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This is the accepted version of a paper published in Scandinavian Journal of Management. This paper has been peer-reviewed but does not include the final publisher proof-corrections or journal pagination.
Citation for the original published paper (version of record):
Sanchez-Famoso, V., Pittino, D., Chirico, F., Maseda, A., Iturralde, T. (2019)
Social capital and innovation in family firms: The moderating roles of family control and generational involvement
Scandinavian Journal of Management, 35(3): 101043 https://doi.org/10.1016/j.scaman.2019.02.002
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Social Capital and Innovation in Family Firms.
The Moderating Roles of Family Control and Generational Involvement
Valeriano Sanchez-Famoso- University of the Basque Country UPV/EHU, Spain Daniel Pittino - Jönköping International Business School, Sweden
Francesco Chirico - Jönköping International Business School, Sweden Amaia Maseda- University of the Basque Country UPV/EHU, Spain Txomin Iturralde- University of the Basque Country UPV/EHU, Spain
Abstract
Drawing on the social capital literature, we examine whether the co-existence of distinct yet interacting social groups, namely family and non-family members, creates the conditions for increased family firm innovation. In particular, we theorize that family and non-family social capital have a joint positive effect on family firm innovation and this joint effect is stronger than the single effects of family and non-family social capital. In addition, we predict that while family control has a positive moderating effect, generational involvement has a negative moderating effect on the above-mentioned relationship. With supportive empirical results, our research makes important contributions to the existing literature.
Highlights
• Both family and non-family social capital affect family firm’s innovation • Family and non-family social capital have a joint effect on innovation
• The joint effect of family and non-family social capital is contingent to family firms’ heterogeneity
Keywords
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Social Capital and Innovation in Family Firms.
The Moderating Roles of Family Control and Generational Involvement
Introduction
Innovation is a fundamental driver of a firm’s long-term survival, profitability, and growth in the global competitive landscape (e.g. Garud, Tuertscher, & Van de Ven, 2013; Lohe & Calabro, 2017) and is of crucial importance to family firms, which account for a majority of the companies worldwide (Astrachan & Shanker, 2003;
Claessens, Djankov, & Lang, 2000). Family firms are organizations in which ownership and management are concentrated within a family, with multiple family members striving to maintain intra-organizational family-based relatedness (Arregle, Hitt, Sirmon, & Very, 2007). The paramount role of the family creates a unique
organizational setting to develop strong social relationships (Chirico & Salvato, 2008; Salvato & Melin, 2008, Zahra, Neubaum, & Larrañeta, 2007). Social capital (SC), defined as the bundle of resources made available through reciprocal and trusting relationships within a group (Adler & Kwon, 2002; Coleman, 1990; Drakopoulou & Anderson, 2013; Hitt, Lee, & Yucel, 2002), is an important source of innovation as it encourages the creation and integration of knowledge (e.g. Cuevas-Rodriguez, Cabello-Medina, & Carmona-Lavado, 2014; Lee, Wong, & Chong, 2005; Moran, 2005;
Nahapiet & Ghoshal, 1998; Subramaniam & Youndt, 2005; Wu, Lin, & Hsu, 2007). Since a family is the social group of reference in family firms, it has been argued that internal SC from relationships among family members involved in a company (i.e., family SC) plays a predominant role in shaping decision-making processes and a firm’s managerial practices (e.g. Arregle et al., 2007). On the other hand, social connections among non-family members lead to the formation of non-family SC (e.g. Mitchell, Morse, & Sharma, 2003; Sieger, Bernhard, & Frey, 2011). Both family and non-family
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SC can positively affect family business outcomes (e.g. De Massis, Kotlar, & Frattini, 2013; Habbershon, Williams, & MacMillan, 2003; Pearson, Carr, & Shaw, 2008; Sanchez-Famoso, Akher, Iturralde, Chirico, & Maseda, 2015, Sanchez-Famoso, Iturralde, & Maseda, 2015; Wang, Poutziouris, & Graves, 2015), and in particular, innovation (e.g. De Clerq & Belausteguigoitia, 2015; Sanchez-Famoso, Maseda, & Iturralde, 2014, 2017). In terms of family SC, family members’ ability to work harmoniously and exchange knowledge within a cohesive network can lead to
innovative outcomes (Chirico & Salvato, 2016). As for non-family SC, a strongly tied group of non-family employees can provide professional skills not available in the family pool and secure access to a more heterogeneous set of resources that may encourage family firm innovation (Adler & Kwon, 2002; Bubolz 2001; Chua, Chrisman, Steier, & Rau, 2012; Granovetter, 1973, 1985).
While there is increasing evidence on the positive effects that family and non-family SC separately exert on innovation (e.g. Sanchez-Famoso et al., 2014; Wang et al., 2015), there remains limited understanding of their joint effects on innovation. The issue is important as organizational processes often result from interplays among confronting social groups, each with their own goals and priorities (Cyert & March, 1963). In family firms, this phenomenon is especially relevant as family and non-family members may exhibit significant differences in their professional backgrounds,
motivations, and performance expectations (Chua, Chrisman, & Bergiel, 2009; Patel & Cooper, 2014). As a result, the influence of internal SC on family firm outcomes cannot be properly understood without considering the joint role of family and non-family social groups (e.g. Arregle et al., 2007).
This research examines this topic while drawing on theoretical insights from the SC literature (Adler & Kwon, 2002; Arregle et al., 2007; Nahapiet & Ghoshal, 1998) and focusing on the joint effects of family and non-family SC on firm innovation and
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whether this joint effect is higher than the individual effects of family and non-family SC. In addition, given that family firm heterogeneity has been depicted as essential to understand family firm strategic decisions and outcomes (Chrisman & Patel, 2012; Gomez-Mejia, Haynes, Nunez-Nickel, Jacobson, & Monayo-Fuentes, 2007; Zellweger, Nason, & Nordqvist, 2012), we explore the moderating roles of different levels of family control and generational involvement in the above-mentioned relationship.
