Too Many Cooks in the Kitchen

Abstract

This study examines the connection between innovative capacity and small family firm performance and how that relation is moderated by collaborative network orientation and family firm ownership. Using regression analyses of survey data, we found support for a link between innovative capacity and performance that was moderated by the collaborative network orientation and the dispersal of ownership of the family firm. Furthermore, our findings indicate that two configurations enhance this link: (a) concentrated ownership combined with high collaborative network orientation and (b) dispersed ownership and low collaborative network orientation.

Keywords

family business innovation collaboration configuration

What determines the performance level of family businesses? Research in family business has examined this at a very high level simply by trying to determine if family businesses have a performance advantage over nonfamily businesses. Several studies suggest that family firms have a performance advantage over nonfamily firms (e.g., Anderson & Reeb, 2003; Andres, 2008; McConaugby, Matthews, & Fialko, 2001; Miller & Le Breton-Miller, 2005). However, other studies (e.g., Bennedsen, Nielson, Pérez-González, & Wolfenzon, 2007; Cronqvist & Nilsson, 2003; Holderness & Sheehan, 1988; Maury, 2006; Pérez-González, 2006) and a recent meta-analysis (O’Boyle, Pollack, & Rutherford, 2012) suggest that family firms do not have a performance advantage and at times have a disadvantage. Given these conflicting results, it is important that the study of family firms move forward and focus on explaining variations in the performance of family businesses by focusing on the underlying routines, activities, and processes that create performance differences in family firms. Building on the resourced-based view (RBV; Barney, 1991; Dierickx & Cool, 1989), prominent in strategic management, this article will focus on how family involvement influences the relationship between resources and firm performance. In this article, we examine the relationship between a specific resource bundle (innovative capacity) and performance in small family firms under different ownership conditions and in the presence of another resource bundle (collaborative network orientation).

The RBV (Barney, 1991; Dierickx & Cool, 1989) provides a theoretical lens through which we can begin to analyze the performance differences among family firms. The RBV posits that competitive advantage is based on heterogeneity among the resource bundles controlled by firms and that sustainable competitive advantage is based on valuable, rare, inimitable, and nonsubstitutable firm-specific resources (Barney, 1995) that are often derived from idiosyncratic and socially complex processes, such as organization culture. Habbershon, Williams, and MacMillan (2003) argue that the bundle of resources created by the interaction of the firm and the family are idiosyncratic and affect the activities and performance of family businesses. This article seeks to extend our understanding of how particular aspects of family ownership dispersion change the relationship between a firm’s resources and its performance. Concentrating on the nature of family ownership, we will examine the impact of two bundles of resources on firm performance. The first bundle is innovative capacity. Building on prior works (Koc & Ceylan, 2007; McGrath, 2001; Nelson & Winter, 1982), we define innovative capacity as the behaviors, routines, and capabilities used by the firm to identify opportunities, openly share information, promote discussion, and implement new ideas that enable the creation of new products, processes, and organizational forms. The second resource bundle is a collaborative network orientation, in this case a family firm’s “preference to build collaborative relationships among networks made up of customers, family members, community members, and, inside the organization, employees” (Sorenson, Folker, & Brigham, 2008, p. 617).

Recent research indicates that the nature of family ownership makes a difference in firm innovation. Studies of Fortune 1000 firms revealed that family firms owned by lone founders have higher performance, stronger entrepreneurial orientation, more intense growth strategies, and greater investments in firm infrastructure than family businesses with multiple owners (Miller, Le Breton-Miller, & Lester, 2010; Miller, Le Breton-Miller, & Lester, 2011). When the number of family owners increased both the dollar amount invested and number of acquisitions decreased (Miller et al., 2011). Furthermore, when scholars compared Fortune 500 firms that had lone owners to those with multiple owners, they found that the firms with lone owners had higher levels of research and development intensity, spending, and productivity (Block, 2012). Another study of 1000 publically traded firms in Europe found that research and development investment was negatively associated with levels of family ownership (Munari, Oriani, & Sobrero, 2010). And a study of family firms in Taiwan found a negative relationship between family ownership and investment in research and development (Chen & Hsu, 2009).

This literature summary suggests that increased family involvement is negatively related to innovation, but why? The answer may lie in conditions created by high numbers of owners. For example, one study found that information exchange requirements increase when numbers of owners increase, and if information exchange does not increase, firm performance decreases (Ling & Kellermanns, 2010). Another study (Schulze, Lubatkin, & Dino, 2003) found an empirical link between the financing decisions of family businesses and the dispersion of the family businesses’ ownership. Thus, it seems that additional family owners add diversity and complexity to the organizational governance and decision processes, which become difficult to manage under high levels of uncertainty, complexity, and ambiguity (Lambrecht & Lievens, 2008). Such conditions exist in firms pursuing and investing in innovation.

With the increasing levels of competition, shrinking product life cycles and the rapid commoditization of new products, it seems that competitive advantages and associated profits may be transitory (Greenhalgh & Longland, 2005). Firms must continue to refine and exploit their existing advantages while simultaneously exploring new innovations that will be the basis of future advantages (Ireland & Webb, 2007). These innovations may include new products and new approaches to technologies and business processes (McGrath, 2001). A firm’s capacity to develop and exploit innovations has been shown to be a key determinant of performance and sustained competitive advantage (Bettis & Hitt, 1995; Helfat & Peteraf, 2003). Given these circumstances, a family firm’s innovative capacity and the ability to profit from that commitment becomes critical to a firm’s ability to develop and/or maintain competitive advantage.

In this study, we will explore the relationships and contingencies among innovative capacity, collaborative network orientation, and ownership dispersion and their impact on firm performance. The goal of the article is to expand our understanding of how the complexity of family ownership moderates the relationship among valuable resources and the performance of family business, and to provide some guidance on how a family business, given a certain level of ownership complexity, can best organize to maximize the returns to its investments in innovative capacity.

