A structural equation model of supply chain management strategies and firm performanceBy Wisner, Joel D

Publication: Journal of Business Logistics

Date: Wednesday, January 1 2003 Share:

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Joel D. Wisner

University of Nevada, Las Vegas

Supply chain management is the integration of key business processes among a network of

interdependent suppliers, manufacturers, distribution centers, and retailers in order to improve the

flow of goods, services, and information from original suppliers to final customers, with the

objectives of reducing system-wide costs while maintaining required service levels (Christopher

1998; New and Payne 1995; Simchi-Levi, Kaminsky, and Simchi-Levi 2000). Other terms

including integrated logistics, value chain management, JIT purchasing and logistics, quick

response, and supply chain synchronization describe subsets of, or specific initiatives within

supply chain management, and have been used in the literature to address the topic of supply

chain management (La Londe and Masters 1994; Tan, Handheld, and Krause 1998). Immediate

supplier and customer relationship activities have thus played an important role in the

development of effective supply chain management (SCM) strategies. Unfortunately, the terms

listed here in many cases have been used synonymously with supply chain management and

have clouded the issue and understanding of SCM. As a result, many practitioners view SCM

strictly from a supplier-base perspective, value chain, or customer-base perspective. This

research takes the broader view of SCM, including the focal firm and integrative activities with its

suppliers, its suppliers' suppliers, its customers, and its customers' customers (for a good

discussion of SCM and its history see Lambert, Cooper, and Pagh 1998; Lummus and Vokurka

1999).

The primary objective of SCM is to increase the value of products and services to customers in

the supply chain vis-A-vis improved customer service and quality, and lower inventory carrying

costs. The value created by a firm's SCM efforts clearly supports organizational strategy.

Successful SCM can result in lower system inventories, a network of firms that responds more

quickly to market changes, and products that more closely match customer expectations. Thus,

firms pursuing differentiation, cost leadership, or quick response strategies, or combinations of

these can all find benefits from value system or supply chain management (Porter 1985).

Today, the SCM concept and its associated activities continue to evolve as new communication

technologies and cooperative efforts emerge to facilitate system-wide process integration. The

body of supply chain-oriented research continues to grow along a number of fronts; many of

these efforts are concerned with further defining the SCM concept and its impact on

organizational characteristics and practices. Interestingly, several researchers have argued that

supply chain management is not feasible in many situations such as when the focal organization

is not in a position of power or structural dominance over its network of suppliers (Cox 2001; Cox

and Thompson 1998). Still others have brought attention to the lack of success in many supply

chain management endeavors (Handfield et al. 2000). However, to date, there has been limited

attention paid to identifying specific processes which have been successfully integrated, supply

chain-oriented issues to be concerned with, how best to design and manage supply chains,

empirically testing supply chain models, and the performance expectations of successful SCM

program implementations (Lambert, Cooper, and Pagh 1998).

This paper adds to the existing body of research by developing and analyzing a theoretical

framework for supplier and customer issues and concerns, supply chain management strategy,

and firm performance using structural equation modeling. This research contends that, like JIT

practices, all firms can benefit from some form or at least limited use of supply chain integrative

practices. As discussed in Porter's landmark book on competitive advantage, differentiation and

thus value are created by activities taking place within the value system (or supply chain) to get

products to the ultimate buyer (1985). Pitting one value system against another can be the source

of competitive advantage for the more effective value system members. Thus, each firm's value

chain (logistics system or network of suppliers, channels, and buyers) should impact the value

created by the entire supply chain, which relates to the current study. The primary research

question under study is: Are there positive linkages between supplier management strategy,

customer relationship strategy, supply chain management strategy, and firm performance? While

these linkages may seem intuitive, as alluded to above, to date there has been limited empirical

research testing these relationships.

LISREL8-SIMPLIS was employed to analyze a hypothetical model for the supplier, customer,

supply chain management, and firm performance items. The findings presented were obtained

using a comprehensive survey circulated to a wide variety of U.S. and European business

executives regarding a wide range of supply chain issues and strategies. Survey participants

were asked if their firm practiced supply chain management. Participants responding in the

affirmative were then asked questions regarding supplier management and customer relationship

strategies, supply chain management strategies, and firm performance. The objective of the

research was to test a number of hypotheses regarding the linkages between these activities and

strategies, and firm performance.