The empirical investigation is conducted on a sample of 172 Spanish family firms. With supporting empirical results, our study makes several contributions. First, we add to the recent developments in the literature on innovation in family firms (e.g. Calabro et al., 2018; Chirico, Criaco, Bau, Naldi, Gomez-Mejia, & Kotlar, 2018; Duran, Kammerlander, Van Essen, & Zellweger, 2016; Rondi, De Massis, & Kotlar, 2018) by offering additional elements to aid in the conceptual understanding of the phenomenon. In particular, in line with the contribution of Rondi et al. (2018), we suggest that the conditions to ‘unlock the innovation potential’ reside not only in the relational
characteristics of the family system, but also in the social interactions with non-family members. Furthermore, we conceptualize the relationship between family and non-family SC as one of the main drivers, at the input level, of the higher innovation output that family firms exhibit in comparison to their non-family counterparts (e.g. De Massis, Di Minin, & Frattini, 2015; Duran et al., 2016; Röd, 2016).
Second, we add to the SC literature, and in particular, studies addressing the intra-organizational dimension of SC, by focusing on different SC types that may co-exist within an organization. Thus far, the literature has mainly focused on internal SC as an undifferentiated construct without considering the possibility that distinct groups within a firm interact with each other (Arregle et al., 2007). On the other hand, we recognize the existence of heterogeneous forms of SC at the firm level and explore how their combination affects organizational outcomes. We also provide evidence of how family
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ownership, family management, and generational involvement affect this relationship. Third, we contribute to the literature on SC in family firms (Arregle et al., 2007; Wang et al., 2015), which so far has predominantly addressed the family side of SC (e.g. Carr, Cole, Kirk-Ring, & Blettner, 2011). Our study explicitly accounts for the combination of the family and non-family dimensions of SC and explores the extent to which this combination leads to advantages or disadvantages at the organizational level. Adopting an SC perspective, we also provide novel insight on the effects of non-family members on family firm outcomes (e.g. Chrisman, Chua, & Litz, 2004; Mitchell et al., 2003). Finally, we contribute to studies on the relationship between SC and innovation. Related research considers SC as a means to produce knowledge and resources that foster
innovation (e.g. Cuevas-Rodriguez et al., 2014; Lee et al., 2005; Moran, 2005; Subramaniam & Youndt, 2005). We take a step further by exploring how factors affecting strategic decision-making influence the translation of SC into firm innovation (e.g. Carnes & Ireland, 2013).
Theory and Hypotheses Innovation and Social Capital
Innovation is an essential process for the survival, success and renewal of
organizations (Brown & Eisenhardt, 1995; Danneels, 2002; Lohe & Calabro, 2017; Lee, Lee, & Pennings, 2001; Subramaniam & Venkatraman, 2001). It reflects a firm’s
propensity to engage in creativity, thereby leading to the development of new products, services or production methods (Lohe & Calabro, 2017; Lumpkin & Dess, 1996; Zahra & Covin, 1995). This definition encompasses the key components of the innovation process (Abernathy & Clark, 1985). The role of innovation in stimulating economic development through creative destruction was first emphasized by Schumpeter (1939). Later, Drucker (1985) suggested that innovation is the primary activity of
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component in a business strategy through which a firm can gain an advantage over its competitors. As such, innovation is considered a primary source of superior returns and competitive advantage (Ahuja, Lampert, & Tandon, 2008; Yeoh & Roth, 1999).
Innovation requires the mobilization of internal and external resources (Lohe & Calabro, 2017; Terziovski, 2010). For example, scholars have proposed that ‘the ultimate source of novelty’ (Fleming, 2001, p. 118) is emanated from a recombination of existing and new conceptual and physical resources (Lohe & Calabro, 2017; Nelson & Winter, 1982). As such, the realization of innovative projects entails the effective management of resources developed and shared through social relationships (David, Hitt, & Gimeno, 2001). Thus, SC plays an important role in promoting innovation. In particular, internal SC has been shown to support the production of inputs that foster the innovative process (e.g. De Clercq, Dimov, & Thongpapanl, 2013; Tsai & Ghoshal, 1998; Yli-Renko, Autio, & Sapienza, 2001) by mobilizing knowledge embedded within, available through, and utilized by interactions among individuals within organizations (Nahapiet & Ghoshal, 1998).
The density of interpersonal ties among people in an organizational setting improves the assimilation and integration of knowledge by facilitating its communication,
sharing, and transfer (Drakopoulou & Anderson, 2013; Nahapiet & Ghoshal, 1998; Subramaniam & Youndt, 2005). Moreover, the quality of relationships supports experimentation and the search for new knowledge (Carmeli & Gittell, 2009;
Edmondson, 1999; Gubings & Dooley, 2013). Good interpersonal relationships help individuals feel psychologically safe and willing to engage in trial and error processes (Carmeli & Azeroual, 2009). These processes stimulate learning and creativity (e.g. De Dreu & West, 2001) and therefore, the development of new knowledge (Edmondson, 1999). SC also allows people to seek advice and expertise to solve problems and
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generate new insight (Carmeli & Azeroual, 2009; Lee, Caza, Edmondson, & Thomke, 2003; Leonard-Barton, 1995).
In family firms, these processes are primarily encouraged by SC at the family level, especially in small to medium family enterprises, but also in larger ones (e.g. Chirico & Salvato, 2016; De Massis, Audretsch, Uhlaner & Kammerlander, 2018). Family SC is enhanced by the strong ties that exist among relatives (Stewart, 2003) and provides a system of connections for mutual advice and communication, which are elements necessary to work towards innovation. Indeed, a climate of trust, friendship, respect, and reciprocity developed through a history of family interactions creates a relational setting that favours collaboration and decreases opportunistic behaviour (e.g. Coleman, 1988; Lohe & Calabro, 2017; Salvato & Melin, 2008; Sorenson & Bierman, 2009) and this, in turn, fosters open interactions and experimentation. In addition, family SC emphasizes common cultural backgrounds and facilitates the development of shared objectives among family members, which allow all parties to understand the potential value of integrating and combining their resources (Chirico & Salvato, 2008, 2016; Kotlar & De Massis, 2013) and develop strategic goals that encourage adaptation, change, and innovation (Salvato & Melin, 2008).
