THE MEDIATING EFFECT OF COGNITIVE SOCIAL CAPITAL ON          KNOWLEDGE ACQUISITION IN CLUSTERED FIRMS                 Glor...
theoretical framework and the derived hypotheses. We then describe the researchmethod and findings. Finally, we outline it...
In our view, and this is the possible contribution of the paper, the cognitive dimensionof social capital offers a congrue...
industrial district (Marshall 1925) identified a number of external economies derivingfrom the pool of common factors that...
2.2. The social capital perspective: the cognitive dimensionThe social capital perspective considers the economic action e...
to act with others, exchange of ideas and resources is fostered (Inkpen and Tsang 2005).On the other hand, common culture ...
actions from the attendance of conferences, courses, workshops, benchmarking withother organizations, interaction with oth...
exchange of ideas (Decarolis and Deeds 1999) and is an element that facilitatesknowledge flows and technological exchange ...
spatial (Martin 1994), since relations, particularly those which are informal in nature,frequently evolve close to home (M...
3.3. Cognitive social capital and knowledge acquisitionAlthough previous research is limited on this specific point, some ...
H3:    COGNITIVE            SOCIAL    CAPITAL        DEVELOPMENT             WILL      BEPOSITIVELY ASSOCIATED WITH KNOWLE...
Figure 1. Model of the determinants of knowledge acquisition in districts                               District          ...
population of 1,403 firms3. A questionnaire was distributed among these firms, of whicha final total of 224 valid complete...
Dependent variableKnowledge acquisition. From precedents in the literature, we included the Kale, Singhand Pelmutter (2000...
is similar to Cronbach’s alpha. As we can observe in Table 1, all constructs exceededthe accepted value of 0.8. For instan...
significant effect on cognitive social capital ( =0.218; p<0.001). These findings supporthypotheses 1 and 2.              ...
In hypothesis 4 we proposed an indirect effect of industrial district on knowledgeacquisition through cognitive social cap...
of district membership on knowledge acquisition through the development of cognitivesocial capital. Moreover, the mediator...
perspective in particular provides a solid base from which to explain heterogeneityamong firm members in industrial distri...
terms of maturity of the industry and social context permit, with obvious caution,conclusions to be generalized.As a final...
Becattini, G. 2005. La oruga y la mariposa. Un caso ejemplar de desarrollo en la Italia de los distritos industriales: Pra...
Dyer, J., and H. Singh. 1998. The relational view: cooperative strategy and sources of interorganizational competitive adv...
Keeble, D., C. Lawson, B. Moore, and F. Wilkinson. 1999. Collective learning processes, networking and institutional thick...
Nelson, R., and S. Winter 1982. An evolutionary theory of economic change. Cambridge: Belknap.Nonaka, I. 1994. A dynamic t...
Yli-Renko, H., E. Autio, E., and H. Sapienza 2001. Social capital, knowledge acquisition, and knowledge exploitation in yo...
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The Mediating Effect of Cognitive Social Capital...

  1. 1. THE MEDIATING EFFECT OF COGNITIVE SOCIAL CAPITAL ON KNOWLEDGE ACQUISITION IN CLUSTERED FIRMS Gloria Parra Requena (Gloria.Parra@uclm.es) Pedro Manuel García Villaverde (Pedro.GVillaverde@uclm.es) Departamento de Administración de Empresas UNIVERSIDAD DE CASTILLA-LA MANCHA ÁREA TEMÁTICA: Distritos industriales / clusters industrialesRESUMEN: (máximo 300 palabras)Recently relational perspective has fuelled the literature on industrial districts.Geographical and cognitive proximity among similar organizations in bounded contextsfavors the creation of diverse forms of social capital (McEvily and Zaheer 1999).Although proximity generates beneficial dense and cohesive social networks, it has alsobeen argued that this characterization of networks restrains the capacity to detect andaccess new ideas and other knowledge resources.The specific concern of this paper is to analyze the role played by the cognitivedimension of social capital on knowledge acquisition in firms belonging to industrialdistricts. The cognitive dimension refers to the degree to which people andorganizations share goals and culture (Bolino, Turnley and Blodgood 2002). Thiscognitive dimension has received much less attention in the social capital literature, asacknowledged by Bolino et al. (2002). However, in our opinion, it is perhaps the mostappropriate dimension to define the relational characterization of clustered firms. Thiscognitive proximity can be found in the notion of feeling of belonging in districts(Becattini 1979).In our view, the cognitive dimension of social capital offers a congruent explanation offirms’ capacity to acquire knowledge and consequently, to improve innovation in acontext of geographical proximity. Therefore, in contrast to the assumption of direct andfree access to common knowledge in territorial agglomerations (Storper 1992), weargue that knowledge access depends on firms’ capacity to share goals and culture withother members of the district.This research draws on an empirical survey in the Spanish footwear industry, based on asample of 224 companies. The paper is structured as follows. First, we explain the 1