The contribution of this research is at least twofold. First, we use the configurational perspective to investigate how the different combinations of innovative capacity, collaborative network orientation, and ownership dispersion affect the pursuit of financial performance in small family firms. The configurational approach to the study of organizational phenomena, such as family business performance, seeks to understand common resources and structural configurations among distinct, internally consistent sets of firms, such as family businesses (Ketchen, Thomas, & Snow, 1993; Miller, 1996). The premise of the configurational approach is that the greater a firm’s ability to align firm attributes with the demands of the environment, the greater the positive influence will be on firm’s performance and survival (Ketchen et al., 1993). Using the configurational approach is critical to moving the RBV forward because it allows us to understand how firms configure bundles of resources, such as innovative capacity and collaborative network orientation under different conditions of high and low ownership dispersion, to affect firm performance. Configurations are generally tested through the simultaneous interaction of three variables (Baker & Cullen, 1993; Dess, Lumpkin, & Covin, 1997). The configurations in this article are represented as the interaction among innovative capacity, collaborative network orientation, and ownership dispersion; this adds to the family business literature by advancing our understanding beyond contingency effects (i.e., the relationship between two variables depends on the third one). Second, we explore the boundaries of the use of collaborative approach and of ownership dispersion in family firms to affect the economic outcomes. The findings will provide small family firms with important managerial implications on their governance strategies.

The rest of the article will proceed as follows. We begin with a review of existing theory and research. We then turn to the development of our hypotheses relating family business performance to innovative capacity, collaborative network orientation, and ownership dispersion. This section is followed by the methods section, which will discuss the sample, measures, and statistical methods used in the study. Finally, we present the results of our empirical analysis, followed by a discussion of our results, the managerial implications, limitations, and future research.

Theory and Hypotheses

A competitive advantage is based on resources that are firm specific and not easily imitated by competitors (Barney, 1995). These resources may be either tangible (e.g., access to inputs) or intangible (e.g., managerial or technical skills). To sustain a competitive advantage, firms must not only refine their current practices but also seek new resources to succeed in the market (Ketchen, Ireland, & Snow, 2007). To sustain competitive advantage, firms that continue to seek and evaluate new opportunities and acquire new knowledge will adapt their organization’s practices and improve performance (March, 1991). The goal to develop organizational routines and approaches that lead to new technologies, business processes, or products, is what McGrath (2001) calls innovative capacity.

Innovative capacity (i.e., the capacity for innovation) is embedded in the organizational routines and rules-based behavioral patterns used by the firm to identify opportunities, openly share information, promote discussion, and implement new ideas (McGrath, 2001; Nelson & Winter, 1982). Firms need specific routines that guide innovation: regular scans of the environment to identify opportunities and threats because of changing market conditions (Shook, 2003), open sharing within the firm of the information gleaned from the scanning process (Barney, 1991), diversity of thought and open discussion of multiple solutions (March, 1991), and a culture that encourages risk taking, experimentation, and putting into action the new strategies that support the firm’s competitive advantage (Ellington, Jones, & Deane, 1996; Thomke, 2003). These routines create and support the habitual norms that are critical to a firm’s capacity for innovation.

As noted earlier, increasing competition, shrinking product life cycles, and rapid commoditization of the modern economy (Greenhalgh & Longland, 2005) mean that family businesses can no longer afford complacency. Family firms must continue to refine and exploit their existing advantages while simultaneously exploring new innovations that will be the basis of future advantages (Ireland & Webb, 2007). These innovations may include new products and new approaches to technologies and business processes (McGrath, 2001). The capacity of firms to develop and exploit innovations has been shown to be a key determinant of performance and sustained competitive advantage (Bettis & Hitt, 1995; Helfat & Peteraf, 2003). However, there is evidence that family businesses may be reluctant to invest in new ventures (Cabrera-Suárez, Saá-Pérez, & García-Almeida, 2001), product development (Carney, 2005), and innovation (Morck & Yeung, 2004) because families believe that those resources need to be spent in other ways more closely associated with direct benefits to the family. However, when family firms do invest in innovation, they create competitive advantages and achieve higher levels of performance for the firm (Eddleston, Kellermanns, & Sarathy, 2008; Gudmundson, Tower, & Hartman, 2003). Thus, we hypothesize that the development of innovative capacity is positively associated with small family firm performance.

Hypothesis 1: Innovative capacity is positively associated with small family firm performance.

Fundamentally, the collaborative network orientation consists of a preference to establish collaborative relationships (Rahim, 1983; Sorenson et al., 2008) that promote both positive relationships and firm success (e.g., Gómez-Mejía, Haynes, Núñez-Nickel, Jacobson, & Moyano-Fuentes, 2007). The basis for the collaborative network orientation construct was a review of the characteristics of women managers, which revealed that women tend to develop cooperative and collaborative relationships both inside and outside their firms (e.g., Aldrich, 1989; Brush, 1992; Buttner, 2001). Specifically, firms with high collaborative network orientation use collaborative approaches in working with internal and external stakeholders to develop networks, which include both professional and personal contacts from inside and outside the business, and to create network team structures within the business (Sorenson et al., 2008). Externally, collaborative relationships are developed that promote long-term mutual interests with customers and within the community. Internally, the firm organizes as a network team, which is participative and decentralized. The external network enables organizations to identify and develop new opportunities. The internal network enables the firm to adapt to and act on opportunities. These interrelated activities and cultural beliefs create an intangible asset that allows the firm to achieve superior outcomes through collaborative efforts both within the firm and beyond the firm’s boundaries (Sorenson et al., 2008).

An empirical study examined the collaborative network orientation using data from firms that described themselves as family businesses (Sorenson et al., 2008). In part, the network measure assessed the extent to which the business actively solicited and adapted the input of family members and ratings of importance to “keep the family together in the business” and to “encourage family members to join the family business” (Sorenson et al., 2008, p. 624). This study revealed that collaborative network orientation was significantly associated with firm performance for CEOs of both genders. Thus, a collaborative network orientation provides a bundle of resources that should enhance small firm performance (Sorenson et al., 2008).

Consistent with a collaborative network orientation, research examining family firms involved in manufacturing found that a moderate individualist-group emphasis, open communication and decentralized decision making, and obtaining and responding to information from customers were positively related to entrepreneurship (Zahra, Hayton, & Salvato, 2004).