On the other hand, non-family SC is crucial in the assimilation and integration of new knowledge in the organization. In this respect, non-family SC can be seen as a crucial antecedent of a family firm’s absorptive capacity (Cohen & Levinthal, 1990), namely the set of ‘organizational routines and processes by which firms acquire, assimilate, transform, and exploit knowledge to produce a dynamic organizational capability’ (Zahra & George, 2002, p. 186). In fact, the relationships among non-family employees contribute to the development of a more diverse set of capabilities that encourage entrepreneurship and innovation (Lohe & Calabro, 2017; Westlund & Bolton, 2003). This especially occurs when family firms are able to attract and retain
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talented employees (e.g. Pittino, Visintin, Lenger & Sternad, 2016). In such cases, non-family members exhibit professional expertise (Dyer, 1988; Hall & Nordqvist, 2008; Stewart & Hitt, 2012; Westhead & Howorth, 2007) and secure easier access to external networks (e.g. Arregle, Naldi, Nordqvist, & Hitt, 2012; Johanisson & Huse, 2000; Nordqvist, 2012), compared to family members, who are more likely to rely on close and strong-tie networks (e.g. Anderson, Jack, & Drakopoulou-Dodd, 2005). Moreover, cohesion and commitment within a group of non-family employees facilitate the sharing and use of specialized knowledge in a company’s internal operations (e.g. Pearson & Marler, 2010).
In sum, the resources embedded in the two social systems appear to be distinct but complementary in fostering innovation. However, the translation of SC resources in actual family business strategies requires appropriate decisions. The resource-based logic (Barney, 1991; Sirmon, Gove, & Hitt, 2008) suggests that important strategic decisions concerning resource management involve the definition of clear directions (Sirmon, Hitt, Ireland, & Gilbert, 2011) and value-creation alignment of co-specialized assets (Helfat, Finkelstein, Mitchell, Peteraf, Singh, Teece, & Winter, 2007). In family firms, these decisions are crucially influenced by the degrees of family control and generational involvement in the company (Carnes & Ireland, 2013; Chirico, Ireland, & Sirmon, 2011). In the following sections, we first discuss the joint effects of family and non-family SC on family firm innovation and then, develop our arguments on the moderating roles of such effects of family control and generational involvement.
The Joint Effect of Family and Non-Family Social Capital
Family members cannot be expected to develop all relevant knowledge needed to avoid the obsolescence of a firm’s capabilities and cope with dynamic environmental
conditions (Chirico & Salvato, 2008). Thus, acquiring external knowledge and
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perspective, non-family members and their social relationships are important in the acquisition and assimilation of knowledge. Non-family members are more likely to have previous experiences outside the family business and be part of different professional communities (e.g. Vandekerkhof, Steijvers, Hendriks, & Voordeckers, 2015). On the other hand, family SC is fundamental in the process of knowledge transformation and exploitation, namely the capabilities to combine existing and newly assimilated
knowledge and apply it to the firm’s operations and strategies (Zahra & George, 2002). In the present study, we contend that non-family SC reinforces the positive effects of family SC by providing resources that invigorate the knowledge integration process occurring in the family members’ network (Salvato, Chirico, & Sharma, 2010; Stewart, 2003).
At the same time, the cohesion in the family group enhances the effectiveness of non-family SC through a ‘social contagion effect’ (Barsade, 2002; Zahra, Hayton, Neubaum, Dibrell, & Craig, 2008). The mutual attachment among family members and their commitment to the firm can create a similar affective response among non-family employees through the processes of emotional and cognitive influences (Barsade, 2002). The literature indeed suggests that firms’ leaders are the main sources of influence on employee behaviour (e.g. Eisenberger, Karagonlar, Stinglhamber, Neves, Becker, Gonzalez-Morales, & Steiger-Mueller, 2010; Rhoades & Eisenberger, 2002). Thus, in family firms, family members behaving in a committed fashion and exhibiting high levels of intra-group attraction stimulate the emergence of similar dynamics among family managers and employees (e.g. Pearson & Marler, 2010). This strengthens non-family SC and therefore improves its potential contribution to innovation.
Non-family SC also contributes to making the possible limits inherent in family SC with respect to innovation less salient. Sometimes, the very ‘established’ and
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Cruz, & Gomez-Mejia, 2012) and render family SC inadequate in rapidly changing contexts (Acquaah, 2012; König, Kammerlander, & Enders, 2013). Moreover, although individual family managers will offer variations in the SC they bring to the firm, the overlaps between family members’ SC will be greater than that among professional managers. Therefore, the combination of family members’ SC with the SC activated, for example, by professional managers, leads to broadening the range of connections
available to the firm (Sauerwald, Lin, & Peng, 2016), while at the same time preserving the depth of knowledge that resides in family-based ties (e.g. Stadler, Mayer, Hautz, & Matzler, 2018).
The effects of family and non-family SC on innovation is therefore, mutually
reinforcing owing to the presence of complementarities between the two groups’ assets. Using Milgrom and Roberts’ (1994) definition of complementarity, an increase in the marginal returns from one form of SC leads to a rise in the level of the other. Hence, the total value of the combination of the two factors exceeds the value generated by
applying the factors in isolation (Dato-on, Banerjee, & Roy, 2018; Ennen & Richter, 2010; Woodfield, Shepherd, & Woods, 2017). We present this in formal terms as follows:
Hypothesis 1a: Family and non-family SC have a joint positive effect on family firm innovation.