  2. 2. theoretical framework and the derived hypotheses. We then describe the researchmethod and findings. Finally, we outline its possible contribution and implications.PALABRAS CLAVE: Industrial district, social capital, cognitive dimension1. INTRODUCTIONRecently, social capital has been considered as an explanatory factor of firms’ behaviorand performance (Adler and Kwon 2002). Previous research, although from verydifferent perspectives, shares some common propositions. Specifically, it has beenargued that dimensions of social capital, that is, how and with whom organizations areconnected, have a significant effect on value creation (Nahapiet and Ghoshal 1998).On the other hand, the relational perspective has fuelled the literature on territorialagglomerations of firms, those referring to concepts of the industrial cluster or district.Geographical and cognitive proximity among similar organizations in bounded contextsfavors the creation of diverse forms of social capital (McEvily and Zaheer 1999).Drawing on these two perspectives, social capital could be expected to explain, to agreat extent, the value creation of clustered firms. However, this has been acontroversial argument in the previous literature. Although proximity generatesbeneficial dense and cohesive social networks, it has also been argued that thischaracterization of networks restrains the capacity to detect and access new ideas andother knowledge resources. Among others, Grabher (1993), Uzzi (1997), Gargiulo andBenassi (2000) have suggested that the same ties that serve as a filter of information andknowledge resources may generate lock-ins, isolating organizations from the externalworld.The specific concern of this paper is to analyze the role played by the cognitivedimension of social capital on knowledge acquisition in firms belonging to industrialdistricts. The cognitive dimension refers to the degree to which people andorganizations share goals and culture (Bolino, Turnley and Blodgood 2002). Thiscognitive dimension has received much less attention in the social capital literature, asacknowledged by Bolino et al. (2002). However, in our opinion, it is perhaps the mostappropriate dimension to define the relational characterization of clustered firms. Thiscognitive proximity can be found in the notion of feeling of belonging in districts(Becattini 1979). 2
  3. 3. In our view, and this is the possible contribution of the paper, the cognitive dimensionof social capital offers a congruent explanation of firms’ capacity to acquire knowledgeand consequently, to improve innovation in a context of geographical proximity.Therefore, in contrast to the assumption of direct and free access to common knowledgein territorial agglomerations (Storper 1992), we argue that knowledge access depends onfirms’ capacity to share goals and culture with other members of the district.This research draws on an empirical survey in the Spanish footwear industry, based on asample of 224 companies. This industry is characterized by the presence of a relevantnumber of districts, making it particularly appropriate for this kind of study.The paper is structured as follows. First, we explain the theoretical framework and thederived hypotheses. We then describe the research method and findings. Finally, weoutline its possible contribution and implications.2. THEORETICAL FRAMEWORK2.1. The concept of the industrial districtThe industrial district has traditionally been defined as a socioeconomic entity which ischaracterized by the active presence of both a community of people and a population offirms in one naturally and historically bounded area (Becattini 1990: 39). An industrialdistrict presupposes the existence of a population of firms that are specialized in one ormore phases of the production process. The district is characterized as a group of firmsthat work together, where the division of labor takes place on an inter-firm rather thanintra-firm basis.Although on the whole, the relations that are developed as a result of geographicalproximity may vary considerably in their details, their underlying logic remainsconstant. Thus, despite having their own specific characteristics, the organizationalprinciples underlying the districts in south-west Germany and north-east Italy arewidely applicable. Similar inter-firm cooperation is often found in economic activitiescarried out on a regional/supranational scale (e.g. Scandinavia) or in local contexts, suchas Silicon Valley in the United States.An initial justification of the benefits of industrial districts for firms comes fromMarshallian or agglomeration economies. The author of the original concept of the 3
  4. 4. industrial district (Marshall 1925) identified a number of external economies derivingfrom the pool of common factors that include qualified human resources, specializedsuppliers and technological spillovers (Krugman 1991). At the same time the notion ofindustrial atmosphere can be translated in the existence of intangible resources based onexperience, knowledge and information that is common to all the firms belonging to thedistrict. In general, authors have argued that firms belonging to districts benefit fromintangible externalities such as mutual knowledge, repeated and long term relationships,or common experience, which build trust and a cooperative attitude (Paniccia 1998).Within the context of our work we understand the notion of the district in the broadsense of the term, as referring to a physical and relational space where externalities aregenerated for firms. Despite the different views expounded, a review of the literatureprovides us with a set of common ideas and postures that are useful for our research andwhich we have set out in the following points:(1) Face-to-face contact and physical proximity between firms facilitates interaction and the transfer of resources and knowledge, which would be difficult to achieve with long-distance relations.(2) The critical value of districts has more to do with social or relational resources than with tangible externalities or physical infrastructures.