Study results supported the proposed structural equation model. Supplier management and

customer relationship strategies were found to be correlated and to impact supply chain

management strategies. Further, these practices and strategies were found to impact firm

performance. Based on these findings, a clearer picture of the practice and benefits of SCM and

its strategic implications emerges. It is interesting to note that while many respondents had

differing views of these activities and strategies, there was still considerable agreement as to the

impact of these practices on the firm.

The following sections describe the existing literature relevant to the study, the research

methodology, the demographic characteristics of the respondents, and an analysis of the

proposed model. Finally the managerial or strategic implications of the study and future research

directions are presented and discussed.

REVIEW OF THE RELEVANT LITERATURE

Increasing global competition, the demands of customers for higher product quality, greater

product selection, and better customer service, the desire of firms to shrink their supply bases

while striving to contain costs, and the rising costs of natural resources today have led many

organizations to adopt cooperative, mutually beneficial partnership strategies with suppliers,

distributors, retailers, and other firms within their supply chains to maintain or improve profitability

and overall firm performance.

The strategic management literature has discussed the relationship between these activities and

firm performance. For instance, Porter (1980) stressed the importance of buyers and suppliers

matching their individual needs with the relative capabilities of the other in order to maximize

product differentiation and minimize cost. Later, Porter (1985) advanced his earlier theories by

presenting discussion of the value system (today, more commonly referred to as the supply

chain) and its impact on competitive advantage. These seminal works have formed the basis for

the development of supply chain management strategies today and their ties to firm

competitiveness and performance. Further, Teece, Pisano, and Shuen (1997) provided an

explanation of how a firm's specific asset position and uniqueness shape its competitive

advantage. The practices of logistics and supply chain management along with their associated

benefits (better customer service, lower cost, higher quality, and improved competitive

advantage) are linked closely with the strategic management literature. Further, these practices

and strategies continue to evolve and the link between supply chain management and firm

performance is beginning to be realized as firms begin to understand and implement SCM.

Specifically, the relevant literature can be classified and discussed from three perspectives:

supplier management activities and strategy, customer relationship activities and strategy, and

system-wide supply chain management strategy. While there is certainly significant overlap

existing among these classifications, the purchasing and logistics literature generally is either

internally focused or spans the boundaries between the firm and its first-tier suppliers and

customers, while the supply chain management literature focuses on the integrating activities

taking place among a network of firms encompassing in many cases several tiers of suppliers

and customers. However, the term supply chain management is not used consistently within the

literature, and in many cases, the reader is left to decide how best to classify a particular piece of

research (Mabert and Venkataramanan 1998).

Supplier Management Strategy

The concept of SCM has slowly evolved. However, greater involvement is noted. For example,

manufacturers have utilized the knowledge and resources of key suppliers to support new

product development efforts (Morgan and Monczka 1995). Further, many firms have successfully

reduced their supply bases in order to form a smaller set of highly competent suppliers to achieve

improvements in purchased product quality and timing (Inman and Hubler 1992). Much of the

recent literature on SCM focuses on attempts to form alliances with suppliers to co-manage the

purchasing and supply function.

Recently, for instance, McGinnis and Vallopra (1999) found that purchasing's strategic

involvement with suppliers contributed significantly to process development and improvement in a

number of industry categories. As an example, involving suppliers early on in product design

efforts allows manufacturers to develop alternative conceptual solutions, select the best and most

affordable components, materials and technologies, and receive help in design assessment (Burt

and Soukup 1985). Future projections indicate supplier selection will increasingly be based on

strategic contributions to the supply chain and will extend beyond first-tier suppliers (Carter et al.

2000).

For a number of years, there has been significant disagreement regarding purchasing's ability to

contribute to the firm's sustainable competitive advantage. While a number of researchers have

suggested that firms cannot "purchase" competitive advantage (since freely traded assets are

available to all competitors, and all purchasing activities can be replicated), others are now

suggesting the contrary view: that purchasing functions and resources are not identical among

competing firms, and can result in proficiencies that are impossible or difficult to copy. Ramsay

(2001) provides a compelling discussion and review of this line of thinking. Several researchers

have discussed or tested for the relationship between supplier management activities and various

performance outcomes. Whipple, Frankel, and Anselmi (1999) discuss case studies in the

grocery industry to highlight inbound supply relationships and their impact on firm effectiveness

and efficiency. In a survey of 57 automotive supplier CEOs, Scannell, Vickery, and Droge (2000)

found significant positive relationships between JIT purchasing, supplier partnership, and supplier

development practices and several performance measures.