Hypothesis 1b: The joint effect of family and non-family SC on family firm innovation is stronger than their single effects.
The Moderating Role of Family Control
Two crucial forms of family control are family ownership and family management. The former is the percentage of ownership held by the family, while the latter is the percentage of family members in the top management team (TMT) (Mazzola, Sciascia, & Kellermanns, 2013). Higher family ownership leads to a stronger desire by family members towards the continuity of the family business, resulting in the transfer of
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ownership of the family firm to the next generation (Miller, Le Breton-Miller, & Lester, 2010) and the retention of wealth within the family (Gomez-Mejia et al., 2007). This commitment to continuity can help the establishment of a common strategic intent towards the use of the firm’s resources for a long-term competitive advantage. High levels of family ownership favour conditions for effective resource coordination (Chirico et al., 2011; Sirmon et al., 2011), ensuring that assets derived from the
combination of family and non-family SC are employed to sustain innovation and trans-generational wealth creation as a unifying family business goal.
This is further encouraged by family participation in strategic decision making (i.e., family control in management) (Mazzola et al., 2013; Scholes, Mustafa, & Chen, 2016). In particular, family involvement in strategic decision making has been positively associated with the capacity to create new knowledge through a combination of existing resources (Carnes & Ireland, 2013). Owing to the high levels of trust and strong bonds in a TMT dominated by family members, the governance costs of knowledge
combinations are likely to be lower. In particular, both family ownership and management reduce the costs of knowledge governance given the lower need for incentive structures, monitoring actions, and control systems (Drakopoulou &
Anderson, 2013; Sirmon & Hitt, 2003). The translation of knowledge embedded in the SC networks towards innovation strategies is facilitated by the shared language among family members. This common way of thinking, developed through shared experiences and interactions over time, helps the effective translation of family and non-family social outcomes into innovation.
Hypothesis 2: Family control strengthens the positive relationship between the joint effect of family and non-family SC and family firm innovation.
The Moderating Role of Generational Involvement
Generational involvement, that is, the number of family generations simultaneously involved in a company, may enhance the potential for effective identification and
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assessment of innovation opportunities (e.g. Ling & Kellermanns, 2010; Sciascia, Mazzola, & Chirico, 2013; Zahra et al., 2007). However, evidence also suggests that increased generational involvement significantly heightens conflict within family firms (e.g. Chirico et al., 2011; Ling & Kellermanns, 2010). When multiple generations are involved in the business, differences intensify between family members, making it more difficult to develop a shared vision of the use of company assets and resources (Jaffe & Lane, 2004; Miller, Minichilli, & Corbetta, 2013).
In particular, when multigenerational family viewpoints are included in the strategic decision-making process, the likelihood of relational conflicts rises. Relational conflict is particularly detrimental to family business processes as it ‘typically includes tension, animosity, and annoyance’ (Jehn, 1995, p. 258) and persists and surfaces in most aspects of family members’ life, including both family and business environments (Kellermanns & Eddleston, 2004). Therefore, negative emotions arising from relational conflicts are difficult to escape in the context of a family business. In decision-making processes, differences in viewpoints among multigenerational family members are often perceived as personal attacks and it may be increasingly difficult to assess and accept others’ ideas (Kellermanns & Eddleston, 2004).
In addition, relational conflict prevents a more beneficial form of disagreement, namely the task conflict, which allows the refining of goals and strategies by considering options in a more comprehensive manner (Jehn, 1995; Kellermanns & Eddleston, 2004). When family members are emotionally challenged, they tend to sacrifice logical arguments and escalate on their positions (Koppius, Germans, & Vos, 2005), thus limiting the range of alternatives assessed in decision making. Overall, these arguments suggest that the involvement of multiple generations in family firms reduce the effectiveness of the strategic decision-making process necessary to coordinate resources embedded in family and non-family SC towards innovation outputs.
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Hypothesis 3: Increased generational involvement weakens the positive relationship between the joint effect of family and non-family SC and family firm innovation.
Methods Data Collection
Data were collected during 2013 through a telephone survey on a sample of Spanish family firms. To ensure quality, the survey was administered by a professional survey research company. The decision to focus on Spain was based on the following reasons. First, according to a report by a European expert group in the field of family enterprises (European Group of Family Enterprises [GEEF] 2009) the percentage of family
enterprises in Spain is above the average 88%. Second, as indicated by the Spanish Family Enterprise Institute (2015), about 1.1 million of the 1.25 million firms in Spain are family businesses, which is 60% of the aggregate Spanish GVA with an
employment rate of roughly 6.5 million (this figure accounts for the 67% employment in the private sector at the national level). Third, the Spanish society assigns significant importance to family relationships (Steier, 2009). Finally, Spain values family unity and harmony more than countries (Poza, 1995). The last two motivations, in particular, make Spanish family firms an appropriate cultural context to test the SC-related issues.
Company-level information is drawn from the Iberian Balance Sheet Analysis System (SABI)1 managed by Bureau van Dijk. From the SABI database, we selected a
sub-population of firms that satisfy the following criteria: (1) non-publicly listed
companies with 10–500 employees (Barbero, Casillas, & Feldman, 2011) (2) companies with a minimum of five years of reported financial information (3) active companies (e.g. those not undergoing insolvency, liquidation, or zero activities), and (4) companies in which at least 50% plus one of the ownership is held by members of the same family (Molly, Laveren, & Deloof, 2010). The careful analysis of shareholder structures and identity2 helped identify 1,122 firms fulfilling our conditions.