(3) Of those who participate in districts, the leading players are not only final firms but also suppliers of the different products and intermediate services, as well as a wide range of institutions, such as universities, trade associations, industrial policy agents and other local or regional institutions.Recently, authors have postulated different paths for district transformation. Most haveadvocated opening the district up to external sources and carrying out substantialinternal restructuring (Belussi, Sammarra and Sedita 2008). This new model may affectsome district principles such as internal homogeneity. Firms may vary significantly interms of resources and outputs, leaving aside previous internal homogeneity Boschmaand ter Wall (2007). Giuliani and Bell (2005), Giuliani (2005) and Morrison andRabellotti (2005) have posited the existence of sub-networks inside the districts, withsignificant differences in terms of network structure characterization. In fact, firms havevaried knowledge bases and in consequence they can perform different roles inknowledge networks. 4
  5. 5. 2.2. The social capital perspective: the cognitive dimensionThe social capital perspective considers the economic action embedded in the networkof relationships which firms maintain, including non-business relationships (Oliver1996). Firms import knowledge through social capital, which indeed constitutes avaluable resource for them (Bourdieu and Wacquant 1992). Some authors have arguedthat social networks are a critical part of the learning process where firms find newopportunities and obtain new knowledge, also improving their previously existingknowledge through interacting with others (Tsai 2000).In creating knowledge and building trust, social capital prevents or restrainsopportunism in relationships (Trigilia 2001). Moreover, social capital reducestransaction costs and uncertainty (Dosi 1988). As Yli-Renko, Autio and Sapienza(2001) have argued, the degree to which firms use external networks to acquire andexploit knowledge is regulated by the amount of social capital they possess. Firmsimprove the quality of mutual exchanges of knowledge through their social interactions(Lane and Lubatkin 1998).Some authors have presented and discussed different mechanisms and potentialoutcomes associated with social capital. Analytically, social capital presents threedifferent dimensions (Nahapiet and Ghoshal 1998). First, the structural dimensionconcerns the density or dispersion of the network of ties. On the other hand, the natureof the ties is related to the relational (strength) and cognitive (shared goals and culture)dimensions.As Tsai and Ghoshal (1998) suggest, there are indubitably connections between all threedimensions, particularly between the cognitive dimension and the other two. Sharedgoals and culture and other elements such as shared values or vision as expressions ofcognitive social capital also favor the development of trusting relationships, associatedwith strong ties. On the other hand, the association between structural and cognitivedimensions is based on the premise that social interactions play a critical role in shapinggoals and values among the members of the network.Shared goals represent the degree to which the members of the network share anunderstanding of and perspective on the achievement of the network’s activities andresults. When members of the network share goals and have similar perceptions of how 5
  6. 6. to act with others, exchange of ideas and resources is fostered (Inkpen and Tsang 2005).On the other hand, common culture refers to the degree to which common behavioralnorms control the relationships, that is, the set of institutionalized rules and norms thatgovern behavior in the network (Inkpen and Tsang 2005). In this respect, sharing thesame entrepreneurial culture implies sharing concepts such as objectives, concerns,processes, routines, etc. (Rowley 1997). In consequence, common culture includesmany different aspects such as codes, language, histories, visions or goals. All theseelements permit and improve the understanding between parties involved in therelationship, thereby facilitating knowledge transmission.According to Tsai and Ghoshal (1998), the cognitive dimension is related to the sharedvision among network members and includes collective objectives and aspirations.Members of the network thus have more opportunities for a free exchange of ideas andresources. Moreover, common objectives and interests help to reveal the potential valueof the exchange and combinations of resources. In conclusion, cognitive capital can beviewed as a relational mechanism that helps network members to integrate andexchange resources.2.3. Knowledge acquisitionKnowledge acquisition is understood as the process used by an organization to obtainknowledge. This process takes place through the organization’s external and internalrelationships. The relationships that provide knowledge vary in nature, and include bothformal and informal daily activities, as well as others. Some authors have systematizedthe processes through which organizations acquire knowledge. Huber (1991) and Grant(2000) provide a categorization of the sources of knowledge generation and acquisition,respectively. These are integrated in the present paper: first, the internal creation ofknowledge, obtained through internal R&D, together with the learning that derives frommechanisms such as the inheritance of knowledge possessed by the founders oradditional knowledge that was acquired before the organization was created. Graftedlearning is also included, since organizations improve their knowledge thanks to newmembers’ knowledge that was not available before they joined the firm. Second,experimental learning, based on action, acquired through direct experiences: thislearning includes processes such as organizational experiments, training in work, andsimulations. Third, external knowledge: these processes include a great variety of 6
