European Journal of Innovation ManagementAn empirical investigation of innovation determinants in food machinery enterprisesBarbara Bigliardi Alberto Ivo Dormio

Article information:To cite this document:Barbara Bigliardi Alberto Ivo Dormio, (2009),"An empirical investigation of innovation determinants in foodmachinery enterprises", European Journal of Innovation Management, Vol. 12 Iss 2 pp. 223 - 242Permanent link to this document:http://dx.doi.org/10.1108/14601060910953988

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An empirical investigationof innovation determinants in food

machinery enterprisesBarbara Bigliardi and Alberto Ivo Dormio

Industrial Engineering Department, University of Parma, Parma, Italy

Abstract

Purpose The purpose of this paper is to present the main findings of an empirical study conductedin the Italian food machinery industry, on identifying the technological innovation determinants insmall or medium enterprises.

Design/methodology/approach On the basis of a research framework, a study was carried outon 98 Italian firms operating in the food machinery industry, by means of a questionnaire survey.A statistical analysis was conducted on the data collected, in order to understand which are the mostimportant factors influencing innovation and the relative effect on the innovation output of the variousfactors considered.

Findings The results of the statistical analysis conducted show that, in contrast with the trend of theindustry investigated, great importance is attributed only to collaboration with universities andresearch centres. Network actors are not perceived as an important source of information for innovation,while universities, conferences and scientific papers are significant sources of information in explainingthe share of total turnover from new products or processes and process innovations, respectively. As faras, obstacles to innovation are concerned, the results indicate that both financial and informativeobstacles are consistently associated with the innovative output. Finally, firms focusing on market andefficiency related innovation objectives realise higher levels of process related innovative output.

Originality/value The study provides some empirical evidence on identifying and prioritising thetechnological innovation determinants for enterprises operating in the context of a northern Italiandistrict.

Keywords Food industry, Food manufacturing equipment, Innovation, Italy

Paper type Research paper

1. IntroductionNowadays, innovation is at the top of many chief executive officers agendas. It isconsidered a fundamental component of entrepreneurship and a key element of businesssuccess. According to several specialists, innovation is now unavoidable for companieswhich want to develop and maintain a competitive advantage and gain into new markets(Stock et al., 2002). The undeniable importance of innovation for contemporary companiesjustifies the increasing interest that researchers are taking in it. Innovation especiallyproduct innovation is recognised as a key element in the process of valuecreation (Han et al., 1998; Vilaseca-Requena et al., 2007; Weerawardena, 2003). Froehleet al. (2000) and Schilling and Hill (1998) pointed out that firms often opt for innovation orrenovation of their product portfolios in order to improve their competitive situation,so that strategy guarantees the increase of consumers satisfaction and loyalty(Atuahene-Gima, 1996a, b; Vorhies et al., 1999). Innovation has been studied in a varietyof contexts, including in relation to technology, commerce, social systems and economicdevelopment. There is, therefore, naturally a wide range of approaches conceptualisinginnovation in the scholarly literature. However, a consistent theme may be identified:

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European Journal of InnovationManagement

Vol. 12 No. 2, 2009pp. 223-242

q Emerald Group Publishing Limited1460-1060

DOI 10.1108/14601060910953988

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innovation is typically defined as the successful introduction of something new anduseful, for example introducing new methods, techniques, or practices or new or alteredproducts and services.

Various definition have been developed to explain innovation, and as a result, theterm has gained greater ambiguity (Garcia and Calantone, 2002). Going back to theroots, Schumpeter (1934) was first to define innovation as the creation of newcombinations. Schumpeters exact definition refers to the introduction of a new good(that is one with which consumers are not yet familiar) or of a new quality of good; theintroduction of a new method of production, which needs by no means to be foundedupon a discovery scientifically new, and can also exists in a new way of handling acommodity commercially; the opening of a new market, that is a market into which theparticular branch of manufacture of the country in question has not previously entered,whether or not this market has existed before; the conquest of a new source of supplyof raw materials or half-manufactured goods, again irrespective of whether this sourcealready exists or whether it has first to be created; and finally the carrying out of thenew organization of any industry, like the creation of a monopoly position (for examplethrough trustification) or the breaking up of a monopoly position.

Recently, the economic landscape has changed considerably in comparison toSchumpeters time, nevertheless his work remains topical. Most of the widely useddefinitions of innovation focus on novelty and newness. The European Commission(1995) Green Paper, for example, defined innovation as the successful production,assimilation and exploitation of novelty in the economic and social spheres. Zaltmanet al. (1973) defined innovation as any idea, practice, or material artefact perceived tobe new by the relevant unit of adoption, while Damanpour (1991) defined it asthe generation, development, and adaptation of novel ideas on the part of the firm.

Regardless of the definition adopted, innovation may be represented by new products,new methods of production, new sources of supply, the exploitation of new markets, newways to organise business. In the economic literature, various classifications of innovationhave been developed and applied. Following Clarysse et al. (1998) and Lundvall (1992)classifications, it is possible to identify four domains of innovation (Figure 1):

(1) Product innovation. Any good, service or idea that is perceived by someone asnew.

(2) Process innovation. The adaptation of existing production lines as well theinstallation of an entirely new infrastructure and the implementation of newtechnologies, and generally it allows the creation of new products.