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Once we identified the relevant sub-population, we opted for a survey-based data collection, as additional company-level information for private firms in Spain is not easily accessible, especially for the behavioural dimensions addressed in this study. In December 2012, the CEO of each firms received a letter asking them about their interest in the survey and informing them that in the subsequent 30–60 days, a professional survey research company would contact them for via the phone for an interview. The participation of one family member and one non-family member (both with
management responsibilities) was requested. To increase the rate and reliability of the responses, we ensured strict confidentiality to the company and promised the delivery of a summary of the results. A reminder was sent two weeks after the first wave of letters. Then, in January 2013, the survey research company initiated the interviews. We
adopted a key informant design, targeting the companies’ CEOs and top managers, who, in family firms, tend to be extensions of the individuals in charge (Wiklund &
Shepherd, 2003). As such, the CEO and top managers are likely to be well informed about the firm’s innovation orientation as well as their relationships with employees (Whetten, Felin, & King, 2009). In fact, both CEO and top managers are likely to play a key role in the development of an innovation orientation and have a keen interest in employees' social relationships. What is more, considering that ‘an organization must be viewed as a social actor rather than as a social aggregate’ (Whetten et al., 2009, p. 544), people with managerial responsibilities such as the CEO or TMT are appropriate targets for collecting data at the firm level.
The questionnaire used for the phone interviews was divided into three parts. The first part focuses on general company information and collects data on innovation, the second part investigates family members’ relationships, and the third part addresses the relationship among non-family members. The questions were formulated either as dichotomous or in the form of Likert scales. A pre-test was performed on seven family
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businesses from different industries, wherein face-to-face interviews were conducted with one family and one non-family member in managerial positions. The comments gathered from the respondents were used to refine the questionnaire. The revised questionnaire was then piloted in eight family firms with the same type of respondents for each company. These refinements led to a survey instrument with appropriate levels of reliability (Cronbach’s alpha was 0.73–0.80). The inclusion of multiple respondents in the survey also strengthens the validity of the reported answers (Yan, Wang, & Su, 2006), thus reducing the probability of a common method bias (Podsakoff, Mackenzie, Lee, & Podsadoff, 2003).
Of the 1,122 firms that were initially contacted, 232 participated in the survey. From these, 60 firms were excluded from the final sample: 28 questionnaires contained responses only by a family member and 32 had answers by only the non-family member. The final sample included 172 usable questionnaires with a response rate of 20.70%, which is in line with other similar studies in the Spanish context (Basco, 2014; Cruz & Nordqvist, 2012). A brief analysis of our sample shows that only 14% of the family firms have less than 80% of their ownership in the family’s hands, with the average family ownership at 92.44%. The average proportion of family members in the TMT is 51.30%; however, 26% of the family firms have no family members in the TMT. In terms of firm size, the sample firms have an average of 93 employees. When we consider the generations involved in joint management, the firms are managed by only one generation in 56% of the cases, by two generations in 40% of the cases, and by three or more generations in 4% of the cases. With regard to the firm generation, 37% are in their first generation, 41% in their second generation, 12% are in their third generation, 8% are in their fourth generation, and 2% are in their fifth or older generation.
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Measurement of model variables. A majority of the items were measured on
five-point Likert scales. Given our research aim and previous attempts to assess firm-level processes using individual-level responses (e.g. De Clercq, Dimov, & Thongpapanl, 2010), the questions were formulated to explore behaviours at the business level rather than at the management level (Brass, Galaskiewicz, Greve, & Tsai, 2004; Whetten et al., 2009).
Dependent Variable
The use of objective measures for innovation presents several problems, especially in non-listed firms. In fact, various objective measures are unavailable or difficult to assess in private firms (Sanchez-Famoso et al., 2017). The number of patents, for example, might be biased due to the inability to account for innovations at the informal and not codified level (Acs & Audretsch, 2005) and the variable propensity to register patents (Edwards & Gordon, 1984; Scherer, 1983). Prior studies have also shown that
innovation is a multidimensional concept which is difficult to summarize in a single indicator (e.g. Subramanian & Youndt, 2005). Therefore, we opted to measure innovation using a subjective and self-reported assessment since perceptual measures are particularly recommended in research-involving behaviour (Spector, 1994) and have been extensively used in innovation research. For measuring innovation (α=0.73) we employed a three-scale measure validated by previous studies (García-Morales, Loorens-Montes, & Verdu-Jover, 2008; Jansen, Van den Bosch, & Volberda, 2006; Miller & Friesen, 1983; Uzzi & Lancaster, 2003). Respondents compared their firm’s levels of innovation with those of their main competitors, specifically, we asked about: a) the rate of introduction of new products or services in the organisation; b) The rate of introduction of new production methods or services rendered in the organisation; and c) If the organisation has become much more innovative in the last years.
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Following Tsai and Ghoshal (1998) and the recent research by Chirico and Salvato (2016), we adopted two six-item scales to capture the levels of SC among family and non-family members. On one hand, in the case of family SC (α = 0.80) the family members were asked to indicate the rate of agreement with the followings statements concerning relationships between family members working in the firm: a) maintain relationships outside the company (e.g. dinners and clubs); b) maintain close social relationships outside the company; that is, they collaborate with one another to solve company problems; c) maintain close social relationships because they share
information and rely on each other to conduct business; d) keep their promises and are loyal to the company; e) share the same ambitions, vision, and values; and f) pursue the same objectives and mission. On the other hand, in the case of non-family SC (α = 0.80) the non-family members were asked to indicate the rate of agreement with the same six statements that were asked family members, however in this case concerning
relationships between non-family members working in the firm.
Moderator Variables
Family ownership and family management were operationalized as the percentage of ownership held by the family (e.g. Mazzola et al., 2013) and that of firm managers who are also family members (e.g. Mazzola et al., 2013; Zahra et al., 2007). Generational involvement was measured as a continuous variable using the following question: how many generations are currently involved in the management of the family firm?
Respondents could choose one (1), two (2), three (3), or more than three (4) (Kellermanns & Eddleston, 2006; Zahra, 2005).