Customer Relationship Strategy

To speed the delivery process and improve customer service, manufacturers, distributors, and

retailers today are integrating their supply chain logistics functions by using transportation

partners for crossdocking and direct store deliveries without the need for incoming inspections

(Ellram, La Londe, and Weber 1989; St. Onge 1996). Transportation and other outbound logistics

functions focus on a number of strategically important supply chain management issues such as

JIT and customized delivery, warehouse and facility location, customized product/service issues,

customer relationship management, and communication/information system deployment. Supply

chain management's origins can be traced to an effort to better manage these transportation and

logistics functions (Fisher 1997; Lamb 1995; MacDonald 1991; Turner 1993; Whiteoak 1994).

Increasingly, product and service customization is performed within the distribution channel to

improve customer satisfaction (Lee and Billington 1995). This in turn, creates the need for third-

party logistics service providers. In a recent survey of European manufacturers, van Hoek (1999)

found customized transportation services, postponement, and the need for consistent, reliable,

on-time delivery to be top considerations in structuring and managing the supply chain. One of

the strategic goals of the transportation and outbound logistics functions is to reduce inventory

along the supply chain while simultaneously maintaining or improving customer service (Houlihan

1988; Jones and Riley 1987). A supply chain can accomplish this task by efficiently redistributing

stock within the supply chain using effective postponement and speculation strategies (Davis

1993; Pagh and Cooper 1998; Scott and Westbrook 1991). Inventory must be replenished quickly

and arrive when and where it is needed, in smaller lot sizes.

Indeed, a number of researchers have focused on the relationship between customer relationship

considerations or activities, and firm performance. For example, Deshpande, Farley, and Webster

(1993) found that customer orientation was positively related to firm performance. Ellinger,

Daugherty, and Keller (2000) used structural equation modeling to test among other things,

whether there was a relationship between distribution service performance and firm performance

(consisting of measures for firm profitability, sales growth, and customer satisfaction). They found

a significant positive association.

Supply Chain Management Strategy

The short-term objective of SCM is primarily to increase quality and productivity while reducing

inventory and cycle time; its long-term strategic goals are to increase customer satisfaction,

market share, and profits for all members of the supply chain network. Supply chain management

is evolving into a common body of literature, with a primary focus on key process integration

throughout the supply chain which should ultimately lead to a balance between customer

requirements and supply chain capabilities (Lummus and Alber 1997). In general, SCM seeks

improved participant performance through elimination of waste and better use of internal and

external supplier capabilities and technologies (Morgan and Monczka 1996).

The SCM philosophy expands the traditional internally-focused integrating activities of logistics

(Kahn and Mentzer 1996) by bringing trading partners along the supply chain together with the

common goals of efficiency, speed, and end-customer satisfaction (Harwick 1997). When

successful, SCM creates a virtual organization composed of several independent entities, often

linked by sophisticated enterprise resource planning (ERP) systems providing global visibility of

real-time information from any part of a company or its supply chain partners. The visibility

enables more effective forecasting, production, and inventory decisions (Chopra and Meindl

2001). To accomplish this, SCM must integrate a number of key business functions, including

purchasing, demand management, distribution planning, transportation, quality management,

production planning, and materials management throughout the supply chain.

Since the wholesaling and retailing industries incorporate a logistics focus into their strategic

decisions, use of the SCM concept would enable channel members to compete as a unified entity

instead of merely pushing inventories down the supply chain to end customers. Thus, the benefits

of vertical integration can be obtained by coordinating the logistics functions of independent firms

in the chain (Gustin, Daugherty, and Stank 1995; La Londe and Masters 1994). In this respect,

SCM involves the integration of logistics systems to control the movement of goods from original

suppliers to satisfied end-customers without waste (Ellram 1991).

Where improving customer service once meant increasing warehouse inventories along the

supply chain, today, integrated logistics systems seek to manage inventories through close

relationships with suppliers and transportation, distribution, and delivery services. A goal is to

replace inventory with frequent communication and sophisticated information systems to provide

visibility and coordination, so that merchandise can be replenished quickly and arrive where and

when it is needed in smaller lot sizes (Handheld 1994; Shapiro, Singhal, and Wagner 1993).

Firms that use advanced process technology to increase flexibility while involving manufacturing

and logistics managers in strategic decision making increase the role logistics plays in firm

success (Tracey 1998). Quick, frequent, and accurate information transfer among members of

the supply chain can counteract the distortion of information (known as the bullwhip effect) as it

passes sequentially up the supply chain (Metters 1997). When utilized effectively, communication

systems and information technology systems can replace inventory and improve organizational

performance (Lewis and Talayevsky 1997).