  7. 7. actions from the attendance of conferences, courses, workshops, benchmarking withother organizations, interaction with other actors or establishing strategic alliances.Searching learning is also included, namely, the information acquired by exploring thefirm’s external environment.External sources of knowledge have been increasingly attracting the attention ofresearchers in recent times. External sources include a broad range of mechanisms suchas external R&D, patent and license acquisition, strategic alliances and othercooperation modalities (see Mowery, Oxley and Silverman 1996; Simonin 1999;Caloghirou, Kastelli and Tsakanikas 2004). External knowledge acquisition becomescrucial for firms since the innovation process requires external knowledge flows toenhance their innovative capacity as some authors have suggested (Dyer and Singh1998; Lane and Lubatkin 1998). In fact, the positive effect of knowledge acquisition oninnovation has already been proved in the literature (e.g., Ahuja and Katila 2001; Yli-Renko et al. 2001; Chen and Huang 2008).3. HYPOTHESES3.1. The industrial district and knowledge acquisitionThe definition of an industrial district suggests that inter-organizational relationships(firms and institutions) and proximity constitute the basic elements of clustered firms.Inter-organizational relationships constitute an external source of knowledge since theyprovide opportunities for acquisition and exploitation of knowledge (Dyer and Singh1998; Lane and Lubatkin 1998). Therefore, these sources of knowledge would appear tobe more relevant in contexts of intense relationships between organizations. Someresearchers have argued and demonstrated that territorial agglomerations of firms permita greater exchange of information and knowledge (e.g. Utterback 1974; Jaffe 1989;Jaffe, Trajtenberg and Henderson 1993). On the other hand, proximity produces andfavors spontaneous, social or non-business interactions between managers andemployees in the industry that also facilitates knowledge dissemination (Lazerson andLorenzoni 1999). In spite of the development of new technologies that improvecommunication between distant actors, tacit or non-codified knowledge is mainlytransmitted between close actors (Uzzi 1996), since intense interactions are required(Dyer and Nobeoka 2000). In conclusion, geographical proximity favors the natural 7
  8. 8. exchange of ideas (Decarolis and Deeds 1999) and is an element that facilitatesknowledge flows and technological exchange between firms (Boschma and ter Wall2007).In the industrial district tradition, the concept of industrial atmosphere refers to theexistence of knowledge shared by all members inside the district. In Marshallian terms,this knowledge is in the air (Marshall 1925). Becattini (2005) defines knowledge insidethe district as mainly contextual, that is, knowledge closely related to the underlyingactivity in which the district is involved. This knowledge gains value within the specificactivity, but on the other hand, it loses value with alternative uses. Furthermore, thisknowledge is difficult to reproduce in other temporal, social and spatial contexts, sinceit is basically tacit in nature and experience based. In fact, as Bellandi (1996) suggests,the district is characterized by gradual learning from experience.Additionally, one of the important elements of the district is the existence of localinstitutions that provide supporting services to the firms in district. These entitiescompile and disseminate knowledge among firms, thereby reducing their search costs(Molina-Morales 2005; McEvily and Zaheer 1999). Specifically, Antonelli (2000)emphasized the role of universities and public research centers, since they can provideinformation on laboratory discoveries, which represent complex and tacit scientificknowledge. In the same vein, technician and employee mobility inside the district offersfurther possibilities to obtain knowledge (DeCarolis and Deeds 1999).To summarize, there are diverse sources of knowledge in the district, due togeographical proximity, and intense relationships between organizations. Both facilitateformal and informal communication, supported by internal mechanisms such asfriendship or family relationships, internal mobility of human resources, a sharededucation from local institutions or spin-off processes, amongst others.From these arguments the following hypothesis can be posited:H1: DISTRICT MEMBERSHIP WILL BE POSITIVELY ASSOCIATED WITHKNOWLEDGE ACQUISITION IN FIRMS.3.2. Industrial district and cognitive social capitalSince social capital refers to the structure and content of relationships, possible effectscan be analyzed at different levels, including individual, organizational, regional ornational levels. Many authors have considered social capital insights as inherently 8
  9. 9. spatial (Martin 1994), since relations, particularly those which are informal in nature,frequently evolve close to home (Malecki 1995). In fact, social capital has been rapidlypropagated in the territorial literature (see Trigilia 2001 or Wolfe 2002; among others).According to Trigilia (2001), a territorial context can be said to be rich in social capital,depending on the degree to which individuals and groups are involved in relationshipnetworks of greater or lesser scope. Previous research has explained how districtsrepresent local configurations made up of many small local enterprises with specializedand complementary competences rich in social capital, characterized by mutual trust,cooperation and entrepreneurial spirit (Dakhli and De Clercq 2004). In fact, trust ismore successfully built up through repeated interactions and personal contacts, such asthose developed under