INTRODUCTION

Although entrepreneurial orientation (EO) has been extensively discussed in the strategic management literature since the early 80s, in the family business literature, it has been treated as an emerging stream with recent studies investigating the antecedents and consequences of EO in family businesses (e.g., Hernández-Linares & López-Fernández, 2018). EO is one of the primary relevant constructs of the corporate entrepreneurship domain (e.g., Covin, Green, & Slevin, 2006; Miller, 1983). For instance, corporate entrepreneurship might comprise product and process innovation strategies and the search for new markets (Covin et al., 2006; Miller, 1983). Rauch, Wiklund, Lumpkin, and Frese (2009) define EO as “the strategy-making processes that provide organizations with a basis for entrepreneurial decisions and actions.” (Rauch, Wiklund, Lumpkin, & Frese, 2009, p. 762). Based on the strategic posture of entrepreneurship, the concept of EO is deployed in some dimensions such as innovativeness, proactiveness, and risk-taking (Covin & Slevin, 1991; Covin & Wales, 2012; Miller, 1983), which have been debated as antecedents for business performance, longevity, and growth (e.g., Lumpkin & Dess, 1996; Rauch et al., 2009; Soares & Perin, 2020).

The shreds of evidence about EO antecedents and consequences in the family firm’s domain have been controversial (e.g., Hernández-Linares & López-Fernández, 2018; Naldi, Nordqvist, Sjöberg, & Wiklund, 2007; Zellweger, Nason, & Nordqvist, 2012). On the one hand, family firms might be less entrepreneurial than non-family firms since family managers are risk-averse toward preservation of their affective needs (Berrone, Cruz, & Gomez-Mejia, 2012; Gomez-Mejia, Cruz, Berrone, & Castro, 2011) and also might not be willing to share control and decisions with non-family members, and in that sense will lack in skills and competencies required to enable entrepreneurial practices (Gomez-Mejia et al., 2007; Naldi et al., 2007). On the other hand, in family firms, managers usually have a higher level of discretion and more extended periods in their positions, which provides a context aligned with nurturing altruistic values, patient capital actions, and stewardship behaviors, which benefit entrepreneurial actions (Lumpkin, Brigham, & Moss, 2010; Mucci, Frezatti, Jorissen, & Bido, 2020; Schulze, Lubatkin, Dino, & Buchholtz, 2001; Sirmon & Hitt, 2003).

Considering these controversies, it becomes relevant to investigate what characteristics drive EO in family firms since EO does not emerge automatically (Covin & Slevin 1991; Ling, López-Fernández, Serrano-Bedia, & Kellermanns, 2019). Therefore, recent studies have focused on business and family firm characteristics to uncover EO’s antecedents. In the general management literature, a set of EO and entrepreneurial behavior determinants have been investigated, such as size, organizational structure, strategy, among other factors (e.g., Hashimoto & Nassif, 2014; Lumpkin & Dess, 1996; Wales, Gupta, & Mousa, 2013). Concerning the family firm particularities, prior studies provide evidence about the antecedents of EO such as family involvement in ownership, management, and governance (e.g., Bauweraerts & Colot, 2017; Casillas, Moreno, & Barbero, 2011; Miller & Le Breton-Miller, 2011; Sciascia, Mazzola, & Chirico, 2013; Stanley, Hernández-Linares, López-Fernández, & Kellermanns, 2019), generational involvement (Cruz & Nordqvist, 2012), organizational culture (Cherchem, 2017; Zahra, Hayton, & Salvato, 2004), management practices use (Eddleston, Kellermanns, & Zellweger, 2012), and socioemotional wealth (SEW) preservation (Hernández-Perlines, Moreno-García, & Yáñez-Araque, 2019).

Therefore, we focus on SEW since it is expected to influence EO (Kellermanns & Eddleston, 2006; Schepers, Voordeckers, Steijvers, & Laveren, 2014; Hernández-Perlines et al., 2019). Based on the behavioral agency theory, family firms are loss-averse regarding SEW non-economic goals. In other words, SEW conceives that family firms will preserve non-economic goals or affective endowments that are family-centric ones and that will affect outcomes and behaviors in family firms. There has been little empirical evidence about SEW’s consequences to each of EO’s dimensions, although emotional and affective needs might influence several outcomes such as entrepreneurial orientation (Gómez-Mejía et al., 2007). For instance, Hernández-Perlines, Moreno-García, and Yáñez-Araque (2019) argue that SEW influences EO by “helping the family achieve the non-economic objectives of improving their reputation, guarantee the provision of employment for members of the family and ensure family control in the next generation.” (Hernández-Perlines, Moreno-García, & Yáñez-Araque, 2019, p. 526). To provide additional evidence to this relation, we also investigate if the SEW-EO association differs between first-generation and later generations of family businesses, following the rationale that generational involvement is a moderation variable (Hernandez-Perlines, Ribeiro-Soriano, & Rodríguez-García, 2021). The underlying assumption is that the SEW-EO relationship might be stronger for first-generation family firms, considering EO’s determinants vary depending on the family business generational stage (Cruz & Nordqvist, 2012). Hence, our research question can be highlighted: How does the generational stage moderate the relationship between socioemotional wealth and entrepreneurial orientation?

