and observed values for the fuel and non-fuel minerals, also included in the World Model projections (Sohn, 2005; Sohn, 2007). Part of the explanation for this may be due to the well-known successes during the 1970-2000 interval of substituting one metal for another, such as aluminum for steel, and using non-metallic materials in place of metal components, such as plastics and composites replacing metals in new aircraft.

With regard to the energy projections, unanticipated large reductions in the energy intensity of the economy over the projection period, i.e., declining energy use per dollar of GDP, because of increased efficiency in the production, distribution, and consumption of energy provided ample opportunities to slow the growth in energy use, even when accompanied by continued population and income growth.

To be sure, as living standards increase, per capita calorie and protein levels increase (often excessively as in the US), along with the gradual shift to grain and livestock products at the expense of slower growth in the production and consumption of root crops. This appears to be borne out by the observed data, which closely follow the projections at the global level.

The “conventional wisdom” regarding minimum required daily calorie levels suggest levels at approximately 2100 calories per capita (Parker, 2011). According to the observed data reported in Table 9, above, at the global level this was easily met even in 1970, not to mention the 14% increase by 2000. It is important to note, that over the 30-year projection interval of this study, the world’s population also increased by 65% over its 1970 level (Table 1).

The “unfinished business” that will be part of the planned future work on this subject includes an investigation into the reason(s) for the large discrepancy between the projections and the observed data in


oil crops (Tables 3 and 4); an in-depth analysis of the projections and the observed data at the regional level beginning with population and income growth data and ending with regional calorie and protein levels; and the incorporation of two other critical components of the food and agriculture sectors tracked by the World Model - projected and observed acreage under cultivation, and projected and observed fish catch.

The proposed follow-up study will also examine the major issues that those who are engaged in today’s long-term modeling efforts, i.e., to 2050 and beyond, will have to incorporate into their projections. These include: a projected 30% increase in the world’s current population by 2050; the growing scarcity of agricultural inputs (land and water) and outputs (maize and sugar cane) due to their diversion to the production of bio-fuels and driven by higher population levels and living standards, along with increased urbanization rates, particularly in Asia and Africa; the expected environmental impacts from global warming on agricultural output on the one hand, and, on the other, the projected elevated levels of methane and nitrous oxide emissions as livestock output and fertilizer use increase along with population levels and living standards, particularly in China, and other high-growth countries in Asia and Africa.

On the production side, increasing food output by a projected 70% by 2050 (Parker, 2011) will require the development and adoption of new technologies such as improved irrigation methods, more widespread planting of genetically modified crops that are resistant to herbicides and pesticides, and the introduction of plants that are drought and/or flood tolerant, reducing the “yield gap” between the “best”, “worst”, and “average” yielding land, and reducing the amount of food in both developed and developing countries that is lost to waste, currently estimated to be 30-40% of the total (Godfray et al., 2010).

Finally, even though daily calorie levels on a per capita basis in all 15 regions in this study are above the minimum required 2100 calories (Table 9), in 2010, according to the FAO, 925m people were classified as “hungry” (World Hunger), and, according to Save the Children, the international NGO that promotes children’s rights, one in four children in the world is malnourished (Associated Press, 2012). Therefore, one of the major challenges in the 21st century is the implementation of food “safety nets” for these vulnerable people through policy and institutional initiatives to the end of reducing, if not eliminating, the daily struggle for food of more than 13% of the world’s population. APPENDIX

TABLE A.1 COUNTRY AND REGIONAL CLASSIFICATION FOR THE WORLD MODEL

REGION COUNTRY OR TERRITORY

Africa, arid (AAF) * 1. Chad 2. Comoro Islands 3. Egypt 4. Ethiopia 5. Djibouti 6. Israel 7. Jordan 8. Lebanon 9. Mali

10. Mauritania 11. Morocco 12. Niger 13. Somalia 14. Sudan 15. Syrian Arab Republic 16. Tunisia 17. Upper Volta 18. Western Sahara

Asia, centrally planned (ASC)

1. China 2. Democratic Kampuchea 3. Democratic People’s Republic of Korea

4. Democratic Republic of Vietnam 5. Mongolia


Asia, low-income (ASL)

1. Afghanistan 2. Bangladesh 3. British Solomon Islands 4. Brunei 5. Bhutan 6. Burma 7. Fiji Islands 8. Hong Kong 9. India 10. Indonesia 11. Republic of Korea 12. Laos 13. Malaysia 14. Maldives Islands

15. Macao 16. Nepal 17. New Hebrides 18. Pacific Territories and Islands, n.e.c. 19. Pakistan 20. Papua New Guinea 21. Philippines 22. Republic of South Vietnam 23. Sikkim 24. Singapore 25. Sri Lanka 26. Taiwan 27. Thailand

Canada (CAN) 1.Canada Eastern Europe (EEM)

1. Albania 2. Bulgaria 3. Czechoslovakia 4. German Democratic Republic

5. Hungary 6. Poland 7. Romania

Asia, high-income (JAP)

1. Japan 2. Ryukyu Islands


Latin America, (LAL)**

1. Barbados 2. Bolivia 3. British Honduras 4. Colombia 5. Costa Rica 6. Dominican Republic 7. Ecuador 8. El Salvador 9. Fr. Guyana 10.Guadeloupe 11.Guatemala 12.Guyana

13. Haiti 14. Honduras 15. Jamaica 16. Martinique 17. Nicaragua 18. Panama 19. Paraguay 20. Peru 21. Surinam 22. Trinidad and Tobago 23. Venezuela

Latin America, Medium-income (LAM)**

1. Argentina 2. Bahamas 3. Bermuda 4. Brazil 5. Chile 6. Cuba

7. Mexico 8. St. Lucia/Grenada/ St.Vincent/Dominica/St.Kitts/Nevis/Anguilla/ Netherlands/Antilles/ Turks and Caicos Islands/ Montserrat 9. Uruguay

Oceania (OCH) 1. Australia 2. New Zealand Middle East-Africa (oil producers) (OIL)

1. Algeria 2. Bahrain 3. Democratic Yemen 4. Gabon 5. Iran 6. Iraq 7. Kuwait

8. Libyan Arab Republic 9. Muscat/ Trucial/ Oman 10. Nigeria 11. Qatar 12. Saudi Arabia 13. United Arab Emirates 14. Yemen


Soviet Union (SU) 1. USSR Southern Africa (SAF) 1. South Africa and Namibia Africa, tropical (TAF)*

1. Angola 2. Benin 3. Botswana 4. Burundi 5. Cameroon 6. Cape Verde 7. Central African Republic 8. Congo 9. Equatorial Guinea 10. Gambia 11. Ghana 12. Guinea 13. Guinea-Bissau 14. Ivory Coast 15. Kenya 16. Lesotho

17. Liberia 18. Madagascar 19. Malawi 20. Mauritius 21. Mozambique 22. Rwanda 23. Sao Tome and Principe 24. Senegal 25. Seychelles Islands 26. Sierra Leone 27. Zimbabwe 28. Swaziland 29. Togo 30. United Republic of Tanzania 31. Uganda 32. Zaire 33. Zambia


United States (USA) 1. United States of America, including Puerto Rico, The Canal Zone, and U.S.Virgin Islands.

Western Europe, high income (WEH)

1. Andorra 2. Austria 3. Belgium 4. Denmark, including Greenland 5. Faeroe Islands 6. Finland 7. France 8. Germany, Federal Republic of 9. Iceland

10. Ireland 11. Italy 12. Luxembourg 13. Netherlands 14. Norway 15. Sweden 16. Switzerland 17. United Kingdom of Great Britain and Northern. Ireland (including the Channel Islands and Isle of Man).

Western Europe, medium-income (WEM)

1. Cyprus 2. Gibraltar 3. Greece 4. Malta

5. Portugal 6. Spain 7. Turkey 8. Yugoslavia

Note: a. Regions followed by an asterisk (*) were aggregated to form a single region, AF, in this study. b. Regions followed by two asterisks (**) were aggregated to form a single region, LA, in this study. Source: (Leontief et al., 1977)


TABLE A.2 AGGREGATED REGIONAL CLASSIFICATION1

I. Developed Countries

A. United States (USA) B. Other “OECD”2 countries

1. Western Europe (high-income) (WEH) 2. Western Europe (medium-income) (WEM) 3. Japan (JAP) 4. Oceania (OCH) 5. Africa (medium-income) (SAF) 6. Canada (CAN)

C. Developed Centrally Planned Countries

1. Soviet Union (SU) 2. Eastern Europe (EEM)

II. Developing Countries

1. Latin America (low income) (LAL) 2. Middle East-Africa (OIL) 3. Africa (tropical) (TAF)

4. Africa (arid) (AAF) 5. Asia (low-income) (ASL) 6. Asia (centrally planned) (ASC) 7. Latin America (medium-income) (LAM)

1. A complete listing of the countries which comprise the sixteen aggregated regions appears as Table A.1, above. 2. Due to the way in which the country and regional aggregations were performed the other "OECD" group includes some countries that were not members of OECD such as, for example, South Africa and Yugoslavia.

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ACKNOWLEDGMENTS

I am grateful for the Sabbatical leave provided to me by Montclair State University that enabled me to carry out this study. I thank the Department of Economics and Finance and the School of Business at MSU for making travel funds available to me to present this paper at the Annual Conference of the National Economics and Business Society in March 2012 in Maui, Hawaii. I am indebted to Claudia Binaghi for building the neat tables that make the paper more readable and for designing the bar graphs that were used so effectively in the Conference presentation.

I thank Paul Westcott, at the USDA’s Economic Research Service, for taking the time to read through the manuscript and for bringing to my attention some errors in Table 6, that are now corrected.

I believe it is also important to express, again, my disappointment with FAO’s staff, who were dismissive of my repeated emails, and, even after contact was finally made, for their unwillingness to answer follow-up questions about their marvelous database, which I could have exploited more effectively if a bit more cooperation would have been forthcoming. A pity!


Risk and Precautionary Approaches to Climate Change: Conceptual and Empirical Lessons from the Insurance Industry

Patrick G. Welle

Bemidji State University

The concept of option value provides insight in weighing the countervailing risks of doing “Too Much Too Soon” or “Too Little Too Late” in addressing climate change. Option value represents profit potential to the insurance industry when it is positive, which occurs if people’s willingness to pay exceeds expected actuarial losses. Climate change could increase both the mean and the variability of actuarial losses. This paper reviews literature relating climate change to the insurance industry and summarizes empirical estimates of damage payments by private insurers. Public data on long-term trends in weather-related disaster and emergency relief payments are cited. INTRODUCTION AND BACKGROUND

This paper focuses on the risk aspects of climate change as part of a larger research project conducted for the Legislative Citizens Commission on Minnesota Resources (LCCMR, 2010). The overall project was directed by the University of Minnesota, Natural Resources Research Institute. According to the project 2007 LCCMR Workplan, the overall purpose was “to quantify climate, hydrologic, and ecological variability and trends, along with economic impacts of environmental fluctuation on water resources, and to identify indicators of future climate change effects on aquatic systems.” This economic component presented economic conceptualizations of climate change as a policy challenge and empirical findings on “economic impacts of environmental fluctuation on water resources.” The Scientific Context for Climate Change Impacts on Minnesota Water Resources According to USEPA Office of Water 2008“Climate change will have numerous and diverse impacts, including impacts on human health, natural systems, and the built environment. Many of the consequences of climate change relate to water resources, including:

• warming air and water; • change in the location and amount of rain and snow; • increased storm intensity; • sea level rise; and • changes in ocean characteristics.” USEPA Office of Water (2008), page 51. The Minnesota Pollution Control Agency (MPCA) climate change website states: “Minnesota is

already experiencing impacts from climate change, and will continue to experience impacts to our ecosystems, natural resources, and infrastructure.” The MPCA website quotes the US Global Change report (2009) which highlights key midwest impacts:


• During the summer, public health and quality of life, especially in cities, will be negatively affected by increasing heat waves, reduced air quality, and increasing insect and waterborne diseases. In the winter, warming will have mixed impacts.

• The likely increase in precipitation in winter and spring, more heavy downpours, and greater evaporation in summer would lead to more periods of both floods and water deficits.

• While the longer growing season provides the potential for increased crop yields, increases in heat waves, floods, droughts, insects, and weeds will present increasing challenges to managing crops, livestock, and forests.

• Native species are very likely to face increasing threats from rapidly changing climate conditions, pests, diseases, and invasive species moving in from warmer regions.

Specific Findings on Climate Change Impacts on Minnesota’s Water Resources Major trends in Minnesota’s climate have important implications for water resources (Skaggs and

Blumenthal, 2009). Those highlighted below are most relevant for this paper given their potential socio-economic significance due to impacts on water resources.

1. Changing character and quality of precipitation: there is an increasing proportion of annual precipitation coming in summer thunderstorms and these have more spatial variability than other precipitation events,

2. Warmer winter minimum temperatures, 3. Higher summer heat indices due to higher humidity and higher ambient air temperature, 4. Increase in the number of freeze/thaw days Dedaser-Celik & Stefan (2009) analyzed trends in streamflow in Minnesota since 1946 using gauges

from five different river basins across the state. The trends observed matched many predicted by other climate change literature such as increased high flow due to increased runoff. While extreme flood events have not increased, flows over a wide range of recurrence intervals have either increased over time or remained the same. These researchers did determine that rivers located in areas with higher rates of precipitation showed increases in streamflow.

Findings from the component of the project on streamflow indicate that the Minnesota River Basin and the Red River of the North have larger increases in streamflow than the other three basins in the state. Even though extreme precipitation events are likely to be randomly located across the state, it would be a wise investment to protect against such disasters in the most vulnerable locations. This would be a sound application of the Precautionary Principle and risk aversion discussed further below.

The overall project also investigated potential impacts of climate change on water quality. This paper focuses on the risks of changes in water quantity, not quality because the scope relates to insurance concepts. While changes in water quality also increase risks, these risks are of more public in nature than the risks related to infrastructure damage and other losses captured by the insurance industry or emergency management activities. CONCEPTUAL FRAMEWORK FOR INFERRING ECONOMIC IMPACTS Potential economic impacts of climate change must be understood within the conceptual framework about what people value. Environmental economics identifies two major conceptual components of value: use values and passive-use value. The theory and practice has developed toward the conventional wisdom that only recognizing use values in evaluating environmental effects would lead to substantial underestimation of value to the public.

In terms of water resources, some of the major use values revealed in market transactions are: recreational fishing, commercial fishing, commercial transportation on waterways, agricultural irrigation, infrastructure damages from flooding (drinking water, wastewater, and stormwater facilities, roads, bridges, culverts, and other structures), flood damages to crops, forests and other lands with commercial yields, hydroelectric power generation, water-borne diseases, and insurance costs.


Some of the major non-market values that could be impacted are: water quality, fish habitat, preservation of “natural” distribution of cold-water species such as lake trout and cisco, preservation of native aquatic plants, and preservation of “natural” levels of surface waters.

Option Value as a Conceptual Framework for Understanding Damages Due To Climate Change

In the extensive literature on option value, the concept is consistently defined as the difference between option price and expected consumer surplus, where option price is the maximum willingness-to-pay to maintain the option of future consumption. The concept is used to explain why people willingly purchase insurance and pay a premium that exceeds the expected loss. Hence option value is referred to as a risk-aversion premium. The conceptual framework for the application of option value to protecting against climate change impacts is adapted from the model in Freeman (1985).

Equivalent surplus, ES, is defined as the willingness-to-pay to avoid certain damages to water resources from climate change. But given climate change poses a risk of impacts greater than zero but less than 100% certain, efforts to reduce the impacts of climate change must be seen as lowering these probabilities. Similarly climate change can be conceptualized as increasing risks by increasing the dispersion of likely future states of the world. Even if the expected values for qualities and quantities of Minnesota water resources are assumed to remain unchanged, the widening of the extreme outcomes increases the riskiness of the world in the future. Given society is made up of individuals who typically are risk averse, increased risk due to climate change causes a loss in well-being.

The theoretical discussion of option value in the economics literature associates risk-averse preferences with characteristics of the typical individual’s utility function. Specifically the utility function is assumed to be concave downward, i.e. exhibiting diminishing marginal utility of income. Departures from these and other theoretical assumptions lead to different conclusions about the sign and importance of option value. Boardman, et al. (2006) provides an informative overview of this debate.