conditions of proximity (Gulati 1995). Various authors havedescribed particular mechanisms in districts that drive the creation of social capital,such as internal human resources, social non-business relationships, spiff-off fromprevious district firms, among others (DeCarolis and Deeds 1999).Specifically proximity and interaction intensity, characteristic of districts, play a keyrole in sharing goals and building common values between network members. In thisway, actors adopt common codes, values and practices through social interactions (Tsaiand Ghoshal 1998). Thus, as a consequence of their frequent relationships, clusteredfirms in districts are more likely to share common cultural elements (Paniccia 1998).Firms especially build a code of communication and common language that uses theseinteractions (Nelson and Winter 1982).In conclusion, districts can be described as groups of firms embedded in a strong localnetwork and sharing a relatively homogenous system of values and ideas (Becattini1990; Barabel, Huault and Meier 2007). In this respect Molina-Morales and Martínez-Fernández (2006) observed greater shared culture and values in firms belonging toindustrial districts as compared to external firms.The above arguments lead us to formulate a positive association between districtmembership and cognitive social capital.H2: DISTRICT MEMBERSHIP WILL BE POSITIVELY ASSOCIATED WITHCOGNITIVE SOCIAL CAPITAL DEVELOPMENT IN FIRMS. 9
  10. 10. 3.3. Cognitive social capital and knowledge acquisitionAlthough previous research is limited on this specific point, some precedents doestablish a positive association between cognitive social capital and firm performance.Krause, Handfield and Tyler (2007) have evidenced that shared values positively affectfirm results. In general, shared goals and objectives among members of a network fostercommon understandings about what an improvement is, and how it should beimplemented, thus leading to better firm performance. In contrast, if they areincongruent, misunderstandings and conflicts are more likely to arise, presenting anobstacle to the exchange of knowledge resources (Inkpen and Tsang 2005; Krause et al.2007).Specifically, the cognitive dimension of social capital may favor knowledge acquisitionin firms. First, it can be argued that in a relational context where actors share a similarculture, the acquisition of tacit knowledge will probably be easier (Storper 1997).Hence, when partners possess the same working culture, knowledge communication,transmission and acquisition become more effective. Compatibility between cultures ofpartners is required to facilitate the understanding of norms and values among parties(Lane, Salk and Lyles 2001; Mowery et al. 1996). In contrast, organizational distancenegatively affects knowledge flows. Cultural conflicts and misunderstanding can limitacquisition of information and learning (Simonin 1999).In the same vein as shared goals, shared expectations affect knowledge acquisition inthe context of intellectual capital creation. When firms have the same perceptions ofhow to act, there are fewer misunderstandings in their communication processes. Thisincreases the opportunities for idea and resource exchange, and for understanding thepotential value of these exchanges (Tsai and Ghoshal 1998). In this way, shared visioncan be considered as a binding mechanism that helps different parts of the network tointegrate knowledge (Inkpen and Tsang 2005).In consequence, we understand that the cognitive dimension not only has a positiveeffect, but it is fundamental to the external knowledge acquisition in firms. Thus, incontexts where the organizations involved attain a better alignment of their goals andculture, they are likely to obtain access to external knowledge. We can express this ideaformally as follows: 10
  11. 11. H3: COGNITIVE SOCIAL CAPITAL DEVELOPMENT WILL BEPOSITIVELY ASSOCIATED WITH KNOWLEDGE ACQUISITION IN FIRMS.3.4. Mediating effect of cognitive social capitalAs pointed out above, in industrial districts knowledge flows with a certain degree offreedom (Brusco 1990). In this vein, some scholars have argued that accessingknowledge is one of main externalities firms derive from belonging to a territorialagglomeration. Additionally, this knowledge is rarely available to firms outside thedistrict (Krugman 1991; Storper 1992).Nevertheless, geographical proximity is not a sufficient condition to enable firms toaccess district knowledge. Firms vary in terms of their ability to understand, and in theirdegree of commitment to the cultural context existing in the district (Storper 1997). Thevision and goals of an individual firm may differ from those of the other firmsbelonging to the district (Inkpen and Tsang 2005). In consequence, firms vary in theircapacity to acquire and learn from the valuable knowledge in district.We consider that cognitive social capital is a basic explanatory factor that linksindustrial district membership and internal district knowledge acquisition. In this way,firms that are able to develop shared representations, interpretations, goals, routines andways of acting are in the best position to take advantage of their membership of anindustrial district. We understand that belonging to an industrial district will have anindirect effect on the firm’s knowledge acquisition through the development ofcognitive social capital.In line with the above arguments, we formulate the following hypothesis:H4 THE DEVELOPMENT OF COGNITIVE SOCIAL CAPITAL MEDIATES INTHE ASSOCIATION BETWEEN A FIRM’S MEMBERSHIP OF A DISTRICTAND ITS KNOWLEDGE ACQUISITION.Figure 1 shows the theoretical model and proposed hypotheses representing therelationship between the analyzed variables. As can be observed, in addition to thehypothesized effects we have introduced size and age as control variables (Yli-Renko etal. 2001). 11
