http://www.smallbusinessinstitute.biz Innovation in small firms: Does family vs. non-family matter? Saurabh Ahluwalia1, Raj V. Mahto2, Steven T. Walsh3 1University of New Mexico, sahluwalia@unm.edu 2University of New Mexico, rmahto@unm.edu 3University of New Mexico, walsh@unm.edu A B S T R A C T Small firms are the backbone of our economy. These firms need to innovate to thrive and compete. However, research on innovation in small firms, especially non-technology and less knowledge-intensive firms, is lacking. In this study, we explore antecedents of in- novation in such firms. We build and test a theoretical model that links employee training, employee commitment, family employees, and emphasis on learning to innovation in small firms. We also argue that a small-firm owner’s perception about his firm being a family firm or a non-family firm will influence the relationship between predictors and firm innovation. Keywords: Journal of Small Business Strategy 2017, Vol. 27 No 03, 39-49 ISSN: 1081-8510 (Print) 2380-1751 (Online) ©Copyright 2017 Small Business Institute® APA Citation Information: Ahluwalia, S., Mahto, R. V., & Walsh, S. T. (2017). Innovation in small firms: Does family vs. non-family matter? Journal of Small Business Strategy, 27(3), 39-49. w w w. j s b s . o rg Small firm, Family firm, Innovation, Owner’s perception, Commitment Introduction Small firms, being a major source of employment and new job creation, make a significant contribution to the de- velopment of regional and national economies. Economies with burgeoning healthy small firms reap many benefits associated with those firms, including economic develop- ment and a higher standard of living for residents in the firms’ communities. Despite agreement among scholars about the benefits of small-firm economies, a consistent definition of “small firm” is absent across the world. In the United States of America, a small firm is defined as a manufacturing entity with fewer than 500 employees or a service firm with annual sales revenue lower than $7.5 million (US Small Business Administration, 2010). These entities are the dominant form of enterprises in the US economy representing 99.7% of employer firms and are responsible for generating 64% of private sector jobs. The dominance of small firms in our economy and their criti- cal role in maintaining the health of our economy requires small-business scholars to investigate and explain factors influencing small-firm performance and survival in an in- creasingly hypercompetitive environment, characterized by short product life cycles and intense competitive rivalry (Wiggins & Ruefli, 2005). Researchers have identified innovation as a key com- petitive tool for firm survival and for maintenance of su- perior performance in an environment of intensifying competition (Dess & Picken, 2000; D’Aveni, 2010). In this paper, we define innovation as “adoption of new idea or behavior by a firm” (Daft, 1978; Damanpour & Evan, 1984). Innovation scholarship has focused mostly on large public corporations or technology-based entrepreneurial firms (a miniscule section of the economy) while ignoring non-tech- nology-based small firms due to the risk associated with innovative activities and endeavors (Crossan & Apaydin, 2010; De Massis, Frattini, & Lichtenthaler, 2013; Terziovski, 2010). Innovation requires significant commitment of re- sources by initiators, and is, therefore, risky. Small firms, susceptible to business failure and resource constrained, are perceived negatively because they lack resources to in- vest in innovation (Chandy & Tellis, 2000) and are unable to absorb the failures associated with high-risk innovative activities (Yap & Souder, 1994). Small firms, especially firms with fewer than 60 em- 40 S. Ahluwalia, R. V. Mahto, & S. Walsh Journal of Small Business Strategy / Vol. 27, No. 3 (2017) / 39-49 ployees, constitute over 90% of all firms in the US econ- omy (US Small Business Administration, 2010). Given that dominance, our limited understanding of factors influenc- ing innovation in small firms is detrimental to ensuring de- velopment of the national economy and the well-being of its citizens. It is important to remove the gap in our under- standing about factors influencing innovation undertaken by small firms to adapt to today’s hypercompetitive envi- ronment. Our research goal in this paper is to address this significant gap in our understanding of innovation in small firms. Given the significant overlap between family firms and small firms in our economy (e.g. Shanker & Astrachan, 1996), a discussion of small firms invariably includes family firms. A key distinguishing feature of the latter type is the involvement of a family or multiple members of a family who intend to maintain control of the firm over multiple generations (Chrisman, Chua, & Litz, 2003). Even though innovation research on family firms is slightly more ad- vanced than innovation research on non-technology-based small firms (De Massis et al., 2013), research on innova- tion in small family firms is almost non-existent. Thus, it is also critical to understand factors influencing innovation in small family firms because family-firm scholars have con- cluded that family involvement has direct and indirect ef- fects