Indeed the debate in the theoretical literature on option value has also played out in the economic analysis of climate change. The Stern Review (2006) provides seminal analysis of potential global economic impacts of climate change. It has been a catalyst for further scholarship on this topic. Stern relies heavily on option value as a component of the economic value of reducing the threat from climate change. Others have concurred with this conclusion while still others vehemently disagree. A key point of disagreement with the conclusion that option value should be counted as a positive benefit of reducing the threat of climate change is the view that individuals are also averse to the risk of losing income by spending on climate change mitigation that may turn out to be unnecessary.

But this argument misses the point that the trade-off in risks uses income as the unit of account. Money is the common denominator for balancing the risks of “doing too much too soon, or too little too late.” The income equivalent to reduce environmental risk is already in the form of this monetary expenditure. The count money again as a risk of unneeded expenditure would be double counting. The WTP of risk-averse individuals exceeds expected loss because they see the risk of environmental damage as warranting the risk of spending money, even if unnecessarily.

The reasoning some authors use to conclude that climate change mitigation will not generate economic benefits in the form of option value would also be flawed when applied to the insurance industry. This reasoning would wrongly imply that individuals would quit buying homeowners insurance. In reflecting back on a year where no insurance claims needed to be filed, would a risk-averse individual attach greater risk to spending on insurance unnecessarily because no damages occurred? The repeated expenditure for insurance demonstrates that individuals benefit from the sense of security from a loss (even if it has low-probability), and weigh avoidance of that loss more heavily than the chance that they could have gotten by without purchasing insurance. The insurance industry depends on individuals having preferences in weighing risks that are manifested in WTP being more than the actuarially expected loss. That risk-aversion premium is the source of profits to the insurance industry.

The discussion above applies to a simple case where option value serves to maximize expected utility when risk is introduced to a previously riskless situation (see Freeman, 1985.) A more realistic characterization of the risks imposed by climate change is to add greater extremes to an already risky


world. The simple case portrays climate change as introducing risk to the future quality and quantity of water resources. In reality, the future of Minnesota’s water resources is already risky, without the added threat of climate change. So the more complex scenario would model climate change as widening the dispersion of likely future states of the world.

The literature on impacts notes that some environmental changes could be negative and some positive. If the negative changes outweigh the positive, there will be a socio-economic loss due to climate change, both due to lower expected income and lower expected utility due to aversion to greater risk. But the case of widening the distribution also shows loss from climate change even if the positive effects are equal to the negative effects in both magnitude and probability, so that expected income is unchanged. In this scenario loss from climate change is not due to a decline in expected values, but rather due to the preference to reduce the risk inherent in more dispersed outcomes. In other words the risk increase due to climate change can be modeled such that the expected value of the resource remains unchanged but the dispersion is more extreme. Here a risk-neutral individual would sense no loss from this greater dispersion because the expected loss is unchanged, so would have no option value. But using Freeman’s framework where most people are risk averse, they would attach substantial option value to insure against the wider dispersion between the best-case and worst-case scenarios.

Option value applies more widely to climate change impacts than just to water resources. In fact it addresses a fundamental aspect of the potential economic loss from climate change. Statisticians characterize distributions with measures of Central Tendency and Dispersion. Much of the concern about climate change impacts has focused on increases in measures of Central Tendency such as higher average temperatures or higher mean precipitation. But from a socio-economic perspective the potential damages linked to increasing dispersion, such as more extreme temperatures or precipitation patterns may be just as damaging to social and economic well-being. Given the probability of greater extremes, the concept of option value is crucial to understanding the economic impacts of climate change. Review of the Literature Applying Option Value to Climate Change

A paper on the economic impacts of climate change by Heal and Kristrom (2002) is particularly thorough on the concept of option value and the Precautionary Principle. They extend the discussion of balancing risks in the previous section by including the aspect of irreversibility and endogenous learning. Heal and Kristrom state: “the preconditions necessary for the existence of an option value seem to be satisfied in the context of climate change. We expect to learn about the costs of climate change and about the costs of avoiding it over the next decades. And we expect that some of the decisions that we could take will have consequences that are irreversible. These are the hallmarks of decisions that give rise to option values associated with conservation. …But although these conditions are necessary for the existence of option values they are not sufficient. …there is another possible real option value at work here. If substantial sunk costs must be incurred to begin the process of abating greenhouse gas emission and avoiding or minimizing climate change, if the return to this investment is the avoidance of climate change, and if we learn about the value of this over time, then there is also a real option value associated with postponing investment in greenhouse gas abatement.” Page 25

Precaution against an irreversible outcome that would destroy information is regarded in the literature as having quasi-option value. This argument assumes environmental damages are harder to reverse than the policies aimed to insure against them. This is referred to as asymmetric irreversibility. One view is that action should be taken to prevent potential impacts because by the time impacts are better known it may be too late. There is an opportunity for exogenous learning in waiting to see how bad damages become, but impacts may be irreversible by then. On the other hand, there could be endogenous learning enabled by taking action in that greenhouse gas abatement will teach us costs and these can be reversed later if we learn abatement is unnecessary. In fact, the EPA classifies pollution-control technologies distinguishing between the best that might be achievable through time versus those already in place. This classification invites an interpretation that endogenous learning can occur with these investments. Policies that generate endogenous learning are often comprised of what are commonly called “demonstration projects.” Attempts to control pollution, or mitigate effects, are needed for endogenous learning to occur.


But an opposing view in the literature contends that pollution control commitments may also be difficult to reverse. Heal and Kristrom advocate that policies be designed to be flexible enough to be adjusted as new information is forthcoming. They provide a conceptual framework with dollar ranges and probabilities of damages and costs of action. (Heal and Kristrom, 2002 also discuss humans’ preferred temperatures and disutility from weather extremes.)

Heal and Kristrom recognize role of the Precautionary Principle in the economics of climate change. A quote from the 1992 Rio Declaration (Article 15) is cited: “where there are threats of serious and irreversible damage, lack of full scientific certainty shall not be used as a reason for postponing cost-effective measures to prevent environmental degradation.” An opposing view is that precautions should be taken against premature expenditures on pollution control. Waiting to act until more is learned about the damages will also have an information value. This is described as the “learn then act” strategy. Heal and Kristrom note that “if we follow this strategy then the risk that society faces in the future will be greater” and that balancing these countervailing risks depends on the shape of the utility function and the level of “prudence” adopted by society. Page 26

Heal and Kristrom (2002) and Heal (2008) discuss uncertainties that are both ecological and economical. A major challenge to the Stern Review is the economic uncertainties that exist about future optimal discount rates, growth rates and technological advancement. However, it should also be noted that human behaviors and adjustments to information likely provide greater reversibility and are likely to be more flexible than ecosystem constraints. Unraveling ecosystem interconnections and irreversible threshold and cascade effects are potential consequences that need to be considered. In ecosystems, constraints such as the First and Second Laws of Thermodynamics and the Law of Conservation of Matter are immutable laws, in contrast to economic laws about behaviors and incentives.

The debate about whether option value would be positive for reducing the threat of climate change boils down to whether there is an income equivalent that expresses WTP as a risk-aversion premium. The conclusion of this analyst is that purchases of physical capital in the form of pollution control equipment - whether it be to reduce greenhouse gases or reduce other causes of potential environmental degradation –can be translated more readily into income equivalents than the consequences of losing natural capital. The same is true for the potential loss of human life.

Reducing the risk to water resources from climate change is one impact that could generate positive option value as a risk-aversion premium to individuals. An individual’s willingness to pay an option price to protect water resources which is greater than expected losses is analogous to the individual motives for paying insurance companies premiums that generate profit. But an important distinction is that option value for protecting water resources accumulates to all individuals that are averse to these risks. So benefit accumulates simultaneously to all of these individuals due to policies that reduce these risks. This collective benefit fits the definition of a public good.

The evidence on climate change impacts suggests that irreversible damages could occur. This implies an asymmetry in the countervailing risks of 1) premature action posing the risk of “Doing Too Much Too Soon” and 2) waiting until scientific evidence is better understood leading to the eventual regret of “Doing Too Little Too Late.” Good policy formulation can provide flexibility to alter future pollution abatement investments. Human/social decisions should be more reversible than many environmental impacts; damages to ecosystems, loss of native species, loss of human life, etc. These risks are seen by this analyst as being less reversible, greater in magnitude and more difficult to monetize than expenditures on pollution control devices. If risks of irreversibility are asymmetric in this way, the risk-aversion premium weighs toward “Doing Too Much Too Soon.” SURVEY OF THE LITERATURE ON ECONOMIC IMPACTS OF CLIMATE CHANGE Insurance Industry Perspectives

Over a decade ago, Michael Tucker (1997) provided a perspective on climate change action based on the market for insurance. “A convincing economic argument for taking action to prevent or ameliorate climate change has not developed because of both uncertainty about the degree of change and its timing.


Recent costly weather-related catastrophes with consequent negative impacts on the insurance industry has made the insurance industry a potential advocate for slowing what has been identified as a causal factor in climate change: emissions of greenhouse gases. However, rising costs of claims, without a longer-term trend of such catastrophic losses, will make it difficult to present a strong case for taking costly economic action.” Tucker developed a technical, industry-specific argument regarding pricing of insurance to strengthen the case for action on climate change. He concluded that “economically justified higher insurance premiums” would result from “increasing levels of climate variability as embedded in the anticipated variability of damage to insured asset.” While potential climate change impacts such as sea level rise are often conceptualized as not occurring until far into the future, Tucker’s perspective of weather related damages brings the consequences into the present day, even in 1997.

In an article on global change, Berz (1999) speculates that “changing probability distributions of many processes in the atmosphere” will result in “serious consequences for all types of property insurance.” “In areas of high insurance density the loss potential of individual catastrophes can reach a level at which the national and international insurance industries will run into serious capacity problems.” Three insurance industry experts, Mills, et al. (2001) estimate a 15-fold increase over the period 1970 -2000 in insured losses from catastrophic weather events (defined as exceeding $1 billion of damages.)

Following is a statement from the website of the Insurance Information Institute. “Catastrophes appear to be growing more destructive, but insured losses are also rising because of inflation and increasing development in areas subject to natural disasters. In 2005, the year of hurricanes Katrina, Wilma and Rita, catastrophe losses totaled $64.3 billion. Hurricane Katrina caused losses of $41.1 billion, the highest on record, about twice as much as Hurricane Andrew would have cost had it occurred in 2005. Seven of the 10 most expensive hurricanes in U.S. history occurred in the 14 months from August 2004 to October 2005. If, as suggested, hurricane-related losses grow by as much 40 percent over the next 20 years, a Katrina-like storm could cause $60 billion in losses, or significantly more if it struck a densely populated metropolitan area like Miami or New York City.”

The evidence from the scientific literature does not lead to consensus about trends in hurricane frequency and severity. But these damage figures are of concern to many in the insurance industry and have broader implications for society as a whole.

In their paper on the economics of climate and insurance, Valerde and Andrews (2006) state: “As a key instrument and enabler of loss mitigation and risk transfer, the U.S. insurance industry lies at the nexus of several crucial dimensions of the climate change problem, especially as it relates to the potential implications of climate change for society and the global economy. Having sustained record-breaking natural catastrophe losses, insurers and reinsurers are openly—and, indeed, justifiably — questioning the potential linkage between anthropogenic climate change and extreme weather, looking at both the likely short-term implications for the industry, as well as potential long-term impacts on financial performance and corporate sustainability.” page 1. “A fundamental question that we pose here, then, is whether the risks posed by global climate change are, in some way, structurally different than what has previously come to pass, thereby presenting insurers with new — and, some would argue, unprecedented—challenges, requiring a fundamental rethinking of the mindsets and methods that are used to manage these risks. Indeed, it may be the case that traditional underwriting and risk management methods are not adequate for this task.” page 3. Despite the highly developed theory and practice of actuarial science, these authors are suggesting that the risks posed by climate change may present new and unprecedented challenges.

In an analysis of trends in the Canadian insurance industry, White and Etkin (1997) state: “At the same time that a scientific consensus has arisen that the world will most likely experience a changing climate in the near future, with more frequent extreme events of some weather hazards, the insurance industry, worldwide, has been hit with rapidly escalating costs from weather-related disasters. This conjunction of scientific belief and economic impact has raised the questions as to (1) whether more frequent extreme events have contributed to the rising insurance costs and (2) how will future climate change affect the industry? Based upon historical data, it is difficult to support the hypothesis that the recent run of disasters both world-wide and in Canada are caused by climate change; more likely other


factors such as increased wealth, urbanization, and population migration to vulnerable areas are of significance. It seems likely, though, that in the future some extreme events such as convective storms (causing heavy downpours, hail and tornadoes), drought and heat waves will result in increased costs to the industry, should the climate change as anticipated.”

The evidence on worsening trends in weather-related damages has continued to grow over the last decade. The World Wildlife Fund for Nature and Allianz Insurance Company issued a report (2009) on tipping points from climate change and damage potential. The report notes that “The phrase ‘tipping point’ captures the intuitive notion that “a small change can make a big difference.” As a concept for understanding risks, the tipping point invites comparisons to the argument by Valerde and Andrews that the insurance industry may need to develop a new paradigm. Tipping points in ecosystems, ecological goods and services and in the planet’s life support systems could force tipping points in many human-social institutions, including the insurance industry. Damages to Public Infrastructure

The economics literature on risk-aversion should inform decisions on climate change. The potential damages from climate change are the types of risks that people typically wish to guard against. Most citizens place a value on risk reduction and are willing to pay for the insurance value this yields. As noted above, public policy that reduces the risks described above is a public good to all those who have risk-averse preferences. It is a collective value derived from the sort of individual value many people place on private insurance. Fundamental aspects of climate change involve risks that are better understood in the context of option value.

Some studies at the national or international level aggregate findings that originate at the spatial scale of states. Research for the National Weather Service has categorized weather-related damages by state. A study by Pielke, et al. (NOAA, 2002) estimates the monetized damage estimates from National Weather Service records for each state. This information is aggregated from separate datasets. Information from local regions was added to statewide data in some cases. Damage information spans from 1925 to 2000. Despite some data limitations that are explicitly noted, the document contains useful information. For example, flooding in Minnesota cost over $900 million in 1993 and $700 million in 1997. The annual damage figures for MN span from 1955 to 2000. Current and constant dollar estimates are provided in Table 1.

Research by Lettenmaier, et al. (2008) examines the current relationship between climate change and water. This study projects the near term impacts of global climate change on water resources in the United States for the next 25 to 50 years. Major aspects included are streamflow, evaporation, drought, precipitation, runoff and water quality. Minor focus areas include land use and ground water impacts. In the analysis of streamflow, trends from 393 stations in the US were plotted on maps with statistically significant increases reported in the central portion of the United States, including source stations in Minnesota. Evaporation rates are examined and where net decreases occur plausible explanations are offered, such as being due to increased cloud cover.

Droughts are anticipated to occur more frequently in the West and Southwest. A wetter climate overall is found to occur based on data from 1915 to 2003. Droughts are not projected to affect the central portion of the United States. Regional analysis is conducted for the central portion of the US, which includes Minnesota. Two separate studies have indicated an overall increase in precipitation in this region.

In relation to increased precipitation, runoff rates are explored using USGS statistics on runoff trends from 1901 to 1970. Projecting these trends into the future suggests an overall increase in runoff in the central US. Within this region, there is likely to be an increase in runoff in the Upper Mississippi basin. POTENTIAL ECONOMIC EFFECTS OF CHANGES IN MINNESOTA’S WATER RESOURCES Potential Economic Impacts from Changes in Water Flows

While the literature on global changes, including US federal government research (2009), indicates


higher lake levels in the Midwest, except perhaps the Great Lakes, research on MN lake levels thus far yields mixed results. Lake levels appear to be less susceptible to immediate pulses of water from precipitation and snowmelt than are rivers and streams. The vulnerabilities of rivers and streams to flash-flooding is not an immediate concern for lakes. This is not to say that fluctuations in lake levels are not a concern in MN, but the evidence thus far points to water levels in rivers and streams warranting more attention.

As noted above, Heinz Stefan and his colleagues (2007, 2008, 2009) have studied water levels in lakes, rivers and streams. The streamflow analysis was based on data from gauging stations in the five major river basins of the state. In general, this evidence is consistent with impacts predicted in the literature. Results vary between the five basins, but generally the data indicate higher median flows and higher 90th percentile flows. Methods of describing riverine flows utilize measurements of time spans, such as 1-year, 10-year, 20-year, 100-year and 500-year floods. Ten-year floods should occur every ten years so should have a one in ten chance of occurring in any given year. One-hundred year floods should have only a one-percent chance of occurring and 500-year floods should have a probability of only two tenths of one percent. The work by Stefan and associates indicates that these floods are happening more frequently than the odds predict, especially for the 10-20 yr. floods. The statistics are less meaningful for the most extreme events associated with the most severe damages: 100-year and 500-year floods.