Recent research papers have explored linkages between supply chain management practices or

strategies and firm performance, either directly or indirectly. For instance, in a survey of North

American manufacturers, distributors, and retailers, Stank, Keller, and Daugherty (2001) found

that supply chain management practices tended to improve internal collaboration which, in turn,

positively affected logistics service performance. Brewer and Speh (2000) examined how the

balanced scorecard could be used to leverage a firm's supply chain into a source of competitive

advantage. An earlier work by Armistead and Mapes (1993) using a very small sample, found that

an increasing level of supply chain integration corresponded with increased manufacturing

performance.

Today, despite its importance, theoretical development, and popular usage in the business press,

there is little empirical research clearly defining the role of external relationship activities in the

development of supply chain management strategy, identifying the specific linkages between

supplier management and customer relationship strategies and supply chain strategy, and

perhaps more importantly, the corresponding impact these strategies have on firm performance.

This research addresses these issues, with particular attention paid to both supplier and

customer oriented activities and their roles in successful SCM.

THE PROPOSED MODEL AND RESEARCH HYPOTHESES

Figure 1 presents the proposed structural equation model and associated hypotheses. Supplier--

and customer-focused activities and their value to the firm and its customers have been the

subject of a number of research efforts (examples include Innis and La Londe 1994; Morash,

Droge, and Vickery 1996; Novack, Rinehart, and Langley 1996; Stank and Lackey 1997). This

body of research has shown that inbound and outbound capabilities such as delivery speed,

reliability, and low cost distribution were significantly related to a number of firm performance

indicators and to competitive advantage. Thus, the first two hypotheses are:

H1: Inbound logistics strategy positively affects firm performance.

H2: Outbound logistics strategy positively affects firm performance.

Supply chain management strategy, as discussed earlier in the literature review, is ideally a

linkage of internally-focused, mature, and successful supplier/customer-oriented capabilities

throughout the supply chain's members. A number of recent studies have discussed this

relationship between these boundary-spanning activities and supply chain management (Cooper,

Lambert, and Pagh 1997; Stank, Keller, and Daugherty 2001). Although supplier management

and customer relationship management is considered a subset of SCM strategy, other value-

adding concepts are also included such as information system integration and top-level planning

and control activities. However, literature suggests that firms must possess a high level of supply

side and distribution effectiveness prior to initiating SCM strategies. Thus, it is hypothesized that

supplier management and customer relationship strategies are positively linked to supply chain

management strategy. These hypothesized links can be stated as:

H3: Supplier management strategy positively affects supply chain management strategy.

H4: Customer relationship strategy positively affects supply chain management strategy.

One of the primary objectives of supply chain management is to create greater levels of customer

value and competitive advantage for organizations comprising the supply chain. While the linkage

between SCM and firm performance has been theoretically argued in the literature (Carter and

Narasimhan 1996; Christopher 1998), there has been limited empirical research in the area

(Armistead and Mapes 1993; Narasimhan and Jayaram 1998; Tan, Kannan, and Handheld

1998). The fifth hypothesis thus becomes:

H5: Supply chain management strategy positively affects firm performance.

Finally, it is hypothesized that as firms implement various boundary-spanning activities, these

activities tend to impact both supplier management and customer relationship capabilities. For

instance, as firms become more accustomed to JIT deliveries from suppliers, they should find

their outbound delivery timing impacted as well, as better transportation providers and delivery

arrangements are found. Additionally, as stronger partnerships and better collaborative efforts are

realized with suppliers through use of supplier reduction strategies and more effective sourcing

decisions, the firm's distribution performance and capabilities also tend to improve (Stank, Keller,

and Daugherty 2001). The final hypothesis can be stated as:

H6: Supplier management and customer relationship strategies impact each other.

RESEARCH METHODOLOGY

The Structural Equation Modeling Approach

Structural equation modeling is a confirmatory approach to data analysis requiring the a priori

assignment of inter-variable relationships. It tests a hypothesized model statistically to determine

the extent the proposed model is consistent with the sample data. Structural equation modeling

incorporates observed (indicator) and unobserved (latent) variables, which are separated into

measurement models and a structural equation model. Observed variables are those that can be

measured, while unobserved variables cannot be directly measured and must be inferred or

hypothesized from the observed variables. The measurement models specify how the latent

variables are measured in terms of the indicator variables as well as address the reliability and

validity of the indicator variables in measuring the latent variables or hypothetical constructs. The

structural equation model provides an assessment of predictive validity, specifies the direct and

indirect relations among the latent variables, and describes the amount of explained and

unexplained variance in the model (Byrne 1998; Schumacker and Lomax 1996).