Given the nature of the collaborative network orientation, it may bolster innovative capacity. Research indicates that innovative firms tend to build long-term collaborative relationships with external stakeholders (Ritter & Gemunden, 2003). Thus, a CEO who has the preference to build collaborative relationships may have relevant skills and a network that would allow him or her to establish relationships and develop mutually beneficial agreements with external stakeholders. The other component of a collaborative network orientation, organizing internally as a decentralized network team (e.g., Zahra et al., 2004), may enable a CEO to lead his or her internal network team in designing innovations to meet stakeholder goals.

Innovative capacity and collaborative network orientation are likely to be complementary and potentially highly correlated bundles of resources; that is to say, CEOs who build innovative capacity may also have a proclivity for collaborative network orientation. As a matter of course, innovative CEOs may prefer to build collaborative relationships because stakeholders may contribute to the firm’s ability to innovate in ways that promote firm performance. Therefore, we hypothesize that collaborative network orientation will interact positively with innovative capacity in contributing to firm performance.

Hypothesis 2: The relationship between innovative capacity and small-family firm performance is positively moderated by collaborative network orientation.

Many family firms have multiple family members involved as employees or in other ownership roles. In a first-generation family firm, the founder is still in control, although a spouse or sibling may have some influence in the firm. Over time, additional family members join the firm as employees or acquire an ownership stake in the business, with either direct involvement in running the business or as stockholders. These changes lead to increased dispersion of control of the family firm with the potential for increased complexity in governance of the family firm (Davis & Harveston, 1999; Gersick, Davis, Hampton, & Lansberg, 1997). Investigations of the impact of ownership dispersion on family firm performance have had mixed results. Ling and Kellermanns (2010) found that ownership dispersion had a positive effect on firm performance and that in firms with high levels of ownership dispersion, more information exchange was associated with higher performance. Zahra (2005) found that innovation was positively related to higher numbers of family members across generations who were actively involved in manufacturing organizations.

Kellermanns and Eddleston (2007) found the main effect for ownership dispersion has a negative effect on firm performance, but in their investigation of moderator variables, they found that high ownership dispersion firms with low levels of cognitive conflict performed significantly better than firms with high levels of cognitive conflict. These results suggest that the relationship between ownership dispersion and firm performance is influenced by other variables (O’Boyle, Rutherford, & Pollack, 2010).

As the number of owners increases and those owners become less attached to the firm, the probability increases that the firm has owners who differ substantially and frequently on both the economic and noneconomic benefits they are seeking from the firm. Differing goals lead to differences regarding the strategies, values, and actions the firm should pursue, which create the potential for significant costs because of ownership conflict (Schulze, Lubatkin, Dino, & Buchholtz, 2001). In public firms, when there is a significant conflict over the goals, strategy, vision, and the future of the firm, equity owners can simply sell their shares and leave the firm. However, in a small family firm, the liquidation of an equity stake is complicated and expensive as well as emotionally difficult if not completely unacceptable. The inability to easily liquidate ownership and the existence of conflicting goals and demands make family businesses susceptible to the agency problems of holdup and altruism (Schulze et al., 2001) as well as increase the time and monetary costs of communications and negotiations among the owners. All of this ends up reducing the speed and flexibility with which the firm can respond to the environment and seize opportunities as well as increasing the potential for misallocation of resources, which in turns deters the ability of the firm to capitalize on its innovative capacity.

Holdup occurs whenever owners use their voting rights or their control over a firm-specific resource to take the ownership interests of other owners “hostage.” As long as the losses the hostages (owners) might suffer from giving in to demands are less than the cost they would incur from not giving in and/or selling their stake in the firm, the hostage taker has incentive to force the firm to take actions that favor his or her interest (Schulze et al., 2001). Altruism, according to economists, arises when the welfare of one individual is positively linked to the welfare of other individuals. Altruism arises within family firms because owners’ welfare is positively linked to the welfare of their children or siblings (Schulze et al., 2001). Driven by altruism, family business owners can become overly indulgent to members of the family, leading to misallocation of resources and underperformance.

In particular, the complex, risky, speculative, and ambiguous nature of the innovation is likely to lead to the existence of goal conflicts (e.g., funding growth vs. cash payouts to owners) in family firms. It is also an area that is particularly susceptible to the indulgences that arise from the biases created by parental altruism. Parents may overestimate the abilities of their children, which in family businesses can lead to demanding that the wrong person be put in charge of a project, overestimating and supporting project proposals of a son or daughter, or other misallocations of resources that lowers firm performance.

Innovation requires firms to be adaptive and willing to change strategy, make investments with uncertain outcomes, and efficiently allocate scarce resources (McGrath, 2001), but the dispersion of family ownership can hinder a firm’s ability or willingness to make those changes. As noted above, this derives from the increased probability of differences among the owners about the goals, strategies, and values of the firm as the number of owners grows the owners are increasingly detached from the firm. Conflicts over goals and values make it difficult to adapt strategies quickly to take advantage of emerging opportunities. When there are more owners, making decisions takes longer because more information has to be exchanged (Dooley, Fryxell, & Judge, 2000). When ownership is more dispersed in a family firm, the CEO may also feel especially obligated to inform owners and obtain their support because of the responsibility he or she feels to the larger family and future generations, as is illustrated by this statement (Ward, 1997, p. 326):

If it were all my business and all my money, I’d take the risk. But it’s not. I have to be careful to protect the welfare of the family, the inheritance of others, and the family name . . .

Overall, we hypothesize that as family ownership is more dispersed, it becomes increasingly difficult to benefit from a firm’s innovative capacity because of goal conflict among owners, holdup, and altruism. As ownership dispersion increases, it negatively affects the relationship between innovative capacity and firm performance in small family businesses.

Hypothesis 3: The relationship between innovative capacity and small-family firm performance is negatively moderated by the dispersion of family ownership.

We see two configurations for small family businesses in regard to innovative capacity, collaborative network orientation, and ownership dispersion that will enhance performance. When a firm has few owners and the resource configuration of high innovative capacity, a high collaborative network orientation provides significant benefits at relatively low costs. When a firm has many owners, the resource configuration of high innovative capacity and low collaborative network orientation minimizes agency costs and maximizes the flexibility of the firm, enhancing its ability to seize opportunities and benefit from its innovative capacity, which will lead to enhanced performance.