on firm innovation (e.g., De Massis et al., 2013). In this study, we also assess the influence of family factors on innovation in the small-firm context. As employees are an important form of (human) capital and a source of competitive advantage, we assess employ- ees’ influence on innovation in small family and non-family firms. Our study complements others that have established the importance of employee involvement in firm innova- tion (De Winne & Sels, 2010). Ours also appears to be the first study to test whether a firm owner’s perception about his or her firm being a family firm or a non-family firm mod- erates the relationship between employee-related predic- tors and firm innovation. More specifically, we theoretically propose and then assess how employee learning, employ- ee training, employee commitment (to the firm), and fam- ily employees (the number of employees related to the family) influence innovation in small firms with fewer than 60 employees. We also assess the moderating effect of the owner’s perception. This is also one of the first studies to examine predic- tors of innovation in the dominant non-technology sec- tors of the economy comprising mostly small family and non-family firms with fewer than 60 employees. The structure of our paper is as follows. We provide a brief overview of the literature on innovation in small fami- ly and non-family firms in the first section. Next, we sketch our theory in the following section. We then offer hypoth- eses and theoretical models followed by a description of our sample, variables, and results in the methods section. We conclude the paper with a discussion of our findings, offering practical implications of study findings, and listing some study limitations. Literature Review In the current economic environment, where firms face intense competition, there is a rush to move up the value chain by engaging in more knowledge-intensive work and by outsourcing the low-value, commoditized portion of the operation. This competitive rush has enhanced the impor- tance of innovation, which positively impacts firm perfor- mance (Christensen & Raynor, 2003). Literature on innova- tion has increased significantly over the last few decades, reflecting the increased importance of the concept among business owners and managers. In their quest to decode the black box and understand various factors associated with the concept of innovation, researchers have focused on innovation inputs (e.g., research and development ex- penses), activities (e.g., firm culture or organization struc- ture) and/or innovation outcomes (e.g., performance) (De Massis et al., 2013). The resource constrains faced by small firms has led to limited research on their innovation with studies focus- ing mainly on the human capital aspect of the firms, such as owner-managers or employee characteristics (e.g., De Winne & Sels, 2010). Studies using the strategic view of hu- man resource management or the knowledge-based view of a firm (i.e., knowledge is required for innovation) have demonstrated the positive influence of small-firm CEOs or owner-managers on firm innovation (Klaas, Klimchak, Se- madeni, & Holmes, 2010). Some scholars have suggested that CEOs or owners have only indirect influence on inno- vation because highly educated CEOs or managers tend to hire talented or educated employees. These employees, in turn, contribute to firm innovation (Winne & Sels, 2010). Studies of employee involvement have suggested that as employees are the primary repositories of knowledge (e.g., Grant 1997), their involvement in enhancing firm innova- tion is critical (Hitt, Bierman, Shimizu, & Kochhar, 2001; Lado & Wilson, 1994). This supposition has been support- ed by small-firm studies that show the positive influence of non-managerial employees on firm innovation (Andries & Czarnitzki, 2014). However, our understanding of non-man- agerial employees’ contributions to small-firm innovation is still limited (Slevin & Terjesen, 2011), requiring a signif- icant amount of future research to build our knowledge base (Andries & Czarnitzki, 2014). Scholarship on innovation in family firms, like schol- arship on small-firm innovation, is thin and underdevel- 41 S. Ahluwalia, R. V. Mahto, & S. Walsh Journal of Small Business Strategy / Vol. 27, No. 3 (2017) / 39-49 oped (De Massis et al., 2013). Still in the early stages of development, most work has focused on establishing a separate identity for the field by comparing family firms’ innovation performance to non-family firms’ performance. These studies generally agree that family involvement or embeddedness in a firm influences its innovation because of a family’s large ownership stake in a firm or their desire to preserve the family entity for the next generation (e.g., Chrisman & Patel, 2012; Gomez-Mejia, Makri, & Kintana, 2010; Breton-Miller & Miller, 2009). In addition, these stud- ies often focus on technological innovation versus adoption of new ideas or behaviors, practices more common in small family and non-family firms in traditional sectors of the economy. The significant differences in small family firms’ and large family firms’ behaviors (e.g, Lussier & Sonfield, 2009) creates a significant void in our understanding of factors influencing