This paper provides some contributions to the family business literature. First, EO was seen as a determinant of many positive outcomes such as innovation (e.g., Craig, Pohjola, Kraus, & Jensen, 2014), firm growth (e.g., Casillas & Moreno, 2010), and performance (e.g., Schepers et al., 2014). Therefore, studying how the family particularistic intentions (SEW) influence EO and the generational stage moderating effect on this relationship might help academics and practitioners since EO does not emerge automatically. Hernández-Linares and López-Fernández (2018) claim that “there is room to broaden our limited knowledge of how the EO relates to non-economic and family-oriented goals.” (Hernández-Linares & López-Fernández, 2018, p. 342). Second, prior literature has provided evidence that EO is less prominent in family firms, if compared with other firm types (e.g., Garcés-Galdeano, Larraza-Kintana, García-Olaverri, & Makri, 2016). Third, we also provide insights about the relevance of SEW to enhance or hinder EO or the EO benefits in family firms (Hernández-Perlines et al., 2019; Llanos-Contreras, Jabri, & Sharma, 2019; Schepers et al., 2014) and argue that this effect is contingent to the presence of the founder or later generation in management, hence aggregating to the evidence from Hernández-Perlines et al. (2019). For Rogoff and Heck (2003), “family is the oxygen that feeds the fire of entrepreneurship,” which might be enhanced with the founder’s presence (Rogoff & Heck, 2003, p. 559). Fourth, we also argue that SEW might be more relevant in later generations since it preserves the affective values that force an entrepreneurial spirit such as tradition, longevity, and family prominence over managing the firm. Finally, we also attend to Wales, Gupta and Mousa (2013) call that there is a lack of EO research in Brazil and other emerging economies. As well as for family firms in Mexico (e.g., Ling et al., 2019), we claim that SEW might be a determinant for nurturing entrepreneurial strategies in family firms in Brazil. Therefore, our empirical evidence allows us to discuss the SEW-EO relation in the context of emerging economies, particularly by highlighting the moderation role of the generation involvement.

The remainder of this paper is structured as follows. Section 2 reviews entrepreneurial orientation literature, especially in family firms, socioemotional wealth (SEW), and generational stage, and further develops the hypotheses. Section 3 presents the research method, the measurement of variables, and data analysis procedures. In Section 4, we report the outcomes of the analyses based on structural equation modeling. Finally, in Section 5, we discuss the study’s results and implications and its limitations and paths for future research.

LITERATURE REVIEW

Entrepreneurial orientation

The field of corporate entrepreneurship has benefited from cumulative evidence since the 80s (Miller, 1983). Derived from this work, entrepreneurial orientation (EO) emerged as a relevant construct of corporate entrepreneurship (Covin, Green, & Slevin, 2006; Covin & Wales, 2019; Wales et al., 2013; Wales, 2016), which explains “the strategy-making processes that provide organizations with a basis for entrepreneurial decisions and actions” (Rauch et al., 2009, p. 762). Entrepreneurial orientation (EO) has also been defined as the “behavioral patterns whose presence enables entrepreneurship to be recognized as a defining attribute of the firm” (Covin & Lumpkin, 2011, p. 858). EO is regarded as a firm-level entrepreneurial attitude (Covin & Slevin, 1991; Miller, 1983), which is seen as a determinant of entrepreneurial behavior (Rauch et al., 2009) and as a consequence for organizations survival, growth, and performance (e.g., Casillas, Moreno, & Barbero, 2010; Covin & Wales, 2012).

Following the definition of an entrepreneurial firm by Miller (1983), which is “one that engages in product-market innovation, undertakes somewhat risky ventures, and is first to come up with ‘proactive’ innovations, beating competitors to the punch,” prior studies have investigated EO as a multidimensional construct delimited by three dimensions: innovativeness, risk-taking, and proactiveness (Miller,1983, p. 771). First, innovativeness refers to organizational behaviors and strategic decision-making processes that create competitive advantage through product and technology experimentation, exploration, and development (Lumpkin & Dess, 1996; Dess & Lumpkin, 2005; Alayo, Maseda, Iturralde, & Arzubiaga, 2019). Alayo, Maseda, Iturrald & Arzubiaga (2019) suggest that innovativeness in their case study involves significant investments in research and development and leadership-driven teams to launch new products and improve existing processes and products. Second, risk-taking is defined as the “willingness to commit resources to projects, ideas, or processes whose outcomes are uncertain and for which the cost of failure would be high” (Covin & Wales, 2012, p. 694). Hence, risk-taking involves making decisions and actions in contexts with insufficient knowledge to determine possible outcomes with an extent of certainty (Covin & Wales, 2019; Dess & Lumpkin, 2005; Lumpkin & Dess, 1996). Third, proactiveness indicates pioneer and anticipation toward circumstances in which the firm disseminates the mentality to be first and one step ahead of the competitors (Covin & Slevin, 1989; Covin & Wales, 2012; Dess & Lumpkin, 2005; Lumpkin & Dess, 1996). Proactive firms can exploit emerging opportunities and lead the competitive market.

There is a current debate about EO’s constituent dimensions (e.g., Lumpkin & Dess, 1996). For instance, Lumpkin and Dess (1996) also identified competitive aggressiveness and autonomy as EO dimensions (e.g., Covin et al., 2006; Hernández-Perlines et al., 2019). However, we follow the three-dimensional conceptualization from Miller (1983) and Covin and Slevin (1989) since it has been extensively used to measure entrepreneurial orientation at the firm level (Rauch et al., 2009; Wales, 2016) and has also been applied in the family firm research field (e.g., Cherchem, 2017; Hernández-Perlines et al., 2019; Schepers et al., 2014).

In this paper, we interpret EO as a multidimensional construct; however, we argue that each of the three constituent dimensions of EO (Covin & Wales, 2012; Hernández-Perlines et al., 2019) might be influenced by different antecedents. Hence, although other studies indicate that EO dimensions might covary, we claim that the three EO dimensions “may vary independently, depending on the environmental and organizational context” (Lumpkin & Dess, 1996, p. 137). This disaggregated analysis is also crucial since two of the dimensions are perceived as behavioral (innovativeness and proactiveness) and one as attitudinal (risk-taking) (Pittino, Martínez, Chirico, & Galván, 2018).