As noted earlier, having more owners increases the potential for goal conflict and significant differences in the economic and noneconomic benefits owners seek from the firm, as well as differences regarding firm strategy, values, and actions. Thus, more owners add to the complexity of decision processes when considering investing in or moving forward with an innovation. If, with greater ownership dispersion, the risk of holdup and altruism increases, the risk which causes the potential for misallocation of resources to increase and for the flexibility of the firm responding to opportunities to decrease, then how does the existence of collaborative network orientation affect this relationship?

As noted in the theoretical development for Hypothesis 2, collaborative network orientation has the potential to provide synergistic benefits in conjunction with innovative capacity by providing internal and external relations that enhance the flow of valuable information into the family firm. Collaborative network orientation also means that there is increased communication and exchanges among owners. Kellermanns and Eddleston (2007) found a related construct, family member exchange (i.e., a family member’s perception of the willingness of his or her family to share ideas, feedback, and expectations with one another) negatively moderated the relationship between cognitive conflict and family firm performance, which led them to conclude that “in family firms where much debate occurs about what work and strategies should be pursued, greater family member exchange seems to simply exacerbate the negative performance effect of cognitive conflict” (Kellermanns & Eddleston, 2007, p. 1054). The same paper also found that generational ownership dispersion negatively moderated the relationship between cognitive conflict and family firm performance, which led to the conclusion that “cognitive conflict is detrimental to performance when ownership is spread through multiple generations” (Kellermanns & Eddleston, 2007, p. 1055). Finally, Eddleston, Otondo, and Kellermanns (2008) found that generational ownership dispersion positively moderated the relationship between participative decision making and relational conflict such that it led to significantly increased levels of relational conflict. These findings, when viewed together, appear to indicate that in family firms with high levels of ownership dispersion, conflict is negatively related to firm performance and that more interaction simply exacerbates the problems. Given the increased potential for conflict over innovation, these results would seem to indicate that family firms with high levels of ownership dispersion and high levels of innovative capacity will not benefit from collaborative network orientation and in fact are actually likely to experience lower benefits from innovative capacity than those with low levels of collaborative network orientation.

In contrast to firms with high ownership dispersion, firms with low ownership dispersion, that have high innovative capacity and collaborative network orientation will experience higher levels of firm performance because a collaborative orientation will enhance relationships with external and internal stakeholders, expand the firm’s network and enhance the stock and flow of information, knowledge, and expertise available through the network. The existence of innovative capacity indicates that firm is configured to absorb and act on the information to create new products, processes, and organizational innovations that will benefit firm performance. On the other hand, when a firm with few owners has high innovative capacity and a low collaborative network orientation, the firm is configured to absorb and act on information from their network, but the level of information, knowledge, and skills available through the networks are lower because of the firms’ decreased ability to form external collaborative agreements and generate collaboration among employees. Thus, we hypothesize that in firms with few owners, collaborative network orientation will positively combine with innovative capacity to enhance firm performance.

Based on the above, we hypothesize that firms that have innovative capacity, few owners and high levels of collaborative network orientation will experience high levels of firm performance. Moreover, firms that have high levels of innovative capacity, dispersed family ownership and low levels of collaborative network orientation will also have high levels of firm performance. Thus, we expect as follows:

Hypothesis 4: In small family firms with concentrated ownership, the configuration in which the firm has high innovative capacity and high collaborative network orientation will enhance firm performance.

Hypothesis 5: In small family firms with dispersed ownership, the configuration in which the firm has high innovative capacity and low collaborative network orientation will enhance firm performance.

Method

Sample and Data Sources

The secondary data used in this study were originally obtained from the Survey of Family Business, a 199-item questionnaire distributed to business owners between 1997 and 2000 (see Sorenson, 1999). To gather sufficient data for statistical analyses, data were gathered in two sampling frames. The first was a traditional probability sample generated from randomly selected businesses from chamber of commerce listings (e.g., Ambrose, 1983) in communities from across the United States. Selected businesses were contacted by telephone and invited to complete the survey. Twenty percent of those contacted completed the survey (n = 212).

The second was a purposive frame that consisted of businesses identified and contacted by student informants who received class credit for participation. Student informants have been employed in several entrepreneurship studies (e.g., Birley, 1986; Covin, 1994; Stewart, Watson, Carland, & Carland, 1999). Although the second sampling frame was a purposive, nonrandom sample, it had advantages. Seventy-four percent of the 260 business owners contacted agreed to complete the questionnaires (n = 193). This high response rate mitigated the possible effects of nonresponse bias. In addition, researchers assumed that owners helping students would be more willing to be accurate and complete in completing the 199-item questionnaire.

The combination of both random and purposive samples has been used in prior literature (Marshall et al., 2006; Sorenson et al., 2008). Analysis of variance tests found no significant differences between the data frames for the variables used in this study. Therefore, the data were combined (n = 405), but we keep only those cases (n = 199) with no more than 500 full-time employees for the purpose of this study and without any missing value in the variables used to test the hypotheses.

The questionnaire specified that the person answering this survey should be a family member and a manager in the business. Those who completed this survey identified themselves as owner (38%), president or CEO (33%), manager (10%), vice president (9%), and various others (10%). Most of the businesses had fewer than 10 employees (57%). The distribution of business sectors was mining (1.2%), manufacturing (9.5%), transportation/communication/electric/gas/sanitary services (4.3%), wholesale trade (6.9%), retail trade (28%), finance/insurance/retail estate (5.5%), other nongovernmental services (2.4%), and other (41.9%). Most were privately held (57%), and a good number were sole proprietorships (25%). On average, 2.98 family members have stock or ownership in the business.

Measures

Dependent variable

Firm performance was measured by seven items (α = .77). Respondents were asked to compare their firm’s performance with that of their competitors in the past 3 or 5 years with regard to growth or decline in the industry, profitability, and market share. They were also asked to characterize profit and growth over the previous 5 years. Because the anchor points were not equal, we standardized all the items and used the average score to generate a measure of this variable. The complete scales and stems are listed in the appendix.