IMAGE CHART 19

FIGURE 1

In structural equation modeling, there is no single test of significance that can absolutely identify a

correct model given the sample data (Schumacker and Lomax 1996). Many goodnessof-fit criteria

have been established to assess an acceptable model fit. Consequently, several authors

recommend presenting a number of indices to support model fit (Bentler 1992; Garver and

Mentzer 1999). This paper presents and discusses a number of fit indices with the results and in

Figures 2 through 6.

LISREL8-SIMPLIS was used to analyze the hypothesized model. A two-step model building

approach was used, wherein the measurement models were tested prior to testing the structural

model. The rationale behind this two-step approach is discussed in Joreskog and Sorbom (1993,

p. 113) wherein they state, "The testing of the structural model, i.e., the testing of the initially

specified theory, may be meaningless unless it is first established that the measurement model

holds." (Interested readers are also directed to Anderson and Gerbing (1988) for a further

discussion of this approach). The maximum likelihood estimation method was used which has

desirable asymptotic properties (e.g., minimum variance and unbiasedness) and is scale-free.

This estimation method assumes multivariate normality of the observed variables. Recent

research has shown that the maximum likelihood method can be used for data with minor

deviations from normality (Raykov and Marcoulides 2000). As a check of normality, the P-P plots

for a number of variables were checked in the sample, and the data appeared approximately

normally distributed.

Research Constructs and Items

The existing research was reviewed to identify relevant practices comprising the supplier

management, customer relationship, and supply chain management strategies. Additionally,

feedback from 30 senior purchasing managers was used to further validate the use of these

activities in developing each of the strategies. Thus, the practices used in each of the research

constructs were based on the literature and management feedback. For this study, respondents

stating they practiced supply chain management were asked to assess 14 supplier management

practices, 16 customer relationship practices, 20 supply chain management practices, and finally,

six performance measures. For each of the questions, assessments were made using a 5-point

Likert scale. These constructs are shown in Table 1.

Data Collection

To examine the relationships described above, a survey was designed, pre-tested, and validated

using 30 senior U. S. supply and materials managers. Feedback from the pre-test was then used

to revise the questionnaire (the pre-test questionnaires were not used for further analysis). Senior

managers, identified from the American Production and Inventory Control Society (APICS) and

the National Association of Purchasing Management (NAPM) databases, were asked to complete

the survey only if they practiced some form of supply chain management, as defined in the

survey. The following definition was supplied in the survey:

"Supply chain management is the integration of key business processes from end user to original

suppliers to provide products, services, and information that add value for customers."

The survey was circulated and responses were received in three phases from senior managers in

U.S. and European manufacturing and service organizations between December 1998 and

October 1999. In each phase, three mailings were conducted, consisting of the survey with a

cover letter, a reminder post card, and a second survey with a follow-up letter. The mailings for

each phase were conducted consecutively over the ten-month period due to the relatively large

manpower requirements. In the first phase, the survey was mailed to 1,500 U.S. manufacturing

firm supply and materials managers, randomly selected from the NAPM membership database.

For the second phase of the study, 3,000 surveys were sent to senior U.S. managers, randomly

selected from the APICS membership database. This sample included 1,000 manufacturing firms

and 2,000 service firms. For the third and final phase of the study, 970 surveys were mailed to

senior European managers, also randomly selected from the APICS membership database.

Multiple databases were used to maximize the sample size. Care was taken in both databases to

delete multiple listings for firms with more than one NAPM or APICS membership listing. A total of

556 useable surveys, consisting of 411 U.S. firm responses and 145 European firm responses,

were received for a response rate of 10.2%. The response rate was considered reasonable, given

the subject matter and complexity, and the survey length. The survey respondents practicing

SCM as defined on the survey were used for this study (350 respondents).

IMAGE TABLE 27

TABLE 1

Non-Response Bias

To investigate the possibility of non-response bias in the data, a test for statistically significant

differences in the responses of early and late waves of returned surveys was performed

(Armstrong and Overton 1977; Lambert and Harrington 1990). For each phase, the last wave of

surveys received was considered to be representative of non-respondents. Each survey sample

was split into two groups on the basis of early and late survey return times; t-tests were

performed on the responses of the two groups. The t-tests yielded no statistically significant

differences among the survey items tested. These results suggested that non-response bias did

not significantly impact the study.