Entrepreneurial orientation in family businesses

Family firms offer a particular context to investigate EO’s antecedents and consequences, whose stream has gained momentum over the last decade (Arz, 2019; Hernández-Linares & López-Fernández, 2018). Prior research shows evidence that family firms’ characteristics are central in driving EO (Hernández-Linares & López-Fernández, 2018). Hernández-Linares and López-Fernández (2018) identified 29 studies investigating EO antecedents in family firms and provide evidence about several independent, mediating, and moderator variables that were used, the most studied being the level of involvement of family members in the firm (governance and management). The antecedent investigated includes family involvement in ownership, management, and governance (Alayo, Maseda, Iturralde, & Arzubiaga, 2019; Arzubiaga, Kotlar, De Massis, Maseda, & Iturralde, 2018; Bauweraerts & Colot, 2017; Casillas et al., 2011; Miller & Le Breton-Miller, 2011; Sciascia et al., 2013), CEO characteristics (Cruz & Nordqvist 2012), generational involvement (Casillas et al., 2010; Cherchem, 2017; Cruz & Nordqvist, 2012; Kellermanns, Eddleston, Barnett, & Pearson, 2008; Sciascia et al., 2013), socioemotional wealth (SEW) preservation (Hernández-Perlines et al., 2019), organizational culture (Cherchem, 2017; Zahra et al., 2004), management practices (Eddleston et al., 2012), differences between short- and long-term orientations (Lumpkin et al., 2010), among other determinants.

The evidence regarding the extent to which family firms’ characteristics enhance or inhibit entrepreneurship has been controversial (Hernández-Linares & López-Fernández, 2018; Kellermanns et al., 2008; Naldi et al., 2007). On the one hand, family firms are less likely to employ entrepreneurial strategies because (1) they are risk-averse and less inclined to pursue radical changes since family firms are willing to protect family wealth for future generations, and this behavior is related to risk avoidance (Chirico & Nordqvist, 2010; Naldi et al., 2007), (2) and when family managers are predominant, the top team might lack diversity competences and skills, and they might not be able to integrate and disseminate knowledge, which is vital for driving EO (e.g., Pittino et al., 2018). On the other hand, family firms are more likely to engage in entrepreneurial behaviors due to its (1) focus on the long-term, which allow patient capital investments, and (2) family managers disseminate altruist values toward the firm and act collectively (as a steward), characteristics that might benefit entrepreneurial actions (Chirico, Sirmon, Sciascia, & Mazzola, 2011; Eddleston et al., 2012; Pittino et al., 2018; Zahra et al., 2004). As claimed by Chirico, Sirmon, Sciascia, and Mazzola (2011), “perhaps neither of these nascent perspectives is fully correct,” and they complement that “integrating family and business makes reaping rewards from being entrepreneurial extremely challenging.” Chirico, Sirmon, Sciascia, & Mazzola, 2011, p. 308). Only a few studies have investigated socioemotional wealth (SEW) as a determinant for EO (Hernández-Perlines et al., 2019) or as a moderator for the relationship between EO and performance (Schepers et al., 2014) while it is considered as an antecedent of several family firm outcomes and behaviors (e.g., Berrone et al., 2012; Gomez-Mejia et al., 2011). Hernández-Linares and López-Fernández (2018) claim that the link between SEW and EO has been quietly explored in the family business literature. The focus has been only on the first dimension of SEW (family control and influence). Therefore, to advance the knowledge about the relationship between family firm particularities and EO, it is crucial to consider the SEW nonfinancial goals and whether the relationship between SEW and EO is moderated by the generational stage, whose discussion we explore in the following subsections.

Socioemotional wealth and entrepreneurial orientation

Socioemotional wealth (SEW) is a construct that describes the stock and flows of affective endowments of the dominant coalition in a family business (Gomez-Mejia et al., 2011; Berrone et al., 2012; Swab, Sherlock, Markin, & Dibrell, 2020). SEW can be defined as “… the stock of affect-related value that a family derives from its controlling position in a particular firm” (Berrone et al., 2012, p. 259). Based on the behavioral agency theory, family firms are loss-averse concerning SEW (Gomez-Mejia et al., 2011; Swab et al., 2020). The proponents of SEW claim that it might determine family firms’ behaviors and decision-making processes associated with several outcomes and behaviors such as performance, internationalization, and risk-taking strategies (Berrone et al., 2012; Gomez-Mejia et al., 2011). Hence, family firms, due to the presence of a dominant coalition, will be led to achieve family-centered goals (FCG), both economic and non-economic goals (Kotlar & De Massis, 2013; Chrisman, Chua, Pearson, & Barnett, 2012). Among those FCG, prior studies mention the preservation of a family’s culture, cohesion, and well-being, a long-term orientation toward the survival and control transfer to upcoming generations, preserving family and businesses reputation, securing jobs for family, among other FCG (e.g., Chrisman et al., 2012; Kotlar & De Massis, 2013).

On one side, based on SEW, family firms are considered reluctant to take risks that could jeopardize their SEW priorities, which is expected to make these firms to avoid entrepreneurial activities, such as innovation, proactiveness, and risk-taking. Based on the SEW background, family firms are susceptible to a range of affection and emotions that might nurture parental altruism and managerial entrenchment in the firm (Schulze, Lubatkin, & Dino, 2003), which inhibit EO to flourish (Cruz, Justo, & Castro, 2012). For instance, Llanos-Contreras, Jabri, and Sharma (2019) comment that a low level of EO arises when the family firm prioritizes family-centered goals (FCG) rather than business-centric goals (BCG). Family-centered goals (FCG) consist, among other elements, of the family’s need to maintain the family’s control and influence over the company.