Figure 1.The four domainsof innovation

Product innovation

Market innovation

Organisationalinnovation

Process innovation

Technological/Technicalinnovation

Non-Technological/ Non-Technical innovation

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(3) Organisational innovation. Changes in marketing, purchases, sales,administration, management, staff policy.

(4) Market innovation. The exploitation of new territorial markets and thepenetration of new market segments within existing markets.

Figure 1 shows the definition of innovation given by Lundvall (1992), that isinnovation can be considered an ongoing process of leaving, searching and exploringwhich results in new products, new processes, new forms of organisation and newmarkets. Most researchers have focused on technological/technical innovations, thatis on product and process innovation. Following the Oslo Manuals lead, we definetechnological innovation as implemented technologically new products and processesand significant technological improvements in products and processes (OECD, 1997).

Underlying all of the studies above mentioned is a fundamental question, namelywhy are some firms more innovative than others. One way to recast this question is toask which factors determine and influence the innovation output of a firm. With thispurpose in mind, we compare innovative firms with non/less innovative firms, in orderto understand which are the most prominent factors explaining the innovative outputof food machinery firms.

The paper is organised as follows. In Sections 2 and 3, a theoretical justification forthe variables considered in the study is provided and the research framework isintroduced, respectively. First, the aspects under which the innovative output of a firmcan be investigated are illustrated, and then the role of factors that are most likely toaffect the innovative output is discussed. Then, the specific research framework isintroduced, and the research hypotheses are formulated. In Section 4, after a clear viewof the context under examination (the food machinery industry), it is illustrated theexperimental design of the survey conducted. Sections 5 and 6 are devoted to thepresentation and discussion of the empirical findings. Finally, in Section 7 conclusionsare drawn and indication for future research are proposed.

2. Factors measuring and influencing the innovation outputThe identification of factors measuring and influencing firms innovation is a populartopic in the empirical literature. Patents are a widely employed direct measure ofinnovation output (Patel and Pavitt, 1992), but other indicators, complementary oralternative, have been developed and used in empirical analyses, such as citationcounts of patents (Albert et al., 1991), self-assessment by managers of the number ofinnovations introduced by their firm (Pavitt et al., 1987; Cohen and Levin, 1989), theshare of innovative products and processes in a firms total share (Brouwer andKleinknecht, 1994).

As far as the factors influencing the innovation output are concerned, variousfactors, have been identified in literature, of both internal and external nature.The research methodology followed to select these factors was a combination ofliterature analysis and interviews with a panel of experts. Once the literature reviewhad been completed, a panel of experts was set up to validate the variables proposed.To this extent, the panel included:

. Five academics whose research studies mainly focus on innovation management.Owing to their expertise in such area, academics could support the panel ofexperts during the decision-making process.

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. About 15 members from as many firms operating in the food machineryindustry. They were selected among people directly operating in the keybusiness functions involved in the research and development (R&D) activities,and were asked to validate the variables selected based on their in fieldexperience in the industry.

Based on findings from the literature, academics initially proposed a viable set offactors, structured into an appropriate questionnaire to be sent to the panel members,to be used as determinants of the innovative output. For each variable, the panelmembers were asked to express their agreement with regard to the suitability ofimplementation in the food machinery industry. Moreover, they could indicate the needfor further specifications of variables, as well as the main strengths and weaknesses ofeach variable identified. Hence, a second questionnaire was organized, incorporatingadditional variables proposed by the panellists and removing non relevant ones, andsubmitted to the panel members. Then, the panel was involved in a final roundtablediscussion, to confirm the agreements on the results and at the end a general agreementwas reached. The final version of the questionnaire contained the variables listedbelow and detailed in the next paragraph:

. reasons for introducing innovation;

. obstacles and barriers to innovation;

. collaboration with external actors; and

. information sources.

3. The research hypothesesIf we look at innovation as a process, first of all we have to consider the decision toinnovate, that is the innovation strategy. A firm can decide to be at the forefront of newdevelopments (the so-called first mover), or to follow the new developments once provensuccessful (the so-called follower) (Schilling, 2005). In the first case, there are severaladvantages that can be gained from entering first: scarce resources can be pre-empted,e.g. occupation of prime retail locations, the ability to register patents and trademarksthat will protect the first entrant from future competition, changing the economics of themarket in a way that second entrants will not have an economic justification to enter,early profits can be re-invested in improving the resource base, and reputation will likelyhave the advantages that come from suppliers, distributors and customers who arefamiliar with and loyal to their products. Nevertheless, there are two obvious drawbacksto being the first mover: costs and risks. Not only it is expensive to be a pioneer, but alsoit is risky, as the first company in a particular market cannot benefit from knowledge ofsuccesses and mistakes of others (Lieberman and Montgomery, 1998). Finally, a firmcan, obviously, decide not to innovate. The technological strategy adopted by a firmdepends on the reason that motivate the firm to innovate. Empirical works have shownthat, at the industry level, a greater range of innovation objectives is associated withgreater rates of innovation, while at a firm level innovation objectives affect the ability offirms to successfully innovate (Cohen and Malerba, 2001).