Independent variable

Innovative capacity was reflected by seven selected items that captured factors on routines, approaches, or rule-based behavioral patterns on innovation embedded in a family business. For example, “willingness to try new things” measured a proactive attitude toward experimenting with new, innovative market offerings (e.g., new product introduction). Survey statements, such as, “We are good at scanning the external environment for opportunities and potential problems” and, “We encourage diversity in people and ideas within our organization” were relevant to the behavioral patterns exploring new opportunities as innovation input (e.g., opportunity recognition). Two other items that captured these routines evaluated possible innovative solutions asking, “How much discussion is there over different ideas in your business” and “How many different solutions do members of your organization consider when making decisions?” The appendix provides all the specific stems, scales, and items of this measure.

Since this is a self-developed construct, we employed exploratory factor analysis to evaluate the structure of this construct. The seven items loaded on one factor and had acceptable reliability (α = .75). The scale formats for these seven items were not uniform, so we standardized all the items before creating an average score for this variable.

Moderator variables

In our research, we used two moderators: ownership dispersion and collaborative network orientation. The variable of ownership dispersion was measured by one open question: “How many family members have stock or ownership in the company (number of family members)?” Because this is a direct measure of the family members’ ownership in the business and it is not rare in prior literature to use such an item as a variable (e.g., Ling & Kellermanns, 2010), we considered it an appropriate and reasonable measure. Following Dawson and Richter’s (2006) procedure in estimating interaction effects, we standardized this variable too.

The scale of collaborative network orientation was adopted from Sorenson et al.’s (2008) validated measure, which included three subdimensions, including collaboration (3 items, α = .79), inclusive network (10 items, α = .74), and network team structure (4 items, α = .79). Because the 17 items used to evaluate collaborative network orientation had different scales, we standardized them before factor-analyzing them and used the means to create the measures. The following are the specifics of our analytical steps.

First, three items were used to measure the collaboration dimension. Because they loaded highest on the five dimensions of the Rahim Organizational Conflict Inventory–R (Rahim, 1983) and helped shorten Sorenson et al.’s survey (2008), these items were directly adopted from Rahim’s (1983) five-item scale. With a 5-point scale from strongly disagree to strongly agree, the three questions measure information exchange, open communication, and willingness to work together and to understand problems. The alpha (.79) was acceptable, so we averaged the items to generate this measure.

Second, the dimension of inclusive network was measured by 10 items, which were adapted from the Survey of Innovative Organization–Revised (SIO-R; Macy & Moore, 2004). The first six items addressed the issues on soliciting and adapting to the opinions of family members, employees, and customers. All six items were rated between 0 (not at all) and 5 (very great extent). The other four items evaluated operating philosophies and beliefs. Rokeach (1973) suggested that such philosophies and beliefs not only provide a link between values and behavior but are the higher order orientations as well. The four items assessing community and family involvement were evaluated with a 7-point scale from minimally valued and used to extensively valued and used. The alpha (.74) of the 10 items loaded on one factor was acceptable. We used the average scores to produce the measure of inclusive network.

Third, the network team structure as a dimension of collaborative network orientation was measured by four items (α = .79). The four items were adapted from SIO-R and describe the operating philosophies and beliefs of a family firm about the firm’s structure and practices. We used the mean of the items for this measure.

Finally, the three composite dimensions loaded on one factor and provided an acceptable reliability (.69). We then used the mean of the three dimensions to create this overall measure, called collaborative network orientation.

Control variables

In our model, we used firm age (years the business had been in operation), firm size (the sum of full-time employees in and outside of the country), generational involvement (the number of generations that have worked in the business), CEO’s education level, and industry dummies (coded 1 = yes and 0 = no, in the areas of mining; manufacturing; transportation/communication/electric/gas/sanitary services; wholesale trade; retail trade; finance/insurance/real estate; other nongovernmental services; and other) as control variables. Firm age is a particularly important variable to control because of the potential impact on firm social capital, internal resources, inertia, and other maturation effects that may confound any examination of firm performance. We also considered that generational involvement in a business may increase the complexity of governance structures (Ling & Kellermanns, 2010), family social capital (Sorenson, Goodpaster, Hedberg, & Yu, 2009), familiness (Gómez-Mejía et al., 2007), or conflicts (Kellermanns & Eddleston, 2004) over time. Firm size could skew performance because of its impact on organizational structures, innovativeness, and cumulated slacks (McGrath, 2001). The CEOs’ level of education may bring different perspectives/values on the directions of corporations (Delmar & Davidsson, 2000; Robinson & Sexton, 1994), affecting firm growth and profitability. Finally, distinct business sectors could have different degrees of profitability or munificence implications. Likewise, we standardized all controls to facilitate the following tests (Dawson & Richter, 2006).

Analyses

Before entering the variables into a regression model, we examined multicollinearity and common method bias. Because all the variables used in the tests were standardized (Dawson & Richter, 2006), we observed that the highest value of variation inflation factor (VIF) was 2.524, demonstrating little threat (Hair, Black, Babin, Anderson, & Tatham, 2006). Then, common method bias was examined with confirmatory factor analysis (CFA). If the one-factor model fit the data reasonably well, a common method bias would be a concern. The results of this factor model revealed a poor fit (χ² = 1629.77, df = 560, p < .00; root mean square error of approximation [RMSEA] = .097, standardized root mean square residual [SRMR] = .096, comparative fit index [CFI] = .5, goodness-of-fit index [GFI] = .69, nonnormed fit index [NNFI] = .47), indicating that common method bias was not a concern. Table 1 shows the means, standard deviations, maximum, minimum, and correlations among the primary variables studied. Observing a high correlation (r = .65) between innovative capacity and collaborative network orientation, we further tested the discriminant validity of the two variables. Since collaborative network orientation is an existing scale (Sorenson et al., 2008) and a higher order factor consisting of three dimensions (i.e., collaboration, inclusive network, and network team structure), we employed a parceling technique called “internal-consistency approach,” using the dimensionality as the grouping criterion (Little, Cunningham, Shahar, & Widaman, 2002, p. 167). We considered this approach was advantageous to “keep the multidimensional nature of the construct explicit” (Little et al., 2002, p. 167). Accordingly, we averaged the indicators under each dimension (first-order factor) to form a parcel item for that dimension and, therefore, got the three manifest items of collaborative network orientation (second-order factor). A CFA indicated that the two variables as a two-factor model had a reasonable fit (χ² = 65.87, df = 34, p < .00; RMSEA = .065, SRMR = .05, CFI = .93, GFI = .94, NNFI = .91). Moreover, following Wang, Law, Hackett, Wang, and Chen’s (2005) suggestion, we compared correlations between firm performance and the two variables. If the results are not equal, discriminant validity can be confirmed. According to the two tests, collaborative network orientation and innovative capacity were distinct. Additionally, all the standardized factor loadings reflecting the two variables in the CFA were significant and greater than .42, indicating reasonable convergent validity.