However, other recent empirical evidence indicates that SEW dimensions are a positive driver for EO and its dimensions (e.g., Becerra, Cruz, & Graves, 2020; Calabrò, Santulli, Torchia, & Gallucci, 2020; Hernández-Perlines et al., 2019). The arguments from these studies are that EO is a means for the family firm to achieve its non-economic goals, such as building and improving reputation, providing employment positions for the family, and ensuring transgenerational orientation (Berrone et al., 2012; Gomez-Mejia et al., 2011). With this regard, Irava and Moores (2010) argue that “the pursuit of an EO can simultaneously assist family firms in achieving their nonfinancial objectives.” (Irava & Moores, 2010, p. 235) Moreover, a family firm willing to preserve its SEW engages in longer time horizon investments (patient capital), which favors entrepreneurial orientation (Fang, Siau, Memili, & Dou, 2019). Finally, Calabrò, Santulli, Torchia and Gallucci (2020) highlight that entrepreneurial families are also accountable that “fostering innovativeness is a way to focus on current performance and long-term future returns.” (Calabrò, Santulli, Torchia, & Gallucci, 2020, p. 4)

Recently, Becerra, Cruz and Graves (2020) provided evidence that a greater emphasis on non-economic FCG such as (1) family cohesiveness, supportiveness, and loyalty, (2) family name recognition and respect in the community, and (3) unifying vision for the business and the family, are positively associated with innovation. They argue that non-economic FCG are present in family firms that “are willing to accept higher strategic risks, even in the absence of financial distress conditions” (Becerra et al., 2020, p. 373). Their arguments are centered on prior evidence regarding family cohesion and commitment to the firm’s long-term performance (Eddleston & Kellermanns, 2007). In addition, a family’s willingness to preserve its identity and reputation might be related to a long-term success, which requires the family firm to innovate, act proactively, and engage in risk decisions (Gomez-Mejia, Neacsu, & Martin, 2019; Lumpkin & Brigham, 2011; Miller & Le Breton-Miller, 2005). Regarding economic FCG, such as maintaining family independence and control over decision-making and providing financial security for the family, these authors claim that these priorities might conflict with innovative actions since innovativeness requires a more diversified pool of expertise, knowledge sharing, and participative management practices (Becerra et al., 2020). Ensuring economic FCG also involves reducing available resources to engage in innovative strategies (Schulze et al., 2001). However, their results do not support this conclusion (Becerra et al., 2020). Based on these arguments, we propose the following hypotheses:

Hypothesis 1: There is a positive relationship between socioemotional wealth and entrepreneurial orientation.

Hypothesis 1a: There is a positive relationship between socioemotional wealth and innovativeness.

Hypothesis 1b: There is a positive relationship between socioemotional wealth and proactiveness.

Hypothesis 1c: There is a positive relationship between socioemotional wealth and risk-taking.

Generational stage moderating effect

Following the rationale from Cruz and Nordqvist (2012), we discuss whether the internal factor related to the importance of family-centered goals in the family firm, debated concerning SEW and EO relationship, is contingent on the family firm generational stage (considering first and later-generation family firms). As argued by Cruz and Nordqvist (2012), “family firms go through different stages depending on the generation in control and ... the firms’ strategic behaviors often change from stage to stage.” (Cruz & Nordqvist, 2012, p. 34) This rationale is developed around the generational perspective of family firms, which determines that family members from different generations have particular resources and capabilities to drive strategic behaviors (e.g., Cruz & Nordqvist, 2012; Kellermanns & Eddleston, 2006; Stanley et al., 2019). The findings of the relationship between generational involvement and EO have been mixed. While some studies have found that EO dimensions decrease in family business of later generations (Miller & Le Breton-Miller, 2011), others found that EO dimensions increase (Cruz & Nordqvist, 2012), and found no direct relationship between generational involvement and EO (Kellermanns & Eddleston, 2006; Casillas et al., 2011).

Considering that the generational stage involvement affects the relationship between SEW and EO, prior studies have provided evidence that family particularities play a vital role in fostering EO due to the founder’s presence (Ljungkvist, Boers, & Samuelsson, 2020). This may not happen to later generations that rely less on family particularities and on the founder, and more on resources and knowledge derived from non-family managers’ presence and management practices (Cruz & Nordqvist, 2012). First-generation family firms are founder-centric, meaning that the decision process resides on the founder’s personality, priorities, values, knowledge, and expertise (Cruz & Nordqvist, 2012; Schein, 1983; Zahra et al., 2004). Consequently, an entrepreneurial orientation (innovativeness, proactiveness, and risk-taking) will be attached to the founder’s intentions. In other words, in first-generation family businesses, EO is pursued because of “business opportunities recognized and exploited in a more or less successful way by an innovative founder (Aldrich & Cliff, 2003)” (Weismeier-Sammer, 2011, p. 130).

As long as the family firm moves to the second and later generations, decisions and behaviors become less centralized in the founder’s hands. In addition, family managers’ competencies become more diverse with the involvement of heirs in the management team and the potential presence of non-family managers, even when the founder is still present on the board or involved in daily operations (Cruz & Nordqvist, 2012). Those family firms are expected to rely more on technical expertise and be more able to identify marked trends while engaging in entrepreneurial activities (Zahra et al., 2004; Cruz & Nordqvist, 2012). Hence, as hypothesized by Cruz and Nordqvist (2012), we argue that EO in second- and later-generation family firms is more likely to “reflect the dynamism, growth, and opportunities within their industry” (Cruz & Nordqvist, 2012, p. 37) and, as a consequence, to rely less on SEW priorities or FCG to drive EO strategies. Therefore, we argue the following:

H2: The positive relationship between socioemotional wealth and entrepreneurial orientation will be higher for first-generation than for later-generation family firms.

H2a: The positive relationship between socioemotional wealth and innovativeness will be higher for first-generation than later-generation family firms.

H2b: The positive relationship between socioemotional wealth and proactiveness will be higher for first-generation than later-generation family firms.

H2c: The positive relationship between socioemotional wealth and risk-taking will be higher for first-generation than for later-generation family firms.

Figure 1
Theoretical research model and hypotheses.

METHODOLOGY

Sample

The data were obtained from a survey developed with Brazilian family firms from the textile and clothing sectors through an online questionnaire using Google Forms®. The firms’ population was selected from the EMIS database (formerly known as the ISI Emerging Markets database). In the database, we identified 1,039 firms from the textile and 2,293 from the clothing industry. We excluded firms that we registered as legal regimes of individual entrepreneurs and individual limited liability companies (EIRELI) to select the survey population. After that, we obtained a survey population of 2,886 firms. The selection of a Brazilian textile and clothing sector was motivated by recognizing the economic and social importance of this industry for both industrialized and lesser economically developed countries (Bruce, Daly, & Towers, 2004). For instance, the turnover of the Brazilian textile industry in 2019 was US$ 48.3 billion, employing around 1.5 million people (Associação Brasileira da Indústria Têxtil [ABIT], 2019).