Reliability Analysis

Since the data for this research was generated using scaled responses, it was deemed

necessary to test for reliability. Table 2 contains this information. Cronbach Alpha tests were

performed on the four constructs shown in Table 1. Based on the coefficient values, the items

tested were deemed reliable for this type of exploratory research (Nunnally 1978).

RESULTS

Respondent Firm Demographics

General demographic information of the respondent firms is presented in Table 3. Over 61 % of

the firms were either final product or raw material/component manufacturers with the remainder

classifying themselves as wholesalers, retailers, or other services (including third party logistics

providers, warehousing, healthcare, software, telecommunications, and utility companies). A

large percentage of the respondents (approximately 63%) stated they practiced some form of

supply chain management. A wide variety of firm sizes (based on number of employees and

annual sales) was also represented in the sample. Over 41 % had fewer than 500 employees,

while over 13% of the respondent firms had over 10,000 employees. Similarly, firm size based on

annual sales was also well dispersed. Eighteen percent had annual sales of less than $25 million,

while over 17% had sales in excess of $1 billion annually.

Analysis of the Measurement Models

To ensure model identification, one can separate the measurement models and the structural

model. If each measurement model is identified independently, then the structural model is

identified (Maruyama 1998).

IMAGE TABLE 37

TABLE 2

IMAGE TABLE 43

TABLE 3

The first measurement model tested was the Supplier Management Strategy model (SMGT). This

model was evaluated using the 14 items shown in Table 1. The model was checked to assure

that the parameter estimates exhibited the correct sign and magnitude and were consistent with

the underlying theory. Seven of the 14 items exhibited either large error variances or insignificant

parameter estimates. These items were considered unimportant to the model and thus were

deleted (Byrne 1998). The modification indices suggested Ql J (quick response time for

emergencies, problems, special requests) and Q IK (flexibility to respond to unexpected demand

changes) influenced each other. Since the firm's flexibility with respect to unexpected demand

changes is likely to influence its ability to respond quickly to emergencies or special requests, and

vice-versa, an error covariance between the two items (0.22) was included in the supplier

management strategy model (see Figure 2).

The Customer Relationship Strategy (CREL) measurement model was tested next. The 16 items

shown in Table 2 were used to evaluate this measurement model. Six of these items were found

to have large error variances and thus were dropped from the model. The modification indices

implied that a number of items were correlated, and this is shown in Figure 3. Q2B (the firm's

ability to meet customer due dates) was found to be correlated with both Q2D (successfully

resolving customer complaints) and Q2I (the firm's flexibility in meeting customers' changing

needs). This seems intuitive, since successfully meeting customer due dates implies a lower level

of customer complaints and a sustained ability to meet changing customer due dates, for

instance. It was also found that Q2J (using a customer satisfaction measurement system) and

Q2L (determining key factors for improving customer satisfaction) were correlated. This is not

surprising, since one of the primary objectives of customer satisfaction surveys is to determine

areas where the firm can concentrate additional resources to boost customer satisfaction. Finally,

Q2N (employing routine follow-up procedures for customer complaints) was correlated with both

Q2M (understanding how customers use the firm's products and services) and Q20 (interacting

with customers to set reliability, responsiveness, and other standards). Customer interaction is

likely to occur as customers communicate complaints and concerns to the firm. The outcomes

from these interactions are also likely to include the setting of customer responsiveness

standards and, in time, will result in a greater understanding of how the firm's products are used

by customers. The model was thus modified and the error covariance terms were added to link

the appropriate sets of indicator variables (see Figure 3).

Figure 4 shows the Supply Chain Management Strategy (SCM) measurement model. The 20

items shown in Table I were initially tested in the model. Examination of the error terms revealed

that eight of the items should be dropped from the model. The modification indices suggested that

improving the integration of activities across the supply chain (Q3C) was correlated with both

reducing supply chain response times (Q3B) and searching for new ways to integrate supply

chain activities (Q3D). In theory, SCM practice should support these correlations. One reason

firms integrate inter-organizational activities is to achieve reductions in response times as

products move through the supply chain. Additionally, firms practicing SCM often look for new

ways to integrate these activities, such as in the implementation of better communication

systems. The end result of these efforts should be better integration and shorter response times.

