Firms financial strength during crisis periods: does “familiness” matter?

Abstract

Purpose

In this paper we propose to study the differences among family and non-family-firms in relation to its financial strength, and therefore its potential position to resist in front of financial crisis and receive financial support or conditions by public or private institutions.

Design/methodology/approach

We used multiple hierarchical regressions on a sample of 137 Spanish medium-sized firms (SMEs).

Findings

We observe that the perspectives and idiosyncratic characteristics of family-firms (strongly influenced by their socioemotional wealth) will affect the way these companies invest and operate in the market, which would be more related to efficiency because of their higher willingness to continue the legacy of the business and their weak risk-bearing attributes.

Research limitations/implications

Our study adopts a measure of familiness with a dummy variable, and not as a continuous variable as proposed by recent research. Therefore, our results although relevant and significant for the family firm literature, must be viewed carefully. Additional research could also retest some prior studies to depict differences caused by “real” family firm involvement.

Practical implications

Under a non-munificent environment, the financial strength maintained by firms will be highly relevant since this context could likely stress and influence their immediate future and viability, overcoming and blurring any other characteristic present in the firm or its managers.

Originality/value

This paper contributes to the family firm literature by offering insights into the nuanced dynamics between family and non-family firms during economic downturns, specifically examining their financial strength when different strategic options are pursued and when firms are managed by different type of managers.

Citation

Villagrasa, J., Escribá-Esteve, A., Donaldson, C. and Sánchez-Peinado, E. (2024), "Firms financial strength during crisis periods: does “familiness” matter?", Journal of Family Business Management, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/JFBM-02-2024-0042

Introduction

The amount of money budgeted by the European Union for Spain as support to overcome the Covid-19 crisis has been €140,000m through the so-called Recovery and Resilience Facility, of which €60,000m corresponds to non-reimbursable transfers and €80,000m to loans (European Central Bank, 2021). This amount contrasts with the €41,300m granted in the 2008–2009 crisis to the same country through the so-called European Stability Mechanism, which was provided only as loans and only to financial firms (European Central Bank, 2021). The difference is of almost four times the initial quantity. But the public institutions learned the lesson, and in the presence of (again) such a deep global crisis, it was not possible to operate in the same way as in the previous one: only supporting financial institutions and not the rest of the firms of other sectors (Royo, 2020).

We examine the differences between family and non-family firms regarding their financial strength, and therefore the potential better position of the first ones to receive support from European institutions. In particular, we argue that the own hard-to-duplicate capabilities of the family firms – or what some scholars call “familiness” (Habbershon and Williams, 1999) or “socioemotional wealth” (SEW) (Gomez-Mejia et al., 2007; Davila et al., 2023) – will affect the way these companies invest and operate in the market, which would be more related to efficiency because of their higher willingness to continue the legacy of the business and remain operating (Gimeno et al., 1997). This, in turn, means that these organizations will act more carefully with their finance, holding greater cash levels (Jensen, 1986; Caprio et al., 2020) and relying less on debt as a form of financing (Anderson and Reeb, 2003; Fang et al., 2021). We evaluate this assumption using the virulent crisis period of 2008–2009 as a time frame, arguing that in a non-munificent environment, the financial strength maintained by firms will be even more relevant because this context could likely stress and influence their immediate future and viability (Amato et al., 2023; Iwasaki, 2014). In this way, we find that family firms' prospects will keep on dominating the financial behavior shown by this type of organizations (even) during crisis periods. Therefore, we argue that these results could be similarly, extrapolated to the recent Covid-19 crisis, suggesting deferential treatment to these companies in terms of the potential business funding received and support provided by governmental organizations. Furthermore, the beneficial impact of these companies on the economy is well-supported by the literature, as evidenced by their lower likelihood of downsizing compared to non-family businesses (Sanchez-Bueno et al., 2020). Likewise, family firms usually behave more responsibly toward their employees as well as the environment, and due to their particular ownership structures, they can make rapid decisions and respond to changes and crisis quicker and less-bureaucratically than non-family firms (Kraus et al., 2020).