Additionally, it is relevant to search the antecedents of EO in the textile industry because of constant change in the last years, related to global sourcing and high levels of price competition (Bruce et al., 2004), the constant demand for innovation (Costa & Rocha, 2009), and technological advancing (Lee, Hsiao, Chen, & Guo, 2020). Those industry characteristics, aligned to the short product life cycle, high market volatility, and low predictability (i.e., Bruce et al., 2004), reinforce the importance of EO in this context. In addition to that, focusing on one industry or segment enables us to control for exogenous factors associated with an entrepreneurial orientation.

For the survey implementation, we followed most of the recommendations from Dillman (2007). Due to the unavailability of contact information with the companies listed in the database, we search for potential contacts from those in the LinkedIn® professional platform. Initially, companies were sought for subsequent application of filters to select managers with expertise in the direction, management, supervision, or coordination of companies. Approximately 1,300 connection invitations were sent. Of these, around 600 managers accepted the connection invitation and were interested in responding to the survey. We obtained 127 responses collected between January and December 2019, totalizing a response rate of 9.7%. From the 127 responses, we excluded 20 firms based on a self-response question in which we asked the respondent if the firm was considered a family business. Therefore, our analyses are based on a final sample of 107 private family firms.

Measurement of the variables

The questionnaire was translated from English into Portuguese and then translated back into English. The questionnaire is based on validated instruments from published studies. Most of the constructs were captured by multi-item questions. All the instruments are based on a seven-point Likert scale (ranging from totally disagree to totally agree), except for the generational stage involvement (treated as a dummy variable).

Entrepreneurial orientation. We measured this construct considering the main three dimensions, which are: innovativeness (EO_Innov), proactiveness (EO_Proac), and risk-taking (EO_Risk). Each of these constructs is measured with three items adapted from Hughes and Morgan (2007). According to Covin and Wales (2012), the approach proposed by Hughes and Morgan (2007) enables to evaluate the factors that make companies entrepreneurial (or those factors that are manifested by entrepreneurial companies). Thus, since the three dimensions of the EO construct are treated as distinct, the strength of their relationships with particular antecedents and consequences can be uniquely identified using such a measurement model specification (Covin & Wales, 2012). Therefore, our study aggregates from the previous studies (for example, Cherchem, 2017) that investigated EO’s dimensions as a one-dimensional construct.

Socioemotional wealth. Following Gómez-Mejia et al. (2007), socioemotional wealth (SEW) can be defined as “nonfinancial aspects of the firm that meet the family’s affective needs such as the ability to exercise family influence, maintaining family control and the perpetuation of the family dynasty.” Gómez-Mejia et al. (2007, p. 106) We measured SEW using four items of the strategic orientations of small and medium-sized enterprises (STRATOS) questionnaire (Bamberger, 1994), which were validated by several studies such as Schepers, Voordeckers, Steijvers and Laveren (2014). Following Schepers et al. (2014), these questions involve maintaining family traditions and creating or saving jobs for the family, which are seen as proxies for the perpetuation of the family dynasty, as well as the independence in ownership and in management, which by the way indicate the family’s influence and control (SEW) (Schepers et al., 2014). Recently, some of these elements also were used to capture family-centric goals by Becerra et al. (2020).

Generational stage. Family generational stage (1rst_generation) is measured as a dummy variable whether the family members involved in the firm are from the first generation (dummy = 1) or a later generation (second, third, or fourth generations) (dummy = 0) (e.g., Hernandez-Perlines et al., 2021; Ljungkvist et al., 2020). For that, when more than one generation was present simultaneously, we considered the older generation for this variable. For instance, a firm managed by the first and second generations simultaneously was categorized as zero. We used this variable since a first-generation family business, despite the lack of experience, might reap the benefits/advantages of being a family business, which prior studies show might create a unique environment for entrepreneurship. Most of the firms from our sample are managed by the first (54.21%) or/and the second generation (56.07%) (Table 1). This variable was treated as a moderator in our model.

Controls. In line with prior studies, we used several controls. We used control variables that are related to the family firm characteristics. First, we controlled for the family firm ownership considering the absence of minority shareholders (dummy = 1) versus the presence of minority shareholders (dummy = 0) (Ownership). Second, we control for the family members’ actual involvement in the top management team (TMT), considering the ratio of family managers in the TMT divided by the TMT size (FamilyTMT). Concerning organizational variables, we controlled for firm size (Org_size), which was treated as dummy variables based on the number of employees for each of the following categories: (a) up to 50 employees (small firms); (b) between 51 and 250 employees (medium firms); (c) between 251 and 1,000 employees (large firms); (d) above 1,000 employees (large firms). The base category is small-sized firms (up to 50 employees). For the structural model analyses, the variable Org_size was included as a formative latent variable composed of the dummy variables of each category, leaving out the base category mentioned. We used two variables to determine the maturity of the firm, which are firm age (Org_age), measured as the number of years in operation after the foundation, and life-cycle state (Life-Cycle), measured considering the five classes also used by other authors (Brettel, Chomik, & Flatten, 2015; Lumpkin & Dess, 1996), which are startup/conception, market entrance, growth, consolidation, and maturity based on a description provided by each of these cycles. For the structural model analyses, the variable Life-Cycle was included as a formative latent variable composed of the dummy variables of each category, leaving out two base categories, being the first two stages (startup/conception and market entrance). Finally, a control variable named ‘Unpredictability’ is measured based on a five-item scale developed by Gordon and Narayanan (1984) and validated by several studies since a firm environment has been shown to affect EO.