Even though the most extreme flow levels do not exhibit strong statistical changes, the increased baseline (median) flows and more frequent 10 to 20-year flood events could be evidenced by a trend toward increasing infrastructure damages. The evidence from the data must be couched in terms of limitations of data availability in terms of temporal and spatial scales: i.e. too few years of water levels are available to show long-term trends and too few flow measures have been taken within watersheds at the levels of tributaries or smaller in the five major basins. Downscaling of data may be necessary to enhance understanding of flooding patterns. Catastrophic events such as the southeastern MN flood of 2007 that severely damaged Rushford, MN and the surrounding area must also be recognized even though data availability may make it hard to place these extreme events in context. The economic evidence below does include these extremely damaging events even though they may be difficult to define in terms of evidence of climate change.

Another nuance of the merging of evidence on streamflows and damages relates to the higher base flow levels, especially in late winter and spring as snow melt enters the major basins. This pattern worsens risks of spring flooding in ways that may be too difficult to discern from data available thus far. Higher base flows and greater snow melt create worse vulnerability to early spring rains putting rivers and streams even higher above flood stage. The extreme flood event in the Red River Valley in 1997 was unusual given the record snow depths of that winter, but increased likelihood of rain at this time would exacerbate the problem. The 1997 floods show up in the damage records below.

It is essential to recognize that many variables are changing through time and in directions that would indicate historical trends for more flood damages for some trends and less for others. One factor suggesting that historical trends would be toward more damages is simply the inflation of the value of the resources and materials that are lost. Increasing development also places more valuable assets in harm’s way. These and other changes make dollar amounts difficult to compare over the years. Policy has been in place for some time to invest in prevention of future damages by making scheduled replacement of transportation infrastructure (roads, bridges, culverts, etc.) to withstand high flow events. Furthermore when damages occur and emergency repairs are needed these too are being done to provide a buffer or guard against the failure of infrastructure repeating itself. This policy should lead to a decrease in damages over time. Historical trends are difficult to interpret given outcomes on damages result from a combination of influences, some positive and some negative. Multiple variables that influence infrastructure damages are in flux in MN so that the data on damages must be interpreted with caution.

Non-transportation infrastructure also merits attention. Some of the most expensive repairs are needed when drinking water facilities are overcome, especially if in conjunction with inundation of wastewater treatment plants. Precautions for human health concerning emergency water supply and long term repair make this category of damages very costly when they occur. The evidence in MN would indicate that


these catastrophic damages are not increasing as dramatically as more numerous washouts of less costly infrastructure such as secondary roads and culverts associated with 10 to 20-year flood events. The data on damages reported below warrants explicit mention of some basic arithmetic: total damages amass just as much through many incidents of low to moderate cost as with fewer incidents of high cost. The former, if not the latter, would appear to be occurring more frequently in MN as a result of climate change.

Before moving on to a discussion of damage figures, greater dispersion of flows, including more extreme low flows should also be mentioned. Project findings on generally higher flows should not mask the possibility of economic costs of extreme low flows during extended droughts. The basins that show the most significant changes in flow are the Red River of the North and the MN River. Concerns over dependable water supply in the Red River of the North (Fargo, ND – Moorhead, MN and Grand Forks, ND - East Grand Forks, MN) have led to research and policy discussions as to these vulnerabilities and possible remedies. Again climate change makes this situation more risky.

Damage figures below are presented in order of most general categories of infrastructure to data more specific to transportation at the end. Table 1 provides figures for Minnesota from a NOAA study (2002) that reports the history of U.S. flood damages from 1955 to the most recent year, 2000. The report re-examines data back to the 1920s but only details damages state-by-state from 1955- 2000. The most informative column shows damages standardized in 1995 dollars, in thousands. This shows that from 1955 – 1970 there were three years with damages in the tens of millions of dollars and two in the hundreds of millions. From 1971 – 1984 (1980-82 missing) there were three years with damages in the tens of millions of dollars and three in the hundreds of millions. From 1985 – 2000 there were three years with damages in the tens of millions of dollars and the two years with the highest damages 1997 and 1993. The latter had damages in excess of $1 billion in constant 1995 dollars.

The MN Department of Public Safety’s Division of Homeland Security & Emergency Management summarized damage information over the decade of the 1990s. The summary is more enlightening than the totals above being the damage figures are broken down into informative categories. The report “A Decade of Minnesota Disasters: A Historical Look at Minnesota Disasters in the 1990s” notes that the specter of climate change places increased importance on changing weather patterns and the increase in storm occurrence and intensity. The report focuses on weather related damages in Minnesota throughout the 1990s. According to the report, these damages are increasing and during the 1990s there were 14 presidential declarations of major disasters. Most of the damages were the result of flooding, ice storms, snow removal, straight-line winds, tornadoes, and heavy rain. From these disasters Minnesota taxpayers spent $827 million and the cost to insurance companies was more than $2 billion.

The report also ranks MN hazards by category of loss that occurs. It is based on data from the Minnesota Hazard Mitigation Plan. The rankings are a composite of: likelihood of occurrence, frequency, and historical impacts as natural hazards affecting the state. On average per year, blizzards are the top cause of deaths, ice and sleet are highest for injuries causes, and floods cause the most economic impact. Table 2 lists the 14 declared disasters in Minnesota for the 1990s, including totals by year. Some years had multiple declared disasters. A report for the last decade is not yet available but Table 3 categorizes the disasters since 2000.

TABLE 1 FLOOD DAMAGE

(in 1000s of Current and Constant 1995 Dollars)

Year Deflator Current $ Constant 1995 $ 1955 0.20163

0 0.000

1956 0.20846

11 52.768 1957 0.21539

9,128 42378.941

1958 0.22059

17 77.066 1959 0.22304

50 224.175


1960 0.2262

212 937.224 1961 0.22875

552 2413.115

1962 0.2318

1,290 5565.142 1963 0.23445

26 110.898

1964 0.23792

0 0.000 1965 0.24241

97,603 402636.030

1966 0.24934

4,300 17245.528 1967 0.25698

0 0.000

1968 0.26809

1,197 4464.918 1969 0.28124

67,168 238828.047

1970 0.29623

4,350 14684.536 1971 0.31111

15 48.214

1972 0.32436

64,318 198292.021 1973 0.34251

242 706.549

1974 0.37329

16,939 45377.588 1975 0.40805

139,726 342423.723

1976 0.43119

0 0.000 1977 0.45892

7,870 17148.958

1978 0.49164

65,000 132210.561 1979 0.53262

13,140 24670.497

1983 0.70214

310 441.507 1984 0.72824

5,000 6865.868

1985 0.75117

500 665.628 1986 0.76769

1,501 1955.216

1987 0.79083

27,800 35152.941 1988 0.81764

555 678.783

1989 0.84883

17,600 20734.423 1990 0.88186

3,032 3438.187

1991 0.91397

1,280 1400.484 1992 0.93619

1,760 1879.960

1993 0.95872

964,050 1005559.496 1994 0.9787

1,867 1907.633

1995 1

3,750 3750.000 1996 1.01937

460 451.259

1997 1.03925

743,218 715148.424 1998 1.05199

2,529 2404.015

1999 1.06677

466 436.833 2000 1.09113

43,112 39511.332

(Note: constant 1995 dollars divide current $ by the implicit price deflator according to the U.S. Bureau of Economic Analysis, 2001. No estimates for 1980-1982.)


TABLE 2 FEMA DECLARED DISASTERS IN MN DURING THE 1990S

1. FEMA 1288 DR MN (1999) Total Cost $11.1 million 2. FEMA 1283 DR MN (1999) Total Cost $52.2 million 3. FEMA 1225 DR MN (1998) Total Cost $1.5 billion 4. FEMA 1212 DR MN (1998) Total Cost $246.1 million 5. FEMA 1187 DR MN (1997) Total Cost $85.4 million 6. FEMA 1175 DR MN (1997) Total Cost $545.0 million 7. FEMA 1158 DR MN (1997) Total Cost $82.4 million 8. FEMA 1151 DR MN (1997) Total Cost $20 million 9. FEMA 1116 DR MN (1996) Total Cost $48 million 10. FEMA 1078 DR MN (1996) Total Cost $6.7 million 11. FEMA 1064 DR MN (1995) Total Cost $18 million 12. FEMA 993 DR MN (1993) Total Cost $215.1 million 13. FEMA 946 DR MN (1992) Total Cost $32.5 million 14. FEMA 929 DR MN (1991) Total Cost $11.7 million

Totals by Year: Sum for Decade $2,874,200,000

Year Totals Year Totals Year Totals 1999 63,300,000 1995 18,000,000 1991 11,700,000 1998 1,746,100,000 1994 0 1997 732,800,000 1993 215,100,000 1996 54,700,000 1992 32,500,000

TABLE 3

DAMAGE TOTALS FOR FEMA DECLARED DISASTERS 2000-PRESENT: DESCRIPTIONS AND TOTALS

Description Public

Assistance Total

*Total

4/19/2010 Flooding (estimates) $ 17,907,069 $ 20,593,129 03/19/2010 Flooding $ - $ - 04/09/2009 Severe Storms and Flooding $ 38,221,852 $ 47,526,068 03/26/2009 Severe Storms and Flooding $ 726,393 $ 726,393 06/25/2008 Severe Storms and Flooding $ 8,238,063 $ 9,176,828 08/23/2007 Severe Storms and Flooding $ 43,753,443 $ 85,439,673 06/05/2006 Flooding $ 9,123,910 $ 9,634,389 01/04/2006 Severe Winter Storm $ 10,465,370 $ 11,089,558 10/07/2004 Severe Storms and Flooding $ 5,037,343 $ 9,712,096 06/14/2002 Severe Storms, Flooding and Tornadoes $ 33,943,265 $ 50,376,450 05/16/2001 Flooding $ 46,526,867 $ 56,712,017 06/27/2000 Severe Storms, Flooding and Tornadoes $ 14,840,929 Declared

*Total includes only the federal and state share of funding paid under the Stafford Act. Other federal funds, special state appropriations, and local funds are not included. The difference between Public Assistance payments and the total is Individual Assistance Program payments and Hazard Mitigation Grants


CONCLUSIONS AND IMPLICATIONS FOR FURTHER RESEARCH Conclusions

The economics literature on risk-aversion should inform decisions on climate change. The potential damages from climate change are the types of risks that people typically wish to guard against. Most citizens place a value on risk reduction and are willing to pay for the insurance value this yields. Public policy that provides this is a public good to all those who have risk-averse preferences. It is a collective value derived from the sort of individual value many people place on private insurance.

Economic efficiency and equity goals are relevant to decisions about climate change. Risks from climate change could be reduced through emission reductions and/or adaptive strategies such as enhancing ecosystem integrity and resilience, precautionary design of infrastructure, etc.) If avoiding potential damages is deemed to generate net benefits and/or enhance equity, ways of achieving these goals at least cost should be pursued. Increasing the prevalence of best land-use practices applied in many watersheds may be a cost-effective way to offset ecological stress on Minnesota’s water resources. Flood Damages

An adaptive strategy to climate change would be to identify settings with the greatest vulnerability to catastrophic failure such as loss of life and property if structures fail. Most of the MN topography does not cause as great of danger of flash flooding as in more mountainous areas. The severe flood in southeastern MN in 2007 demonstrates that the topography of that part of the state makes it more vulnerable to severe flash floods. Elsewhere in Minnesota, overland flooding is more likely to occur rather than the deep rush of water with floods in hills and valleys. A two-pronged approach to risk management would inventory watersheds for greatest vulnerability to damages from flash floods according to two characteristics: 1) geomorphology conducive to flash floods and 2) human and natural environments that put highly valued assets and human life in harm’s way.

Findings from the component of the project on streamflow indicate that the Minnesota River Basin and the Red River of the North have the largest increases. Even though extreme precipitation events are likely to be randomly located across the state, it would be a wise investment to protect against such disasters in the most vulnerable locations. This would be a sound application of the Precautionary Principle.

The longest yearly record for weather-related damages in MN comes from figures reported in a NOAA study (2002) that re-examines damage figures from 1925-2000 using constant 1995 dollars. From 1955-2000 occasional weather events caused damages in the tens of millions of dollars. Damages in the hundreds of millions of dollars also occurred over this time period. By far the two years with the highest damages were 1997 and 1993. The floods of 1993 caused damages in excess of $1 billion in constant 1995 dollars.

The MN Department of Public Safety’s Division of Homeland Security & Emergency Management provided summarized damage information over the past two decades. According to the report “A Decade of Minnesota Disasters: A Historical Look at Minnesota Disasters in the 1990s” these damages are increasing with 14 presidential declarations of major disasters over the decade. Most of the damages were the result of flooding, ice storms, snow removal, straight-line winds, tornadoes, and heavy rain. The disasters of the 1990s cost Minnesota taxpayers $827 million and more than $2 billion to insurance companies.

Examination of transportation infrastructure as a major category of damages revealed that numerous weather-related events have occurred in the last two decades that caused damages to roads, bridges and culverts in the millions or tens of millions of dollars, per event. Implications for Further Research

The larger MN research project identified future needs for data at scales appropriate to understanding climate change impacts in Minnesota. Much of the discussion in the research community at the national and state level is emphasizing the need to “downscale” data to allow meaningful analyses for smaller


geographic areas, such as states. Needs to improve scale are: 1. Spatial Scale: consensus on need for “downscaling.” Scaling Down Global and Regional Patterns

to State Level and 2. Temporal Scale:

A. Data to Determine variations over long enough time span and B. Hydrologic Data to Determine variations in Stream Flows that occur within 7-day period,

such as extreme flows within a 24-hour period. One major example of limitations due to too short of time span is described in an earlier project

summary. It pertains to projecting biological responses to changing climate. Fish populations and other biological communities will be affected by warmer water temperatures, and altered thermal regimes, changes in flow regimes, total flows, water level, and water quality. These changes will affect the health of aquatic ecosystems, with impacts on productivity, species diversity, and species distributions. The paucity of historic data makes it difficult to assess past changes and predict biological responses to climate change.

The overall project, and the economic component, generated useful information as an indication of where the state might be headed in terms of climate change. It also indicates how much remains to be done in order to generate more precise empirical evidence. A great deal is being learned about how climate change may impact the future and what options exist to address it. Climate change has implications in time scales longer than most institutions are equipped to handle. Research design and policy formulation needs to reckon with these long time horizons in determining actions today that will benefit the future. REFERENCES Berz, G. (1999). “Catastrophes and Climate Change: Concerns and Possible Countermeasures of the Insurance Industry” Mitigation and Adaptation Strategies for Global Change, Volume 4, Nos. 3-4. Boardman, A., Greenberg, D., Vining, A., and Weimer, D. (2006) Cost-Benefit Analysis: Concepts and Practice, 3rd Edition. Upper Saddle River, New Jersey: Prentice Hall. Dedaser-Celik, F., & Stefan, H. G. (2007). Lake level response to climate in Minnesota. (Project Report No. 502). St. Paul, Minnesota: Legislative Citizens Commission on Minnesota Resources. Dedaser-Celik, F., & Stefan, H. G. (2008). Lake evaporation response to climate in Minnesota. (Project Report No. 506). St. Paul, Minnesota: Legislative Citizens Commission on Minnesota Resources. Dedaser-Celik, F., & Stefan, H. G. (2009). Stream flow response to climate in Minnesota. (Project Report No. 510). St. Paul, Minnesota: Legislative Citizens Commission on Minnesota Resources. Freeman, A.M., III. (1985). “Supply Uncertainty, Option Price, and Option Value”. Land Economics. 61: 176-181. Heal, G., (2008). “Climate Economics: A Meta-Review and Some Suggestions for Future Research, Review of Environmental Economics and Policy, pp. 1–19. Heal, G. and B. Kristrom (2002).“Uncertainty and Climate Change” Environmental and Resource Economics 22: 3–39. Insurance Information Institute, website http://www.iii.org/issue_updates/222678.html Legislative-Citizens Committee on Minnesota Resources. (2010) L. Johnson, Principle Investigator.