innovation in small family firms. This, combined with our limited understanding of factors influencing inno- vation in small firms in non-technology industries, magni- fies the urgency to undertake more studies on innovation in this context, as these are the dominant entities in major economies across the globe. In this study, we attempt to address this important and critical void in the field. Theory It is widely accepted that a firm’s innovation output is related to availability of resources and firm capability. The resources and capability of small firms operating in tradi- tional non-technology sectors of an economy are depen- dent on the firm’s employees and managers, as these firms are resource-constrained in other aspects. This argument is consistent with two theoretical frameworks commonly utilized to study innovation, the Resource-based View (Bar- ney, 1991) and the Absorptive Capacity Theory (Zahra & George, 2002). We utilize these two theoretical perspec- tives to build hypotheses. The Resource-based View (RBV), which emerged out of strategic management scholars’ quest to search for sourc- es of competitive advantage (possibly innovation), is based on Wernerfelt (1984) and Penrose’s (1959) seminal work. Barney’s (1991) conceptualization of RBV attracted a signif- icant following to this theoretical framework in many dif- ferent streams of the business discipline. Per RBV, resourc- es that are valuable, rare, inimitable, and non-substitutable provide firms with a competitive advantage. For small firms, employees and the management team (founders and CEOs) are the resources because of their knowledge base (about the firm, its customers, and market inter-link- ages). The knowledge that employees possess is often rare and socially complex (Hitt, Dacin, Levitas, Arregle, & Borza, 2000). We argue that the small firms can make this key re- source more valuable by training their employees, empha- sizing learning, increasing employee commitment to the firm, and having a higher composition of employees with a connection to the founder and owners (i.e. family employ- ees). Family embeddedness in firms has been identified as a resource that offers family firms a performance edge over non-family firms (Habbershon & Williams, 1999). Absorptive Capacity Theory has been used extensively in the literature to explain sources of innovation in firms (e.g., Zahra & George, 2002; Cohen & Levinthal, 1990). The multidimensional construct absorptive capacity is a firm’s ability to value, assimilate, and apply knowledge (Cohen & Levinthal, 1990) to create innovation. The primary focus of this theory is the utilization of knowledge to create innova- tion that gives firms a competitive advantage. Even though this theoretical framework has been applied primarily in the context of large firms (e.g., Qian & Acs, 2013), it is an appropriate model for explaining innovation in small firms. For most firms, employees are the key repositories of valu- able knowledge and skills (Schultz, 1961). A small family firm may emphasize enhancing its absorptive capacity and the employee knowledge base to enhance the firm’s posi- tion because of its desire to preserve the family entity for future generations. Hypotheses In this study, we argue that employees are the prima- ry source of innovation for small firms. Various employ- ee characteristics may help a small firm increase its level of innovation. We focus on a small firm’s training of em- ployees, emphasis on learning, employee commitment, and family employees as predictors of firm innovation. A small firm owner’s perception about theirs as a family firm or non-family firm may influence the relationship between employee-related variables and firm innovation. Employee Training and Innovation Knowledge residing in small-firm employees contrib- utes to firm innovation. Many small firm owners recognize the importance of employees in increasing firm innovation and competitiveness, and surveys of small firm owners/ managers confirm it (Lichtenstein & Brush, 2001). Per Ab- sorptive Capacity Theory, knowledge allows employees to understand and absorb new knowledge in their daily prac- tices. With time, however, knowledge can become obso- lete, endangering a firm’s competitive position in the mar- ket. In the absence of new knowledge, a small firm’s ability to learn and solve problems will decline, resulting in lower levels of firm innovation (e.g., Kim, 1998). Employee training is a way to keep the employee knowl- edge base updated and enhance an employee’s capacity to 42 S. Ahluwalia, R. V. Mahto, & S. Walsh Journal of Small Business Strategy / Vol. 27, No. 3 (2017) / 39-49 engage in innovation. Through in-firm training small firms can allow employees to continue to accumulate the latest knowledge (Killingsworth, 1982) and utilize it to solve or improve a firm’s complex processes and/or product/service offerings. A higher level of employee knowledge enhances a firm’s absorptive capacity and thus its ability to gather knowledge and apply it to invent or innovate. Studies have supported the benefits of employee training on firm inno- vation (e.g., Bauernschuster, Falck, & Heblich, 2009). Thus, we propose the following hypothesis: Hypothesis 1. In small firms, employee training is positively