Table 1.

Means, Standard Deviations, Maximum, Minimum, and Pearson Correlations.

Variable	Mean	SD	Maximum	Minimum	1	2	3	4	5	6	7
1. Firm performance^a	.10	0.63	1.38	−1.58
2. Innovative capacity^a	.04	0.60	1.31	−2.07	.35***
3. Collaborative network orientation^a	.03	0.51	1.19	−1.58	.28***	.65***
4. Ownership dispersion	2.98	2.52	19.00	0.00	.12	−.05	−.09
5. Firm size^b	30.52	65.72	500.00	0.00	.15*	−.04	−.09	.39***
6. Firm age	27.12	26.16	127.00	1.00	−.17*	−.25***	−.17*	.36***	.32***
7. Generational involvement	1.90	0.91	5.00	1.00	−.14*	−.18*	−.13	.35***	.21**	.72***
8. CEO’s education level	2.63	0.98	6.00	1.00	−.01	.06	−.01	.03	.10	.06	.05

Note. n = 199 with listwise deletion.

Because items with different anchor points were used to generate this variable, the variable was standardized.

The minimum of firm size was zero because we asked how many people are currently employed full time in and outside of the country.

p < .05. **p < .01. ***p < .001.

Using a hierarchical regression model to test the five hypotheses, we entered the variables in the following the sequence: control variables, main effect model (one independent variable and two moderators), contingency model (three two-way interaction terms), and configurational model (one three-way interaction term). For every step, the variance explained (R²), overall model significance (F statistic), significance level (p value), and incremental R² and F values were evaluated. Then, we followed the procedures outlined by Dawson and Richter (2006) to create the interaction plots.

Results

Table 2 shows that three out of the five hypotheses were supported, including the main effect of innovative capacity to firm performance (Hypothesis 1) and the two configurational models (Hypotheses 4 and 5). However, the two contingency models (Hypotheses 2 and 3) were not supported.

Table 2.

Results of Hierarchical Regression Analysis.

Variable	Model 1	Model 2	Model 3	Model 4
Controls
Mining	−.050 (.030)	−.043 (.029)	−.053 (.029)	−.058 (.029)
Manufacturing	.019 (.043)	.028 (.041)	.025 (.041)	.017 (.041)
Transportation/communication/electric/gas/sanitary services	−.043 (.042)	−.010 (.041)	−.019 (.041)	−.009 (.041)
Wholesale trade	.074 (.043)	.074* (.040)	.077 (.041)	.075 (.040)
Retail trade	.006 (.051)	−.008 (.048)	−.023 (.049)	−.029 (.048)
Finance/insurance/real estate	.054 (.045)	.055 (.043)	.055 (.043)	.049 (.043)
Other nongovernmental services	−.056 (.037)	−.026 (.035)	−.029 (.036)	−.032 (.035)
Firm size	.323**(.100)	.238* (.101)	.292**(.107)	.270* (.106)
Firm age	−.140* (.057)	−.108 (.055)	−.124* (.056)	−.136* (.056)
Generational involvement	−.016 (.060)	−.026 (.058)	−.025 (.059)	−.014 (.058)
CEO’s education level	−.023 (.053)	−.030 (.050)	−.038 (.051)	−.051 (.051)
Main effect model
Innovative capacity (IC)		.239**(.092)	.211* (.093)	.194* (.093)
Collaborative network orientation (CNO)		.137 (.105)	.193 (.108)	.177 (.108)
Ownership dispersion (OD)		.080 (.042)	.083 (.042)	.129** (.048)
Contingency model
IC × CON			−.055 (.112)	.003 (.115)
IC × OD			.078 (.100)	.084 (.100)
CON × OD			−.178 (.092)	−.254* (.099)
Configuration model
IC × CON × OD				−.218* (.106)
R ²	.135	.236	.253	.270
ΔR²		.101	.017	.017
F	2.646**	4.064***	3.611***	3.705***
ΔF		8.151***	1.378	4.214*

Note. All the study variables were standardized. Regression coefficients are unstandardized and standard errors are in the parentheses. The industry category of “other” not shown here was the reference group in controls. n = 199 with listwise deletion. Two-tailed tests.

p < .05. **p < .01. ***p < .001.

Hypothesis 1, which predicted that innovative capacity would be positively related to performance, was supported. Model 2 in the regression equation revealed a main, positive effect between innovative capacity (β = .239, p < .01) and firm performance. Compared with Model 1 as a control, Model 2 had a significant 10.1% increase on variance explained (ΔR² = .101, p < .001).

Model 3 tested the two contingency hypotheses but received no support. Although the entire model was significant, there was no significant increase in variance explained (ΔR² = .017, not significant) compared with the previous main effect model.

Instead, Model 4 had a statistically significant contribution to variance explained (ΔR² = .017, p < .05) and was used to test the two configurational hypotheses. In Hypothesis 4, we expected that the combination of low ownership dispersion, high innovative capacity, and high collaborative network orientation would enhance performance. Hypothesis 5 predicted that high ownership dispersion combined with high innovative capacity and low collaborative network orientation would increase performance. As expected, the three-way interaction term (β = −.218, p < .05) had a significant impact on firm performance. To help interpret the results, we followed Dawson and Richter’s (2006) suggestion, generating interaction plots, as Figure 1 shows. Line 2 represents Hypothesis 4 and shows an upward firm performance under the situation of low ownership dispersion, high innovative capacity, and high collaborative network orientation. Thus, this hypothesis was supported. Hypothesis 5 was supported as well; Line 3 demonstrates the enhanced performance when the combination of high ownership dispersion, high innovative capacity, and low collaborative network orientation.