“Minnesota's Water Resources: Impacts of Climate Change- Phase II”. Lettenmaier, D. P., Major, D., Poff, L., & Running, S. (2008). The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity. Retrieved February 14, 2010, from http://www.climatescience.gov/Library/sap/ sap4-3/final-report/sap4-3-final-water.pdf Mills, E., Lecomte, E. and A. Peara, (2001). “U.S. Insurance Industry Perspectives on Global Climate Change.” US Department of Energy. MN Department Public Safety: Homeland Security & Emergency Management. “A Decade of Minnesota Disasters: A Historical Look at Minnesota Disasters in the 1990s” MN Pollution Control Agency, climate change website National Oceanic and Atmospheric Administration, National Center for Atmospheric Research, (2002). “Flood Damage in the United States, 1926–2000: A Reanalysis of National Weather Service Estimates.” Skaggs, R., & Blumenfeld, K. (2009). Full report of climatic analyses for LCCMR 2005 Impacts on Minnesota’s aquatic resources from climate change, Phase I – W-12, Result 2: Historic Climate Data. Unpublished manuscript. Department of Geography, University of Minnesota, Minneapolis, MN. Stern, Nicholas (2006). Stern Review on the Economics of Climate Change. London, UK: Her Majesty’s Treasury. Tucker, M. (1997). “Climate Change and the Insurance Industry: The Cost of Increased Risk and the Impetus for Action” Ecological Economics, Volume 22, August 1997, Pages 85-96. U.S. Environmental Protection Agency, Office of Water, (March 2008). NATIONAL WATER PROGRAM STRATEGY: Response to Climate Change. U.S. Global Change Research Program. (2009). “Global Climate Change Impacts in the United States” Cambridge University Press. Valverde, L. Jr., and Andrews, M. (2006). “Global Climate Change and Extreme Weather: An Exploration of Scientific Uncertainty and the Economics of Insurance” Insurance Information Institute Working Paper Series. Welle, P. and Vandergon, R. (2010). “Potential Impacts of Climate Change on Minnesota’s Water Resources: An Economic Analysis”. St. Paul, Minnesota: Legislative Citizens Committee on Minnesota Resources. White, R. and Etkin, D. (1997). “Climate Change, Extreme Events and the Canadian Insurance Industry”, Natural Hazards, Volume 16, nos. 2-3. World Wide Fund for Nature and Allianz Ins. Co. (2009). “Major Tipping Points in the Earth’s Climate System and Consequences for the Insurance Sector.” *This paper includes analysis that is part of a larger study conducted on behalf of the Legislative-Citizens Commission on Minnesota Resources titled “Minnesota's Water Resources: Impacts of Climate Change- Phase II.” Author’s contact information: [email protected], (218) 755-4103, fax (218) 755-4107. Research assistance on the larger study was provided by Rabi Vandergon and Brett Nelson.


A Study of Original Equipment Manufacturing in China: Current and Future Trends

Min Z. Carter

Troy University

Hank Findley Troy University

This study examines issues faced by Chinese original equipment manufacturing firms (OEMs) and explores OEM future development. Qualitative data, consisting of responses from 32 managers in 16 OEMs, were content analyzed. Results reveal various threats to OEM development and numerous opportunities that have yet to be fully explored by OEMs, as well as OEMs strengths and strategic and managerial challenges. Further, this study interprets the future OEM trends, particularly the shift from an OEM business model to the original design manufacturer (ODM) and original brand manufacturer (OBM) models, as well as, the development of long-term relationships with their clients. INTRODUCTION

Manufacturing outsourcing, aiming at reducing production cost and efficiently using worldwide labor and resources (Bhagwati, Panagariya, & Srinivasan, 2004), has become a widespread and prominent business practice for over three decades (Berggren & Bengtsson, 2004; Wadhwa & Ravindran, 2007). For example, Chrysler outsourced 100 percent of its manufacturing on half of its minicompact and subcompact cars (Gilley & Rasheed, 2000). Typically, an outsourcing company (an outsourcing client) keeps its core business components (i.e., research and development (R&D), ownership of its intellectual properties, and distribution of its final products), while contracting all or part of its non-core productions to outside businesses (outsourcing providers; Insinga & Werle, 2000; Kakabadse & Kakabadse, 2000). The client-provider economic transactions are governed by business contracts so that providers are paid for producing goods in accordance with clients’ particular specifications (Grossman & Helpman, 2005).

As one of the most important off-shore locations for U.S. manufacturing outsourcing, China has dominated the world’s outsourcing manufacturing sector due, in part, to low labor costs (Hexter & Woetzel, 2007) and large-scale manufacturing capacity (Wendin, 2005). The Chinese outsourcing manufacturing industry is mainly made up of three business models. The first business model is original equipment manufacturers (OEMs), which produce a variety of goods from semi-commodities to finished products including automobile parts, furniture, toys, and clothing. Original design manufactures (ODMs) are more than ‘factories-for-hire’ (i.e., OEMs); they design products for and/or co-design products with their clients, products such as printed circuit boards and finished electronics-based products. It is predicted that China’s ODMs will continue expanding in capacity and number, while competing with OEMs for business contracts by producing value-added products at competitive prices (Merritt, 2005).


The third business model is original brand manufacturers (OBMs) which design, manufacture, and market their products under their own brand names.

The lines of these three business models, however, are blurring. Some ODMs also have OBMs functioning, shifting from being simple outsourcing providers to also becoming emerging competitors of outsourcing clients. Moreover, when opportunities present themselves, OEMs may move beyond just manufacturing products for their clients by adopting ODM/OBM characteristics, thus moving up the supply chain from efficiency to innovation (Horng & Chen, 2008). Although some studies have suggested OEMs shift to ODMs/OBMs (e.g., Chu, Chang, & Cheng, 2006; Horng & Chen, 2008), the driving force for such a transformation, the time required for achieving the industry transformation, and the scope at which it will occur, remain unclear. Thus, one purpose of our study was to explore OEM managers’ views of the OEM business model transformation.

At the same time, environmental factors, such as labor market, the legal system, technology development, global and domestic competition, and market liberalization, continue to evolve in China (Minevic & Richter, 2005). To OEMs, one of the biggest environmental changes is that China became a member of the World Trade Organization (WTO) in 2001. Thus, China has agreed to open and liberalize its regime in order to better integrate in the world economy and offer a more predictable environment for trade and foreign investment in accordance with WTO rules (World Trade Organization, 2001). For instance, “China has repealed, revised, or enacted more than one thousand laws, regulations, and other measures” (The United States Trade Representative, 2007, p. 3) in compliance with the WTO agreement, such that price controls will not be used for purposes of affording protection to domestic businesses against international competitors (World Trade Organization, 2001). These political opening, market liberalization, and private entrepreneurship may contribute to the growth in the OEM industry and China’s economy at large (cf. Fligstein & Zhang, 2011; Huang, 2010).

Since these environmental changes may result in new business practices and shifts in its business models, issues affecting China’s OEM industry and challenges faced by OEMs need to be re-examined. In an effort to reduce the dearth in research examining the provider’s position within the outsourcing relationship, this study targets the OEMs in China. Therefore, a second purpose of our study was to explore the industry’s current situation to outsourcing providers, elucidate strengths and managerial challenges faced by OEMs, and provide insight into opportunities, threats, and future trends. We believe that our study have implications to both providers and clients such that the reveal of current OEM business practices and industrial trending development will provide insight into business model change, efficiency, innovation, and supply chain survivability. METHOD

A qualitative methodology was chosen due to the exploratory nature of this study. We reasoned that querying OEM managers by allowing them to express their insights to open-ended questions would provide rich information not possible with a quantitative methodology. We sought to collect managers’ perspectives regarding current outsourcing conditions (i.e., external opportunities and threats, internal strengths and managerial challenges) while providing insight into future trends. The overarching research questions were: What are the external opportunities and threats and internal strengths and weaknesses currently being faced by Chinese OEMs? And how are the OEMs reacting and evolving?

Procedure and Participants

Data were collected via anonymous web survey. The survey contained nine open-ended questions for capturing rich information at three levels of analysis (the OEM industry as a whole, OEM organizations, and OEM individual managers). Survey questions were written in both English and Chinese; back-translation (Brislin, 1980) was used to translate the questions from English to Chinese. The survey questions were:

1. In the OEM industry in China, how has the external environment changed since China entered the WTO in December 2001?


2. What opportunities exist in the OEM industry in China? 3. What are the threats in the OEM industry in China? 4. What are the strengths of your company? 5. What are the major managerial challenges that your company faces? 6. What recent companywide changes are you aware of? 7. What recent changes have you witnessed in your job? 8. What are the major challenges faced by you due to the changes in your job? 9. Please list any other comments and insights about the OEM industry in China, your company, and

your job. Respondents had the option of choosing to answer the survey in either English or Chinese. They were

also asked to complete demographic information such as company’s name, job position, years of work experience in current company, and total years of experience in the OEM industry.

Contact was made with 16 OEM firms, all of which were willing to participate in the study. These 16 OEMs produced a wide range of manufactured products for major U.S.-based firms as clients. The OEMs were located in, ranging from north to south along China’s coastline, eleven cities across three provinces (Guangdong, Fujian, and Jiangsu) and two municipalities (Beijing and Shanghai). The primary author sent out a solicitation email to these 16 OEMs and asked the firms to post the email in their public poster areas. To reduce response bias and produce a rich data that included a variety of perceptions common within OEM firms in China, we invited managers at all levels (i.e., top-, middle-, lower-level) to participate in the survey.

In total, usable data were obtained from 32 OEM managers, ranging from 1 to 4 managers per OEM firm. In terms of OEM product types, the 32 responses were distributed as follows: clothing (25%), textile machines (16%), construction equipment (16%), handcrafted products (13%), electronics (9%), sportswear (9%), hardware and tools (6%), and furniture (6%). Of the 32 responses, 9 responded in English and 23 in Chinese. The 23 Chinese responses were first translated from Chinese to English by the primary author, and then translation was independently verified by a researcher whose native language is Chinese. Among the 32 OEM managers, 7 (22%) were top management, 12 (38%) were middle management, and 13 (41%) were lower management. Respondents’ work experience ranged from 8 months to 10.5 years within their current firms, and 1.6 years to 20.1 years overall within the industry. ANALYSIS AND RESULTS

To analyze qualitative data, content analysis (Krippendorff, 2004) was conducted by three researchers. First, textual raw data were unitized on the basis of categorical distinctions by two researchers. Second, using the constant comparison method, these two researchers independently examined data units and inductively classified them into meaningful themes at the respective levels of analysis (i.e., OEM industry-, OEM organization-, and OEM individual-level). Discrepancies in the derived themes by the two researchers were identified, discussed, and reconciled to ensure 100% agreement. Third, after the themes were finalized, definitions for all the themes were developed by the two researchers. Fourth, based on the definitions of the themes, three researchers independently unitized the textual raw data, coded data units, and classified the data units into defined first- and second-order themes at the three levels of analysis. Last, we computed the inter-coder reliability, with an overall kappa coefficient of .94 (Cohen, 1960; Futrell, 1995). The Kappa coefficients for the first-order themes at three levels were .89 at the industry level, .95 at the organizational level, and .96 at the individual level. The Kappa coefficients for the second-order themes at three levels were .78 at the industry level, .86 at the organizational level, and .92 at the individual level. The first-order themes and random examples of responses of the second-order themes are outlined in Tables 1, 2, and 3.


TABLE 1 INDUSTRY LEVEL FIRST-ORDER AND SECOND-ORDER THEMES AND

SAMPLES OF RESPONSES

Major Themes N Samples of Responses Industry Environment and Transformation

76

Potential for Foreign Investors into the OEM Industry in China

9 Free trade fosters foreign investment into China. The industry is attracting more clients from all over the world. More multinationals build their manufacturing facilities in China.

Governmental Advantages

17

China's healthy open market environment. The customs duties on imported materials and parts are lower. The government is more open and helpful.

Business Opportunities

28

China's OEM industry has more business opportunities. Their (the OEM industry) revenue and profit are increasing. The (OEM) exports hit record high.

Employment Opportunities

4 Individuals working in the OEM industry have more employment opportunities and higher income. The industry has created more employment opportunities in China.

Low Costs 2 China has low labor cost advantage. Low production cost, and low labor cost destinations such as China.

Maturity of the Industry

3 The OEM industry is close to its maturity stage.

Shift to ODM/OBM

13 China's OEM industry… has started to transform into an industry that develops its own brand products. Every OEM firm in the industry wishes/plans to have its own brand products in the future.

Challenges to Industry Development 57 Competition for Business

26 The competition in the OEM industry is intensifying. (The industry is) facing competition from some foreign competitors.

Profit Margin

10 Although the total output value in the industry has been increasing, the profit margin is constantly dropping.

Cost 4 Labor and material costs are rising. Exchange Rate

7

This (increasing exchange rate) is a big problem to OEM firms. Higher foreign currency exchange risk.

Client Quality Expectations

4 Clients are asking for higher quality standard products. The OEM firms in the industry must improve their product quality.

Competition for R&D Professionals/ Engineers

6

Lack of talented employees (such as R&D engineers) to develop and manage brand products. Needs more engineers in the industry.


Industry Capabilities/Competencies 9 Technology/R&D Advancement

6 The OEM industry is learning advanced techniques and technology. R&D is still underdeveloped in the industry.

Production Capabilities

3 The industry can produce almost everything. The industry has very large production capacity.

Note: 1. First-order themes are numbered, and second-order themes appear in italic font. 2. N represents the numbers of units that fall in first- and second-order themes. 3. The samples of responses are randomly selected from responses of top-, middle-, and lower-level managers. OEM = original equipment manufacturer. ODM = original design manufacturer. OBM = original brand manufacturer.

TABLE 2

ORGANIZATIONAL LEVEL FIRST-ORDER AND SECOND-ORDER THEMES AND SAMPLES OF RESPONSES

Major Themes N Samples of Responses

Strategic Planning 99

Strategic Thinking/Top Management 19 Low cost strategy is no longer a good strategy (in my company). The top management needs to have a long-term strategy to expand our business globally. My company is located at a geographic advantage point, close to sea port and airport (concerning transportation of products), and accessible to adequate labor forces.

Business Expansions 25 Our company is expanding, from small to big. My company has more business contracts.

Increase in Branding and Marketing / Shifting to ODM/OBM

34 Our company is building a foundation to develop our own brand products. We (the company) are preparing to transform into an ODM company.

Organizational restructuring

10 The company should have a well-designed organizational structure. We restructured the organization in coping with the changing environment. For example, VP-Marketing used to be in charge of the Import/Export department. Now, we have created a new position -VP, International who is in charge of all import/export businesses.

Building Relationships with Clients

11 We have long-term clients in partnership with our company; the clients and our company share risk and profit; we have built trustful relationship between our company and our clients. As a new CEO, I focus on building sharing-risk-sharing-benefit long-term partnerships with our clients.

Efficacy and Development 82 Development of Reputation 3 Good reputation (is my company's strength.)


(My company) builds its own reputation.

Organizational Learning– Technology/R&D Innovation

23 My company is increasing technological component in product. To my company, it is a constant learning process. We have learned advanced production techniques and technology.

Organizational Efficacy – Production /Product Quality

56 We guarantee our clients for high quality manufactured products. (My company has) strong mass production capability. My company maintains adequate production capacity.

Organizing 110

HRM - Planning

6 HR management (is the challenge my company faces.) (My company is) improving our HR policy and practice.

HRM – Recruitment and Selection – Inadequacy of the Labor Force

23 It's harder to hire talents who can speak fluent English and also know the business environment. Lack of talented employees, especially those R&D engineers (which is the challenge the company faces.)

HRM - Recruitment and Selection – Other Comments

19 Our company has attracted talented employees. My company needs to hire more technology talents and experienced managers (which needs to be improved).

HRM – Orientation and Training

20 The company lacks training programs for the employees. We should hire a professional training firm to provide companywide management training programs.

HRM – Performance Management / Promotion Fairness

2 The company cannot promote an employee because he/she has relationship with company's management. The company should not promote an employee because he/she has Guanxi (relationship) with or a relative of the top management.

HRM – Compensation and Benefits

6 The company needs to give engineers more incentives (salary plus stock shares/bonus). (My company needs to) increase employees’ salaries.

HRM – Career Prospects and Development – Turnover

18 High employee turnover is always a big problem (in my company). Turnover is high in my company.

HRM – Career Prospects and Development – Retention

14 To retain talented employees is my job focus (as a CEO). We are competing with multinationals and large SOEs for engineers. How to retain engineers is a big challenge to my company.

Communication

2 Managers need to improve their communication skills. The company needs to improve communications between branches - headquarters and among branches.

Controlling 67 Operations Management - Scheduling 12 Clients are very demanding on product delivery schedules.


Sometimes, we have to work 3-shift to keep up the production.

Operations Management- Production

8 The physical environment of the assembly line is not good enough. Operations management (needs to be improved.)

Operations Management - Client Quality Expectations

3 Our clients now are product-quality oriented rather than previously low-cost oriented. We had one client who rejected our products due to product quality issues.