associated with firm innovation. Emphasis on Learning and Innovation In small firms, employees’ motivation to enhance their knowledge and firm-related expertise is dependent on a firm’s culture. A firm that hopes to maintain a competitive position in the industry by building and ensuring its capaci- ty to innovate will not only train its employees but will also motivate employees to acquire knowledge on their own (e.g., MacDonald, Assimakopoulos, & Anderson, 2007). Conversely, firms with low emphasis on learning will emphasize efficiency, resulting in employees focusing more on doing their work efficiently. Without an owner’s empha- sis on learning, employees will have less incentive to ac- quire or accumulate new knowledge and thus build a firm’s absorptive capacity to innovate. Thus, we propose: Hypothesis 2. In small firms, emphasis on learning is posi- tively associated with firm innovation. Commitment and Innovation Employee commitment is a measure of an employee’s identification with a firm. It is among the most extensively researched organizational constructs. Employee commit- ment toward a firm has been shown to produce firm-valued outcomes, such as lower turnover (Bellou, 2008), higher employee performance (Weeks, Loe, Chonko, & Wakefield, 2004), and higher employee creativity (e.g., Chang, Jia, Takeuchi, & Cai, 2014). Given the resource constrains that small firms face, employees demonstrating a higher commitment are espe- cially important to firm innovation levels. Employees with lower commitment are likely to perform at a minimum required level for continued employment (Riketta, 2002), which implies that employees will not be engaging in new knowledge acquisition activities that build a small firm’s absorptive capacity. Conversely, employees who are more committed feel a greater sense of responsibility (Morrison & Phelps, 1999) and are more likely to learn and acquire new knowledge to enhance their firm’s capability to inno- vate. Studies have also found that employees with high- er commitment support and accept change (indicators of innovation) more strongly compared to employees with lower commitment. In addition, employee commitment is shown to be an important factor in fostering innovative behavior in a firm (Xerri & Brunetto, 2013). Therefore, we propose: Hypothesis 3. In small firms, employee commitment is pos- itively associated with firm innovation. Family Employees and Innovation Employees’ relationships to owning family (i.e., family members who are employees) or to the firm owner should influence their contribution to a firm’s innovation. Fam- ily members employed in the firm have a higher stake in performance of the firm. These family employees benefit financially (profit sharing or appreciation of firm equity holding) and emotionally (their concern for family well-be- ing). Unlike non-family employees, who can terminate employment with the firm with no or negligible emotional cost, most family employees may endure significant emo- tional harm on terminating their employment with the firm (Kellermanns & Eddleston, 2006). Thus, family employees are more likely to exhibit a higher level of commitment to the firm. Because of their commitment and deep connec- tion, these employees are more likely to engage in knowl- edge-acquisition behavior to build their firm’s capability to innovate and to achieve a higher market standing for the firm. Thus, we propose: Hypothesis 4. In small firms, a higher number of family em- ployees in a firm is positively associated with firm innova- tion. Owner Perception and Innovation Studies on innovation have suggested that firm own- ership has an influence on innovation levels (e.g., Classen, Carree, Van Gils, & Peters, 2014). Empirical studies com- paring innovation performance of family and non-family firms have produced inconsistent results (Carnes & Irland, 2013). Some studies find support for the superiority of fam- ily firms over non-family firms in innovation practices (e.g., Gudmundson, Tower, & Hartman, 2003) because of these firms’ ability to stimulate learning, innovation (Zellweger, 2007), and knowledge sharing (Zahra, 2012). Literature on innovation that supports the superiority of non-family firms is equally strong, with these studies suggesting that a family’s desire to pass the family entity to the next gen- eration forces them to act cautiously and deter innovation (Gomez-Mejia et al., 2010). Others studies suggest that a high degree of family ownership negatively influences a 43 S. Ahluwalia, R. V. Mahto, & S. Walsh Journal of Small Business Strategy / Vol. 27, No. 3 (2017) / 39-49 firm’s innovation output (Chrisman & Patel, 2012). Thus, family ownership can influence a firm’s innovation output either positively or negatively. As we mentioned previously, a significant overlap ex- ists between small firms and small family firms in our econ- omy. Not all small-firm owners consider theirs a family firm (e.g., Fernández & Nieto, 2005), however, because of the negative connotation associated with the term. Small-firm owners who do not consider their firm to be a family firm are likely to operate it differently compared to owners who consider theirs a family firm. As family and non-family firms have different firm innovation outputs, small-firm