Following Miroshnychenko et al. (2021), Sharma et al. (1997) among others, we argue that considerable understanding can also be gained by appending strategic management insights into the family firm research approach. Hence, in this study, we also assessed whether other characteristics related to organizations' scope of operation (such as the internationalization or diversification of a firm) or their managers (especially the educational level or average age of the top management teams (TMTs)) affected the financial strength of these companies, and especially during the aforementioned crisis period. In other words, we wanted to examine whether the financial strength of family businesses is similar (or higher than non-family firms) if they decided to operate only in one country or in several countries, whether they focused their attention on a single industry or on several and whether they had managers with certain characteristics or others (De Massis et al., 2021). Thus, we (try to) isolate the varied factors responsible for the best financial situation of these firms (versus the non-family ones), capturing the drivers for the preservation or enhancement of such a situation and examining the differences between them (King et al., 2022).

Our findings suggest that family firms, driven by their commitment to preserving the legacy of the business, may exhibit greater efficiency and resilience in navigating economic downturns compared to non-family firms. Besides, the financial strength maintained by family corporations emerges as a critical factor influencing their viability and susceptibility to external pressures, acting as a “regulatory system” that would be automatically activated in front of non-family business behaviors (such as the excess of leverage and decline of the financial strength of the company). Therefore, the eligibility of these firms to receive the aforementioned institutional financial support will be discussed in this paper.

The remainder of the article is structured as follows. In the following sections, the theoretical framework as well as the hypothesis development will be introduced. Next, the methodology used for data collection and analysis carried out will be detailed, the key findings of the study will be presented and the implications of these results will be discussed, ending with a comment on the limitations of the work, practical implications and future lines of research.

Theoretical framework

The economies of most nations are dominated by family firms (Astrachan and Shanker, 2003). These organizations are unique, have inherent features and are sources of distinct advantages and disadvantages in such economic systems (Tagiuri and Davis, 1996). Their uniqueness stems from the fact that often parents and children may be part of the same family, members of the same ownership group and team members of the same management group (Diaz-Moriana et al., 2020). The literature on family firms has extensively acknowledged the differences across such firms (Amato et al., 2023; McConaughy et al., 2001; Miroshnychenko et al., 2021). While most family companies are small, some are relatively large, being able to grow into large publicly listed entities, such as S&P 500 firms (Anderson and Reeb, 2003), dominating their respective industries (Tagiuri and Davis, 1996). They tend to contribute considerably to the national product and employment in an economy, which underlines their prevalence and importance in society [1] (Astrachan and Shanker, 2003). However, further studies about their specific idiosyncratic characteristics and its relationship with the environment are awaiting further study by the literature (Miroshnychenko et al., 2021).

The uniqueness of family firms is also on account of the significant role played by emotions in their functioning (Baron, 2008). Emotions may be present in all types of firms but are likely to be more dominant in family firms (Gomez-Mejia et al., 2007). SEW is the emotion-related factor that captures this special essence of family firms and is believed to be the single most important feature for separating family firms from other organizational forms (Berrone et al., 2010; Davila et al., 2023). It refers to “the non-financial aspects of the firm that meet the family's affective needs, such as identity, the ability to exercise family influence, and the perpetuation of family dynasty” (Gomez-Mejia et al., 2007, p. 106). In this sense, the literature argues that the preservation of SEW exists outside the realm of purposeful organizational activities and, therefore, may cause family firms to consider their firms as something more than just a “source of income” but also as a context for family activities and the embodiment of their pride and legacy (Meyer and Zucker, 1989). In fact, as stated by McConaughy (2000, p. 121), managers of family firms “have superior incentives for maximizing firm value and, therefore, need fewer compensation-based incentives.” These managers do not prioritize their individual interests but those of the organization. Thus, family ties are commonly associated with weak risk-bearing attributes (e.g. Fang et al., 2021), affecting how these companies invest, which will be closely related to efficiency because of their higher willingness to continue the legacy of the family business (Gimeno et al., 1997). This supposition is confirmed by several studies, such as Caprio et al. (2020), who argue that family firms generate greater cash levels, which make them rely less on debt in the form of financing, and Anderson and Reeb (2003), who anticipate their likelihood of default to be lesser and value to be higher, as these firms have greater reliance on self-financing than non-family firms. For its part, Moreno-Menéndez and Casillas (2021) summarize this phenomenon suggesting that family businesses hold different growth patterns than non-family firms, due to their different characteristics and the effect of SEW.