Quality Control /Management Systems

14 Our company has established a quality management system that meets the international standard. Stable product quality.

Financial Controls –Revenue/Profit/Cost

23 In order to keep our clients, sometimes we have to do business that breaks even or even lose money. This downward spiral is not a good sign for any business.

Financial Resources

7 The biggest challenge is we need more financial resources to ensure successful transformation (into an ODM firm). We have retained financial resources.

Note: 1. First-order themes are numbered, and second-order themes appear in italic font. 2. N represents the numbers of units that fall in first- and second-order themes. 3. The samples of responses are randomly selected from responses of top-, middle-, and lower-level managers. OEM = original equipment manufacturer. ODM = original design manufacturer. OBM = original brand manufacturer. HRM = human resource management.

TABLE 3

INDIVIDUAL LEVEL FIRST-ORDER AND SECOND-ORDER THEMES AND SAMPLES OF RESPONSES

Major Themes N Samples of Responses

Job Characteristics 31 Job Function Changes/Role Changes

6 I was promoted to Director from a front-line worker. I am transferred to the Import/Export department.

Job Demands

15 I often need to work long hours. I am asked to travel on more business trips.

Job Stress

10 I feel increasing job stress. It is stressful to work over 60 hours a week.

Self-Motivation 18 Self- Learning 18 I will continuously learn new knowledge to improve myself in

coping with the development of my company. I need to improve my English language proficiency so I can communicate with foreign clients directly. I also need to improve my computer skills since I often need to rely on electronic devices at work.

Note: 1. First-order themes are numbered, and second-order themes appear in italic font. 2. N represents the numbers of units that fall in first- and second-order themes. 3. The statements are randomly selected from responses of top-, middle-, and lower-level managers.


A SWOT (strengths, weaknesses, opportunities, and threats) framework was applied as an analysis tool in order to uncover various strengths and managerial challenges encountered by OEMs across all management levels, as well as current opportunities and threats within the industry. We classified the content analyzed data into major issues in each SWOT category and computed additive percentages at the industry level as well as at the organizational and individual levels. These findings are summarized in Tables 4 and 5.

TABLE 4

OPPORTUNITIES AND THREATS

Opportunity Percentage Business Growth/Opportunity 30 Government Advantage 12 OEM Shifting to ODM/OBM 9 Industry Capability/Competency 6

Threat Percentage Strong Competition 21 Rising Cost/Decreasing Profit Margin 10 High Currency Exchange Risk 5 Lack of R&D Engineers 4 Note: 1. The percentages are additive.

2. The major issues in opportunity and threat categories are derived on the basis of frequency of the responses in the second-order themes at the industry level. OEM = original equipment manufacturer. ODM = original design manufacturer. OBM = original brand manufacturer.

TABLE 5

STRENGTHS AND WEAKNESSES

Strength Percentage Business Prospects 15 Organization Capability/Competency 14 Organizational Learning 6 Self-Learning 4 Quality Management 4

Weakness Percentage Human Resource Management Issues 25 Strategic Planning and Resources 14 Job Characteristics Related Issues 7 Operations Management Issues 7 Note: 1. The percentages are additive.

2. The major issues in strength and weakness categories were derived on the basis of frequency of the responses in the second-order themes at the organizational and individual levels.

Current: Opportunities and Threats

Findings suggest China’s OEM industry is likely to continue growing primarily due to ever-burgeoning business opportunities (30%) and an optimal governmental environment (12%). Other factors, such as prospects of OEM transformation (9%) and strong industrial competency and capability (6%), also contribute to the OEM growth. Nevertheless, two serious threats are strong competition in the industry (21%) and rising cost/decreasing profit margin (10%). In addition, appreciating value of Chinese


currency (5%) and R&D engineer shortage (4%) represent great concerns to all levels of management within the OEM industry.

Our results indicate that perceived opportunities (57%) outweigh perceived threats (40%). Across all managerial levels, surveyed managers displayed confidence in their industry’s competencies in producing “all kinds of high quality products” to capture business opportunities. On the other hand, they voiced concerns of “intensified competition” from OEMs counterparts in “China” as well as “overseas” such as “India” and “Vietnam.” In addition, they pointed out the rising cost in “labor”, “raw materials”, and “utility” may hinder the industry “future growth” and diminish its “competitive advantage.”

An interesting finding is that all surveyed top level managers expressed a strong desire for industrial transformation–shifting from their current OEM manufacturing-only function toward the development of, and, ultimately the marketing of, their own brand products–transforming the firms into competitors within the ODM and OBM segments. As previously stated, no clear distinctions exist separating the OEM and ODM models. In fact, some OEMs, once they develop the core competencies and activities of ODMs, approach a hybrid model in which they offer both OEM and ODM services (Carbone, 2004). Due to the fact that OEM/ODM firms do not own their own brands, the business volume and profit margin of OEM/ODM firms are inevitably affected by the profitability and market performance of their clients and by OBMs (Yu & Hsu, 2002). Thus, there is more incentive for OEMs to become OBMs. Current: Strengths and Managerial Challenges

Major strengths of OEMs include optimism concerning future business prospects in their OEM firms (15%), as well as high competencies and wide-ranging capabilities in manufacturing a variety of products (14%). In addition, our respondents expressed a strong focus on organizational learning (6%), the value of self-learning at an individual level (4%), and the implementation of quality management control and systems (4%).

Our results suggest that perceived managerial challenges (53%) exceed reported strengths (43%). The greatest managerial challenges faced by OEMs are almost invariably human resource (HR) related (25%), including such issues as: the “inadequacy” of the labor force; a “lack of formalized training”; and high “employee turnover.” Based on the large quantity of qualitative units related to these issues, it seems that OEM managers were well-aware of these HR-related issues and were on the forefront of their minds such that their concerns concentrated on recruitment and selection, training, and retention areas. They stressed that these areas were in need of “revision” and “improvement” in terms of “HR policies and practices.” As survey responses stated, to sustain current operations and fuel future growth, OEMs “must deal with” these HR-related issues, recognizing that knowledge workers are corporate assets crucial to their R&D and branding functions in light of their desire to progress to ODM/OBM models.

The second grouping of prevalent managerial challenges is strategy-related issues (14%) which, in line with the industry transformation, mainly concern difficulties in organizational transformation. Specific areas include “strategic planning,” “branding and marketing,” “organizational restructuring,” and “financial resources” issues. Respondents reported that their top management needs to work on a better strategic architecture to assure their firm’s short-term success, and should focus on increasing R&D capabilities to build future, long-term success through. In addition, responses suggested that, at the individual level, high job demands, coupled with job function changes and resulting role changes and perhaps role ambiguity, provide for greater job-related stress (7%). Last, production scheduling, clients increasing demands for quality and delivery deadline, and work environment represent concerns in the operations management area (7%). DISCUSSION

Three future trends can be drawn from our data. First, OEMs are not satisfied with a strict contractual relationship with their clients; instead, they desire to establish long-term, strategic relationships with key clients. Second, as strong competition and rising costs continue to affect OEMs, some OEMs will look for ways to exit the OEM sector by transitioning into the ODM and/or OBM sectors. Third, OEMs continue


to promote strong organizational leaning culture. Within this discussion, we interpret our findings regarding these three trends to provide further insights into business model change, efficiency, innovation, and supply chain survivability.

Concerning the first trend, the conventional view in the outsourcing literature is that short-term contracts tend to be used in manufacturing outsourcing (i.e. non-core component parts), and that clients and providers form a strict contractual relationship at the operational or transactional level (Greaver, 1999). However, our study indicates that OEMs are struggling (i.e., concerns of production scheduling, high job stress among employees) in meeting their clients’ increasing demands for low price and strict delivery deadlines (cf. Jiang, Baker, & Frazier 2009). Our data suggest that OEMs have a strong desire to establish and building long-term, strategic relationship with key clients. This is in line with outsourcing as defined by Grossman and Helpman (2005), who, in fact, emphasized a mutual bilateral relationship between a client and a provider. Such mutual bilateral relationships foster trust and commitment between a client and a provider in the supply chain which, in turn, reduce transaction costs such as verification, inspections, and certification of the provider (Kwon & Suh, 2004). The reduction of transaction costs associated with outsourcing contracts will create a win-win situation for both supply chain partners in their respective cost structures and contract management. Further, if client and provider sustain their supply chain partnership/relationship in long run, further vertical integration may be a solution to gain competitive advantages (Cacciatori & Jocobides, 2005). In this regard, our study of providers coincides with Kakabadse and Kakabadse’s (2005) study of clients. Their study identified the critical future outsourcing trend to be effectively managing client-provider relationships. They emphasized that establishing meaningful relationships (i.e. Keiretsu-type relationships), governed by performance-based contracts, with a number of key trusted providers, will become an ever-increasing competitive imperative for outsourcing clients because they can apply great cost discipline and improve product quality simultaneously. Conceivably, clients must strategically analyze how their current outsourcing practices will have an impact on building relationship with their key providers, and how, if any, ODMs/OBMs transformed from the OEM industry will reshape the domestic market and global market as well.

With regard to the second trend, based on our data, at the industry level, OEMs recognize the massive demand from the Chinese domestic market, and are therefore transforming themselves in order to tap into the huge market opportunity. Our data highlight some specific strategy and tactics that OEMs are pursuing, including: (a) focusing on organizational learning on gaining business and marketing knowledge of the products they manufacture, (b) increasing their investment in R&D, and (c) aiming at developing and marketing their own brands in the domestic market. This may be the first step in the OEM-ODM-OBM transitioning. It is foreseeable that, after newly transitioned OBMs successfully launch their own products in the domestic market, some of them may aggressively pursue initiatives focused on entering the global market by means of strategic alliances with foreign companies, organic expansion, and/or acquisition of foreign brands and companies (via forward vertical integration) (Child & Rodrigues, 2005). According to China’s Ministry of Commerce (2011), in 2010, Chinese firms invested in 3,125 overseas companies in 129 countries and regions, and total foreign direct investment in non-financial sector rose 36 percent to 59 billion in comparison to that in 2009. This clearly indicates that a growing number of Chinese companies are seeking business opportunities overseas. As the manufacturing powerhouse in the world, we can speculate that China’s OEM industry’s enormous economies of scale and competency can be leveraged toward achieving further growth in both its domestic market and international markets as well.

Conversely, also driving the trend for changing business models is that OEMs are facing fierce competition both domestically and internationally. Production low-tech competency and over capacity, coupled with intensive competition, are driving gross margins to an unprecedented low level (cf. Wendin, 2005). Consequently, OEMs are under constant pressure to add value, fueling their march toward the OEM-ODM-OBM transformation. As summarized in the Outline of the Eleventh Five-Year Plan (2006-2010), the Chinese government is “promoting development by optimizing industrial structure” and “improving the capacity of independent innovation,” indicating a countrywide industrial change pattern of development toward growth driven by technology and innovations (National Development and Reform


Commission, 2006, Chapter 1). Our data indicate that some respondents did urge that the Chinese government should include the OEM industry transformation as part of the China’s industrial restructuring plan and provide necessary support, such as financial resources and tax incentives, to the successful transformation. In addition, at the organizational level, managers recognized certain obstacles in such a transformation, including an underdevelopment of technology, a lack of R&D capability, and insufficient financial capital and human resources.

Concerning the third trend, many comments in our data regarding organizational learning and self-learning are encouraging for the industry and its transformation. Our data reveal that OEMs are eager to learn business knowledge and internalize new technology. Knowledge and technology are essential resources for OEMs to gain competitive advantage in competing with other domestic and international OEMs, as well as reduce dependent relationships with their clients (Pfeffer & Salancik, 1978; Ulrich & Barney, 1984). Through their learning processes, OEMs exploit what has already learned and explore new knowledge (Crossan, Maurer, & White, 2011) which, in turn, prepare them to capture market opportunities such as business contracts and/or develop their own brands. At the individual level, the data indicates that employees are self motivated to learn work-related knowledge and improve their language proficiency. Given the content of the individual responses, the reason behind the employees self-learning motivation is most likely due to the fast-changing environment, the challenging nature of their jobs, and employees’ language proficiency levels. It was once reported that the language barrier is one of the most serious obstacles preventing Chinese firms from entering the outsourcing market (Qu & Brocklehurst, 2003). As OEMs work more frequently with foreign clients, employees feel a strong need to improve their English language proficiency as well as their work-related skills and knowledge. These activities are recognized as leading to desirable outcomes such as getting promotions in their firm or being more marketable within the industry job market. Additionally, collective self-learning at the individual level also serves to informally fuel organizational learning.

Before discussing implications, we note our results reveal that reported managerial challenges exceed reported strengths, despite the respondents reporting that the industry as a whole is continuously growing. One explanation could be that, when the data were content analyzed, no comparative weight was assigned to data units. Instead, major issues in the strength and managerial challenge categories were derived based solely on the frequency of the responses mentioned by the respondents at the organizational- and individual-level, and there were far more managerial challenge-related units than strength-related units. It may be that one data unit within the strength category may weight more than that in the managerial challenge category. Another explanation may lay in the fact that 78% of the respondents were middle- and lower-level managers who manage day-to-day operations involving work challenges and in some cases, if not many, job frustrations. One should consider that the 16 OEMs within this study are located at the China’s manufacturing outsourcing frontier, where OEM firms are highly concentrated, and where most potential clients make their first stop in looking for outsourcing providers. The strong competition, constant changing environment, fast work pace, and high job stress contribute to their responses in managerial challenges. It is not surprising that the major managerial challenges pertain to job and/or HR related issues, accounting for 32% of the total responses at the organizational and individual levels. Implications for Outsourcing Providers and Clients

The study findings are of significance to OEMs. Our study identifies current opportunities and threats in the OEM industry and uncovered the types of strengths and weaknesses facing OEM firms. Our results suggest that, in order to capitalize OEMs’ unique assets and capability such as competency and organizational learning ability as well as capture the market opportunities, mangers need to have a better understanding of the pervasiveness of the managerial challenges, especially in the HR area. The increasing competition, both domestically and internationally, requires that OEMs address their HR-related issues quickly. This would likely entail adopting well-established HR policies and procedures that not only address the specific issues identified by this study but also cover the entire HR spectrum from self-managed work teams to incentive pay programs.


The duality of the OEM strategy, shifting to the ODM/OBM models and developing stronger, long-term ties with foreign clients, seems contradictory on the surface in terms of moving in different strategic directions. In fact, they both make sense according to the resource dependence perspective (Pfeffer & Salancik, 1978). When outsourcing activities are not critical and can be performed by many providers, they may be outsourced at market value rather than through established, long-term contracts. This is the case with most surveyed OEMs in this study, who are usually dependent on foreign clients for business. Such a power-dependent business relationship seems to be a primary reason that OEMs desire to turn into ODMs/OBMs, especially given that foreign clients now place increasing demands on the OEMs in terms of delivery deadline and price. Furthermore, OEMs can reduce risk in such a fast-changing environment by establishing long-term relationships with their clients–exploiting and exploring opportunities and resources and knowledge of the partners, which will give them the greater share of economic return over time.

Our findings are of value to both current outsourcing clients and those firms that have plans to outsource their business operations to China. The study provides insight into OEMs as outsourcing providers, in particular, how the external environment is affecting them, and what are driving them to pursue OEM-ODM-OBM transformation. Clients, in order to reduce environment uncertainty and sustain competitive advantage in the market, may need to evaluate business relationships with their providers and assess the impact of the industry transformation on their business.

According to strategic network theory (Gulati, Nohria, & Zaheer, 2000), the need for alliances is low when market-based exchange is less costly and more substitutes are available. As such, clients are not at great risk for lock-in or lock-out effect, in terms of opportunities for strategic relationships. Therefore, they have not tied themselves specifically to OEMs long-term. Instead, many foreign firms maintain their alertness and responsiveness through plenty of weak strategic network ties with OEMs, high centrality, wide geographical scope, and organizational quickness to respond (Zaheer & Zaheer, 1997). Conversely, many clients find that establishing long-term relationships with key OEMs is less risky than working with numerous OEMs on a contract-by-contract basis, since using fewer OEMs allows for the establishment of knowledge-based trust–knowing what their OEM partners are doing. It can also lead to greater coordination because of less need for monitoring OEM activities (Gulati et al., 2000). At the same time, clients may need to take precautions in protecting their intellectual properties which have a strong impact on their survivability in the supply chains. The consequence can be of collapsing pricing structures and shortening the profit cycles of products, diminishing the return of investment from R&D and product development (PriceWaterhouseCooper, 2005). Limitations and Future Research

This study has several limitations. First, the study findings cannot be generalized beyond the Chinese OEM industry. In addition, although our sample contained 16 OEMs manufacturing different types of products from different geographic locations, cautions should be taken when generalizing our findings to the entire OEM industry.