Figure 1.

Interaction effects of innovative capacity with ownership dispersion and collaborative network orientation on small-family firm performance.

Discussion

The purpose of this study was to examine how the configuration of bundles of resources may give family firms an advantage under different ownership conditions. The first bundle of resources was innovative capacity. We defined and measured innovative capacity as the extent to which family firms value innovation and change, scan the environment for opportunities, encourage discussion of many and diverse ideas, open information systems, and show a willingness to try new things. Results indicate that, as expected, innovative capacity is positively related to firm performance.

The second bundle of resources that could provide an advantage for family firms was a collaborative network orientation. A collaborative network orientation is a preference for building collaborative relationships with family members, customers, the community, and a network team inside the firm. Previous research found that collaborative network orientation is positively related to firm performance (Sorenson et al., 2008). We predicted that collaborative network orientation would positively interact with innovative capacity to contribute to firm performance.

Unexpectedly, we found that the interaction between innovative capacity and collaborative network orientation was not significant. Moreover, unlike previous research (Sorenson et al., 2008), collaborative network orientation was not significant as a main effect in the regression model. However, the interaction between collaborative network orientation and ownership dispersion was negative and significant, indicating that there are significant costs to seeking collaboration among large numbers of owners. This is consistent with Kellermanns and Eddleston’s (2007) findings that family member exchanges negatively moderate the relationship between both cognitive conflict and family firm performance, and generational ownership dispersion and family firm performance. It seems that under conditions of ownership dispersion, seeking too much discussion and collaboration is detrimental to firm performance.

Both the lack of a significant main effect for collaborative network orientation and a significant interaction between collaborative network orientation and innovative capacity may be explained by the high correlation between innovative capacity and collaborative network orientation (r = .65). While tests in this study found that innovative capacity and collaborative network orientation were distinct constructs, these two constructs may have shared enough variance that when innovative capacity was present in the regression model, collaborative network orientation did not have a significant effect on performance. Innovative capacity and collaborative network orientation were similar in that they both focused on openly sharing information and discussing ideas. But they were different in that innovative capacity focused on scanning the environment for opportunities and being willing to try new things, whereas collaborative network orientation focused on developing collaborative relationships and agreeing with the family, customers, and members of the community. Innovative capacity focused largely on looking outward to find opportunities and produce innovation. In contrast, collaborative network orientation focused on a broad range of noneconomic or socioeconomic outcomes important to the family (e.g., Basco & Rodríguez, 2009; Gómez-Mejía et al., 2007; Sorenson, 1999). Taken together, these results suggest that if firm performance is paramount, small family firms should focus on building innovative capacity.

Our results contribute to the RBV and agency theory by highlighting the importance and applicability of the configurational approach for research in these areas. We contribute to the discussion of agency theory by highlighting how governance structures can affect the value firms receive from investments in the development of different resource bundles. We extend the RBV research by expanding our understanding of how the configuration of firms’ bundles of resources affect firm performance under different conditions. Innovative capacity has a significantly positive relationship to firm performance. However, the combined impact of innovative capacity and collaborative network orientation on performance depends on a third firm characteristic—the dispersion of ownership.

Research within the RBV tends to posit that the development of bundles of resources and capabilities is always positive, but under conditions of high ownership dispersion and high collaborative network orientation, the addition of innovative capacity has no significant impact on performance. In fact, the combination of high collaborative network orientation, high ownership dispersion and high innovative capacity may decrease performance. In a tightly held family firm with low collaborative network orientation, investment in the development of innovative capacity may have no impact or even hinder family firm performance.

The RBV posits that firm performance is a function of the firm’s resources. The coefficient of the measure of resources in this function has generally been assumed to be positive under almost all conditions, but our results challenge this assumption. The assumption that many have used in RBV research that more resources are always better under all conditions is challenged by our results. Leonard-Barton (1992) noted that core capabilities could turn into core rigidities and over time can negatively affect performance. Her findings have been extended and duplicated in numerous studies, but our results provide a substantively different insight: Simply put, not all bundles of resources positively interact to increase firm performance under all conditions. In fact, under some conditions (high ownership dispersion), the addition of a new resource bundle (collaborative network orientation) to a firm with an existing resource bundle (innovative capacity) may add nothing or decrease performance. Thus, future research in RBV needs to continue to explore the potential for both positive and negative interactions among various resource configurations and conditions.

Managerial Implications

The finding of most interest in our study was the relationship among innovative capacity, collaborative network orientation, and dispersion of ownership. Results revealed that when there were few owners, high levels of collaborative network orientation combined with innovative capacity enhanced firm performance. When there were many owners, low levels of collaborative network orientation combined with innovative capacity enhanced firm performance whereas high levels of collaborative network orientation combined with innovative capacity had little impact on firm performance.

Owners typically have influence in forming strategy, including innovation. For a variety of reasons, family firms may have high numbers of family member owners. For example, when businesses are passed to the next generation, owners often prefer to divide ownership among family members, which increases the likelihood of higher numbers of owners.

As owners, family members can, and often do, exert influence. For a variety of reasons, owners may have diversified desires for the business. For example, they may be interested in socioeconomic outcomes (Gómez-Mejía et al., 2007) or in developmental opportunities for family members (Basco & Rodríguez, 2009). And, owners who do not work in the firm may prefer sizable and steady dividends over investing in what they may view as “risky” innovation. Alternately, owners who work inside the business may prefer reinvesting profits over promoting innovation and growth. The results of this study suggest that even when a firm has innovative capacity, collaboration among many owners may limit the use of innovative capacity to promote business performance.