  12. 12. Figure 1. Model of the determinants of knowledge acquisition in districts District Membership H2 H1 Age H4 Cognitive Knowledge Social Capital Acquisition H3 Size4. METHOD AND EMPIRICAL STUDY4.1. SamplingThe empirical study focused on the Spanish footwear industry. This labor intensiveindustry is characterized by the existence of small and micro enterprises (accounting for99% of the total). These firms are concentrated in Spanish regions such as the ValencianCommunity (65.9%), Castilla-La Mancha (9.94%), La Rioja (7.1%) and the BalearicIslands (3.55%), among others. In 2007, the industry produced 108.4 million pairs ofshoes, with a value of 1,905 million euros. Most of the total production is exported(93.7% of total production in 2007). Finally, the Spanish footwear industry is mainlystructured in industrial districts, as mapped by Boix and Galleto (2004, 2006).In our opinion, such a mature and traditional industry is particularly appropriate for ourresearch proposals. First, social capital requires a certain period of time to developcompletely. Second, a highly competitive environment, characteristic of matureindustries, allows us to better analyze aspects related to the accumulation and diffusionof knowledge. In addition, the geographical distribution of firms combines the presenceof industrial districts with a significant number of isolated or non-district firms.We used two databases to establish the population of firms, in particular SABI1 andCamerdata2, which provide descriptive and financial information about Spanish firms.Once we had filtered the initial list of firms from different sources, we determined a1 SABI is a directory of Spanish and Portuguese firms that gathers general information and financial data.In the case of Spain, it compiles information on more than 95% of the firms with total yearly revenuesover 360,000-420,000 € from the 17 Spanish regions.2 The Camerdata database compiles a directory of all Spanish firms from the network of local Chambersof Commerce. 12
  13. 13. population of 1,403 firms3. A questionnaire was distributed among these firms, of whicha final total of 224 valid complete questionnaires were returned, constituting a responserate of 16.97%. This can be considered an acceptable rate in comparison with similarsurveys. The sampling error was 5.96% for a confidence level of 95%, and the leastfavorable situation of p=q=0.5. Furthermore, when we tested for non-response bias, nosignificant differences were observed between respondent and non-respondents onstructural characteristics.4.2. VariablesIndependent variablesDistrict membership: To identify firms belonging to industrial districts, we asked for thelocation of the firm. District membership was established when the firm was located inone of the industrial districts identified by previous research. We therefore incorporateda dummy variable to distinguish between district member and non-member firms,similarly to other previous studies (Hundley and Jacobson 1998; Molina-Morales andMartínez-Fernández 2004; among others)4. In order to reinforce the internal consistencyof the objective measurement of district membership, we included a perceptual variablein the questionnaire to measure feeling of belonging. Following the criterion of Becattini(1979), we used a 7-point Likert scale with only one item to measure this perception(see appendix5).Cognitive social capital: The variable shared goals was measured by a six-item Likertscale. This scale is comprised of those used by Tsai and Ghoshal (1998), Young-Ybarraand Wiersema (1999) and Yli-Renko et al. (2001). We adapted the scales to theparticular characteristics of our study. We used the Simonin (1999) scale to measureshared culture and a second order construct to measure cognitive social capital. Thisconstruct is formed by two first order constructs (shared goals and shared culture).3 We excluded companies with fewer than 6 employees. This criterion was suggested by other studiesbecause a minimal operative structure is required to define their behavior and performance (Spanos andLioukas 2001). A similar criterion is also used in other industrial district studies, such as Boschma and terWall (2007).4 We considered all firms that were members of any district to be in the same category when testing ourhypotheses. Thus, in order to test for bias, we analyzed mean differences of the variables of the studybetween firms belonging to each of the industrial districts. We ran an ANOVA and a Scheffe’s testbetween pairs of groups and found no significant differences for variables.5 After running an ANOVA on the feeling of belonging variable for firms both internal and external to theindustrial districts, we observed the existence of a significant difference (p<0.001) between the twogroups. This feeling of belonging is greater for firms belonging to industrial districts. These resultsreinforce the nomological validity of the objective criterion used to measure belonging to a district. 13