Creating a greater level of trust throughout the supply chain (Q3E) was correlated with identifying

and participating in additional supply chains (Q3H). As firms become more comfortable with their

supply chain partners, greater levels of supply chain management success can be achieved,

leading firms to seek out still other supply chain relationships. Additionally, establishing more

frequent contact with supply chain members (Q3I) was correlated with creating a compatible

supply chain communication/information system (Q3J). Again, this seems intuitive - more

frequent contact is likely to result in a more compatible communication system, and vice versa.

Also, involving all supply chain members in the firm's marketing plans (Q3N) was correlated with

communicating the firm's future strategic needs to suppliers (Q3Q). Certainly, one way to involve

suppliers in the firm's marketing plans is to communicate upcoming strategic material needs to

them in a timely fashion. The SCM measurement model was modified accordingly to reflect the

dropped items and the additional error covariance terms (see Figure 4).

Finally, the Firm Performance (PERF) measurement model was evaluated using the six observed

measures shown in Table 1. One of the performance measures exhibited a large error variance

so it was eliminated. The modification indices suggested that market share (Q4A) affected both

return on assets (Q4B) and overall competitive position (Q4E). Understandably, as market share

improves for a particular firm, asset utilization would likely increase, resulting in higher return on

assets. Also, market share is typically used as a proxy for competitive position, so this

relationship would be expected. Overall product quality (Q4D) and overall customer service levels

(Q4F) were also correlated. With respect to services in particular, service product quality and

customer service can be seen as synonymous. The final firm performance model is shown in

Figure 5 with the three error covariance terms.

When viewing the model fit indices for each of the measurement models in Figures 2-5, a good fit

is apparent regarding each of the measurement models. The x2/df statistic for each of the

measurement models was less than 3.0, suggesting that each of the measurement models fit the

sample data well. The commonly cited fit indices such as GFI, NFI, CFI, and IFI were all greater

than 0.90, suggesting excellent model fit. Finally, the critical N, or CN, was greater than 200 for

each of the measurement models, indicating the sample size of 350 was sufficient to yield

adequate model fit.

Analysis of the Structural Model and Hypotheses

The structural model was analyzed based on the modified measurement models using the

maximum likelihood estimation method. The initial model as shown in Figure 1 was tested,

resulting in two insignificant path coefficients, suggesting a lack of support in the data for this

model. Acting on the assumption that the original model was specified incorrectly, the model was

subsequently modified in stepwise fashion (see discussions of post-hoc modification in Hoyle

1995; Maruyama 1998; Raykov and Marcoulides 2000) resulting in a final model exhibiting good

fit, as shown in Figure 6. The data thus supported hypotheses H3-H6, namely, that the supplier

management and customer relationship strategies significantly impacted supply chain

management strategy, supply chain management strategy significantly influenced firm

performance, and that supplier management and customer relationship strategies significantly

impacted each other.

IMAGE CHART 48

FIGURE 2

IMAGE CHART 53

FIGURE 3

IMAGE CHART 58

FIGURE 4

IMAGE CHART 62

FIGURE 5

Figure 6 shows the modified structural equation model, standardized coefficients, and model fit

indices. All coefficients shown were significant at the die.05 level. The X2/df statistic (1.53)

indicates the modified hypothesized model fit the sample data well. The other fit indices shown in

Figure 6 also tended to confirm this. The results thus support the structural equation model and

the underlying theory.

IMPLICATIONS AND CONCLUSIONS

This study endeavored to identify and empirically verify relationships between current supplier,

customer, and supply chain management practices. Firms operating in the U.S. and Europe were

examined and a structural equation model for supply chain management was derived from the

literature. In general, the data supported the proposed structural equation model. A bi-directional

relationship exists between the items used to assess supplier management and customer

relationship strategy. Additionally, both supplier management and customer relationship strategy

positively impact supply chain management strategy, which in turn, influences firm performance.

These findings have a number of managerial implications. Firms should not view or evaluate their

supplier or customer practices independently. Instead, a systems approach should be used,

wherein firms recognize for instance, that inbound delivery timing and material quality, price, and

quantity all impact the firm's outgoing product and customer services (as represented by H6 in

Figure 1). Increasing information and coordination capabilities with suppliers tends to increase

those same capabilities with customers as well. Managers should be cognizant that increasing a

firm's external relationship capabilities in one area has a synergistic impact on yet other external

capabilities.