Hypothesis development

Agency theory establishes that a high concentration of ownership leads to risk-avoiding strategic choices because of the governance structure of such firms. The reason is simple, when the capital is widely dispersed, managers have more possibilities of engaging in opportunistic behaviors. However, greater concentration of capital would imply superior monitoring of the manager's work by the shareholders. In the case of family firms, they exhibit a higher ownership concentration than non-family firms, therefore expecting a higher risk aversion in their decisions (Becerra et al., 2020). Likewise, there are other reasons to believe that risk avoidance is stronger in this type of firms (De Massis et al., 2021). First, family ties correlate with weaker risk-bearing (Fang et al., 2021), influencing investment strategies and efficiency choices of these firms due to its commitment to the family legacy (Gimeno et al., 1997). Second, in family businesses, the management tends to invest its wealth in the firm and thus assumes full financial repercussions of failed investments (Gedajlovic et al., 2004). Third, in family firms, apart from the family's current wealth, the financial and social well-being of future generations is also at stake (Schulze et al., 2002). For example, family name and reputation, often built-up over generations, is in play in such firms (Bartholomeusz and Tanewski, 2006; Yu et al., 2022). In contrast, this is not the case in other types of firms, where the connection to a wider family and to previous and future generations is less clear (Erdogan et al., 2020). Based on these findings, we propose the following hypothesis:

H1.

Family ownership positively affects an organization's financial strength.

We evaluate this hypothesis using the virulent financial crisis period of 2008 and 2009, which has been characterized by its non-munificent features. This type of environment comprises a relative scarcity of resources (Keats and Hitt, 1988), fewer strategic options, fewer opportunities for expansion and development, more competitive pressure and unfavorable, complex and variable external forces for companies to develop their activities (Gul, 2020). Hence, firms must deal with overall poorer results and survival problems, as more resources are needed than are available under such environmental conditions (Zhang et al., 2020).

Therefore, in a non-munificent environment, the financial strength of these firms will be even more relevant, as this context may influence their immediate future and viability (Amato et al., 2023; Iwasaki, 2014). The literature widely agrees that family firms are positively related to higher values and financial position; however, researchers have paid scant attention to specifically evaluate these findings in the context of the 2008–2009 financial crisis, and more concretely with the goal of establishing conclusions for the public financing of such companies. Prior research disagrees on the exact timing of this economic shock. Cole and White (2012) clarify the extent of this crisis by illustrating the number of banks that went bankrupt during those years. They argue that only 31 banks went bankrupt between 2000 and 2007, whereas 30 banks failed during 2008 and over 100 bank failures occurred in 2009. Thus, there is wide acceptance in the literature to consider those years a turning point for the Spanish industry (for instance, see Instituto de la Empresa Familiar (2022) or International Monetary Fund (2009) among others). Therefore, understanding the relationship between family ownership and a firm's financial strength in this specific context may help us better understand the differences between both types of organizations (family firms and non-family firms), unravel whether their characteristics and preferences are accentuated during these periods and even anticipate repercussions on their potential discontinuance.

Additionally, we establish that the effect of family ownership on a firm's financial strength does not occur in isolation, as it is also affected by several other factors, such as an organization's scope of operations and the characteristics of its key players. In other words, we anticipate that the financial strength of all family businesses will not be the same, as it is also impacted by factors like whether they operate only in one country or in several countries, whether they focus their attention on a single industry or on several and whether they have only highly educated managers or they have managers of varied educational levels (De Massis et al., 2021; Miroshnychenko et al., 2021).

For instance, in the case of diversification prior literature anticipates that mitigating risk levels through corporate diversification may be an effective investment strategy for family firms (Berger and Ofek, 1996; Hafner, 2021 among others). Internationalization strategies would follow a similar purpose. However, family firms are less internationally oriented, attributing this fact to agency conflicts between majority family shareholders, who are better positioned to reap the private benefits of control, and minority shareholders, who stand to benefit from internationalization and reduced family control (Arregle et al., 2021).

This study will eschew conjectures regarding the relative success probabilities of both types of strategies, concentrating instead on analyzing the effect of internationalization and diversification on the relationship between family ownership and a firm's financial strength. With this, we expect to contribute to a better understanding of whether family ownership would act as the main and principal cause of a firm's financial strength or whether the breadth of the company's focus would also affect this outcome.