Data analyses methods

As a data analysis method, we applied the multivariate technique of structural equation modeling (SEM-SmartPLS). This technique has some advantages: it estimates reliably complex models with fewer observations in comparison to regression analysis, for example, and does not impose a data distribution assumption (Hair, Hult, Ringle, & Sarstedt, 2013); in addition, it has been applied in the management and family business areas (Nitzl, 2016; Sarstedt, Ringle, Smith, Reams, & Hair, 2014).

We developed a post hoc test using GPower 3.1.9.2 software (Faul, Erdfelder, Lang, & Buchner, 2007) to analyze the suitability of our sample size to the application of SmartPLS (Nitzl, 2016). Considering the most complex model with nine predictors as well as (a) a statistical power of 0.8 (20% type-II error) and a (b) 5% significance level (type-I error), we would detect a medium relative effect (f² higher than 0.159) as statistically significant.

Before testing the hypotheses, we addressed validity concerns regarding the possibility of common method bias. We conducted Harman’s single factor test to explore common method bias. We obtained three factors with an eigenvalue higher than one, accounting for 70% of the variance, where the first factor accounts for 39% of the items’ variance.

DATA ANALYSIS

Descriptive statistics

Our survey respondents are predominantly composed of firms with all the shares on the controlling family’s hands (88.79%) (see Table 1). In 80.37% of the firms, the chief-executive officer (CEO) is a family member. Our sample firms are managed mainly by the first and second generations, and in terms of size, they are mainly medium- and large-sized family businesses (83.18%). In terms of size, respondents mentioned that the firm is mainly in the consolidation and maturity stages, respectively 42.06% and 29.9%. Regarding our respondents, they are working for more than 10 years in family firms, and most are non-family managers (65.30%). In terms of their position, about 33% are CEOs or directors, about 32% are managers, and 18% are senior coordinators. Concerning their hierarchical level, 23.65% are in Tier 1 and 49.53% in Tier 2.

Table 1
Sample’s descriptive information

Note. * It can be more than 100%, considering that more than one generation of the family might be active in management. Tier 1 are those managers that report directly to shareholders and the board of directors, and Tier 2 are managers that report directly to the top management team.

Panel A: Controlling family ownership				Panel E: Size (employees)
There are minority shareholders	12	11.21%		Up to 50	18	16.82%
Family owns 100% of the shares	95	88.79%		Between 51 and 250	42	39.25%
				More than 250	47	43.93%
Panel B: Percentage of family members in the TMT
Up to 25%	19	17.76%		Panel F: Firm life cycle
More than 50% but less than 100%	19	17.76%		Commercialize	7	6.54%
100%	38	35.51%		Growth	21	19.63%
				consolidation	45	42.06%
Panel C: Is the CEO a family manager?				Maturity	32	29.91%
Yes	103	96.26%
No	4	3.74%		Panel G. Respondents hierarchy
				Tier 1	36	23.65%
Panel D: Generations in management*				Tier 2	53	49.53%
1st generation	58	54.21%		Other	18	16.82%
2nd generation	60	56.07%
3rd generation	13	12.15%
4th and later generation	5	4.67%

Measurement model

We first developed the validation of the measurement model based on the steps recommended by Hair, Hult, Ringle and Sarstedt (2013). We analyzed the outer loadings, average variance extracted (AVE), and Cronbach’s alpha for convergent validity and composite reliability (CR) for internal consistency. We examined the discriminant validity based on the cross-loadings (level indicators), Fornell-Larcker criterion (Fornell & Larcker, 1981), and heterotrait-monotrait ratio (HTMT). As we present in Table 2, the latent variables’ AVE and CR are respectively higher than 0.5 and higher than 0.7. In terms of discriminant validity, we show that AVE’s square roots are greater than the correlations between the latent variables (Hair et al., 2013), results that are consistent with the HTMT ratio (below 0.85). We also show the cross-loadings in Table 3, which also suggest convergent and discriminant validity. We finally assess multicollinearity in the inner model evaluation considering the variance inflation factor (VIF), which indicates that multicollinearity does not bias our conclusions.

Table 2
First-order latent variable correlations

Note. The diagonal values are the square roots of the average variances extracted; because these values are higher than the correlations between the latent variables (values outside the diagonal), there is discriminant validity (Hair et al., 2013). The heterotrait-monotrait ratio (HTMT) values are all below 0.850, being the maximum value presented at 0.825. This parameter also indicates discriminant validity.

	1	2	3	4
1. EO_Innovativeness	0.933
2. EO_Proactiveness	0.745	0.892
3. EO_Risk-taking	0.663	0.547	0.848
4. SEW	0.272	0.218	0.205	0.845
Cronbach’s alpha	0.925	0.874	0.806	0.803
Composite reliability	0.952	0.922	0.884	0.880
Average variance extracted	0.870	0.797	0.719	0.714

Table 3
Cross loadings between the items and the construct

Note. We excluded the Sew_2 indicator because it lacks convergent and discriminant validity. This item indicated “Creating and maintaining jobs for family members.”

	EO_Innovativeness	EO_Proactiveness	EO_Risk-taking	SEW
EO_Innov1	0.923	0.706	0.656	0.288
EO_Innov2	0.948	0.688	0.617	0.203
EO_Innov3	0.926	0.688	0.578	0.264
EO_Proac1	0.679	0.896	0.509	0.191
EO_Proac2	0.638	0.890	0.467	0.230
EO_Proac3	0.674	0.891	0.482	0.160
EO_Risk1	0.443	0.337	0.833	0.144
EO_Risk2	0.577	0.494	0.884	0.163
EO_Risk3	0.701	0.594	0.824	0.227
Sew1	0.137	0.138	0.060	0.673
Sew3	0.227	0.201	0.115	0.909
Sew4	0.287	0.203	0.277	0.929

Structural model

Supported by Hair et al.’s (2013) recommendations, we developed the structural equation model analyses. First, we analyzed the path coefficients considering both the size and statistical significance using the following parameters: bootstrapping procedure with 5,000 repetitions, bias-corrected confidence level, and two-tailed tests (Hair et al., 2013). We also present the effect size coefficient (f²). We tested the moderating effect based on the statistical significance of the moderation variables and interpreted it graphically. We used the multiplicative term as the moderation variable. We present these results in Table 4.