owners’ perceptions about their firm as family or non-family oper- ated may influence a firm’s innovation, and influence the relationship between predictors and firm innovation. Thus, we propose: Hypothesis 5. In small firms, owners’ perceptions about their firm (being family or non-family) will moderate the relationships between predictors and firm innovation. Method We tested the proposed study hypotheses using a sam- ple of small firms located in the southwestern part of the United States. The data was collected toward the end of 2011 through a survey instrument developed by one of the study authors. The sampled firms were selected from a da- tabase of local businesses maintained by the executive arm of a business school from a state university located in the region. The organization maintained the data to market its executive graduate and certificate programs and advertise multiple business events. The organization was in the pro- cess of developing new executive education programs tar- geting small-business owners in the surrounding communi- ty and the state. Organization leadership approached one of the authors to develop a survey instrument to assess the suitability of those programs for the target audience. The organization allowed the author to include additional ques- tions and items in the survey instrument in exchange for help on the survey. The organization’s original database contained a total of 3902 active firms operating in the state. The data con- tained the names of firms, addresses (street, city, county, state, and zip code), and title and contact information of firm insiders. Given budget constraints, the author could only survey about 300 contacts from the database. To ran- domly select a sample of 300 firms from the 3902 firms, the author used a two-step process. In the first step, he used the randomization function available in Microsoft Ex- cel to assign a random number (in format 0.xxx, xxx, xxx) to each company in the database. In the second step, he used the sort function to rearrange companies in the data from the smallest to the largest (on random number) to select the first 300 companies in the list. If any firm in the select- ed list was a local branch of a large corporation, he moved to the next firm on the list after removing the branch loca- tion from the selected list. He continued the sample refine- ment process till our final sample of firms to be contacted for the survey included only local firms. As the database lacked email addresses, the author personally called the listed contact person for each firm to extend an invitation to participate in the survey and re- confirm the firm’s address and the name and contact infor- mation for the top executive. Most of the contacted firms agreed to participate in the survey due to the reputation of the associated business school. We mailed the survey questionnaire to these firms along with a letter explaining the survey instrument and the purpose of the survey. A single respondent from each targeted firm completed the mailed survey. As multiple researchers have raised con- cern about the reliability of organizational data obtained using a single firm respondent (e.g., Bowman & Ambrosini, 1997), we used only respondents who were either owners of the firm or the top officers of the firm. Such respon- dents have been shown to be knowledgeable about or- ganizational practices and to possess reliable information about the firm, especially if the firm is small (Zahra & Covin, 1995; Mahto, Davis, Pearce, John, & Robinson, 2010). We received completed surveys from 66 firms, representing a response rate of 22%. The average age of respondents in the study sample was 53.62 years with the majority of respondents being male (46 males and 20 females). On average, the sample firms had 30 full-time employees and sales revenue of about $2 million (average 2.66 with 1 represents less than $550K per year and 5 represents more than $5 million per year). Employee Training Firm Innovation Owner’s Perception Family Employee Employee Commitment Learning Emphasis H5 H1, H2 H3, H4 Figure 1. Proposed theoretical model. 44 S. Ahluwalia, R. V. Mahto, & S. Walsh Journal of Small Business Strategy / Vol. 27, No. 3 (2017) / 39-49 These firms represented 20 different industries (food man- ufacturing to medical, precision, and optical instruments) with fabricated metal and transportation equipment, air- craft etc. being the dominant group, with each constitut- ing 12% (8 observations) in the sample. A large number of respondents (20 out of 66) left the nature-of-business question unanswered. In general, small firms in our sam- ple were engaged primarily in manufacturing. Finally, 36 respondents identified their firm as a family firm, while 29 identified their firm as a non-family firm. One respondent failed to answer the question. Survey respondents’ failure to complete all survey questions (e.g., innovation and employee training) result- ed in a smaller usable sample of 47 firms for the study. The average firm age in our sample was 30 years and most firms had an average of 14 employees. These firms also had av- erage sales revenue of between $1 million and $2 million per year and an average annual growth rate of about 5%, which was higher than the state