Especially in the non-munificent context in which we set our analysis; we anticipate a positive moderating effect of both the variables. We do so because when a firm opts to internationalize its activities, it obtains greater access to exploit economies of scale, lower labor and material costs and bigger market scope (Alayo et al., 2021). Likewise, when it opts to diversify, it increases the number of markets it has access to, reduces the impact of fraud and bad information on its portfolio and improves its capacity to respond to market volatility (Anderson and Reeb, 2003; King et al., 2022). Empirical evidence correlates both variables with superior financial performance, despite the inherent complexities of regulatory compliance, cultural or business adaptation and strategic resource allocation, necessitating meticulous planning and dynamic capability leveraging (Pukall and Calabrò, 2014). Thus, we predict that both actions will potentially minimize the global risk faced by such firms and increase their opportunities for success because of their access to more heterogeneous markets, which will provide them with more prospects for prosperity and growth (Sanchez-Bueno and Usero, 2014). Based on prior arguments, next we propose hypothesis 2 and hypothesis 3:

H2.

Firm internationalization positively moderates the relationship between family ownership and organization's financial strength.

H3.

Firm diversification positively moderates the relationship between family ownership and organization's financial strength.

Meanwhile, based on the prior literature on the upper-echelons theory (Hambrick and Mason, 1984), we also hypothesized that TMT characteristics, and in particular TMT educational level and TMT average age, would influence the relationship between family ownership and firm's financial strength. Upper-echelons theorists emphasize that organizational outcomes (both strategies and effectiveness of its implementation) are viewed as reflections of values and cognitive biases of an organization's powerful actors (c.f., Villagrasa et al., 2018). In the specific context of family firms, TMTs are argued to be even more responsible for strategic decisions (Villagrasa et al., 2024). Indeed, family managers have the authority and legitimacy to pursue what they perceive as being the “best option” (Gedajlovic et al., 2004), making decisions that are less based on closely calculated risks, less based on a systematic way and with less incorporation of outsiders' perspectives and opinions (Schulze et al., 2003).

We argue that highly educated managers will leverage more because of their inherent characteristics, such as higher confidence in investments, more openness to change, better ability to deal with ambiguity and complexity and more facilities to provide solutions (Barker and Mueller, 2002; Calabrò et al., 2021; Herrmann and Datta, 2005), thereby negatively affecting the financial strength of their family firms. By contrast, we anticipate that older managers will leverage less (positively affecting financial strength), as they tend to choose more conservative capital structures (Chen et al., 2010), take less risk (Barker and Mueller, 2002; Hambrick and Mason, 1984), be more prudent with their actions and behavior (Wiersema and Bantel, 1992), be less able to organize information effectively (Calabrò et al., 2021; Taylor, 1975) and possess less physical and mental stamina to seize perceived opportunities (Hambrick and Mason, 1984).

Furthermore, in the non-munificent context (in which our study is set) with an elevated uncertainty and variability, scarcity of opportunities, lack of demand, intense competition and risk (Amato et al., 2023; Instituto de la Empresa Familiar, 2022; International Monetary Fund, 2009), we postulate that this higher/lower leverage (especially the one dragged from the prior benevolent cycle) will have an even clearer negative/positive effect on a firm's financial strength. This argument is supported by Claessens et al. (2000, p. 23), who assert that firms' difficulties during crisis periods are not produced by these “external shocks, including a drop in aggregate demand […] (but they are) apparent well before the crisis and the risky financial policies pursued by these firms (are the ones which truly) left them vulnerable.” Based on these arguments, we articulate hypothesis 4 and hypothesis 5 (which can be seen graphically represented together with hypotheses 1, 2 and 3 through Figure 1):

H4.

TMT educational level negatively moderates the relationship between family ownership and organization's financial strength.

H5.

TMT average age positively moderates the relationship between family ownership and organization's financial strength.