We also used as control variables the number of contextual factors that could impact firm innovation: company lifecycle, sector of activity, company age, financial
performance, company size, number of family members active in the company, and the presence of a family CEO - given their potential effects on the dependent variable
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(Chrisman, Chua, Sharma, 2005; Le Breton-Miller & Miller, 2006; Sauerwald et al., 2016). Stage in the lifecycle was self-reported by the respondents following Adizes’ (1979) definitions. This variable is important because it is common for family firms to exhibit higher innovativeness in the early stages of their lifecycle (e.g. Dyer, 1988). The sector of activity was operationalized as a dichotomous variable that took the value of one for manufacturing firms and zero for service firms, following the Spanish industrial classification (National Classification of Economic Activities). Company age was measured as the natural logarithm of the years following the establishment of the company (Zahra et al., 2007). Financial performance was assessed through the natural log of the return on assets (ROA) (Peng & Luo, 2000). Company size was measured using the natural logarithm of the total number of employees in the company. These last three control variables (company age, financial performance, and company size) were lagged at t – 1 (Chen & Hsu, 2009; Chrisman & Patel, 2012). Finally, we have also controlled for the following two variables3: number of family members active in the
company, measured as the natural logarithm of the number of family members working in the company, and family CEO, which was captured as a dummy variable.
Data Analysis
The hypotheses were tested using structural equation modelling (SEM). In particular, we used partial least squares (PLS), a technique that relies on a principal component-based estimation approach (Chin, 1998) and is a variance-component-based technique. When dealing with latent constructs that cannot be directly observed (Astrachan, Patel, & Wanzenried, 2014) and in the presence of moderating variables (Chin, Marcolin, & Newsted, 2003), PLS is preferred to linear modelling as well as to other SEM
covariance-based techniques. Our models were estimated using the SmartPLS software (Version 2.3; Ringle, Wende, & Will, 2005). Estimations were performed following the bootstrapping procedure with 5,000 re-samples (Chin, 1998).
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Yet, before testing our hypotheses, we checked whether common method variance (CMV) might inflate the data (Podsakoff et al., 2003). We followed Lindell and Whitney’s (2001) method, employing a theoretically unrelated construct (marker construct) to adjust the correlations among the principal constructs. To conduct the marker construct test (Podsakoff et al., 2003), we used an empowerment three-item scale adapted from Fuller, Marler, and Hester (2006)4. This construct met the required
criteria (Chin et al., 2003; Lindell and Whitney, 2001), namely, that it is theoretically unrelated to at least one of the other variables. Moreover, it is a multi-item measure (composed of three items) with high reliability (α = 0.878; CR = 0.923; AVE = 0.801). This marker construct assesses the CMV by determining the correlation between the marker construct and the latent variables. If the correlation between any latent variables and the marker variable is greater than 0.30, then the study contains CMV (Tehseen, Ramayah, & Sajilan, 2017). The correlation between all latent variables and the marker variable (empowerment) was less than 0.30, indicating no evidence of CMV in this study5.
Tables 1 and 2 present the main descriptive statistics, pairwise correlations, and reliability information for the constructs6. The composite reliability (CR) for the
measures ranges from 0.87 to 0.93. All measures present a score above the 0.60
threshold (Bagozzi & Yi, 1988): the value of average variance extracted (AVE) is above 0.50 and ranges from 0.51 to 0.86 (Fornell & Larcker, 1981). All R2 values are above
the 0.10 level (Falk & Miller, 1992), specifically between 0.21 to 0.32 interval, thus, showing a good explanatory power (Boakye, Prybutok, & Blankson, 2016; Hair, Hult, Ringle, and Sarstedt, 2014; Correia-Loureiro & Pereira-da-Cunha, 2017; Roldan, Jaafar, and Ramayah, 2017).
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Additionally, according to the Q test value, our models offer satisfactory predictive relevance (Sarstedt, Ringle, Smith, Reams, & Hair, 2014). Discriminant validity is lower than the AVE for the individual construct and shared variances between all possible pairwise scale combinations indicate that the variances extracted in all cases were higher than the associated share variances (Fornell & Larcker, 1981)7. We also
performed a Kolmogorov–Smirnov test (Siegel & Castellan, 1988) between responding and responding firms in the sub-population of 1,122 companies to check for a non-respondent bias; 50 non-responding companies were randomly selected from the initial population and the analysis did not reveal significant differences in the main
demographic features (i.e., sector, number of employees, annual sales, firm size, and age).
As multicollinearity is a well-known problem that arises in the context of modelling moderating effects through multiplicative terms (Henseler & Fassott, 2010), following the indications of Aiken, West, and Reno (1991) we have mean-centred the indicators of the independent and moderator variables. As a consequence, the variance inflation factor (VIF), a metric for multicollinearity, was calculated. Although there is no clear threshold value for multicollinearity (Götz et al., 2010), as a rule of thumb, the VIF should not exceed 10 (Götz et al., 2010). In our case the results showed minimal collinearity with the VIF of all items ranging between 1.08 and 3.77. These results suggest the lack of problematic levels of multicollinearity in our structural model.
After the validation of our psychometric measures, we tested the study’s hypotheses (i.e., hypotheses 1 (a and b), 2, and 3). We estimated seven models. Models I and II include the effects of family and non-family SC on innovation. Model III shows the effects of both constructs (family and non-family SC) on innovation. Model VI depicts the joint effects of family and non-family SC on innovation and Model V comprises the three-way moderation effects of family and non-family SC and family ownership on
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innovation. Model VI shows the three-way moderation effects of family and non-family SC and family management on innovation. Finally, Model VII shows the three-way moderation effects of family and non-family SC and generational involvement on innovation. An effect is significant with 95% probability if, after running 5,000 bootstrap samples, the resulting confidence interval does not include the value zero (Hair, Hult, Ringle, & Sarstedt, 2017; Hayes, 2013). The PLS results, as well as the bias-corrected confidence intervals at the 0.05 significance level with a two tailed test for seven models are presented in Table 3.