Future research should be conducted utilizing a broader sample of OEMs, including firms that manufacture other types of products and are located in other geographic regions. Moreover, quantitative studies would be beneficial in further corroborating the findings of this study, as well as in uncovering other strategic and managerial issues. Future research may also examine client-provider relations in the contractual relationship, long-term partnership, and vertical integrated association. Additional research should examine HR-related policies and practices in the Chinese OEM industry, thus presenting a clearer picture on where HR-related issues lie as well as providing guidance of sound policy and practices.

In conclusion, our study reports Chinese OEM managers’ views of the industry’s environmental and organizational dynamics such as the market evolution, business model changes, and managerial challenges. Although facing various threats and numerous strategic and managerial challenges, OEMs are optimistic in its competency and capacity to capitalize market opportunities. Our study further provides insight into the future trends of the China OEM industry as well as implications to both outsourcing providers and clients.


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Enotourism as a Form of Activating Rural Areas (On the Basis of the Province of Podkarpackie)

Wiesława Kuźniar

The University of Rzeszow, Poland

This study encompasses selected issues connected with the development of wine tourism in the province of Podkarpackie. Its development is based on wine production which has been of greater and greater importance in Poland. Wine tourism defined as enotourism provides the opportunities of local development, especially for the areas of natural predispositions to wine making. The example of such a region is the province of Podkarpackie, which has been playing a significant role in the revival of Polish contemporary wine making. In recent years, many initiatives been observed, including marketing ones, stimulating development of enotourism in the studied region. INTRODUCTION

Tourism as a dynamic phenomenon, undergoes constant transformations under many factors,

including social and cultural, economic, political, natural and technological ones. The introduced changes have caused an increase of interest in new forms of tourism which may include wine tourism in Poland defined as enotourism. This kind of tourism has been developed particularly in Western Europe, in highly developed countries in the scope of wine production and drinking (Italy, France, Spain, and Germany). In recent years, also in Poland, a growth of interest in wine making has been observed, which is mainly connected with development of wine tourism. One of the regions of high predispositions to develop enotourism is the province of podkarpackie, in which there are favourable conditions for keeping vineyards.

The aim of this study is to present the significance of development of enotourism in the context of activating rural areas on the basis of the province of Podkarpackie. Along with the theoretical considerations, predispositions of the province of Podkarpackie to develop-ment of wine production have been presented, with a particular emphasis on connecting this form of activity with tourism. Moreover, attention has been paid at the necessity of marketing support of enotourism, identifying the examples of selected actions in this capacity. WINE PRODUCTION AND ENOTOURISM – MUTUAL RELATIONS

The condition for proper local development relies on correlation and integrity of long term

development of the economic, social and natural subsystem, having its material implications in developing and using a geographic area (Brol, 1998). In relation to the areas predisposed to development of wine making and having any experiences in this capacity, the ideal form of activity is development of enotourism.


Referring to the statement that the condition for tourism existence relies on differentiation of space (areas), C.M. Hall and co-authors (2002) emphasises that wine is presently one of the products that have names based on geographical names of their origin. As a result, there are strong connections between the location of areas for viticulture and wine production (wine regions) and development of tourism on them, which exerts an influence not only on the development of local economy but also on sustaining residents’ awareness of the geographical and cultural autonomy of a given location (by aiming at preserving a specific cultural landscape, preservation of the tradition connected with cultivating, production, trade and consumption of wine etc.).

The aforementioned authors identified three stages of development of wine tourism in the context of its influence on regional development. The first phase relies on the fact that owners of particular vineyards, producers of wine and owners of wineries lack cooperation and each of them separately performs actions relying on gaining customers etc. In the second phase, it may be claimed that these are actions aimed at performing a coordinated promotion policy. However, the final stage is characterised by developed cooperation in the scope of wining customers and their servicing.

The significance that is attached to wine tourism in particular regions of viticulture may prove the fact that in Alsace around 23% of wines offered by producers are purchased by tourists and in Burgundy the share of wines purchased by tourists amounts to 12% (Cambourne, Macionis, 2002). It shall be emphasised that apart from wines, tourists also purchase other products and they take advantage of many accompanying services.

Apart from economic significance, wine tourism has also great cultural importance. From the viewpoint of regions and other locations in which grapevines is cultivated, interest of tourists in wine and wine making allows for preservation of tradition and its habits. Tourism also forces care for tidiness and proper rural development, favouring the maintenance of durability of cultural landscape. In order to make the tourists’ stay more attractive, interesting events are organised, pertaining to local traditions, customs and old recipes. It is mainly connected with the period of grapevine harvesting, production of wine or its tasting. SELECTED DETERMINANTS STIMULATING DEVELOPMENT OF ENOTOURISM IN THE PROVINCE OF PODKARPACKIE

The province of Podkarpackie is one of the most important regions for wine making in Poland as well as it has played a crucial role in revival of contemporary Polish winery. It is a typical piedmont area; there are gentle slopes, clay soil, hot summers, sunny autumns and snowy winters, which constitute favourable conditions for viticulture.

Among vineyards of Podkarpackie, small plantations with the area of several or even several dozens of areas are dominant, whereas there is a lack of multihectare vineyards. The overall area of vineyards in the province of Podkarpackie amounts to more than 30 hectare and encompasses several average and more than hundred small and very small vineyards.

An important stage in development of wine production was the year 2004, in which the three year pilot project was commenced, known as Vineyards of Podkarpackie. This was the first initiative supporting development of wine making in contemporary Poland. Within the framework of the project more than 150 people participated in professional trainings in the scope of viticulture, wine production and winery economics. Part of them took a chance to visit small wine households in Hungary, Austria and Germany. There was also established the Winery Association of Podkarpacie Region in 2006 and now it brings together the majority of vineyards in the region.

The development of wine production in the region of Podkarpacie is closely connected with development of wine tourism. As a result, an initiative has been undertaken in order to establish the Wine Route of Podkarpackie aimed at promoting wine tourism and vastly understood wine making in the province of Podkarpackie. It is also an interesting form of promotion for the entire region of Podkarpacie, which strengthens its competitiveness in comparison to other regions of Poland. At present, the Wine Route of Podkarpackie has around 40 vineyards, in the future it is planned to enrich it by additional


touristic attractions and infrastructure. The indispensible condition for its success are professional promotion actions which mainly rely on simple forms of advertising (e.g. colourful folders) and Public Relations (e.g. organising events). A professional website also plays essential its role in this capacity. In future, it is planned to place offers of enotourist households (with the possibility of booking rooms) or a possibility of holding tastings or vineyard sightseeing. A separate section of the website would be an e-shop with wines from the region of Podkarpacie. The important form of gaining marketing information may constitute a forum thanks to which it is possible to exchange opinions, sharing experiences or ask questions. In the nearest future, it is planned to use billboarding or informative tables with the map of the Wine Route of Podkarpackie which will be placed at the entry routes to communes or towns in which vineyards are located. It is very important to visualise the promotion information along with exposing its logo (Wine Route of Podkarpackie, 2011).

Within several years, two models of wine tourism have been established, that is the European model which is clearly connected with culture tourism as well as American and Australian model, which is more connected with entertainment and trade. The common element for both wine tourism models relies on active relaxation and tourists’ desire to maintain contact with nature (Kowalczyk, 2003). Similar expectations also refer to the persons visiting the region of Podkarpacie. Wine gourmets benefiting from wine tourism relies on the persons interested not only in tasting but also cultural wealth or regional cuisine. Consequently, their expectations in the scope of enotourist offers encompass willingness to gain information on a given wine, its history, producer or history of the region. The condition for satisfaction of tourists shall be subject to creating a complex marketing product whose significant elements are based on exceptional atmosphere of places and regions in which wine is made, accessibility to tourist infrastructure of proper quality, ability to take advantage of original cuisine or a range of additional services of a cultural and entertaining character allowing for nicely spending time with family and friends. Enotourism is connected with development of many accompanying services that create new workplaces, which contributes to local revival of a given entity. SUMMARY Podkarpacie is a typical mountainous region, with favourable climate conditions, having a rich tradition in viticulture. Consequently, the studied province is a magnificent area for wine making. Concurrently, thanks to natural and landscape values such as rich cultural heritage, the region of Podkarpacie has natural predispositions to development of tourism. In recent years, tendencies of combining these two functions have been observed, meaning development of wine tourism that constitutes one of activating form of selected communes in the province of podkarpackie.

In the light of shaping partnership relations that integrate actions of many local entities, a vital role is played by creating the conception of the wine route. It is especially useful in development of local regions which apart from natural predispositions to viticulture and wine production experience, similarly as the province of podkarpackie, social and economic difficulties. Wine tourism may constitute an alternative source of incomes not only for producers but also for the persons providing tourist services in its vast capacity.

Forms of local initiatives in the scope of development in enotourism allow for statement that in the next few years in the region of Podkarpacie, the number of vineyards will be increasing especially those which are worth visiting and which have a kind of image within Poland. In order to stimulate further development of actions in the scope of enotourism, it is indispensible to provide marketing support of tourist products especially by various promoting actions, in particular, advertising and PR. A significant role in promoting wine tourism of the studied region is played by the “Wine Route of Podkarpackie” which is aimed at moulding the tourist image of Podkarpacie in which a significant role may be played by dynamically developing enotourism.


REFERENCES Brol, R. (1998). Zarządzanie rozwojem lokalnym – studium przypadków. Akademia Ekonomiczna, Wrocław, p. 9. Cambourne, B., Macionis, N. (2002). Meeting the wine-maker: wine tourism product development in an emerging wine region [in:] Hall, C., M., Sharples, L., Cambourne, B., Macionis, N. (red.) Wine tourism around the world: development, management and markets. Butterworth-Heinemann, Oxford- Amsterdam-Boston-London-New York-Paris-San Diego-San Francisco-Singapore-Sydney-Tokyo, p. 81-101. Hall, C.M., Johnson, G., Mitchell, R. (2002). Wine tourism and regional development [in:] Hall, C.M., Sharples, L., Cambourne, B., Macionis, N. (red.), Wine tourism around…, p. 196-225. Kowalczyk, A. (2003). Szlaki wina- nowa forma aktywizacji turystycznej obszarów wiejskich [in:] Geografia turyzmu. Wydawnictwo UW, Prace i Studia Geograficzne, Tom 32, Warszawa, p. 72. Podkarpacki Szlak Winnic (Wine Route of Podkarpackie), http://www.podkarpackiszlakwinnic.pl. (2011-01-15).


En Route to a Typology of the Female Entrepreneur? Similarities and Differences Among Self-Employed Women

Paul J. Davis

Kazakhstan Institute of Management, Economics and Strategic Research

Fatima Abdiyeva Kazakhstan Institute of Management, Economics and Strategic Research

This paper explores the extent to which women entrepreneurs and their businesses share a set of common characteristics and/or experiences internationally and introduces new research on women entrepreneurs in Kazakhstan. It finds that while women entrepreneurs around the world share many common characteristics, there exist sufficient exceptions or insufficient evidence to validate any unifying typology. Further, that the experiences of women entrepreneurs and the women themselves are not homogenous and that formulation of a typology would be simplistic and, in itself, sexist. The Kazakhstani research introduced suggests the experience of women entrepreneurs there is similar to that of women entrepreneurs in many other countries. INTRODUCTION

Female entrepreneurship has been increasing dramatically over the past 30 years. It is estimated that internationally one in ten women are self-employed (McClelland, et al., 2005) and, in the industrialized nations, women own or manage about 30 per cent of all small businesses (Farr-Wharton and Brunetto, 2009). Evidence of the dramatic increase in the number of businesses run by women is exampled in Turkey where between 1984 and 1999 the number of businesses owned by women increased fourfold (Hisrich and Ozturk, 1999). In the United States it is estimated that there will be more women than men entrepreneurs in little more than a decade from now (Knorr, 2011) and last year women-owned businesses there generated revenues of $3.6 trillion (Yu, 2011). It is also true that female entrepreneurship is gaining popularity among minority groups in industrialized countries (Sarason and Koberg, 1994).

Women-owned small businesses play a vital role in our societies far beyond contributing to job creation and economic growth. For example; because women tend to own different types businesses to men, women contribute to entrepreneurial and economic diversity (Jamali, 2009). Further, women-owned businesses are incubators for innovation and ideas and they contribute to social cohesion and stability (Sarri and Trihopoulou, 2005). A study of Ghanaian women entrepreneurs, by way of illustration, found that the women surveyed had significantly improved upon and broadened the goods and services they sold in their businesses through their own innovations. The women had also grown and diversified their customer base (Dzisi, 2008). Additionally, small business also provides an avenue for survival and self-sufficiency. In less industrialized countries, where unemployment may be high and opportunities few, self-employment sometimes offers people the only escape from poverty available and this is especially


the case for women (Malach-Pines et al., 2010). Indeed, in developing nations many women turn to small scale food production not just to derive an income but as the only apparent means of survival. To highlight the extent of this endeavour it has been found that women produce 80 per cent of all the food grown in Uganda (Snyder, 2003) and a similar proportion throughout the rest of Africa (Yu, 2011). LITERATURE REVIEW Business Size

The research strongly indicates that women are mostly confined to running very small enterprises; many of them microenterprises. Alam et al (2011) for example, found the majority of women business owners in Malaysia had small businesses with few employees. In Jordan, it was found that 75 per cent of women-owned businesses were based in the home and 66 per cent were microenterprises of less than 10 employees (Al-Alak and Al-Haddad, 2010). Similarly, a six country African study found that women entrepreneurs in Botswana, Kenya, Lesotho, Malawi, Swaziland and Zimbabwe are predominantly operating microbusinesses. On average two-thirds of the surveyed businesses women operated were sole trading enterprises (Ndemo and Maina, 2007). The evidence is that this is phenomenon is not restricted to developing or less industrialized countries. In Norway, for example, a review of women-owned businesses during the 1990s presented findings that showed women overwhelmingly operate very small businesses (Spilling and Berg, 2000). Women-owned businesses are also small in terms of annual turnover. A study of women owned businesses in the United States found almost half had annual revenues of less than $1 million (Bledsoe and Oatsvall, 2010). In Norway, during the period 1990-1999 it was found that women-owned businesses were economically marginal for the most part and that self-employed women were themselves economically poor relative to self-employed men. (Spilling and Berg, 2000).

Exactly why women tend to run businesses with very few employees is contestable. The literature is divided on whether women consciously choose not to grow their businesses or whether growth is seldom an option because of the type of businesses women generally seem to operate. In India, by way of example, it has been found women choose not to grow their businesses because they feel the demands of a bigger business will compromise family harmony and relationships (Mitra, 2002). However, other studies have concluded that women mostly operate businesses that are non-scalable and so low-growth (Tan, 2008).

A British study observed that women tend to run businesses with limited growth potential. However, those businesses that were growth-oriented were hindered by a range of factors such as inability to secure credit, inadequate childcare facilities, and inexperience (Roomi et al., 2009). Women entrepreneurs in some African countries have their business growth hindered by dependence on their spouse. The husband controls the family resources and is pivotal in any decision making and this compromises a woman’s freedom to decide what is best for her business (Ndemo and Maina, 2007). Nature of Business

In many cases women do not have free choice about the type of businesses they start. Because women have less social capital than men, including networks, education, influence and prior experience, they have fewer self-employment options. Jamali (2009) explains this restricts both the type of businesses women can operate and their growth potential. On the point of networks, Naser et al (2009) and Gonzalez-Alvarez and Solis Rodriguez (2011) explain that women’s networks are comprised largely of close family and friends and are of limited use to their businesses and spotting business opportunities. In the United States, however, there is evidence that the types of businesses women are running are becoming more diverse. For example, there is growth in the number of women running construction, manufacturing and transportation firms (Knorr, 2011). It should be noted that this appears to be an exception to the trend globally. Indeed, it is to some extent contradicted by a recent US study of women entrepreneurs which found 90.9 per cent of those American businesswomen surveyed operated businesses in the service and retail industries (Bledsoe and Oatsvall, 2010).


Weeks (2009) found in a study of businesswomen in Lebanon, United Arab Emirates, Tunisia and Jordan that most women operated a business in personal services, retail or non-durable manufacturing. Lituchy and Reavley (2004) found the same in Poland and the Czech Republic. However, in contrast with nearly all other studies, Weeks discovered nearly half of the women were trading across borders, the businesses had a lot of employees and most businesses were growth focused.