One reason to encourage collaboration in a family firm is that it helps to maintain positive relationships among family members and develops solutions that satisfy the interests of both the family and the business. Research indicates that collaboration within small family firms enable owners to achieve both firm performance and desired family outcomes (Sorenson, 1999). Thus, collaboration may be very important for promoting a wide range of family outcomes, including acceptable firm performance, socioeconomic outcomes, and the ability to sustain the business and the family for the long term (Lumpkin, Brigham, & Moss, 2010; Lumpkin, Martin, & Vaughn, 2008). However, the results of this study suggest that when a firm has dispersed ownership and the objective is to enhance performance through innovation, a high collaborative network orientation may stifle innovation and firm performance.

The results of this and previous studies may provide a profile that will aid firm performance and maintain family relationships. First, the firm could build routines that support innovative capacity. Firms that have few owners could also consider building the skills and abilities that help establish and sustain a collaborative network orientation.

Firms that have many owners could profit from innovative capacity through selective use of collaboration. For example, the owners might collaborate annually to discuss the overall strategy for the business or enter into targeted collaborations with customers, which may simultaneously build relationships and obtain important information about the environment. Openly sharing information and collaborating with employees could provide rapid innovations. However, the firm might find ways to limit overinvolvement among many owners.

Firms could limit overinvolvement among owners by keeping a trusted CEO for long tenure, which may be one reason that CEOs of family firms have longer tenures than in nonfamily firms (e.g., Westhead, Cowling, & Howorth, 2001). If the CEO has been successful, owners may feel little need to exert influence over the firm. However, some research suggests that long-term CEOs limit innovation (Zahra, 2005; Zahra et al., 2004). Another approach would be to structure the nature of input from shareholders. For example, CEOs in small businesses may feel obligated to consult owners on many issues, including operational decisions. If shareholders agree on strategy and policy in formal meetings, such as quarterly or annual meetings among shareholders (see Sorenson, 1999; Zahra et al., 2004) and allow the CEO to operate within those parameters, the CEO would, at least to some degree, be able to take advantage of innovative capacity.

Limitations and Future Research

Although the results of this study are interesting, caution is warranted in generalizing the findings. The sample for this study was drawn from smaller businesses. The range for ownership dispersal (i.e., number of family member owners) in the sample may be relatively low. Further research should include larger family businesses in the sample to determine if even higher levels of ownership dispersal combine with collaboration to create complexity. Larger firms may have more sophisticated professional management systems, structures, and processes that replace the more informal entrepreneurial management practices of smaller firms (Flamholtz & Randle, 2007). In addition, our measure of ownership dispersal may not capture the level of influence family members hold. Subsequent studies could incorporate additional measures of influence, such as the percentage of family ownership or the number and percentage of family members on the board of directors. Finally, the role of innovative capacity in the development and sustainability of competitive advantage needs further definition and integration into the theory and practice of family business. Questions such as, “What are the key characteristics of innovative capacity for family firms” and, “What are the unique barriers to innovation for family firms” are crucial to the continued success of family business.

Footnotes

Appendix

Acknowledgements

The authors thank the editor, associate editor, and the anonymous reviewers for their helpful comments and suggestions on early drafts of this article.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

a.

This set of questions asks for information about your performance in the industry in which your business operates and your approach to financial management.

b.

The following statements describe types of operating philosophies and beliefs that may or may not exist in your business. Please indicate the extent to which each philosophy or belief is valued by your business and used in daily operation by checking the appropriate answer provided. Scales used: 1 (minimally valued or used) through 7 (extensively valued and used).

c.

Below, you will find listed practices some organizations have adopted to improve productivity. Please indicate whether your business has adopted the following practices by indicating the percentage of employees using the practices. If you do not use the practice, mark “NA” meaning that you do not use the practice in your business. Scales used, Percentage of employees included in practice: NA (does not apply); 1 (none, 0%); 2 (almost none, 1% to 20%); 3 (some, 21% to 40%); 4 (about half, 41% to 60%); 5 (most, 61% to 80%); 6 (almost all, 81% to 99%); 7 (all 100%)

d.

The following questions ask about your perceptions of conflict in your business. Please indicate the extent to which each of the following statements describes conflict in your business. Scales used, 1 (none); 2 (little); 3 (some); 4 (many/much); 5 (a great deal).

e.

The following questions ask about business’s organizational learning. Please indicate the extent to which each of the following statements is characteristic of your business. Scales used, 0 (not at all); 1 (very little extent); 2 (some extent); 3 (moderate extent); 4 (great extent); 5 (very great extent).

f.

The following questions ask about your perceptions of conflict and how conflict is handled in your business. Please indicate the extent to which each of the following statements is characteristic of conflict in your business. Scales used 1 (strongly disagree) through 5 (strongly agree).

g.

This set of questions asks for information about your relationships inside and outside your business. Please indicate the extent to which you agree with each of the following statements by placing a check mark in the scale provided. In this questionnaire, Family Members refers to the relatives of the principal owners of the business, which would include spouses. Scales used, 0 (not at all), 1 (very little extent), through 5 (very great extent).

Author Biographies

Mark Spriggs is an associate professor and the director of the Schulze School of Entrepreneurship, Opus College of Business at the University of St. Thomas. He received his PhD from the University of Wisconsin–Madison, and his current research interests are early stage investing, the role of advisory boards for SMEs, and franchising.

Andy Yu is an assistant professor of management at the College of Business & Economics at the University of Wisconsin–Whitewater. His work has appeared in Family Business Review and Advances in Entrepreneurship, Firm Emergence and Growth. He currently serves on the editorial review board of Family Business Review and was the first person to receive Outstanding Reviewer Award of this journal.

David Deeds is The Schulze Chair in Entrepreneurship at the Opus College of Business at the University of St. Thomas. He received his PhD from the University of Washington in 1994. He has published numerous articles in management and entrepreneurship in journals, including the Strategic Management Journal, Journal of Business Venturing, and Entrepreneurship Theory and Practice. His current research interests include alliances, innovation, technology commercialization, and social networks

Ritch L. Sorenson is the Opus Endowed Chair in Family Business and the Director of the Family Business Center at the University of St. Thomas in Minneapolis. The Center includes family business research, outreach, and education, including a major in family business. He has been an associate editor and a guest editor for a special issue for Family Business Review. His current research interests include governance, family capital, collaboration, and values in family business.

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