economic growth rate over the same period. Study Variables Innovation. A review of innovation literature suggests that researchers have employed different measures of the construct, such as patents (Archibugi & Planta, 1996), Re- search and Development expenditure and intensity (Arm- bruster, Bikfalvi, Kinkel, & Lay, 2008), or number of new products and/or services introduced by the organization (e.g., Nohria & Gulati, 1996; Damanpour, 1996; Johannes- sen, Olsen, & Lumpkin, 2001). In a small-business context, however, especially among micro-firms, some measures, such as R & D intensity and patents, are inappropriate to assess innovation. Resource constraints limit such mea- surement. As a result, we operationalized innovation in our study using the number of new products or services introduced by a sample firm (e.g., De Massis, Frattini et al., 2013). We asked respondents to indicate the number of new products or service families that they introduce each year to obtain innovation measure. Respondents indicated their preference on a scale of 1 to 4, where 1 indicated 1 to 2 introductions and 4 indicated 10 or more new products or service families. Employee Training. Uniformity is lacking in employee training literature on operationalizing the construct (e.g., Tharenou, Saks, & Moore, 2007). Given small-business resource constraints, it is unrealistic to utilize absolute, proportional, or content measures of training in such an environment. The emphasis measure of training, which as- sesses the importance of training for an organization, is a better measure of a small firm’s commitment to employee training (e.g., Bassi & McMurrer, 1998). Thus, in this study we measured employee training using a single indicator that asked respondents to indicate the percentage of sales revenue their companies spent on training employees. The respondents indicated their response on a 5-item Likert- type scale, with a range of 1, representing “Less than 1%,” to 5, representing “more than 20%”. Learning Emphasis. We measured a firm’s emphasis on learning using a two-item scale that we adopted from the learning-orientation scale utilized in the marketing litera- ture (Sinkula, Baker, & Noordewier, 1997). The first item on the scale asked respondents about the importance of learning to the company’s competitive position. The sec- ond item of the scale assessed linkage between learning and the firm’s values. The respondents indicated their preference on both items using a 5-point Likert-type scale ranging from with 1, representing “Strongly Disagree,” to 5, representing “Strongly Agree”. The scale had a reliabili- ty (Cronbach’s α = .87) higher than recommended (.70) in the literature. We average the two items to obtain a single measure representing the firm’s level of learning emphasis. Employee Commitment. We measure employee com- mitment using three items of effective commitment scale developed by Meyer and Allen (1984). The first item of the scale assessed consensus on organizational vision. The second item of the scale assessed employee’s commitment to firm goals. Finally, the third item assessed employees’ participation in the company’s strategic direction. The re- spondents indicated their preference for all three items us- ing a 5-point Likert-type scale ranging from 1, representing “Strongly Disagree,” to 5, representing “Strongly Agree”. The scale with a Cronbach’s α = .71 satisfied the reliability requirements recommended in the literature. Family Employee. As the family-employee construct focuses on the presence of members of a business-owning family, we follow Mahto et al. (2010) to measure the con- struct by counting the number of employees related to the owner(s) of the firm. We obtained this number by asking firm respondents to indicate the number of family mem- bers currently employed in the firm. Owner Perception. Multiple definitions of family firm exist in the literature (Mazzi, 2011) with the broader defini- tion of the construct suggesting a majority of private firms being family firms (Shanker & Astrachan, 1996). As firms in our study sample are private small firms, they satisfy the broad definition of family firms as suggested in Shanker and Astrachan (1996). In this study, however, we want to assess if a firm owner’s identification of theirs as a family firm or non-family firm influences firm behavior. Thus, we followed Mahto et al. (2010) and Kotey and Folker (2007) in allowing respondents to self-classify their firm as either 45 S. Ahluwalia, R. V. Mahto, & S. Walsh Journal of Small Business Strategy / Vol. 27, No. 3 (2017) / 39-49 a family firm or a non-family firm. We operationalized this construct by asking firm respondents to respond “yes” or “no” to the question of whether theirs was a family firm or a non-family firm. Gross Margin. We utilized gross margin as the control variable in our model to parse out the effects of profitabili- ty in our model. The summary statistics of the variables are presented in Table 1. Analysis As we obtained the study data about small firms from a single firm respondent, we first assessed if our data suf- fered from the common method bias. We utilized Her- man’s single factor test, outlined in Podsakoff, MacKenzie, Lee, and Podsakoff (2003), to confirm or rule out