In Jordan a study found 60 per cent of women-owned businesses were either in delivering personal services or non-durable manufacturing (Al-Alak and Al-Haddad, 2010). In Poland too, women’s business have been found to be concentrated in sales, services and human resources (Zapalska, 1997) while in Uganda women entrepreneurs are mostly involved in handicrafts, textiles and clothing and small-scale farming (Snyder, 2003). The difference between men and women entrepreneurial ventures in terms of industry type is evidenced in a Swedish study which found men far more involved in construction and manufacturing firms while women were running businesses in retail, sales and healthcare (Tillmar, 2007).

The gender gap between male and female entrepreneurs can also be observed in the setting of small businesses. A study in Iowa of regional and rural small businesses found that men-owned businesses are more successful in both rural and urban settings and that the success gap between men and women owned businesses was even more pronounced urban settings (Bird and Sapp, 2004). The authors identify many factors which contribute to the phenomena including finance and networks which are discussed in more detail at other points in this paper. Financing

Financing, specifically the ability to secure credit, is imperative for the majority of people who wish to launch their own business. This is especially true for people in less industrialized or developing economies. The National Entrepreneurship Development Fund in Tanzania, for example, provides the only source of legitimate credit for the majority of Tanzanians who have either insufficient or no assets against which they can secure a bank loan. The Fund lends to start-up and established small businesses and has documented a very significant increase in productivity of small businesses that have gained access to credit through the Fund (Kuzilwa, 2005). This provides evidence of the link between financing and business activity which might be the difference between survival and bankruptcy; financial loss or profitability.

A recent survey of Malaysian businesswomen found that 69 per cent had started their business with bank financing; 29 per cent had begun with family loans and 2 per cent had borrowed from friends (Alam et al., 2011). The Malaysian survey is interesting in that it stands apart from most of the research. The experience of most women entrepreneurs is that attaining finance from banks is very difficult. Gatewood et. al. (2008) note that even seasoned and well educated women entrepreneurs, with proven success, find it difficult to attract finance. A study in Lebanon found most women entrepreneurs have no option but personal and family savings to finance their business ventures (Jamali, 2009) and in Ethiopia finance has been noted as the major challenge facing would-be female entrepreneurs (Singh and Belwal, 2008). A similar finding was reported following a study of women entrepreneurs in Indonesia (Tambunan, 2009). In an Australian survey it was discovered only 24 per cent of women access bank finance to begin their business while 67 per cent use their own savings. Where formal finance is available it can make a big difference to women and their businesses. In South East Asia for instance, 35 per cent of self-employed women escape poverty when they get a microfinance loan and they then go on to grow their business (Jani and Pedroni, 1997).

Not all women entrepreneurs have interpreted a difficulty getting finance as discrimination. In France businesswomen according to one survey felt they had been denied financing by banks because of their youth and inexperience (Orhan, 2001). In Oman and Bahrain a study found women entrepreneurs preferred to use their own savings than take a bank loan because they wished to avoid incurring debt (Dechant and Al-Lamky, 2005). However, the World Bank has stated very recently that women are less able to secure finance for their businesses than men in developing and emerging countries. One reason given is the lack of personal collateral and land title against which they could secure a loan (World Bank, 2011). This is supported by Weeks (2009) who found in the Middle East and North Africa that three-


quarters of female entrepreneurs who applied for bank financing did not receive it. They were left to finance their ventures using personal savings and family loans. Further, in Uganda, only 7 per cent of women own land under their own names (Snyder, 2003).

In Industrialized countries too, evidence supports the financial discrimination against women entrepreneurs. A New Zealand study (de Bruin and Flint-Hartle, 2005) found that women only received about 5 per cent of the estimated venture capital pool of $73 billion. The study found inadvertent discrimination in the marketing of available finance which was said to be designed by men with men in mind. The websites, as an example, lacked any stories of women-owned businesses. Education

The literature on education levels among female entrepreneurs indicates that women business owners are very well educated generally. As many of the examples that follow indicate, women entrepreneurs have higher levels of education than women in general society (Naser et al., 2009). For example; Lee (1999) found among a survey of businesswomen in Singapore that 57.2 per cent had post-secondary education while a survey of female employees found that more than 50 per cent had a secondary school education or lower only. However, while it is largely true that female entrepreneurs tend to be very well educated, there are several exceptions to this. For example, a study in Malaysia found that 70 per cent of women entrepreneurs had less than an undergraduate degree (Alam et al., 2011) while in Ghana a study observed that 60 per cent of women business owners had a primary level education only (Dzisi, 2008).

Most studies, however, do conclude that women entrepreneurs are very well educated. For example; a study of 25 Omani women entrepreneurs found that 21 had a post-secondary qualification (McElwee and Al-Riyami, 2003). Another study in the same region that looked at Middle East and North African businesswomen found that 91 per cent of the women surveyed had post-secondary qualifications (Weeks, 2009). Similarly, a study of Czech and Polish businesswomen found 78.5 per cent had either university degrees or post-secondary vocational training (Lituchy and Reavley, 2004). French women entrepreneurs, according to one study, are very well educated with many having business degrees (Orhan, 2001). In Turkey a survey found 70 per cent of women entrepreneurs had a minimum of an undergraduate degree (Hisrich and Ozturk, 1999).

Other research concurs: a study of women entrepreneurs in Bahrain and Oman found all of the women had undergraduate degrees (Dechant and Al-Lamky, 2005) while in Uganda 82 per cent of women entrepreneurs in one study were found to have post-secondary qualifications (Snyder, 2003). A study of 449 women entrepreneurs in the United Arab Emirates discovered that 95.6 per cent had some kind of post-secondary qualification (Naser et al., 2009). Motivations

Gray (2002) has argued that the primary drive behind entrepreneurship, independence, is similar for men and women and that financial gain is almost always less important. This is contradicted by a study of Singaporean businesswomen which found that those surveyed did not express a need for autonomy or independence as being a motivation for becoming self-employed (Lee, 1999). Further, most studies find a difference between men and women on business motivations. Still and Walker (2006) argue men are more likely to be pulled towards entrepreneurship and women are more likely to be pushed. However a study of women entrepreneurs in Bahrain and Oman found the women were almost exclusively pulled towards self-employment (Dechant and Al-Lamky, 2005). In Greece, according to Sarri and Trihopoulou (2005) women became entrepreneurs mostly due to ‘pull factors’ such as a search for fulfillment; desire to be creative and for independence and autonomy. A similar finding was noted in a UK study of migrant businesswomen from Asia. These women claimed they started their own businesses to have a meaningful purpose in life; to fill a lot of free time and to challenge themselves (Dhaliwal, 2000).

A French study, however, found women became self-employed for a mix of ‘push’ and ‘pull’ factors. These women took up entrepreneurship partially due to lack of enticing alternatives and partially due to opportunity. Quite a few women in the study became entrepreneurs because they inherited family businesses or were influenced by self-employed relatives (Orhan and Scott, 2001). Contrary to the Greek


and UK studies, Zapalska (1997) found women in Poland became entrepreneurs because of ‘push’ factors. Mostly, they were disaffected with government jobs. In Lebanon too, women have been found to take up self-employment out of frustration and lack of other opportunities (Jamali, 2009).

Malach-Pines, et al (2010) have said that women in developed countries are generally ‘pulled’ towards entrepreneurship while women in developing countries are generally ‘pushed’ towards entrepreneurship. However, for the most part, women seem to be pushed or compelled to work for themselves far more than pulled towards self-employment. This is especially true in countries with higher levels of poverty and less developed industry. It is also true in countries known to conflict. A study of Tamil women entrepreneurs in Sri Lanka, for example, found many women were forced into self-employment because they had lost their husbands in the war there (Ayadurai and Sohail, 2006). A further example is Russia where, after the collapse of the Soviet Union, unemployment, especially for women, soared. This drove many women into self-employment as there were no alternatives (Izyumov and Razumnova, 2000). However, in industrialized and prosperous nations, such as Australia, entrepreneurial activity has still been found to have its genesis in compulsion rather than attraction (Wood and Davidson, 2011).

There is also some evidence that the nature of the business women launch has a relation to their business motivations. One study found that women entrepreneurs who entered masculine industries were more driven by wealth generation than those women who started businesses in more traditionally feminine fields (Sappleton, 2009). Most research on these issues has been insufficiently sophisticated according to Rosa et. al. (1994) and the gender differences that can be observed are far more complex than often reported. Barriers

Women not only must overcome a disparate range of barriers as entrepreneurs but must struggle first to become an entrepreneur at all. In China, for example, women account for just 14 per cent of entrepreneurs (Yu, 2011) while in Jordan women comprise just 3.9 per cent of the country’s self-employed (Al-Alak and Al-Haddad, 2010). In Lebanon twice as many men are entrepreneurs than are women (Jamali, 2009). Throughout the Middle East and North Africa only 13 per cent of businesses are owned by women. In Cyprus the percentage is 12 per cent; it is 5 per cent in Israel and just 1.5 per cent in Malta (Nearchou-Ellinas and Kountouris, 2004). The statistics are a little more encouraging in fully industrialized, western countries but even there women account for a far smaller percentage of business owners than they do for a percentage of the population as a whole. In Norway and most western European countries women account for about 25 per cent of small business owners (Spilling and Berg, 2005). Indeed, a UK study has criticized the assertion that women can simply overcome social exclusion by taking up entrepreneurship. In fact, the study argues, the socially excluded are poorly positioned to launch their own businesses because they lack the finance, resources and often education necessary (Marlow, 2006). Getting into business for yourself if you are a woman is clearly a barrier in itself.

The barriers women entrepreneurs face include unique barriers specific to the social, political, legal, religious and cultural environments in which they live and common barriers which appear to exist irrespective of their environment. Black women entrepreneurs in South Africa, for example, face the unique barriers that remain as a legacy of apartheid such as exclusion from authority, entrenched racism and inferior quality of life to white South Africans (Kwesiga, 2008). Extreme levels of HIV/AIDS and poverty are also barriers for black women business owners in South Africa (Al-Alak and Al-Haddad, 2010). Endemic and rampant corruption is also a major obstacle to small business operation in some countries such as Ethiopia (Singh and Belwal, 2008); Russia (Izyumov and Razumnova, 2000) and Kazakhstan (Can, 2003).

However, the discrimination and prejudice women experience by virtue of being women and being business owners is common to most societies according to the literature. Professional women who are driven away from the corporate world to escape the artificial ‘glass ceiling’ limitations imposed on their careers, for example, are found the world over (Nixdorff and Rosch, 2010; Northouse, 2010; Nahavandi, 2009). According to Knorr (2011) these women seek self-employment because the corporate world offers


them less pay, fewer promotion opportunities and fewer professional development options than it does men. Entrepreneurship may appear a way out, but, in most cases, the discrimination and prejudice continue. In Kazakhstan, for example, women in one survey said that the prejudice that held women back in corporations was symptomatic of a wider, societal subjugation of women that permeated all aspects of life for them (Low, 2007).

The suppression of women by patriarchal norms and masculine cultures is a common theme in women entrepreneurship. It presents barriers in different forms. In Kenya, for example, sexual stereotyping of women is claimed to be sustained by government policies and male family members who strongly influence the work choices of women (Ndemo and Maina, 2007). The situation is more even more dire in Cameroon where husbands are permitted under law to stop women’s business activities if they consider those activities detrimental to family life (Treacy, 2003). Business women in South East Asia, meanwhile, claim to have little control over income they generate and see much of this money spent on gambling and alcohol by their spouses. It prevents them from investing in their businesses (Jani and Pedroni, 1997).

Discrimination and societal stereotyping of women entrepreneurs is not restricted to the less industrialized world. In a UK study of women business owners half the respondents reported experiencing prejudice and discrimination owing to their gender (Davidson et al., 2010). In Hungary women entrepreneurs cited, in addition to sexism and prejudice, family responsibilities, obtaining credit and low personal collateral as challenges they regularly faced (Hisrich and Fulop, 1994). Again, in Sweden, women entrepreneurs recounted sexist attitudes and stereotyping directed against them and the kind of businesses they run. One account was of a woman who said men did not consider her a real businessperson because she ran a hairdressing salon (Tillmar, 2007).

However, not all women entrepreneurs experience spousal and family conflict. In India, Das (1999) found that women experienced very few such difficulties. One reason given for this was the high value placed upon mutual support within the family. Often the extended family live together in one household where inter-dependence is not merely a cultural norm but an economic necessity.

Another barrier that women entrepreneurs encounter is restrictions and prohibitions of their religion. Several studies have highlighted the challenge Islam poses businesswomen in some societies such as the United Arab Emirates (Naser, et al., 2009) and Saudi Arabia (Al-Alak and Al-Haddad, 2010). It has been argued that conservative Islam as practiced in some Middle East countries limits women’s ability to be self-employed and the nature of the businesses they can run. Religious rules around freedom of movement, freedom of association and deferment to male relatives (McIntosh and Islam, 2010) places considerable restrictions on women entrepreneurs. This is especially true for women who would need to travel away from home as part of their business. In Saudi Arabia women are prevented from driving and moving around un-chaperoned by a male relative. It is self-evident that such a circumstance inhibits the freedom required to operate a range of different kinds of business.

It should be noted that barriers to small business creation, development and survival and not exclusively encountered by women. Yusuf (1998) found in a study of six South Pacific countries that men and women face significant challenges in accessing technology, raising capital, skilling themselves, connecting with helpful support networks and overcoming poor infrastructure. However, the evidence is that women do face some unique barriers and that, overall, women disproportionately encounter barriers as they embark on and pursue self-employment. Propensity for Risk Taking

The literature has a tendency to portray women entrepreneurs as more risk averse than their male counterparts. A notable exception has been reported in China (Tan, 2008) where women entrepreneurs in hi-tech industries were observed to take more risks than men. This was noted to be particularly true in relation to financial gain and building competitive advantage. Propensity for risk is clouded by the perceptions of third parties to some degree. Brindley (2005) claims that it is the banks that perceive women as less entrepreneurial than men and therefore banks evaluate women as more averse to risk taking. This in turn influences the ability of women entrepreneurs to gain credit. Maxfield et al., (2010)


found there to be no difference between women and men entrepreneurs in terms of taking business risks. Further; women’s motivations for taking risks in business are the same as those for men. The authors also found that there was not a particularly female business decision making process. Leadership Style

Women entrepreneurs have largely been found to have a people-centric leadership style. Nixdorff and Rosch (2010), for example, found American female business owners involved their employees in decision making whereas male business owners tended not to. Also in America, Buttner (2001) discovered women entrepreneurs prioritize good will, relationships, empowerment and a sense of team in their businesses. Yu (2011) found Chinese women business owners take a consultative approach to leading their businesses. Rather than making important decisions alone, they are more likely to consult with senior employees. This has been described as a preference for maintaining harmony in the business among all employees by developing positive and cooperative relationships (Orhan, 2001).

Women entrepreneurs have also been said to work hard to build trust in their businesses by finding ways to involve employees in achieving business outcomes. Women work in greater collaboration with their employees; sharing responsibilities and seeking greater input. An Israeli study of female business owners (Dafna, 2008) characterized the owners as people-oriented rather than profit-oriented. That at the center of the business’ success is its people.

Women have also been described as transformational in their business leadership style (Tibus, 2010; Buttner, 2001) rather than transactional. Women lead in a way that transforms both their lives and their employees’ through the ways in which they lead people. Women tend towards a participative, shared decision making model of leadership and this appears to distinguish them from their male counterparts based upon available research. An Australian study (Kotey and Sheridan, 2001) of the practice of human resource management in small business found few differences between the way men and women tend to manage people; both tend to be informal and quite flexible. However, the differences that did emerge support the above studies. The study concluded that women are likely to lead in somewhat more personable ways because of the industries in which they operate businesses: personal services; hospitality; retail. The point is an important one: women do not inherently lead differently to men but adopt their people-management style to reflect the nature, context and dynamics of the business itself. Professional Development

The literature strongly supports the assertion that women entrepreneurs lack access to business related training and professional development. In Cyprus, 64 per cent of female entrepreneurs said they had never attended a business related seminar or workshop (Nearchou-Ellinas and Kountouris, 2004). Furthermore, it has been noted that strong business skills are a critical factor for the success of women entrepreneurs (Naser et al., 2009). Weeks (2009) found in the Middle East and North Africa that women entrepreneurs were in need of financial management training and technical training in particular. In Nigeria a study concluded that women business owners were in need of business skills training, professional mentoring and learning networks (Riddle and Boyede, 2003). Also in Africa, women entrepreneurs in Ethiopia were found to have significant knowledge gaps in key business skill areas that hindered their businesses (Singh and Belwal, 2008). Similarly, in Cameroon, training and professional network building were found to be particular needs for women entrepreneurs (Treacy, 2003).