Among all, the most important reasons for firms to innovate can be listed as follows:the value added, the differentiation of products, the enhancement of firms efficiencyand effectiveness, the possibility to gain a funding, or just to meet legislative demands

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and quality standards. All these reasons can be grouped together into three types ofinnovation objectives:

(1) Market or efficiency related objectives, that is firms innovate in order tostrengthening the value added or products differentiation, or in order to enhancetheir efficiency, effectiveness or flexibility.

(2) Legislative related objectives: in the context investigated, regulations for foodsafety, for the use of specific technologies or ingredients as well as labellingrequirements are of particular relevance (Menrad, 2004). As a consequence, firmscan decide to innovate in order to meet legislative demands and quality standards.

(3) Financially related objectives, that is the possibility to gain a funding for R&Dprojects.

This variety of motivations can push and pull firms along the innovation path. Themotivations listed above may be classified as proactive and reactive. Proactivemotivations may represent stimuli for firm-initiated strategic change, that is the wish toenhance its product mix, efficiency or effectiveness. Reactive motivations may on thecontrary describe stimuli that result in a firms response and adaptation to changesimposed by the outside environment (typically, legislative demands and qualitystandards). Proactive firms are more likely to have solicited their innovation process,whereas reactive firms frequently begin innovative activities after receiving an unsolicitedorder from abroad. In general, firms that are more successful in the innovation process areusually motivated by proactive factors (Cohen and Malerba, 2001), the contrary forreactive factors. Proactive firms are frequently more product/service-oriented thanreactive firms. Further, they are more marketing and strategy oriented than reactive firms,which have as their major concern operational issues. Since Porter (1980), most authorshave confirmed direct and positive links between proactive strategy and financialperformance (Aragon-Correa and Rubio-Lopez, 2007). Generally, we expect that firmsfocusing proactive objectives (that is on market or efficiency related objectives) will realisehigher levels of innovation output, the contrary for reactive innovation objectives of types(2) and (3). These considerations support the following hypotheses:

H1a. Firms focusing on market related innovation or on efficiency relatedinnovation objectives realise higher levels of innovative output.

H1b. Firms focusing on legislative related or financial innovation objectives realiselower levels of innovative output.

Once a firm decides if and how to innovate, the innovation process not necessarily hasa successful conclusion. Innovation process can be regarded as a complex managementprocess associated with many failures and related obstacles (Tidd et al., 2005), that canbe of different nature. In several countries, the main obstacles are the financial ones(Garcia Martinez and Briz, 2000), that is, for example, the lack of the necessaryfinancial resources or to too high-innovation costs. Financial problems are particularlyacute in the case of innovation activities due to some of their inherent characteristics:risk, appropriability, and use of intangible assets (Hall, 2002; Myers and Majluf, 1984).

Next to financial obstacles, firms may experience also organizational obstacles (forexample a lack of qualified staff, a lack of knowledge, or an inflexible internalorganisation), too much uncertainty of future benefits and costs, and uncertainty of future

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market developments. With reference to the former type of obstacles, small and mediumfirms have often faced with difficulties integrating new complex technologies in theexisting processes, or developing new products using such technologies. On the otherhand, large firms, having more resources available for innovation, are hampered by theinflexibility and weak entrepreneurial drive within bureaucratised innovationdepartments. Finally, firms may experience obstacles from outside the firm, e.g.difficulties with regulations or standards, limited market acceptance of new products, alack of information about the innovation process or about the market.

Previous studies analysed the effects of the different kinds of obstacles listed aboveon the innovative output (Mohnen et al., 2008; Santarelli, 1993). Results from thesestudies show that firms generally do not only experience financial constraints, but alsothey are hampered in various ways with economic market uncertainty, organizationalrigidities and lack of information. Regardless from the type of obstacles, their effects onthe innovation output varied from the abandoning of the innovation project, to theprematurely write off or the slow down of the project, until not starting the project atall (Gomes et al., 2006; Mohnen et al., 2008). Therefore, it is to be expected that firmsexperiencing obstacles have lower levels of innovative output compared with firmswho do not experience innovation obstacles, that is:

H2. Firms that experience innovation obstacles perform worse in terms ofinnovative output.

Innovations are more and more seen as the result of an interactive process ofknowledge generation, diffusion and application. The importance of these interactionsfor innovation and the role of collaboration as a means of accessing external knowledgeby extending the knowledge boundaries of firms has been widely stressed by thestrategic management literature (Camagni, 1991; Bottazzi and Peri, 2003; Edquist,2005; Miotti and Sachwald, 2003; Powell and Grodal, 2005; Rothaermel and Deeds,2006; Womack et al., 1991). Womack et al. (1991), for example, highlighted the potentialrole of collaboration as a means of accessing external expertise to allow concurrentdevelopment to take place and to accelerate the product development process.Networks may also allow firms to take advantage of potential agglomeration andinformational advantages in both high-tech (Saxenian, 1996; Shefer and Frenkel, 1998)and more traditional sectors (Perry, 1999). With reference to small and mediumenterprises (SMEs) that characterise the selected industry, since innovation strategieslook increasingly similar and commoditized, more and more organizations try tofurther improve their innovation performance through intensifying collaborationacross industry networks and partnerships, opening up their innovation processes inline with the open innovation framework (Chesbrough, 2003; EIRMA, 2004). Inter-firmsrelationships in terms of networks and alliances have been recognised as important forthe development of their innovations and technologies (Gandolfi, 1999).