  14. 14. Dependent variableKnowledge acquisition. From precedents in the literature, we included the Kale, Singhand Pelmutter (2000) and Maula, Autio and Murray (2003) scales. Since these scaleswere used in the fields of strategic alliances and customer relationships, we adaptedthem to our specific context. Thus, this construct allows us to measure knowledgeacquisition of one organization derived from the relationships with different agents.Control variables. This study included two variables to control their effects onknowledge acquisition. Previous studies strongly support the use of these variables (e.g.Yli-Renko et al. 2001). Some studies suggest that a firm’s age can affect its ability toacquire knowledge (e.g. Lane and Lubatkin 1998; Zahra, Ireland and Hitt 2000), asolder firms can gain advantages from their experience of knowledge acquisition (Autio,Sapienza and Almeida 2000). Firm size can also affect knowledge acquisition (Autio etal. 2000), since larger firms have more resources to spend on relationships (Yli-Renkoet al. 2001). Size was measured by number of employees and age was measured by thenumber of years from the foundation of the company to the survey date (2008).4.3. Analysis techniquesStructural equations analysis was used since it has some advantages over traditionalmultivariate techniques (Haenlein and Kaplan 2004). Specifically, we used partial leastsquares (PLS) with PLS-Graph software to analyze data. PLS is particularly suitable fordata analysis during the early stage of theory development where the theoretical modeland its measures are not well or definitely formed. The level of statistical significance ofthe coefficients of both the measurement and the structural models was determinedthrough a bootstrap re-sampling procedure (500 sub-samples).5. RESULTS5.1. Measurement modelTo evaluate item reliability, we controlled the value of the loadings ( ). All loadingvalues exceeded the recommended threshold of 0.7 (Carmines and Zeller 1979).Construct reliability was assessed using the composite statistic of reliability ( c), which 14
  15. 15. is similar to Cronbach’s alpha. As we can observe in Table 1, all constructs exceededthe accepted value of 0.8. For instance, Nunnally (1978) suggested that values above 0.8can be considered as strict reliability. To assess the convergent validity we used averagevariance extracted (AVE). All constructs exceeded the recommended threshold of 0.5(Fornell and Larcker 1981). Table 1. Reliability Construct Composite reliability AVE Cognitive social capital 0.919 0.851 Knowledge acquisition 0.954 0.774Finally, in order to control discriminant validity (Barclay, Higgins and Thompson 1995)the mean extracted variance should be used (Fornell and Larcker 1981). We comparedthe square root of the AVE (the diagonal in Table 2) with the correlations betweenconstructs (the off-diagonal elements in Table 2). We can observe that the square root ofAVE for both constructs is greater than the correlation between constructs, suggestingthat each construct relates more strongly to its own measures than others. Table 2. Discriminant validity and correlations Construct Cognitive S.C. Knowledge acq. Cognitive S.C. 0.923 0.554 Knowledge acq. 0.554 0.8805.2. Structural modelWe evaluated the structural model by examining the size and significance of the pathcoefficients and the R2 values of the dependent variable. Figure 2 shows the results ofthe model analysis and the explained variance. The results allow us to corroborate allthe research hypotheses.Table 3 shows that district membership has a positive and significant effect onknowledge acquisition ( =0.172; p<0.05). District membership also has a positive and 15
  16. 16. significant effect on cognitive social capital ( =0.218; p<0.001). These findings supporthypotheses 1 and 2. Table 3. Direct effects of industrial district N= 224; **p<0,05; ***p<0,01; ****p<0,001 Construct Knowledge Cognitive social acquisition capital Path T Path T Industrial district 0.172 2.264** 0.218 3.677****Hypothesis 3 proposed a positive effect of cognitive social capital on knowledgeacquisition. The results presented in Table 4 allow us to confirm this hypothesis( =0.558; p<0.001). Table 4. Effect of cognitive social capital on knowledge acquisition N= 224; **p<0,05; ***p<0,01; ****p<0,001 Construct Knowledge acquisition Path T R2 Cognitive social capital 0.558 9.105**** 0.316 Figure 2. Model of the results of the determinants of knowledge acquisition in districts District membership **** ns 0.218 0.044 ns Age 0.084 Cognitive Knowledge Social Capital Acquisition **** 0.549 ns Size 0.050 R2= 0.317 16
  17. 17. In hypothesis 4 we proposed an indirect effect of industrial district on knowledgeacquisition through cognitive social capital. To confirm this hypothesis the fourconditions established by Baron and Kenny (1986) must be met. For this mediatoreffect, the first condition is satisfied since the independent variable (districtmembership) has a positive and significant influence on the dependent variable(knowledge acquisition). The second condition establishes a positive relationshipbetween the independent variable and the mediator variable, that is, cognitive socialcapital. This condition is satisfied through the corroboration of hypothesis 2. The thirdcondition requires a relationship between the mediator variable –cognitive socialcapital- and the dependent variable –knowledge acquisition-. This condition is satisfiedby the confirmation of hypothesis 3. The fourth condition establishes that therelationship between the independent variable and the dependent variable should beeliminated —or at least reduced— when the mediator variable is included in the model.When we introduced these three variables into the model, the effect of industrial districton knowledge acquisition disappeared (from 0.172 to 0.044 and is not significant).That means that cognitive social capital wholly mediates the relationship betweenindustrial districts and knowledge acquisition. Therefore, we can accept hypothesis 4since we see that the industrial district has an indirect effect on knowledge acquisitionthrough cognitive social capital. This effect has a value of 0.1206.The model shows a high consistency, since the value is over the 0.1 established by Falkand Miller (1992). Thus, the model allows us to explain 31.7% of the total variance ofthe dependent variable, in our case firms’ external knowledge acquisition.6. DISCUSSION AND CONCLUSIONSThis paper analyzes how the cognitive dimension affects knowledge acquisition byclustered firms. Firstly, findings show how firms belonging to an industrial districtacquire a significant amount of knowledge from contacts inside the district. In fact,there is a positive and significant association between district membership and cognitivesocial capital and also with knowledge acquisition. However, when we introduced allthe factors into an integrated structural model, we observed a significant indirect effect6 This value is computed by multiplying the significant structural paths. 17