the possi- bility of common method bias in our data. In the test, we conducted a factor analysis (principal component analysis) in which all study variables were allowed to load on a sin- gle factor to assess the existence of a high correlation be- tween them. Results of the component analysis suggested a five-factor solution including two factors with Eigen val- ue greater than 1. In the resulting model, the factor with the highest Eigen value (1.69) explained only 34% of the variance in the sample. Thus, based on the result of factor analysis we rule out the possibility of common method bias in our sample. We tested study hypotheses using linear regression us- ing STATA®. In addition, we also performed a descriptive analysis for study variable (presented in Table 1) along with a correlation among study variables. The correlation among study variables and the results of the regression analysis are presented in Tables 1 and 2, respectively. As can be observed in Table 1, some study variables are correlated as expected, but the correlation between study variables are not too high to reach a level indicating collinearity in the data. For example, employee commitment and family em- ployees are positively and significantly correlated with the dependent variable innovation. However, the rest of the four independent and control variables are not significantly correlated with innovation. Some inter-correlation also ex- ists between independent variables. For example, employ- ee commitment is correlated with emphasis on learning. Results The results of regression analysis are illustrated in Ta- ble 1. The regression model for the study sample was sig- nificant and explained approximately 27% of variance in innovation, the dependent variable. The two sub-samples’ regression models were also significant with independent variables explaining approximately 47% and approximately 14% of variances in innovation in family firms and non-fam- ily firms sub-samples, respectively. We also obtained Vari- ance Inflation Factor (VIF) statistics in regression analysis results for all three models to assess collinearity issues in our model. None of the VIF measures reached higher than 1.5, thus ruling out the possibility of collinearity influencing our results. In Hypothesis 1, we suggested a positive influence from employee training on firm innovation. However, as can be seen in the Table 3, the employee training variable failed to reach the significance level, thus Hypothesis 1 is not supported. Similarly, Hypothesis 2, which predicted a positive influence from learning on firm innovation is not supported, as the learning emphasis failed to reach signif- icance level. In Hypothesis 3 we predicted a positive influ- Table 1 Descriptive statistics and pairwise correlations between sample variables Variables Innovation Employee Training Learning Emphasis Employee Commitment Family Employee Owner Perception Gross Margin Innovation 1 Employee Training -0.005 1 Learning Emphasis 0.162 0.243 1 Employee Commitment 0.332* 0.090 0.4313** 1 Family Employee 0.426** 0.167 0.196 0.228 1 Owner Perception -0.029 0.145 -0.084 0.137 0.263 1 Gross Margin 0.077 -0.079 0.018 0.101 0.052 -0.156 1 Mean 1.326 1.651 4.163 3.915 1.558 0.600 3.326 Std. Dev. 0.778 0.686 0.705 0.663 1.736 0.495 1.375 Sample N = 43 Significance level † p < 0.10 * p < 0.05 ** p < 0.01 *** p < .001 46 S. Ahluwalia, R. V. Mahto, & S. Walsh Journal of Small Business Strategy / Vol. 27, No. 3 (2017) / 39-49 ence from employee commitment on firm innovation. In Table 3, employee commitment has a positive and signif- icant influence on firm innovation, thus providing support for Hypothesis 3. Similarly, Hypothesis 4, which suggested a positive influence from family employees on firm innova- tion, is also strongly supported. Overall, among the four hypotheses predicting positive influence from independent variables on firm innovation, two Hypothesis (H3 and H4) are supported, and the other two (H1 and H2) are not sup- ported. Finally, in Hypothesis 5 we suggested a moderating in- fluence from a firm owner’s perception of theirs being a family or non-family firm. To assess this Hypothesis, we divided the sample into two sub-samples of family firms and non-family firms to rerun the regression analysis. We included the results of sub-sample regression analysis in Table 3 with results of regression analysis for family firms and non-family firms displayed under the columns Fami- ly Firm and Non-Family Firm, respectively. As can be ob- served in the Table, the results are quite different for family and non-family firms. In the family firm sub-sample, family employees and employee commitment have positive and significant influence on firm innovation. While the results in the non-family sub-sample are quite different, with nei- ther family employee nor employee commitment reaching significance level. The regression coefficients for the other two predictors, learning emphasis and employee training, are also quite different for both sub-samples. We also as- sessed for heteroscedasticity using a robust standard error regression and results largely remained the same. Thus, the result offers partial support for Hypothesis 5. Discussion and Conclusion Our results are consistent with findings