The Role of Personal Relationships in SME Networks

The Role of Personal Relationships in SME Networks Federica Ceci, Daniela Iubatti Università G. d Annunzio Chieti - Pescara (Italy) 1 Introduction The literature focusing on networks has devoted closer attention to the analysis of the impact of relationships on the generation and the diffusion of innovations inside networks (Granovetter, 1985; Gulati, 1998; Lorenzoni & Lipparini, 1999; Kogut, 2000; Padgett & Powell, 2003; Giuliani, 2007). Padgett and Powell (2003) hold that the dynamics of economic activities are largely influenced by the multidimensional characteristics of networks. In the present study, we explore the ways by which innovations are diffused within a network of firms. Despite significant attention devoted so far to the issue of innovation diffusion, we still know very little about how the different domains support the diverse innovation activities. The research questions that we address in the present work are the following: (1) How do the different types of relationships existing in a network of SMEs favour the development of economic activities? (2) Do personal relationships play a role in supporting innovative activities? Answers to these research questions are provided by means of an empirical analysis of data from a consortium of SMEs operating in Abruzzo (Italy) in the automotive industry. This context represents a unique setting in which we analyse the role that personal and professional relationships play in promoting the diffusion of innovations. Data collected are analyzed using the content analysis method (Berelson, 1952). 2 Literature review and model development 2.1 Networks and the diffusion of innovation Recently, networks have been hailed as a third organizational form combining the advantages of traditional governance mechanisms (Kogut, 2000; Powell, 1990). A network, defined by Powell and Smith-Doerr (1994, p. 3) as a set of nodes linked by a set of relations, such as friendship, kinship, political, etc., seems to be able to rapidly evolve and adapt to changing environments, due to the flexibility provided by the smaller organizational units existing within a network (Dosi, 1988; Cooke, 1998; Cooke & Wills, 1999). Scholars have largely devoted their attention on the topic to increase networks understanding, starting from studying factors that enable networks creation (Gulati, 1998), their inner characteristics (Granovetter, 1983; Granovetter, 1985; Powell & Smith-Doerr, 1994), and the distinctive features that determine networks unique ways of knowledge sharing and transfer (Knoke, 1990; Edquist, 2000; Kogut, 2000). 2.2 Personal relationships in networks Padgett and Powell (2003) demonstrated that networks are composed by multidimensional links that emphasize contribute in different ways to networks social and economic development, to knowledge sharing, to the development of new links among actors and to the generation of new sub-networks. An important contribution to our understanding of the role of personal relationships in economic systems comes from Granovetter (1985), who argue that there is a widespread preference for transacting with individuals of known reputation (pp. 490). This behavior leads to the concept of embeddedness, that refers to that process by which social relations shape economic action (Uzzi, 1996, p. 674). Activities based on close relationships are facilitated through the development of a sort of business friendship, which can motivate firms to exceed their formal contracts when doing business together (Granovetter, 1985; Larson, 1992; Uzzi, 1997; Gulati, 1998). 1

2.3 Analytical model development Following Lincoln (1990), we identified a classification of different types of relationships: personal and professional. Personal relationships are defined as those that produce relations of trust, obligation, and custom (Lincoln, 1990, p. 281) among formally independent nodes, while professional relationships are identified in terms of the various connections that bring people together to make a business, pursuing economic goals. In our model, we categorized personal relationships as: (i) familiar, (ii) friendship, (iii) geographical, (iv) political, and (v) other trust-based relationships. Family and friendships are characterized by the existence of pre-developed and close ties among individuals that operate in network s firms (Powell, 1990; Padgett and Powell, 2003; Cross & Borgatti, 2000). Geographical relationships has been included in this category because. Since we defined personal relationships according to the existence of trust and obligation, the reciprocal closeness of network s members, working in the same geographical area, allows the development of personal ties (Rallet & Torre, 1999). As regard to political relationships, the presence of stable links with the local public authorities constitutes an important framework for any activity, facilitating the generation of knowledge flows within networks (Johnson & Edquist, 1997; Gulati, 1998). Professional relationships rely on specific business-related knowledge exchanges (Lincoln, 1990). Many authors focused on the management of business activities through what they called business relationships (Achrol et al, 1983; Baker, 1990; Holm et al., 1999), defining them as relationships where two partners coordinate a number of exchange and production activities (Holm et al. 1999, pp. 469) to increase the joint economic performance of the involved