  18. 18. of district membership on knowledge acquisition through the development of cognitivesocial capital. Moreover, the mediator effect of the cognitive dimension is particularlystrong. In fact, the significant association between membership and knowledgeacquisition now disappears under the effect of the cognitive variable.Specifically, this paper has focused on the cognitive dimension of social capital, rarelystudied, yet indubitably related to the other two structural and relational dimensions(Tsai and Ghoshal 1998). This dimension is particularly relevant to explain theconnection between location inside the district and valuable knowledge acquisitionthrough external contacts7. Therefore, our findings underline the decisive role played byshared goals, values and culture in the capacities and knowledge acquisition process inthe context of the industrial district.The main contribution of this research is the way it identifies and proves that thecognitive dimension of social capital explains why firms take advantage of the commonknowledge generated in contexts of territorial proximity. It has been suggested thatcontexts like industrial districts are appropriate for efficient knowledge acquisition;however, this acquisition only occurs when firms are immersed in a common culturalcontext, sharing visions and goals with other firms in the local neighborhood. In factindividual firms vary in their access to knowledge and market power (Boschma andLambooy 2002). These findings support previous research suggesting that the degree towhich firms use external networks to acquire and exploit knowledge is conditioned bythe amount of social capital they possess (Yli-Renko et al. 2001). Our proposal providestheoretical linkages between key concepts of three different theoreticalconceptualizations, namely the industrial district (Marshall 1925; Becattini 1979), socialcapital (Putman 1993; Nahapiet and Ghoshal 1998) and the knowledge-based view(Nonaka 1994; Grant 1996).Our findings also at least partially contradict some of the industrial district literature thatfocuses exclusively on the district-level or systemic advantages (Signorini 1994),without considering the relevancy of the individual firm. In contrast, our findings are inline with recent research emphasizing internal heterogeneity inside the district (Giuliani2002; Giuliani and Bell 2005; Morrison and Rabellotti 2005). The social capital7 We undertook exploratory tests on the indirect effect of the two other dimensions, with the result thatthe structural and relational dimensions have a minor significance. 18
  19. 19. perspective in particular provides a solid base from which to explain heterogeneityamong firm members in industrial districts in order to access common knowledge andcapacities.Moreover, this research supports the conceptualization and delimitation of the industrialdistrict. Following Becattini (1990), we have used both objective elements to identifythe district and perceptual elements such as the feeling of belonging. In addition, byconsidering the whole Spanish footwear industry we reduce risks in the generalizationof findings. This study therefore overcomes some of the traditional limitations ofempirical studies in the district field, such as potential specific case bias.These research findings support the competitiveness of firms in mature industries suchas the footwear industry, since they can still offer potential knowledge and specificabilities for member firms. However, a firm’s membership of a district is not sufficienton its own to ensure advantages are harnessed. Firms must engage in actions anddevelop specific strategies to exploit the opportunities districts offer. Particularly, firmsshould address their efforts to building common norms, values and cultural elementswith their contacts to efficiently acquire relevant knowledge. In this vein, firms mustpromote cooperative relationships and favor understandings with others in order tofacilitate knowledge transmission.On the other hand, local institutions involved in districts, such as universities,technological institutes, policy agencies, trade associations and others, must coordinatetheir actions to encourage flows of valuable and non-redundant knowledge betweenfirms. These actions may be complemented with institutional efforts to boost collectiverepresentation as well as common goals and vision (Keeble, Lawson, Moore andWilkinson 1999), in order to strengthen shared norms and values in the district. In thisway, the promotion of commercial and technological projects that bring together effortsand interests between firms will foster the climate of trust necessary to integrate andexchange abilities and knowledge.One of the limitations of our cross-section analysis refers to its static nature. However,longitudinal studies could be much more demanding because of the data andinformation required for a study like this one. Moreover, in spite of our efforts to assurerobustness in the validation of data and constructs, potential bias cannot be dismissed.Finally, the study focuses on the footwear industry in Spain, specificities that canrestrain possible generalization of the findings. However, similarities with other cases in 19
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