First, our independent and control variables explain a large amount of the variance (R²) of innovativeness (R²= 0.264) and risk-taking (R²= 0.210) and a medium level of the variance of proactiveness (R²= 0.135), taking into account the parameters from Cohen (1988) for social sciences. Regarding our control variables, we suggest that unpredictability is positively and statistically significantly associated with innovativeness and risk-taking. These results are consistent with prior literature (e.g., Casillas et al., 2011; Lumpkin & Dess, 2001), considering that firms that face an uncertain market employ EO strategies. In addition, we also found a statistically significant association between life cycle and EO dimensions, supporting that mature firms (from the stages of growth, consolidation, and maturity) are more entrepreneurial-oriented than firms from startup/conception and market entrance stages. The other control variables (ownership concentration in the family’s hands, the ratio of family managers in the top management team, firm age, and firm size) were not statistically significant.

With respect to our hypothesis, our results support that the association between socioemotional wealth (SEW) and the three dimensions of an entrepreneurial orientation is positively and statistically significant: innovativeness (β = 0.284; p-value < 0.007), proactiveness (β = 0.219; p-value < 0.045), and risk-taking (β = 0.209; p-value < 0.050). Regarding the size of the effect, SEW presents a medium effect (f² = 0.117) on innovativeness and a small effect on proactiveness (f²= 0.060) and risk-taking (f²= 0.059). Hence, although prior literature indicates the influence of the dark side of family on entrepreneurial strategies (e.g., Cruz et al., 2012; Schulze et al., 2003; Schepers et al., 2014), our findings suggest that family firms that are willing to preserve the family’s independence over ownership and management, as well as the family’s tradition over time, are more likely to innovative, behave proactively, and pursue risk-taking strategies than those family firms in that SEW non-economic goals do not have a high level of importance (e.g., Becerra et al., 2020; Gomez-Mejia, Cruz, Berrone, & Castro, 2011; Hernández-Perlines et al., 2019). Therefore, different from Schepers et al. (2014), we show evidence about SEW’s bright side on entrepreneurial orientation (long-term orientation, employee commitment, emotional attachment), which confirms our hypotheses H1a, H1b, and H1c.

Table 4
Structural equation modeling results

Note. Classification of Cohen (1988): small effect (f² = 0.02), medium effect (f² = 0.15), and large effect (f² = 0.35). Life-Cycle, Ownership, FamilyTMT, Unpredictability, Org_age, and Org_size are the control variables in our model.

	H	β	|t-statistic|	p-value	f2	R2adj
SEW -> EO_Innovativeness	H1a	0.284	2.733	0.007	0.117	0.264
1st Gen -> EO_Innovativeness		0.186	2.185	0.029	0.043
SEW*1st Gen -> EO_Innovativeness	H2a	-0.212	2.221	0.027	0.063
Life-Cycle -> EO_Innovativeness		0.245	2.874	0.004	0.086
Ownership -> EO_Innovativeness		-0.149	1.711	0.088	0.031
FamilyTMT -> EO_Innovativeness		0.060	0.713	0.476	0.005
Unpredictability -> EO_Innovativeness		0.237	2.004	0.046	0.077
Org_age -> EO_Innovativeness		0.084	1.126	0.261	0.009
Org_size -> EO_Innovativeness		0.074	0.569	0.569	0.008
SEW -> EO_Proactiveness	H1b	0.219	2.008	0.045	0.060	0.135
	H	β	|t-statistic|	p-value	f2	R2adj
1st Gen -> EO_Proactiveness		0.176	1.630	0.104	0.033
SEW*1st Gen -> EO_Proactiveness	H2b	-0.149	1.404	0.161	0.027
Life-Cycle -> EO_Proactiveness		0.187	1.990	0.047	0.043
Ownership -> EO_Proactiveness		-0.065	0.671	0.503	0.005
FamilyTMT -> EO_Proactiveness		-0.051	0.544	0.587	0.003
Unpredictability -> EO_Proactiveness		0.151	1.206	0.229	0.027
Org_age -> EO_Proactiveness		-0.029	0.332	0.740	0.001
Org_size -> EO_Proactiveness		0.141	0.840	0.401	0.023
SEW -> EO_Risk-taking	H1c	0.209	1.961	0.050	0.059	0.210
1st Gen -> EO_Risk-taking		-0.121	1.239	0.216	0.017
SEW*1st Gen -> EO_Risk-taking	H2c	-0.208	2.395	0.017	0.057
Life-Cycle -> EO_Risk-taking		0.208	2.021	0.044	0.058
Ownership -> EO_Risk-taking		-0.079	0.980	0.328	0.008
FamilyTMT -> EO_Risk-taking		0.099	1.005	0.315	0.013
Unpredictability -> EO_Risk-taking		0.251	2.277	0.023	0.081
Org_age -> EO_Risk-taking		-0.066	0.711	0.478	0.005
Org_size -> EO_Risk-taking		0.226	0.994	0.321	0.065

Regarding the effect of the family’s generational stage involvement in the firm (moderating hypotheses), our results only support a statistically significant effect on the relationship between SEW and innovativeness and SEW and risk-taking (see Figure 2). Unlike our hypotheses (H2a, H2b, H2c), our results provide evidence that the positive relationship between the level of SEW and the dimensions of EO (particularly innovativeness and risk-taking) is weaker for first-generation family firms compared with later-generation family firms. Figure 2 shows that the effect of a high SEW level in innovativeness is similar for first- and later-generation family businesses. The line for later-generation family firms’ slope is much more inclined than for first-generation ones, which indicates that SEW is a relevant ingredient for innovativeness in later-generation family firms. Regarding risk-taking, our interpretation is aligned with the one presented in Figure 2 for later-generation family firms. Regarding first-generation family firms, there seems to be no benefit from SEW for enhancing risk-taking behaviors (see the angle of inclination in the first-generation line). In other words, different from innovativeness, for risk-taking as an outcome, high levels of SEW seem to benefit only firms in later generations. Finally, our analyses do not provide statistically significant results for the moderation effect considering SEW and proactiveness, which indicates that proactiveness is not an issue of the generational stage.