firms (Barney, 1996). Professional interactions among firms generate interdependent capabilities and routines with regard to production, logistics, quality and so forth (Cunningham and Homse, 1986), and the coordination and the allocation of resources for improving the joint productivity (Johnston and Lawrence, 1988; Anderson et al., 1994) and knowledge sharing ( Powell, 1990; Larson, 1992; Ferlie et al., 2005). The professional relationships presented in our model are classified as: (i) association-related, such as relationships with other member of any industrial associations, (ii) relationships with clients, (iii) relationships with competitors and (iv) relationships with suppliers. In our model, the considered activities are distinguished in three types namely: (i) innovative, (ii) strategic and (iii) operational activities. We identified four categories of innovative activities: (i) the use of IT (Information Technologies), (ii) innovations related to the introduction of ITs, (iii) organizational innovations and (iv) product and process innovations. We paid special attention to the use of ITs because the adoption of ITs represents an important issue for small and medium firms and, due to the retard in their adoption, occurring in SMEs, the use of such technologies is considered an important innovative process. The second type of activities relates to the firms strategies. Rumelt (1984; pp. 569) defined strategy formulation as the constant search for ways in which the firm s unique resources can be redeployed in changing circumstances. Firms activities are improved by the belonging to the network, in which reciprocal relationships contribute significantly to their rapid growth and economic success (Walker, 1988; Doz,1987; Hakansson and Johanson, 1988; Larson, 1992). We consider marketing and growth-related activities as strategic ones because of their inner purpose of gaining competitive advantage, through a collaborative action of all the firms in the network (Porter, 1991). Finally, we considered the ongoing activities such as purchases, sales, planning or engineering design and we called them operative activities (Larson, 1992). Although, scholars highlighted the different impacts of personal and professional relationships on economic activities, we still know very little about how personal and professional relationships support the different economic activities. Drawing upon the discussed scholarly contributions and with the aim of filling such theoretical gap, we develop the analytical model reported in figure 1. - Insert figure 1 about here 2

3 Method 3.1 Data collection and questionnaire administration The empirical context of this study is the CISI consortium (Consorzio Italiano Subfornitura Impresa), a consortium of SMEs operating in Abruzzo, Italy. CISI is composed by a 15 SMEs operating in the automotive industry and located in Val di Sangro, an important industrial area specialized in the mechanical sector. CISI comprises the subsidiaries of a major automotive player, Honda Italia, which has a production plant located in the same area. In this study we used a qualitative research approach. Case study methodology is appropriate for explorative analysis because it allows us to identify and understand the different dimensions that characterize a phenomenon (Eisenhardt, 1989; Leonard-Barton, 1992; VanMaanen, 1998; Yin, 2003). Open-ended interviews constitute our principal source of data (Oppenheim, 2000). The interviews in this study are based on a semi-structured questionnaire, divided into three parts. The first section asked for a description of the work flow in the firm and, for each phase, a description of all the firm s personal and professional relationships with third parties and their frequencies. The second part of the questionnaire focused on the role of information technologies (ITs) in business activities. The third part of the survey focused on the characteristics of the external environment. We conducted a total of 25 interviews, 12 with general managers or CEOs and 13 with those responsible for other functions (e.g., sales, purchasing, and IT). All interviews were digitally recorded and transcribed in their entirety. 3.2 The content analysis procedure Content analysis is a research technique for the objective, systematic, and quantitative description of the manifest content of communication (Berelson, 1952, p. 18; Kassarjian, 1977). Advantages of this research method are high levels of objectivity and external validity. We identified the sampling and context units of analysis. The sampling unit is a unit that is distinguished for selective inclusions in an analysis (Krippendoff, 2003; p. 98). In the present research, the sampling units are represented by the firms, since in our research design firms are the units that can assure the independence among observed variables. The context units are the units of textual matter that set the limits on the information to be considered in the description of recording units (Krippendoff, 2003, pp. 101): we selected the sentence as context units. The choice to use the sentence is motivated by a holistic approach to the text because Italian language, the language of the interviews, is rich in synonyms and many words have ambiguous meanings that cannot be understood without reference to the context of the entire sentence. Once the units of the analysis have been defined, we proceeded to develop a list of relationships and activities to operationalize