The significant relationships represented by H3 and H4 in Figure 1 suggest that firms seeking to

initially develop or further refine their supply chain management capabilities should look to

improve or expand their immediate supplier and customer relationship capabilities first. For

instance, finding and developing suppliers that can deliver on time, in the right quantities with

more flexibility, and directly to the points of use in the firm, can improve the integration of these

activities in the supply chain. Building and improving interdependent and trusting relationships

and then expanding them throughout the supply chain should begin with sound logistics

practices. Managers investing resources in the implementation of various external relationship

practices will find they lead to the generation and adoption of more effective supply chain

management strategies later.

Finally, the significant relationship represented by H5 implies that immediate and second-tier

supply chain management strategies all impact firm performance either directly or indirectly.

Specifically, managers wanting to improve market share, competitiveness, product quality, and

customer service should begin a process of internal assessment whereby their firm's immediate

supplier and customer relationship capabilities are assessed and potentially modified. Following

this, firms should consider identifying highly capable supply chain partners, creating better inter-

firm cooperation and integration capabilities through information sharing and exchange, reducing

response times throughout the supply chain, and sharing future strategic plans and requirements.

These relationships between supplier and customer strategies, supply chain management

strategy, and firm performance may well be the key to sustained competitive advantage.

The research here empirically illustrates the relationships between strategies focusing on

immediate suppliers and customers, supply chain management strategy, and firm performance.

Managers can thus use this information to effectively create a general supply chain management

strategy that will lead to improved firm performance. This is particularly important as competition

and customer requirements increase, forcing firms to continually evaluate and improve their

capabilities.

This study attempted to increase the understanding of supply chain management, in order to

provide useful insights to managers seeking to improve firm performance. This study, like others,

has limitations. The random sample for the survey was obtained from the NAPM and APICS

membership databases; thus, the results are generalizable only to the extent that the NAPM and

APICS members resemble the population of all U.S. and European firms and were

knowledgeable about their firms' SCM efforts. The response rate was also somewhat low;

however given the length, complexity, and subject matter, this is considered reasonable. Some

potential respondents may have decided not to reply once they learned the survey was primarily

for firms practicing SCM. For this reason, the percentage of firms practicing SCM (as shown in

Table 3) may be overstated, The survey mailings and returns covered a ten-month time period,

which may have introduced a slight time lag problem. Readers should also be reminded that

much of the data reported here is based on management perceptions. Past research however,

supports the use of qualitative assessments and has found them to be a reliable alternative to

actual performance data (Dess and Robinson 1984; Venkatraman and Ramanujam 1986).

Because of the use of qualitative assessments from managers, firm performance data were not

collected. Only general overall performance assessments relative to competitors were requested.

This could be seen as a limitation. Also, the term supply chain management may be interpreted

differently across industry and academic groups alike. These varied perceptions may have played

a role in the answers provided on the survey and impacted the findings. To minimize potential

confusion, a commonly used definition of supply chain management was provided on the survey.

Finally, respondents whose firm did not practice SCM were not used in this study beyond the

general sample description provided in Table 3. Thus, the measurement models and structural

equation model were based on the set of respondent firms practicing SCM. This could be seen as

a limitation of the study, given that certain responses were omitted, however the aim of the study

was to analyze firms practicing SCM.

Future research efforts in this topic area should include further studies of the supply chain

management and firm performance relationship, such as an assessment of the type of

performance measurements used among firms practicing supply chain management, and studies

that look at the triads of suppliers-buyers-customers and their specific interactions and practices.

Additional studies of the specific processes integrated, the types of information shared, and the

linkages between second- and third-tier suppliers and customers should also be investigated.

Finally, the dynamic roles power and trust play in the success of supply chain management has

yet to be fully investigated.

ACKNOWLEDGMENT

This research was funded by a grant from the APICS Educational and Research Foundation, Inc.

The author would also like to thank the editor and reviewers for their many thoughtful and valued

comments.

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AUTHOR_AFFILIATION

ABOUT THE AUTHOR

AUTHOR_AFFILIATION

Joel D. Wisner, Ph.D., C.P.M., CTL is an Associate Professor of Supply Chain Management at

the University of Nevada, Las Vegas. He received his Ph.D. in Operations Management and

Logistics from Arizona State University in 1991. Dr. Wisner's research interests are in the areas of

quality assessment and improvement strategies across the supply chain. His articles have

appeared in numerous journals including the European Journal of Purchasing and Supply

Management, Journal of Business Logistics, Journal of Operations Management, Journal of

Supply Chain Management, Journal of Transportation, Production and Operations Management

and Quality Management Journal.