--- Insert Table 3 about here ---
Hypotheses 1a and 1b
In support of Hypothesis 1a, which suggests a positive interaction effect of family and non-family SC on firm innovation, we find the interaction of the two SC groups to be positive and statistically significant. Therefore, Hypothesis 1a is supported. Figure 1 also shows that innovation is maximized when both family and non-family SC are high. As for Hypothesis 1b—the joint effect of family and non-family SC is a stronger
determinant of family firm innovation than the single effects of family and non-family SC—we find that R2 is higher for the joint effect of family SC and non-family SC (Model IV, R2 = 0.29) than for the single effects of family SC (Model I, R2 = 0.21) and non-family SC (R2 = 0.24). Furthermore, we estimated the ratio F2, as suggested by Chin (1998), to provide the significance level of improvement. When F2 is greater than 0.02, the improvement is considered significant (Cohen, 1988). In comparison with Model I (single effect of family SC), F2 is 0.32 in Model IV and in comparison with Model II (single effect of non-family SC), F2 is 0.21 in Model IV. We can, thus, conclude that Hypothesis 1b is supported.
--- Insert Figure 1 about here ---
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The results in Table 3 (Model V) show that the positive three-way interaction effect among family and non-family SC and family ownership is supported (β = 0.14, p < 0.01, [0.03; 0.16]). Similarly, the results in Table 3 (Model VI) show that the positive three-way interaction effect predicted among family and non-family SC and family management is supported (β = 0.08, p < 0.01. [0.03; 0.17]). We also plotted the three-way interaction effects in Figures 2 and 3, confirming that innovation is maximized when family and non-family SC and family ownership or management are high.
--- Insert Figure 2 and 3 about here ---
Hypothesis 3
The results in Table 3 (Model VII) show that the negative three-way interaction effect among family and non-family SC and generational involvement are also supported, yet marginally (β = −0.07, p < 0.10, [-0.12; -0.01]; Model VII, Table 3). We also plotted the three-way interaction effects in Figure 4, confirming that innovation is maximized when family and non-family SC are high but generational involvement is low.
--- Insert Figure 4 about here ---
Robustness Test8
Given that our empirical analysis is cross-sectional, we examined the robustness of our results by addressing potential endogeneity issues related to reverse causality. We followed the practice adopted in SEM studies (Antonakis, Bendahan, Jacquart, & Lalive, 2010; Santos, Ramos, & Almeida, 2017) of using ‘the best remedy for endogeneity collecting data on independent and dependent variables from different times’ (Jean, Deng, Kim, & Yuan, 2016, p. 497). In particular, we collected additional data 36-38 months (t + 3) after our initial data collection and received responses from 71 of the original respondents (41.28 %). For these firms, we ran separate path analyses using family SC, non-family SC, and family firm innovation variables obtained from the first (t0) and second data collections (t + 3). The direction and magnitude of the
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relationships between the joint effects of family and non-family SC (t0) and family firm innovation (t3) (β=0.352; t = 35.421) were consistent with our original results. In view of this evidence, we conclude that endogeneity is not a serious issue in our study.
We also analyse the robustness of our results by estimating structural models for several subsamples according to firm characteristics (Gruber, Heinemann, Brettel, & Humbeling, 2010). We divide the sample in terms of company size (less than 100 and equal to or greater than 100 employees) and age (less than 30 and equal to or greater than 30 years). These analyses produce minimal differences in the path coefficients for the various sub-models9. Therefore, we conclude that our results are robust.
Finally, we ran the analysis including an objective single variable: the percentage of sales deriving from new products or services as a dependent variable (Mean = 15.19; S.D. = 18.03). Those results did not substantially differ from those reported. Yet, the model fit got worse. Overall, structural equation modelling is indeed a technique that especially relies on multidimensional constructs (Chin, 1998; Ringle, Wende, & Will, 2005).
Discussion
Previous studies have suggested that resources embedded in social relationships are crucial for family firms’ innovation and competitiveness (e.g. Carr et al., 2011; Lohe & Calabro, 2017; Pearson et al., 2008; Sanchez-Famoso et al., 2015a, 2015b, 2017). However, different dimensions of SC and heterogeneous features of a family business may influence the relationship between socially embedded knowledge and innovation. In particular, we argue that the co-existence of distinct yet interacting social groups in the family firm, namely family and non-family members, creates the conditions for increased firm innovation. In line with general arguments on the complementarity of resources (e.g. Ennen & Richter, 2010; Lohe & Calabro, 2017; Tiwana, 2008), our results support Hypothesis 1 and confirm that family and non-family SC jointly produce
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a positive effect on family firm’s innovation (see Figure 1). The result is important as it advances the knowledge on the consequences of an interplay between social groups in an organization (Cyert & March, 1963; Patel & Cooper, 2014), suggesting that the presence of a strong dominant coalition (i.e., the family; Arregle et al., 2007) creates the conditions for a positive reciprocal influence between social communities within an organizational setting. Our study also highlights the complementarity between different forms of internal SC in the creation of innovation, thus enriching the extant literature on SC that addresses the nature of interaction effects between internal and external
dimensions of socially embedded resources (e.g. Cuevas-Rodriguez et al., 2014). By assessing the moderating effects of family control (see Figures 2 and 3) and generational involvement (Figure 4), we also show that the decision-making setting is important in realizing the innovative potential of SC. That is, our work shows how a combination of family control, in terms of family ownership and management, and generational involvement forms different configurations that influence the relationship between the joint effects of family and non-family SC and innovation. As seen in Figure 1, when non-family SC is high, a positive relationship is observed between family SC and innovation. Such a relationship weakens when non-family SC is low. Reviewing the graphs in support of Hypothesis 2 provides a clear understanding of the joint effects of family and non-family SC and family control (in ownership and management). In Figures 2 and 3, which focus on family control, it can be observed that in all cases, the slopes are positive, but the highest level of innovation is achieved when family and non-family SC and non-family control are high. On the other hand, in Figure 4, which focuses on generational involvement, the highest level of innovation is achieved when family and non-family SC are high, while generational involvement is low.