the constructs. First, two researchers independently developed two lists of activities and relationships. After discussing their thoughts and ideas, they elaborated a unique list, working jointly, which formed the basis for textual coding. On the basis of the list of activities and relationships, the researchers elaborated a set of rules that minimized the possibility that the findings would reflect the analysts subjective predispositions (Kassarjian, 1977). These rules are represented by dictionaries, constructed as a list of words that interviewees used to refer to specific concepts (either an activity or a relationship). We extracted a list of the words appearing more than 10 times in the texts, using the software Nvivo7. Finally, a list of 141 words remained. We assigned to each concept (activity or relationship) the relevant words among the 141 identified. Coders, working independently, proceeded to code the relevant sentences using the text search function in the NVivo7 software. 3.3 The statistical analysis 3

The output of the content analysis is the Word-Count matrix that counts the number of words that has been used in the text while referring to a specific concept and it is usually used to compare items and identify patterns. The relationship are considered isolated as well as in their interction effects. 5 Results - Insert table - - Role of clients and key clients in the diffusion of innovation On the basis of the data in the Word Count matrix, we costructed Table 1 that indicate how the relationships enable the three diverse activities: innovative, operational and strategic. The Relationships are ordered in decreasing value according to the degree to which support the specific activity. In the first column, four of the first seven relationships that promote the diffusion of innovation involve clients: Personal*Other Clients (43%); Personal*Clients (30%); Other Clients (30%); Clients (26%). Moreover, the client Honda, has a central role in professional activities and in the diffusion of organizational innovations. The matrix reports 992 words related to organizational innovations and client relationships, and 822 words for organizational innovations and the CISI-Honda relationship. In particular, we refer to of just-in-time practice (JIT), which has been adopted by Honda and diffused among all its contractors. - Strategic activities are enabled mostly by consortium-related associations In Table 1, we notice that the top two places of strategic activities are occupied by relationships association-related: Personal*Associations (78%), and Associations (45%). This is consistent with the nature of associations in general and with the CISI Consortium in particular. Another important insight that arises from the analysis of the data is the central role that is played by one key individual, specifically Pietro Rosica, the president of CISI, who acts as a catalyst for strategic activities. In the list of most frequent words, Pietro and Rosica are present 16 and 13 times, respectively. - Personal relationships positively mediate the role of professional relationships in enabling the innovation and strategic activities Table 1 shows the relationships, reported in increasing order according to their propensity in enabling different activities. Analysing the relations that support innovative activities, we note that the first four position are occupied by personal relationships: friendship (45%); the interaction between personal relationships and clients (43% for the relationships exluding Honda and the 30% for the relationships with alle the clients); the interaction between personal and professional relationships (30%). As we noted before, the relationships with clients are the main enablers of innovative activities. However, the personal aspect of those relationships increases their innovative potential. In the last column we note a similar situation for the strategic activities: in the first seven positions we find five strategic-related relationships: the interaction between personal relationship and associations (78%), Honda (36%), clients (23%) and professional relationships (23%); trust based (42%) and geographic relationships (22%). We further explored this result by performing a nonparametric test, the Wilcoxon Signed Ranks test. Results of the Wilcoxon Signed Ranks test and the statistics for this test are omitted in the short version of the paper. Surprisingly, we found that the test is significant for operational and strategic activities, but not for innovative and strategic activities. We conclude that personal relationships play a central role in enabling strategic activities (p value = 0.05) and, conversely, that operational activities are not enabled by personal relationships (p value = 0.05). The role of personal relationships in enabling innovative activities cannot be determined, since the p value of the test does not allow us to confirm our hypothesis. We 4