Partners for collaboration may be part of the supply chain or belong to otherindustries, and may influence and determine the type of collaboration. Collaborationwith customers, for instance, could be generally associated with retrieving marketinformation, whereas cooperation with competitors could be associated with exploitingeconomies of scale and reducing individual costs of innovation. Moreover, the type ofcollaboration may change in function of the type of innovation to be introduced.Todtling et al. (2009) showed that advanced or radical innovations are drawn on new

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scientific knowledge, generated in universities and research organizations, whileincremental innovations take place more in interaction with partners from the businesssector often located at higher spatial levels beyond the region. The majority ofinnovation studies found a positive effect of collaboration on innovation performance(de Man and Duysters, 2005). Then, following de Man and Duysters (2005), wehypothesise that collaboration is positively related to innovative output:

H3. Collaboration for innovation is positively related to innovative output.

As previously stated, collaboration is used also as a means to gather knowledgerequired for the innovation process. The knowledge-based view of the firm (Kogut andZander, 1992; Grant, 1996) has focused attention on the importance of knowledgesources to innovative success. For example, information from supply chain partnersare important for innovation activities: customers provide feedback regardingproblems with, and desired modifications of, existing products (von Hippel, 1976),while suppliers provide knowledge regarding inputs, including raw materials, plant,equipment and components. In the industry selected, in particular, an important sourceof information for innovative firms is represented by customers, that is firms belongingto the food industry. Past studies (von Hippel, 1976; Montoya-Weiss and Calantone,1994; Cooper, 1999) show that by incorporating the interests of the final customer in theinnovation process, the chances for success can be increased. Other studies indicatecompetitors and institutions (i.e. universities and research institutions) as an importantsource of informations for innovation: academic research provides, for instance, theaccess to basic scientific knowledge (Arora and Gambardella, 1990). Further, it ispossible to list among the possible sources of innovation, scientific literature, fairs andtraders (Gandolfi, 1999). Researches on innovation management suggest two mainreasons why multiple knowledge sources may be associated with greater innovationsuccess. First, firms may be able to increase the value of their innovation success bysampling a range of knowledge sources; second, firms may benefit fromcomplementarities and synergies among knowledge sources.

Helfat and Leiponen (2005) suggested that broader horizons with respect toknowledge and information sources are associated with successful innovation.Moreover, the innovation objectives above mentioned can benefit from the range ofknowledge sources, that provide the opportunity for technological advance (Klevorichet al., 1995). As a consequence, access to a greater range of knowledge sources mayhelp firms to improve their odds of successful innovation (Helfat and Leiponen, 2005).Based on these arguments, we expect that firms who use informations gathered fromtheir network realise higher levels of innovative output, and thus we postulate thefollowing hypothesis:

H4. Firms that gather information from their network realise higher levels ofinnovative output.

The research model that summarises the hypothesis is shown in Figure 2.

4. Research methodology4.1 The context investigated: the food machinery industryThe empirical research was based on the study of the food machinery industry, in whichresearch and development into new technological solutions for the processing of food

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products is extremely active and dynamic. The choice of this specific industry wasmotivated by two reasons. First, it represents one of the most important industrialsectors of northern Italy. In particular, this sector is the most important, together withthe food industry, as for the Parma District. As an indication of its importance, it shouldbe pointed out that this sector represent the 48 per cent of the total of industrial sectors,reaching a turnover of e8.500 million out of a total of e17.700 million (www.upi.pr.it).Moreover, since the middle of the nineteenth century, preservation and processing ofagricultural products has constituted a major part of the Parma area economy andrepresents the primary and most significant impulse to the mechanical industry.

Complete food processing systems, designed and produced in Parma, are installedthroughout the world, particularly for mass production of canned tomatoes and sauces,vegetables in general, regular and exotic fruit, juices, preserves, beverages and cannedmeats and fish. Also companies involved in the production of cooling systems, food anddrink bottling equipment and packaging machinery in general, are very active. For thesereasons, the biennial trade fair of world food technology, CIBUS TEC, is held in Parma,which has become known as the sector capital thanks to the high-concentration of food andfood engineering enterprises in the area. Of course, the application of data from just oneparticular industry reduces on the one hand the number of observations but has, on theother hand, the advantage that firms are relatively homogeneous (Kraft, 1990). Given thatthe technical opportunity for innovations presumably differs considerably, an aggregationof observations from different industries could be problematic (Cohen et al., 1987).

4.2 DataThe results presented in the paper come from an in depth questionnaire survey carriedout among firms operating in the food machinery industry in northern Italy in ParmaDistrict, in the period 2006-2007. Prior to the survey, in order to provide more completeinformation for the hypotheses and render the preliminary version of the questionnairevalid, the questionnaire was tested. This stage has been particular useful since itprovided a direct insight into how specific phenomena, which came to the fore during theliterature survey, found actual application in the industrial practice within the contextunder investigation. This activity pursued two distinct objectives: building a frameworkfor a structured research hypothesis concerning the factors explaining the innovationoutput, and, second, to decide upon which data should be collected in a subsequentquestionnaire survey. The results of this process were edited for overlaps to produce aquestionnaire with a final list of more than 50 items. The questionnaire consisted of threeparts: the first referred to the collection of general information about the company,

Figure 2.The research model

Innovation objectives

Information sources

Collaboration

Innovation obstacles

Innovation output

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its competitive environment, its characteristics in terms of human resources and itstechnological strategy. The second aimed at investigating the characteristics of theinnovative activity carried out by the firm, both in terms of technological/technicalinnovation (product and process innovation), and in terms of non technological/nontechnical innovation (marketing and organisational innovation). Finally, Section 3concerned the relationships between innovation and organisational culture.