We expected SEW to be a relevant source for fostering EO strategies for first-generation family firms since the founder’s decision processes are centralized (e.g., Ljungkvist et al., 2020). In that sense, EO’s achievement would be a means for perpetuating his/her control and independence over decisions and legacy or tradition. However, this bright side of SEW was not evidenced, and on the other hand, we did not find the dark side influence (Schepers et al., 2014). This result might indicate that the focus on innovativeness and risk-taking might reside in the founder’s personality and characteristics (Ljungkvist et al., 2020; Schein, 1983). Besides, the first generation is expected to innovate in products and processes and take more risks due to environmental conditions such as market hostility or turbulence (Casillas et al., 2011) since they wish that the firm survives. In addition, maybe SEW is not yet accumulated in the sense that it can drive family firm decisions and behaviors (Berrone et al., 2012; Chua, Chrisman, & De Massis, 2015).

Figure 2
Moderating effect. Panel A: SEW and innovativeness. Panel B: SEW and risk-taking.

For later-generation family firms, we expected that they were less dependent on the affective needs and family-centric goals as drivers for engaging in innovative and proactive actions and taking risks. Later generations of family firms have diversified skills and competencies (due to the mix of family and non-family managers), decentralized structure, and more formal and informal mechanisms, which might drive EO strategies (Cruz & Nordqvist, 2012; Zahra et al., 2004). However, our results support that SEW seems to be a bright ingredient for later-generation family firms of to engage in innovative strategies and take risks. For instance, we contradict Stanley et al. (2019) that in “the later stages, family firms are often risk- and change-avoidant and may simply want to maintain the status quo (Kellermanns & Eddleston, 2006) or even to avoid opportunities in order to maintain SEW.” (Stanley et al., 2019, p. 180) In other words, the employment of EO strategies is a mean that later-generation family firms have for achieving family-centric goals such as the family’s power and prominence and tradition toward the organization.

FINAL REMARKS

This study investigated the association between socioemotional wealth (SEW) and the three dimensions of entrepreneurial orientation (EO): innovativeness, proactiveness, and risk-taking. We also explored the moderating role of the family businesses’ generational stage (first and later generations). For that, we collected a survey with 107 family firms from the textile and clothing manufacturing industry and provided evidence that SEW is positively associated with the three dimensions of EO. Nonetheless, we only find a moderation effect of the generational stage for the relationship between SEW and innovativeness and risk-taking. Different from what we have hypothesized, we showed that a high SEW effect on risk-taking is stronger for family firms in later generations than first generations. For innovativeness, the level of SEW seems to be significant only for later-generation family firms.

This paper provides evidence about one of family firms’ main particularities in driving entrepreneurial orientation by looking at SEW and FCG. We also shed more light on the complexity of SEW-EO relationship by looking at each of the three defining dimensions for EO (innovativeness, proactiveness, and risk-taking) and a moderating effect (considering first versus later generational stage). Hence, we contribute to the controversial findings regarding SEW-EO relation from prior literature (Hernández-Perlines et al., 2019; Schepers et al., 2014) and to the call for more studies regarding economic and non-economic family-oriented goals (Hernández-Linares & López-Fernández, 2018). These empirical findings are also important for advancing the SEW literature, particularly concerning SEW’s consequences in family firms’ decisions and behaviors (Chua, Chrisman, & De Massis, 2015; Swab et al., 2020). We also provided evidence about how SEW is linked to each constituent dimension of EO, providing a disaggregated view on this issue. However, it is important to highlight that the three dimensions constitute an entrepreneurial orientation (Lumpkin & Dess, 1996).

Additionally, there is a claim for more evidence about how EO emerges in developing countries such as Brazil since most of the evidence is from North American and European countries, with few exceptions (e.g., Ling et al., 2019; Wales et al., 2013). As in other Latin American countries, firms in Brazil face several challenges and drawbacks during their existence. These issues can be explained by the instability and complexity of the Brazilian environment, derived from economic, political, and social factors (Xu & Meyer, 2013). Hence, to be long-lived, those firms have to foster entrepreneurial orientation and act in a resilient manner. So EO can be seen as a pivotal issue for Brazilian family businesses’ survival and sustainability. In addition to that, prior studies in Latin America and Brazil also suggest that a family business’ culture is distinctive and might largely explain family business heterogeneity (Frezatti, Bido, Mucci, & Beck, 2021; Gupta & Levenburg, 2010), which characteristics have implications on different outcomes such as governance strategies, strategic orientations, and initiatives (i.e., risk-taking, innovativeness), as well as the performance of those firms. Our study also adds to this discussion by investigating the consequences of SEW intention and the family business generational stage; however, these topics deserve further research.

This paper also provides some implications to practitioners. Since EO has been shown as a determinant for a family firm’s growth and performance, owners and managers should understand how to nurture EO through the family firm’s generational stages. SEW seems to be a relevant determinant for EO dimensions, especially in the later generational stage, which shows that preserving a family’s tradition, control, and influence drives family businesses’ entrepreneurial strategies.

This study is subject to some limitations. First, we collected a survey based on Likert scale items using a single respondent for each firm. We also focused on a specific segment of organizations (textile and clothing industry) to cope with exogenous factors related to EO. Maybe future studies could provide evidence about how EO emerged in different industries. Furthermore, we used one instrument for SEW to capture the intention to preserve nonfinancial FCG, while other studies might use a multidimensional scale to consider different dimensions of SEW (e.g., Becerra et al., 2020; Hernández-Perlines et al., 2019). In addition, our sample size can be perceived as small; however, based on power analyses (Faul et al., 2007), it is considered sufficient for the employed data analyses. Future studies could provide evidence about a larger and multi-industry sample and investigate the EO phenomena into one organization calling for a qualitative perspective.

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