believe that this is mainly due to the strong influence of association-related activities, which may affect the results of the test. - Negative correlation between strategic activities and operational/innovative activities Another interesting result is reflected in the output of the correlations between the relationships that enable the three types of activities. A significant negative correlation appear to exist between operational and strategic activities, and between innovative and strategic activities, because the type of relationships required for operational and for innovative activities differs from that necessary for strategic activities. Operational and innovative activities are not correlated, but it seems that strategic activities involve different types of relationships than do the other two activities. 6 Discussion and Conclusion In the present work, our aim has been to contribute to this stream of research by analyzing the role played by personal relationships in enabling the diffusion of innovation. Our work yields important implications for scholars. It enlarges the existing knowledge on innovation diffusion and adoption and on the significant role played by personal relationships and trust within economic contexts. The main contributions of this paper are threefold. Firstly, we find that personal relationships positively mediate the role of professional relationships in enabling innovative activities. Secondly, we proved that personal relationships positively support also the development of strategic activities. Thirdly, we document a negative correlation between strategic activities and operational/innovative activities. Consistent with the conclusions of Granovetter (1985) and Powell (1990), our first finding contributes to the research stream documenting the importance of personal relationships in economic contexts. Our empirical evidence shows that: if personal relationships exist alongside professional ones, the likelihood that these relationships enable innovative activities increases. The uncertainty that characterizes the innovation process is decreased by a firm s increased trust in its partners. Hence, this finding has important implications also for managers and policy makers. Our second finding is that personal relationships play an important role also in enabling the development of strategic activities. This finding, supported also by the statistical analysis, lead to conclusions similar to the previous one: the likelihood of taking strategic decisions increase if the parts involved also share personal relationships. Also in this case, the presence of shared value and trust represent an important and intangibles dimension of economic activities. In contrast, our results show that this dimension is not present in while tha analysed activities are operative. We expect other factor to be important to support operative activities since the different dimensions of personal relations are not relevant. Our third finding demonstrates the existence of a negative correlation between strategic activities and operational/innovative activities. This is an indicator that such activities occur in different settings. The situations, both formal and informal, in which strategies are discussed and executed differ from the situations in which operational and innovative activities take place: the channels of communication, locations, and social environments are distinct. In contrast, innovative activities are likely to take place in the same contexts in which operational activities are performed. This also has important implications for practitioners and policy makers. To increase the likelihood of the adoption of an innovative practice, information about the new practice should also be offered in those settings in which operational activities are performed. In addition, the present work has analyzed the data using an innovative research approach, namely content analysis. The use of this technique allows us to overcome some of the limitations of case study methodology: in content analysis, researchers follow strict guidelines that limit arbitrary judgments and personal decisions made by researchers in the process of data analysis. To enhance the generalizability of the results, a replication of the case study with the use of the same methodology is suggested. Such a 5

replication would allow researchers to determine whether the results of the present study are due to specific contingencies of firms operating contexts or rather are generalizable to different contexts. To augment the generalizability of the results, it may also be possible to structure the quantitative data collection (e.g.: by means of a survey) in such as way to capture the characteristics of the phenomenon on a larger basis, in different sectors and geographical contexts. References omissis - Please contact the authors to obtain the full list of references. Figures and tables Fig. 1: Analytical Model Table 1: Words Frequencies in Percentage Divided by Activities Innovative Activities Operational Activities Strategic Activities Friendship 45% Competitive 83% Personal*Consortium 78% Personal*Other Clients 43% Suppliers 75% Associations 45% Personal*Clients 30% Professional Relations 63% Consortium 45% Personal*Professional 30% Clients 62% Trust 42% Other Clients 30% Honda 62% Personal*Honda 36% Personal Relationships 29% Others Clients 60% Personal*Clients 23% Clients 26% Friendship 55% Personal*Professional 23% Geographic 25% Geographic 53% Geographic 22% Professional Relationships 25% Personal Relations 51% Personal Relations 20% Honda 22% Personal*Clients 47% Personal*Other Clients 16% Trust 21% Personal*Professional 47% Honda 16% Personal*Honda 18% Personal*Honda 46% Professional Relationships 12% Competitors 16% Associations 41% Clients 12% Suppliers 16% Consortium 41% Others Clients 10% Associations 13% Personal*Other Clients 41% Suppliers 9% Consortium 13% Trust 37% Competitive 1% Personal*Consortium 0% Personal and Consortium 22% Friendship 0% 6