4.3 Characteristics of the sampleAn overall population of 201 firms was obtained from different data sources: the CIBUSdatabase (an annual exhibition of food and beverage machinery manufacturers), thechamber of commerce, and different professional associations. All 201 firms were sentthe questionnaire and were contacted by mail in order to check their willingness toparticipate in the survey. A final number of 98 usable questionnaire was obtained, with asatisfying return rate of 48.75 per cent. The questionnaire was submitted to managerswho were identified as being responsible of the innovative process.

4.4 Variables and measuresBased on the research framework, indicators were selected for the questionnaire. Theseindicators relate to innovation objectives, innovation obstacles, collaboration andinformation sources. In order to reduce the total number of variables, some questionswere grouped according to their relations to particular concepts. In the remainder ofthis paragraph we operationalise the research framework.

4.4.1 Dependent variable. In our research, we used as indicator of the innovativeoutput the share of innovative products and processes in a firms total share.This method, used by Brouwer and Kleinknecht (1994), consists in asking firms toreport for a certain period the percentages of their sales which are due to productsand/or processes incrementally improved, radically changed, or newly introduced, thatcan in turn be divided into products/processes new to the firm and already known inthe industry, or products/processes new to the market and not introduced earlier byanother firm. For the purpose of our research, and on the basis of the prevalence in themechanical industry of process innovation, with reference to the last classification, wereferred only to process innovation (see the following indicators (2) and (3)).Summarising, the four indicators used are listed below:

(1) the impact of new products and/or processes on firms total turnover;

(2) process innovation new to the market;

(3) process innovation new to the firm; and

(4) type of product and process innovation (radical vs incremental).

The first indicator refers to the impact of new or strongly improved products and/orprocesses realised during the last five years on firms total turnover, and allows us tomeasure the fact that a firm has been innovating, but also the perceived impact of theseinnovation activities on its turnover. The second indicator determines whether a firmrealised one or more process innovation in the past five years that were new to themarket. We used a similar indicator for process innovations from the past five yearsthat were new to the firm. As for the last indicator, it takes into account the type ofinnovation introduced in the last five years (radical or incremental).

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4.4.2 Independent variables. The proposed analytical model considers four factorsas possible determinants of innovation: objectives (OBJ), obstacles (OBST),collaboration (COLL) and information (INFO). The innovation objectives, that is themotivation that prompts firm at introduce an innovation, were grouped into fourcategories: market related objectives (larger market share, new market and new foreignmarket penetration and broader assortment), efficiency related objectives (higherproductivity, cost reduction), normative related objectives (meeting legislation onsafety, quality, food health and environmental protection) and financial objectives (thepossibility to gain financial incentives). For these variables, group averages werecalculated and used in the analysis. The obstacles met in the development and/orintroduction of innovation are assessed by considering the importance attributed bythe firm to different factors hampering their innovation activities, or even hamperinginnovation activities from getting started. In particular, obstacles were groupedtogether: financially related obstacles (lack of finance, too high costs), informationrelated obstacles (lack of information about market and/or about technologies),internally related obstacles (lack of qualified personnel, lack of knowledge) andexternally related obstacles (lack of partnerships or difficulty in establishing them). Tomeasure collaboration, we take into account of the importance attributed by the firm tocollaboration with industry and non-industry agents for the development of innovativeactivities. Specifically, we distinguish between customers, suppliers, competitors,universities and research centres. The variable INFO refers to the importanceassociated with several sources of information for innovation. The possible sources inthe questionnaire were: not completed projects or past patents, competitors,customers/suppliers, universities, research institution, conferences and fairs,literature, and professional associations. Table I shows all the variables includedinto the analysis and their scale of measurement.

5. Data analysisFirst of all, we conducted a descriptive analysis, with the purpose to understand thecharacteristics of the sample in general terms and in terms of innovation in particular.Then, in order to investigate the hypotheses, we propose eight models, with referenceto the eight variables used to describe the innovative output (Model 1 refers to theanalysis conducted for the dependent variable IMPPROD, Model 2 refers to the sameanalysis conducted for the dependent variable IMPPROC, and so on). We have chosen amultiple linear regression (Hair et al., 1998) as estimation technique to evaluate thesemodels. An assessment of multicollinearity was carried out through the computation oftolerance value and variable inflation factor (VIF). For most of the variable, thetolerance values were well above ten cutoff and the VIFs were substantially below tencutoff, indicating multicollinearity was not a problem. Only for few variables there wasproblem of multicollinearity, as such these items have been eliminated and notconsidered in the analysis (Field, 2000).

6. ResultsDescriptive data are presented in Table II. Only 18.4 per cent of the firms are big firms,the remaining 81.6 per cent are SMEs, in confirmation of the structure of the industryunder investigation. This fact is confirmed also by the breakdown of turnover intocategories.