A study of self-employed women in Ghana found just 8 per cent had any vocational training despite nearly all the women working in businesses for which vocational training would be considered extremely important (Dzisi, 2008). Vocational training is a particular need for women entrepreneurs, especially in less industrialized countries where dress making, textiles, food retailing and handicrafts are common avenues for self-employment. Like business skills training, there is a shortage of vocational skills training for women entrepreneurs. In Oman, it is claimed that vocational training for women is essentially non-existent (McElwee and Al-Riyami, 2003). Similarly, in Zimbabwe, research indicates women entrepreneurs had to launch their businesses with no training at all and had to learn everything on the job (Mboko and Smith-Hunter, 2007).


Outside of Africa the dearth of business training has been given as problem in Hungary (Hisrich and Fulop, 1994); Britain (Roomi et al., 2009) and Indonesia (Tambunan, 2009). A trial entrepreneurship training program for women in Russia concluded that there are many willing and capable Russian women ready to become entrepreneurs but that sufficient training is not available to enable them to realize self-employment (Izyumov and Razumnova, 2000). Support and Assistance

Professional and personal networks have been found to be integral to the success of small businesses (Loscocco, et. al., 2009; Davis, et. al., 2006). Networks create opportunities for small business owners but they also compensate for the lack of social contact that many small business owners experience and that employees enjoy by virtue of working for a company. Yet women fare poorly when it comes to building and accessing useful networks that serve to meet their needs and interests as small business operators. Not only is there a lack of support for women business owners at the initiative of governments, in some cases government has been found to thwart small business development. Examples include business infrastructure and government policy (Al-Alak and Al-Haddad, 2010) that make it harder for women to conduct business rather than easier. Even where government is not actively detrimental to women entrepreneurs there is often limited active support such as in Ethiopia (Singh and Belwal, 2008). In Cameroon, too, there are no professional organizations to assist women entrepreneurs yet such organizations do exist for men (Treacy, 2003). Women entrepreneurs in Britain have cited that a lack of business support and development agencies serve to restrict business growth (Roomi et al., 2009) while in Oman, Arab businesswomen rarely seek help from the business associations that do exist because they are organized for and by men. The male entrepreneurs are said to network among themselves and exclude women. In the absence of a formal networking opportunity, the women entrepreneurs tend not to network at all (Dechant and Al-Lamky, 2005). This significantly inhibits the growth and development potential of women-owned businesses but also isolates them from helpful knowledge and advice which might save the women time and money by learning from the experiences of self-employed men.

There are examples of women entrepreneurs receiving support to help them in business. Indian women entrepreneurs, for example, have organized themselves and established the Self-Employed Women’s Association (SEWA). This organization supports women business owners and advocates for their interests. For example, the organization lobbies local authorities to promote its members’ interests. SEWA provides a range of professional development courses for its members to help develop business-critical skills (Al-Alak and Al-Haddad, 2010). In the United Arab Emirates the government has taken positive steps to enable women to acquire key business and technical skills to encourage entrepreneurship. This is part of the ‘Emiratization’ policy to up-skill local people and thereby reduces the reliance on expatriate personnel. Women comprise 70 per cent of the students at the High College of Technology and they benefit from established businesswomen’s associations and councils (Naser, et al., 2009). THE KAZAKHSTAN PILOT RESEARCH PROJECT Kazakhstan and its Growing Culture of Entrepreneurship

2011 marked the twentieth anniversary of Kazakhstan’s independence. Prior to 1991 Kazakhstan was part of the Soviet Union. Kazakhstan is situated in Central Asia along with Kyrgyzstan, Uzbekistan, Tajikistan and Turkmenistan. It shares a border with China to the East, Kyrgyzstan and Uzbekistan to the South, the Caspian Sea to the East and Russia to the north.

Since its inception, Kazakhstan has been led by President Nursultan Nazarbayev who has overseen the country’s rapid economic development and transformation from a Communist planned society to a free market economy. The country has a population of approximately sixteen million but is about the size of Western Europe. Gross National Income (GNI) per capita is US$6,740. Kazakhstan is a predominantly Muslim country operating a moderate, secular form of Islam similar to Turkey.


Kazakhstan emerged from the Soviet Union in a far better position than its neighbors. The country enjoys significant natural resources, especially large oil reserves, and bountiful productive farmland. What Kazakhstan did not inherit was a culture of entrepreneurship. Only in the dying days of the Soviet Union were laws passed to legalize private enterprise. The legacy Kazakhstan inherited from seven decades of Soviet governance was a corrupt and inefficient bureaucracy, a central planning mindset and under-developed infrastructure (Tovstiga et al., 2004). In light of this, Kazakhstan’s progress towards a small business-friendly culture in just twenty years is surely remarkable.

If, as Knorr (2011) observed, entrepreneurship is one of the most reliable indicators of a country’s economic success, then Kazakhstan is positioning itself to continue its rapid rise to regional economic superiority. Today, Kazakhstan is one of the fastest growing economies in the world (Das et al., 2010). Within six years of achieving independence in 1991, the percentage of the population that is self-employed grew from 4.3 per cent to 24 per cent, more than double the number of entrepreneurs in Russia at the same time (Verme, 2000). Since this time entrepreneurship has continued to grow exponentially. For example; in 2005 there were approximately 70,000 small businesses in Kazakhstan; by last year this figure had doubled (Teal et al., 2011). The authors also note that 90 per cent of businesses in the country are family owned and 50-60 per cent of businesses are of some type of trading entity. It is also significant to note that the southern city of Almaty is the center of small business in the country (Teal et al., 2011) because this is where this research project was conducted.

While most Kazakh businesses remain indigenous, informal microenterprises (Verme, 2000), franchising is now beginning to emerge as a choice within the self-employed sector. It will provide new opportunities for local people to realize entrepreneurship and will further diversify the base of small business in the country. KFC, Pizza Hut, Gloria Jeans and Baskin Robbins are some of the foreign franchise chains that today have a presence in Kazakhstani cities. The Kazakhstan Pilot Study – Exploratory Research

A survey was distributed to women entrepreneurs in Almaty, Kazakhstan. The survey intended to collect data on women-owned businesses for the purposes of comparison with women entrepreneurs in other societies. To the best of the author’s knowledge, this is the first attempt to survey women entrepreneurs in Kazakhstan. For this reason, and because third-party surveying of citizens is not well established in Kazakhstan, the survey was brief and the sample size small. The findings discussed here should be considered as a cautious, preliminary exploration of the topic. The sample size of 28 women entrepreneurs is insufficiently representative of Kazakhstani female entrepreneurs and, as such, no conclusions can be drawn from the findings. It is hoped that this pilot study might inspire other researchers to conduct a far more thorough and sizeable research project on one or more of the broad issues raised by this study. Further, more extensive research may be hampered by the fact that Kazakhstan is a new country and was for many decades part of the Soviet Union where a culture of research conducted by foreigners was not well established.

Twenty-eight women entrepreneurs completed the survey. It was discovered that 89 per cent of the women were operating a business in some kind of retailing (including food and clothing), hospitality or personal services. The remaining 11 per cent operated construction/building firms. 100 per cent of the women entrepreneurs employed 30 staff or less. 50 per cent of the businesses were microbusinesses with 10 or fewer employees. Most of the women’s businesses were relatively new. 57 per cent had been operating their business for two years or less. Only 7 per cent of the female entrepreneurs had been operating their business for more than 11 years.

When asked to identify the biggest challenges they encounter as entrepreneurs, 64 per cent nominated raising the capital to start their business. 92.8 per cent of the respondents also said that getting bank finance to build and grow a small business was a big challenge. The same percentage of women said that government bureaucracy was a major obstacle to doing business. 64 per cent of survey participants reported that registering, licensing and paperwork to start a new business was also a big challenge. 57 per cent of women indicated that following legal requirements pertaining to running and growing their business was also a major challenge.


Asked whether, all things considered, conditions for running a small business had improved in Kazakhstan over the past ten years, 43 per cent of women said they had not. 21.5 per cent of respondents reported that they believed there was not less bureaucracy concerned with running a business now compared with a decade ago. 36 per cent of those surveyed also said that it had not become easier to obtain bank finance for their business over the past ten years. 43 per cent of the women entrepreneurs reported that they believed government rules and requirements had not improved over the past ten years to make business easier to conduct.

The survey asked respondents to indicate how important a range of motivators are to them in terms of providing the impetus to operate their own business. For each of the 10 motivators respondents were asked to select either ‘very important’; ‘quite important’; ‘not very important’ or ‘not at all important’. 64 per cent of respondents said that being their own boss and determining their own future was very important while 57 per cent said having independence and freedom were very important motivators. However, the two most important motivators for the women were increasing their earning potential (71.5 per cent) and doing work they were passionate about (78.5 per cent). The least important motivators for the women entrepreneurs surveyed in terms of selecting the ‘very important’ option were: being a more visible part of their community (21.5 per cent); to take risks and challenge oneself (21.5 per cent); to make a difference to others (21.5 per cent) and to contribute to Kazakhstan’s economic development (28.5 per cent). Risk taking scored the highest ‘not important at all’ score with 28.5 per cent of respondents selecting this option. DISCUSSION

The findings of the Kazakhstani research project, where comparisons are possible, generally corroborate the observations of earlier studies. As the literature review highlighted, for example, the majority of businesses owned by women around the world tend to be small in terms of staff numbers. The high percentage of micro-businesses being operated by women in developing and emerging economies was reflected by the Kazakhstani findings. Kazakhstan too is an emerging and developing country. The Kazakhstani businesswomen were predominantly operating businesses in retail, services and hospitality. Again, this pattern of business ownership is common to female entrepreneurs in societies around the world where retail and services account for a disproportionately high percentage of businesses owned by women.

Another commonality between a large amount of the earlier research and the Kazakhstani study is the challenge women entrepreneurs encounter accessing formal financing for their businesses. More than 9 out of 10 respondents in the Kazakhstani study reported difficulty getting bank finance to grow their business and more than one-third said bank financing had not become easier to obtain over the past 10 years. The literature review highlighted the particular challenge women entrepreneurs in developing countries face accessing formal finance because of their lack of capital. Private capital is a new concept in Kazakhstan; until very recently private ownership and private enterprise were illegal in the country (Izyumov and Razumnova, 2000) and this could, in part, explain why women entrepreneurs struggle to secure formal financing for their ventures. Furthermore; the economic position of women in today’s CIS countries deteriorated very considerably following the collapse of the Soviet Union. Not only was there very little employment for them but they suffered considerable discrimination and marginalization (Izyumov and Razumnova, 2000). It is conceivable that the legacy of this experience also partially explains why Kazakhstani women entrepreneurs report finding it difficult to raise finance.

The most contentious issue discussed in the literature review was about women’s motivations for self-employment. The Kazakhstani women strongly related to pull motivators such as a desire to do work they are passionate about and to be their own boss. Many of the studies referenced earlier also found women entrepreneurs, particularly in industrialized countries such as France, Britain and the United States, were attracted to entrepreneurship rather than compelled to undertake it. It was noted in the literature review that women in less industrialized and developing countries were more likely to be forced into entrepreneurship. Although Kazakhstan is an emerging and developing nation, Almaty, where this


research was conducted, is a prosperous city and the hub of finance and commerce in Kazakhstan. Had the research been conducted in rural and remote areas of the country the research findings may well have narrated different results. Essentially, women entrepreneurs in Kazakhstan report being motivated by autonomy and independence and this is consistent with much of the earlier research.

A very interesting observation from the research data emanating from the Kazakhstani study which is somewhat incongruous with the wider research is the munificent and benevolent characterization of self-employed women in earlier studies. The literature review revealed that women entrepreneurs are selfless in their leadership style. They are strongly committed to inclusive and transformational leadership. Moreover, women largely run businesses that they design to be people-centric and based upon participative management principles and these businesses are most typically in industries including retail, personal services and hospitality with a ‘high-touch’ customer culture. However, the Kazakhstani research participants placed least importance on motivators such as being a visible part of their community, making a difference to others and contributing to the development of their country. While a direct comparison between leadership style and personal motivations would be injudicious, one can cautiously propose that there is some inconsistency between an altruistic disposition to leading others and a predilection for selfishness in so doing.

With regards to barriers, the women in the Kazakhstani study highlighted that government bureaucracy and, more specifically, business registration, licensing and paperwork are barriers to doing business. The literature review also highlighted examples of government presenting a challenge to conducting business. Government apathy and policy were also cited as barriers which small business owners find challenging. Bureaucracy, over-regulation, government intrusiveness and public officialdom have all been exampled as sources of frustration for small business in Kazakhstan (Bhuiyan and Amagoh, 2011; Low, 2007; Can, 2003). Earlier studies also demonstrate that women business owners across the world experience sexism, discrimination and prejudice. This has in some instances been attributed to women entrepreneurs operating in patriarchal societies; to cultural norms and to religion. Although the Kazakhstani study did not investigate this specific issue, it is noteworthy that Kazakhstan has been identified as a patriarchal and culturally traditional society based on Islamic values (Low, 2007). This could provide an interesting avenue for further research on barriers faced by Kazakhstani businesswomen.

There is some debate about whether women entrepreneurs are more risk averse than their male counterparts. Studies have come to different conclusions and one study, referenced earlier, found it is more the perception of lenders that women are more risk averse. According to the women entrepreneurs surveyed in Kazakhstan, risk seems not to be a big motivator for being in business. Only one in five of the respondents rated risk taking as being very important to them. 50 per cent said risk taking was not a very important motivator for them and 28.5 per cent said risk taking was not at all important. While this finding does not indicate a propensity for risk taking per se, it does give an insight into the lack of predilection Kazakhstani businesswomen have for risk taking generally. Situational variables may well influence how women might respond to questions on risk and so return a different finding. It would also be interesting to explore whether the disinterest in risk taking among Kazakhstani women entrepreneurs has any bearing on the growth potential of their businesses. These considerations have potential as areas for further scholarly research. CONCLUSION

The literature review revealed a number of commonly shared characteristics and experiences among the world’s female entrepreneurs. Women tend to run very small enterprises with few employees. Microenterprises with ten or fewer employees are very common, especially in less industrialized countries. It is also true that internationally women-owned businesses are concentrated predominantly in just a few industry sectors such as retail, sales, personal services and small-scale, non-durable manufacturing. It is also the case that accessing formal financing is a challenge for women entrepreneurs wherever they are. Women entrepreneurs, with just a few exceptions, appear to be very well educated irrespective of their location. The literature also supports the assertion that women entrepreneurs face


considerable barriers in starting and building their businesses. Prejudice, sexual stereotyping and discrimination are common challenges women encounter internationally. The research also indicates that women tend towards a transformational leadership style in that it is collaborative, participative, team-oriented and centered on trust, harmony and building relationships. There is also a widespread, almost universal, shortage of professional development and business-skills training opportunities for female business owners and women everywhere are in need of such professional development. Finally, women entrepreneurs generally lack sufficient support networks in the form of professional associations and government agencies.

The new research introduced here and conducted in Kazakhstan for the most part supports the findings of earlier studies. The size and nature of women-owned businesses, difficulty accessing finance and barriers to business development are examples. The motivations that drive women entrepreneurs in Kazakhstan are not dissimilar to those in other countries. The Kazakhstani research has also raised some further points of interest which require additional investigation if they are to be compared with research in other societies.

All of this said, the research and the literature review have also highlighted differences and inconsistencies in the experiences of women entrepreneurs around the world. By way of example; women are motivated differently to become entrepreneurs. Some women are compelled by circumstances to start their own businesses. They enter entrepreneurship out of necessity. Many other women, however, are attracted to entrepreneurship to exploit an opportunity or in search of self-fulfillment. Other women transition to self-employment for a mix of very different reasons. Also, in relation to barriers, while barriers to entrepreneurship are commonly experienced by women entrepreneurs everywhere, their source and nature are often disparate. It seems that the particular circumstances of a given environment influence the specific barriers women face. Propensity for risk, too, is an issue still debatable as it relates to women entrepreneurs.

Wherever there is strong evidence that a particular experience or preference typifying women entrepreneurs is universally true, there is also a compelling exception. For example; it is largely true that women entrepreneurs lack targeted professional development opportunities and yet, as the literature review described, there are impressive exceptions such as in the United Arab Emirates. Similarly, self-employed women seem to generally lack professional associations and third-party support networks to advocate for them. However, as in India, there are strong exceptions. A further example is education; almost everywhere women entrepreneurs seem to be very well educated but the opposite was found to be true in the Malaysia and Ghana studies.

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