in the fami- ly-business literature that suggests family involvement in a firm influences firm innovation (De Massis et al., 2013). Our findings about innovation in family firms and non-fam- ily firms is consistent with previous findings in the litera- ture that indicate that family firms are more likely than non-family firms to invest in innovation (e.g., Classen et al., 2014). However, this is the first study to replicate those findings in the context of small family firms operating in traditional sectors of our economy. Study findings suggest that family employees are the key predictor of innovation in firms, which offers support for the stewardship perspec- tive advanced in the family-firm literature. Given the multi- ple benefits that family employees receive from the family firms, their commitment to and ownership of innovation in such firms is understandable. In addition, the emergence of employee commitment as another predictor of innova- tion in the sample mirrors the effects of family employees. On a psychological basis, non-family employees with high levels of commitment to a firm may resemble family em- ployees (e.g., Mahto et al., 2010) and thus can contribute to higher level of innovation in firms. An important finding that emerged from our study is the influence of a firm owner’s perception about his firm being a family firm or a non-family firm. Even though our sample comprises of only small firms, which are mostly owned by an individual or family, some owners consider their firms as family firms while others label it as non-fam- ily. In our total sample almost 60% of firm owners iden- tifying their firm as a non-family firm reported employing at least one family member besides themselves. Unlike previous studies that allowed firm owners to self-identify their firm as a family firm or a non-family firm but then im- posed additional restrictions to identify a family firm (e.g., Schulze, Lubatkin, & Dino, 2003; Mahto et al., 2010), we trusted the firm owner’s decision and assessed its impact on firm innovation. It seems a firm owner’s classification of their firm as a family firm or a non-family firm not only helps in identification of family firm but also influences firm outcomes, probably indirectly. This is consistent with similar findings in the family-firm literature (Mahto et al., 2010; Mahto & Khanin, 2015). Owners who perceive their firms as a family firms operate them differently and may Table 2 Regression results of survey variables on innovation Full Sample Family Firm Non Family Firm 1 2 3 Employee Training -0.077 0.056 -0.066 (0.167) (0.243) (0.265) Learning Emphasis -0.039 -0.034 -0.248 (0.182) (0.206) (0.507) Employee Commitment 0.329* 0.526** 0.207 (0.189) (0.211) (0.564) Family Employee 0.191*** 0.200** 0.148 (0.069) (0.071) (0.233) Gross Margin -0.003 -0.117 0.158 (0.083) (0.101) (0.170) Owner Perception -0.273 (0.2435) Constant 0.2074 -0.763 1.003 (0.8511) (0.984) (1.603) Observations 43 26 17 R-squared 0.274 0.468 0.135 Standard errors in parentheses * p < 0.10 ** p < 0.05 *** p < 0.01 47 S. Ahluwalia, R. V. Mahto, & S. Walsh Journal of Small Business Strategy / Vol. 27, No. 3 (2017) / 39-49 experience different relationships between employees and firm innovation as compared to owners of small firms, who identify theirs as a non-family firms. Practical Implications Our findings have multiple important implications for small-business owners. A key implication is that small-busi- ness owners are more likely to experience positive out- comes associated with employees when they classify their firms as family firms. Small-business owners who classify their firms as non-family firms are unlikely to transform higher employee commitment to high firm innovation. A small-business owner who classifies his firm as a family firm generally has employee commitment and family em- ployees that transmute to higher innovation output for the firm. However, owners who do not consider their firms as family firms are unable to reap the benefits of relationships between employees and firm innovation. Limitations Our findings have significant implications for small firms, especially for firms with fewer than 60 employees. Nevertheless, we caution readers in interpreting our find- ings because of limitations associated with the study. Sam- ple size is a limitation of this study. Limited sample size con- strained our choice of statistical methods available to test our study models and hypotheses. We encourage scholars to test these relationships using a large sample of small firms to reconfirm the findings. A second limitation of the study is the geographical location of the sample firms, in the southwestern part of the United States. Since all our sample firms are from a specific area of the nation, read- ers should be cautious in generalizing our findings to small firms operating outside the study’s geographical area. This also presents an opportunity for future research, where researchers can assess the strength of study relationships using data from different regions and countries across the globe. Finally, our study only assesses association be- tween independent and dependent variables because of the cross-sectional nature of study data. 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