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Variable Description (items in the questionnaire) Scale of measurement

IMPPRODIMPPROC

Impact of product innovation on firms total turnoverImpact of process innovation on firms total turnover

1 null2 low3 medium4 high5 very high

NEWMK

NEWFIRM

INCRPROD

RADPROD

INCRPROC

RADPROC

Firm develops predominantly process innovationnew to the marketFirm develops predominantly process innovationnew to the firmFirm develops predominantly incremental productinnovationFirm develops predominantly radical productinnovationFirm develops predominantly incremental processinnovationFirm develops predominantly radical processinnovation

1 strongly disagree2 disagree3 neither agree nor

disagree4 agree5 strongly agree

OBJ1

OBJ2

OBJ3

OBJ4

Firm introduces innovations in order to meetlegislation in matter of safety, quality, food healthand environmental protectionFirm introduces innovations in order toincrease its market share, to enternew market or foreign market, or to enlarge itsproduct assortmentFirm introduces innovations in orderto increase its productivity or to decrease itsproduction costsFirm introduces innovations becauseof the possibility to gain financialincentives

1 strongly disagree2 disagree3 neither agree nor

disagree4 agree5 strongly agree

OBST1

OBST2

OBST3

OBST4

Importance of lack of finance or presence of costs toohigh as obstacle at the development/introduction ofinnovationImportance of lack of information abouttechnology and/or market as obstacleat the development/introductionof innovationImportance of lack of qualified personnel andknowledge as obstacle at thedevelopment/introduction of innovationImportance of lack of partnership or difficulty inestablishing them as obstacle at thedevelopment/introduction of innovation

1 unimportant2 of little importance3 moderately

important4 important5 very important

COLL1

COLL2COLL3

Importance of collaboration with customers and/orsuppliersImportance of collaboration with competitorsImportance of collaboration with universities an/orresearch centres

1 unimportant2 of little importance3 moderately important4 important5 very important

(continued )Table I.

Description of variables

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Almost all of the firms (84 per cent) exports their product, while 71 per cent owns a ISO9000 certification. As far as legal and organisational structure is concerned, 80.6 per centof the firms are limited liability company or commercial partnership, the remainingpercentage are public limited company, while almost half of the firms has a functional

Variable Description (items in the questionnaire) Scale of measurement

INFO1

INFO2

INFO3

INFO4

INFO5

INFO6

INFO7

INFO8

INFO9

Importance of unfinished projects as informationsource for innovationImportance of past patents as information source forinnovationImportance of competitors as information source forinnovationImportance of customers and/or suppliers asinformation source for innovationImportance of universities as information source forinnovationImportance of research centres as information sourcefor innovationImportance of conferences and fairs as informationsource for innovationImportance of literature and scientific papers asinformation source for innovationImportance of professional associations asinformation source for innovation

1 unimportant2 of little importance3 moderately important4 important5 very important

Table I.

Per cent

Turnover (e million)#2 2.02-10 13.310-25 45.925-50 36.7.50 2.0No. of employees1-9 1.110-49 14.250-150 66.3150-249 15.3.250 3.1Percentage of employees staffed in R&D departments,5 48.05-10 12.210-15 14.315-20 19.4.20 6.1Education (percentage of employees with graduate degree),5 5.15-10 37.810-15 28.615-20 20.4.20 8.1

Table II.Descriptive data

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(41.8 per cent), informal (36.7 per cent) or divisional (13.3 per cent) structure. Only fourfirms (corresponding to 4 per cent) present a matrix structure. As for the average age ofemployees, it is comprised among 35- and 39-years old. With regard to innovation, 50firms (corresponding to 51 per cent) own a R&D unit, where the main innovationactivities pertain to the acquisition of plants or software/hardware equipment aimed atintroducing product/process innovation, followed by the acquisition of R&D unitsbelonging to other companies and, less important, the acquisition of patents orinnovation not patented.

It is interesting to note that more than half of the firms (56) indicates that they didnot introduce product innovation, while only six firms did not introduce processinnovation; this evidence confirms the prevalence of process innovation on productinnovation in the industry investigated. With regard to process innovations, these arepredominantly incremental innovations, in confirmation of the literature review aboutthis type of innovation.

As far as the regression analysis is concerned, its results are presented in the sequelof the section. The aim of the regression analysis was to measure the impact of eachindependent variable on each dependent variable. Results of the multivariate analysesare presented in Table III.

WithH1we argued that there is a significant positive relationship between firms whointroduce innovation focusing on market- or efficiency related objectives and theinnovation output, while we expect a negative relationship between firms who introducean innovation motivated by financially or normative related objectives. We see anegative relationship between normative (OBJ1) and market related (OBJ2) objectivesand the dependent variables impact of process innovation on total turnoverand incremental process innovation ( p , 0.05 and p , 0.01 for Models 2 and 7,respectively). A strong positive relationship exists between the dependent variableimpact of process innovation on total turnover and efficiency related (OBJ3) objectives( p , 0.01, Model 2). The results of the analysis with Model 8 show negative relationshipbetween normative (OBJ1) and efficiency related (OBJ3) objectives and firms whointroduce radical process innovation ( p , 0.01 and p , 0.05, respectively), and a strongpositive relationship ( p , 0.01) between market related objectives (OBJ2) and the samedependent variable. We do not find any significant relationship with the other models. Insum, H1 is confirmed for a limited number of objectives and for different variables forinnovation output.