Overall, our findings allow us to make several contributions. First, we add to studies on the intra-organizational dimension of SC. We recognize the existence of
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heterogeneous forms of SC at the firm level and explore how their combination affects innovation. Thus, we contribute to the extant literature that thus far, has mainly
considered internal SC as an undifferentiated construct without accounting for the possibility that distinct groups within the firm possessing their own SC endowment interact with each other (Arregle et al., 2007). Second, we contribute to studies analysing SC as a means to produce knowledge and resources that foster innovation processes (e.g. Cuevas-Rodriguez et al., 2014; Lee et al., 2005; Moran, 2005;
Subramaniam & Youndt, 2005). Within this line of research, we take one step further by exploring how factors affecting strategic decision-making influence the translation of SC into firm innovation.
Third, we add to the knowledge on SC in family firms (Arregle et al., 2007; Wang et al., 2015) by explicitly considering the combination of family and non-family
dimensions of SC and evaluating when and the extent to which this combination leads to positive or detrimental outcomes. In particular, our results advance previous research on the role of SC in family firms’ innovation by exploring the simultaneous effects of different forms of SC coupled with different dimensions of family involvement. The SC perspective is also a novel way to address the topic of non-family members’
contribution to family business outcomes (e.g. Chrisman, Chua, & Litz, 2003; Mitchell et al., 2003; Sanchez-Famoso et al., 2015a, 2017) as it goes beyond the individual level of analysis.
Fourth, this research theorizes and provides empirical evidence that family firms are heterogeneous, and as such, behave differently (Chrisman et al., 2005; Sharma, 2004). In line with the arguments proposed within the resource-based view (e.g. Carnes & Ireland, 2013; Drakopoulou & Anderson, 2013; Sirmon et al., 2008; Sirmon et al., 2011), we highlight that increased levels of family control in the ownership and management functions provide the necessary vision to mobilize knowledge in support
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of innovative strategies and ensure that the knowledge emerging from the interactions between family and non-family SC through assimilation and integration processes are effectively combined and aligned towards innovation goals.
This result contrasts and complements previous findings of scholars who suggest that the contribution by non-family members, to be translated into effective strategies, must occur at the level of strategic decision making, that is, there is a need for a balanced composition of TMT in terms of family and non-family managers. For example, Patel and Cooper (2014) argue that a balance in TMT structural power between family and non-family members encourages the participation of non-family members in terms of knowledge access and integration. Instead, our results indicate that it is preferable that the strategic decisions concerning the implementation phase in resource management occur in a context wherein cohesion is high and information asymmetry and governance costs are low, such as within a TMT dominated by family members. In addition, when multiple generations are involved in the company, there is no evidence of a
complementary effect of family and non-family SC. This suggests that the increased potential of affective conflict hampers the decision-making process, off-setting the benefits of the family and non-family groups and impeding an effective combination of family and non-family SC toward innovation strategies.
It is also noteworthy that this study could have relevant implications for practice. We agree with Sciascia, Nordqvist, Mazzola, and De Massis (2015) who suggest that
managers should adopt best practices reported in the innovation management literature to meet the idiosyncratic characteristics of their firms. First, the results provide evidence that family firms should manage internal relationships carefully to stimulate knowledge integration and enhance innovation activities. Owners and managers in family firms should be aware of the need to nurture strong and collaborative internal relationships among both family and non-family members. Second, the results can guide consultants
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and advisors in their attempts to improve the effectiveness of relationships within family firms.
Our research is subject to limitations that suggest avenues for future research. First, we considered the SC endowment separately for the family and non-family sub-groups (Arregle et al., 2007). Future studies should, therefore, examine the SC construct within the network of relationships that include both family and non-family members. In addition, among non-family members, we did not differentiate between organizational roles and positions, and thus, further analyses should consider addressing the varying importance of non-family SC at different organizational levels. External SC may be investigated as a complementary or substitutive resource of the internal network. In addition, future studies may employ a more fine-grained definition of innovation, for example, by distinguishing between incremental and radical innovation. In fact, the impact of internal SC may have varying intensity depending on the type of innovation output being considered. The conclusions of this study are also limited by its cross-sectional nature. Cultural differences between family firms in different countries are another issue worth considering. For example, in Spain, significant weight is placed on family relationships (Steier, 2009); interestingly, the current model could be tested in other contexts wherein family relationships may be less intense.
In sum, we believe that this study marks an important step towards gaining important insights into how family SC, non-family SC, and different forms of family involvement jointly affect innovation in family firms.
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Footnotes
1 The SABI database contains data on 2,500,000 organizations (2,000,000 from Spain and 500,000 from Portugal) and open and private Spanish and Portuguese organizations.
2 In Spain, people have two surnames: first is the father’s surname and second is the mother’s maiden name. Therefore, family relationships among shareholders are quite evident.
3 We thank one of our anonymous reviewers for this insightful suggestion.
4 Specifically, we asked them to rate their degree of agreement with the followings statements: a) A top management team (TMT) has significant autonomy to determine how its members do their jobs; b) A TMT can decide how its members will perform their work; and c) A TMT has considerable opportunity for independence and freedom in how its members do their jobs.
5 Correlations among latent variables and the marker variable are available upon request.
6 Separate summary statistics and correlations for the dimensions or constructs are available upon request. 7 Detailed results for the predictive relevance and discriminant validity are available from the authors upon request.
8 The robustness tests performed are available from authors upon request. 9 Results are available from the authors upon request.
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