With H2 we argued that obstacles to innovation are negatively related to theinnovation output. This hypothesis is confirmed only for two types of obstacles andonly for process innovation. In fact, Table III shows that there are negative strongrelationships ( p , 0.01) only between financially related (OBST1) obstacles andincremental process innovations, and between internal (OBST3) obstacles and radicalprocess innovations ( p , 0.05). For the other models the obstacles variables are notsignificant.

H3 regards the relationship between collaboration and the realised levels ofinnovative output. Model 1 represents the regression with the impact of productinnovations on total turnover. It indicates a positive relationship with collaborationwith universities and research centres (COLL3) ( p , 0.05). For the same, independentvariable is shown a negative relationship ( p , 0.05) with the dependent variableimpact of process innovations on total turnover. The results of the analysis with

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Model 8 show a positive relationship ( p , 0.05) between collaboration withcompetitors (COLL2) and firms who innovate in processes, specifically with firmswho introduce radical process innovations. We do not find any significantrelationships with the other models. As a consequence, this hypothesis is confirmedfor product related innovative output (the impact of product innovations on the totalturnover) and for process related innovative output (Models 2 and 8).

Finally, with H4 we argued there is a significant positive relationship between firmswho use different sources of information and realised innovative output. The only strongpositive relationships resulted from the regression analysis is between Universities(INFO5) and the impact of product innovations on total turnover ( p , 0.05), betweentrade-union (INFO9) and incremental process innovations ( p , 0.05), and betweenliterature and scientific papers (INFO8) and radical process innovations ( p , 0.05).This is quite surprising, as traditionally these sources of information are considered theless important for the development and introduction of innovation. The test for the samehypothesis shows negative relationships ( p , 0.05) between Universities (INFO5) andthe dependent variable impact of process innovations on total turnover (Model 2),past patents and the dependent variable incremental process innovations (Model 7),and finally between the dependent variable radical process innovation andconferences and fairs as source of information (Model 8).

There is no support for the four hypotheses for Models 3, 4, 5 and 6, that is when theinnovation output is measured by means of process innovation new to the market or to

Model 1 Model 2 Model 7 Model 8IMPPROD IMPPROC INCRPROC RADPROC

Variables b t b t b t b t

OBJ1 0.142 1.259 20.226 22.236 * 20.125 21.139 * * 20.157 21.421 * *

OBJ2 20.051 20.388 20.226 21.925 * 20.303 22.374 * * 0.247 1.921 * *

OBJ3 20.013 20.98 0.563 4.633 * * 0.143 1.082 20.088 20.663 *

OBJ4 0.129 1.133 20.066 20.651 0.052 0.468 0.106 20.950OBST1 20.002 20.013 0.094 0.748 20.293 22.408 * * 0.311 3.013OBST2 0.223 1.334 0.077 0.459 0.327 2.028 0.617 4.508OBST3 0.193 21.264 0.005 0.032 20.025 20.169 20.554 24.420 *

OBST4 0.062 0.591 20.055 20.522 20.179 21.754 0.018 0.210COLL1 20.168 20.826 20.033 20.162 20.027 20.132 0.298 1.734COLL2 0.074 0.355 0.355 1.698 20.251 21.227 0.330 1.884 *

COLL3 0.319 1.462 * 20.420 21.915 * 20.380 20.177 20.023 20.126INFO1 0.126 0.753 20.147 20.867 20.098 20.582 0.026 0.159INFO2 20.117 20.846 20.046 20.332 20.162 21.161 * 20.123 20.915INFO3 0.098 0.618 20.050 20.309 20.102 20.639 0.079 0.513INFO5 0.280 1.270 * 20.183 21.321 * 20.029 20.129 20.091 20.425INFO6 20.060 20.442 0.077 0.346 0.011 0.083 20.078 20.587INFO7 20.118 20.376 0.170 0.536 0.264 0.834 20.453 21.485 *

INFO8 0.104 0.438 20.069 20.287 20.315 21.316 0.595 2.577 *

INFO9 0.040 0.244 0.000 20.002 0.291 1.760 * 20.054 20.339

Notes: Significance at the *5 and * * 1 per cent. The modelling strategy used is the method of forcedentry (enter), in which all predictors, selected based on past works, are forced into the modelsimultaneously

Table III.The results of theregression analysis

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the firm, and by means of radical or incremental product innovation. As a consequence,all the models tested and found to be not significant were deleted from Table III.

7. Conclusions and future researchThe study of innovation process in organizations has evolved as a multidisciplinaryendeavour. Research into the managerial and economics aspects of technologicalinnovation has undergone some substantial changes in direction and emphasis sincethe early work of Schumpeter (1934). Over the past years, technological innovation hasbecome increasingly critical for firms as they struggle to achieve and maintaincompetitive advantage, and as a consequence technological innovation managementhas become one of the most attractive and promising areas of study in the field ofmanagement. This fact is confirmed by the increasing number of scholars that haveoriented their research towards this area and, not least, that every year there are newscientific journals specialising in the study of innovation phenomena.

This paper focus on technological/technical innovation, that is on product andprocess innovation. These innovations are often classified into different types,requiring different kinds of underlying knowledge and with different impacts on theindustrys competitors and customers (Schilling, 2005). For successful innovation tooccur, the process of innovation needs to be carefully managed, and to do this, it is ofprimary importance to know which factors influence the innovation activities andoutputs. The purpose of this paper was exactly to understand which factors, amongthose proposed in literature, most influence and explain the innovation output in aspecific context, that is the food machinery industry. In order to reach this purpose, wedeveloped a research model and a questionnaire, and conducted a multivariate analysis(specifically, a regression analysis one). The research model encloses all the variablesthat were first selected from the economic literature as potential influencing factors ofthe innovation output, then validated by a panel of experts by means of interviews.Result from the literature review and interviews was a list of variables included in thequestionnaire, that is the motivation that prompt firms to innovate, the obstacles to theintroduction of an innovation, the main form of collaboration, and the sources ofinformation useful in order to develop and introduce an innovation.

The findings in this paper partly support existing findings pertaining to successfactors for innovation, partly contradict existing theories. The different models (one foreach dependent variable used to describe the innovation output), show differentrelationships between the factors and the different variables for innovative output, bysupporting the primary proposition of the study. Firms innovate in process in order toenhance their market share, to improve product quality and to improve their productassortments. This results from the fact that market and efficiency related objectives arestrongly related with process related innovative output variables, and confirms earlierfindings (Montoya-Weiss and Calantone, 1994) that market-orientation is crucial forthe innovation process. Firms that innovate in order to meet legislative requirementsperform worst in term of process innovative output, as confirmed by the strongnegative relationship resulted from the analysis. Moreover, the same objectives werenot consistently significant predictors of product innovation success. In this paper, wehave analysed also the nature and the degree of obstacles to innovative activity. Ouranalysis led us to conclude that the constraints faced by innovative firms are importantand have a major negative impact on innovative activity. Financial constraints and

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internal obstacles turned out to be the major factors hampering firms that innovate inprocess. Our empirical results are in line with the conclusions of numerous studiesabout the important beneficial effects of the absence of barriers to innovation. We canconclude that in order to innovate a firm must have the right organisational conditions,such as sufficient qualified personnel, sufficient knowledge, and a flexible organisationstructure, but it must also have the right financial conditions, that is financial resourcesand costs for innovation not too high. Without these right conditions, innovationhardly can take place. With regard to the role of collaboration for innovation, thefindings show that firms introducing innovations are cooperating more often withuniversities and research organizations, and with competitors. Given the potentialadvantages of collaboration advocated by various scholars, in the industry and inthe area taken into consideration the network with customers and suppliers seems tobe under-utilised for innovation purposes. At the same way, the network cannot beconsidered as an important source of information for innovation. As for the sources ofinformation, once again universities and scientific literature are important sources,together with trade association. We could not find a significant relation betweeninnovative output and customers and/or suppliers as source of information. This isremarkable, as earlier research found contrary results (Claro et al., 2004). These resultsare quite surprising. First, in fact, generally it is not recognised as an important role foruniversities and research centres as form of collaboration or as source of information.Second, the fact that actors from the network are not considered as collaboration orsources of information is remarkable, given the theoretical arguments in favour ofcollaboration with suppliers and customers (Boon, 2001).

To date, this is the first quantitative research that focused on the factors explaininginnovative output of Italian food machinery firms. By using multiple indicators forinnovativeness, this study contributes to a broader understanding of the factors thatdetermine the innovative output. As such, we found differences in the factorsexplaining product innovation and process innovation. The research entails someweaknesses as well. In fact, while this quantitative study has established a clearpicture of relationships between the innovation output and its determinants, somecaution must be exercised when interpreting these findings due to a number of limitingfactors. First, the use of a relatively underdeveloped instrument measuring thedeterminants of innovation output and the relatively small sample size. Our resultsshow that several variables included in the questionnaire are not significant, that isthey do not impact on the innovation output of firms. Second, a quantitative study isnot suitable at well explaining the reasons behind these relationships. Thus, futurequalitative research needs to be considered. Moreover, the study provides a static view,while future research should be extended and supported by a number of case orlongitudinal studies showing the connection among the variables considered. It wouldalso be interesting to extend the analysis to other Italian or European areas, and carryout comparative studies to identify innovation patterns that are either region-specificor generalisable, or to extend the study to near industries, such as the food one, that isstrictly connected with the industry investigated.

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About the authorsBarbara Bigliardi graduated (with distinction) in 2004 in Industrial Engineering andManagement at the University of Parma and holds a PhD in Industrial Engineering from thesame university in 2008. Since 2005, she has been a researcher at the Department of IndustrialEngineering of the same university. Her research activities mainly concern innovationmanagement, human resources management and technology transfer. Her research has beenpublished in international journals, such as the European Journal of Innovation Management,Technovation and The Leadership & Organization Development Journal.

Alberto Ivo Dormio graduated in Mechanical Engineering at the Politecnico of Bari. He holdsa Master in Management of Innovation and a PhD in Management Engineering. Since 2006, he isan Associate Professor at the University of Parma. His research activities mainly concerninnovation management, project management and technology transfer. His research has beenpublished in international journals, such as the European Journal of Innovation Management,Technovation and The Leadership & Organization Development Journal.

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4. Paul Kruse, Peter Geiler. 2014. Benefiting from External Knowledge in Open Innovation Processes.International Journal of Knowledge and Systems Science 3:10.4018/IJKSS.20121001, 16-27. [CrossRef]

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