Method

To examine the proposed hypotheses, we used multiple hierarchical regressions on a sample of 137 Spanish medium-sized firms (SMEs) (over one hundred and up to five hundred employees). This dataset contains primary data obtained from the chief executive officers (CEOs) of each organization (who previously received a pre-notice letter explaining the baseline of our research and where we assured them total confidentiality) and secondary data collected from the SABI Informa Database (Bureau Van Dijk), the most important source of business, accounting and financial information in Spain. Our sample was formed by SMEs because we intended to be as representative as possible of all Spanish companies, of which about 99.9% are SMEs. These companies are large enough to possess a formal organizational structure and pre-established decision-making processes, while they usually lack the excess of resources, organizational structure and support functions that bigger companies preserve for their daily-basis operation (Lubatkin et al., 2006). Consequently, managers hold an even more relevant position in these firms (Villagrasa et al., 2024).

We selected a random sample of 1,000 SMEs, of which 60% were from the manufacturing sector and the remaining 40% were from the service sector. In addition, due to the significance of family ownership in this study, we checked for a balance of this factor in our sample. Hence, among all the organizations of our dataset we found a similar percentage of family and non-family firms (55% family vs 45% non-family organizations). In total, we received 190 filled questionnaires (representing a response rate of 19%). Of this figure we got to eliminate a total of seven firms for reasons of incompleteness. Consequently, our final sample was composed by a total number of 183 valid questionnaires (meaning a response rate of 18.3%). However, the test of our hypotheses demanded the combination of subjective and objective data from the organizations. Thus, we complemented the information gathered from the questionnaires (representing the subjective data) with organizations' financial statements obtained from SABI Informa Database (representing the objective data). Unfortunately, we had to drop 46 firms from our final sample as they did not have full information available (i.e. they did not possess both subjective and objective data). Therefore, eventually this sample embraced full information from 137 firms (representing a valid response rate of 13.7%). Among them, 57.66% were family firms, whereas 42.34% were not – which represented a fairly close percentage to our original sample of 1,000 organizations (see Table 1). However, for the sake of completeness we developed a comparison t-test between them which did not show significant differences among both groups (p < 0.05). Additional tests comparing early and late respondents, and sectoral distributions, also found no significant differences (p < 0.05). We further analyzed residual behavior, variable linearity and collinearity, finding no significant issues. Full analyses are available upon request.

Variables

Dependent variable: “Firm's financial strength.” We use the Finance MORE ratio, an equity ratio commonly used by scholars and practitioners to determine the financial situation or strength of a company, as it includes predictions of yield spreads, financial leverage and other relevant accounting information (Campbell and Taksler, 2003). This ratio was obtained from the SABI Informa Database.

Independent and moderating variables: “Family ownership.” We use a single dummy variable. To avoid a simple differentiation between companies that have family members on their governing bodies and firms that do not, we provided a full definition of what a family firm means as suggested by prior research (e.g. Daspit et al., 2021; Sharma and Chrisman, 1999). Respondents were asked to categorize their corporations as a: 1 (for firms with “family ownership”) and 0 (for firms with “non-family ownership”).

The “internationalization” of an organization was operationalized as the ratio of its foreign sales to total sales (e.g. Alayo et al., 2021; Tallman and Li, 1996 among others). A firm's “diversification” was operationalized as the number of businesses it was involved in (e.g. Khanna and Palepu, 2000). We prevented individual firms within a group from appearing to be singularly undiversified by directly asking their group's CEO about the number of additional businesses of their group (excluding the main business). As far as possible, these responses were validated using the objective information obtained from SABI database.

“TMT educational level” was defined as the average educational level of TMT members (including the CEO) who had completed higher education. We categorized managers into two different educational levels: 0 = “non-university studies” and 1 = “university studies or higher.” Subsequently, a percentage of TMT members with at least a university degree to the total number of TMT members was calculated.

“TMT average age” was measured as the average age of an organization's TMT members (e.g. Herrmann and Datta, 2005). For this purpose, during the questionnaire, CEOs directly responded to the question: “what is the average age of the TMT (including the CEO)?”

Control variables: CEOs are distinguished by their diverse experiences and vast preparation to make complex decisions (Priem, 1994). Consequently, they are typically considered as central actors in strategic decision-making processes. However, they unusually act alone but interact with the other members of the TMT in order to take strategic decisions and plan the future course of the organization (Tang and Crossan, 2017). Decision-making processes do not just involve the CEO of the firm but the TMT members, whose participation will also influence firms' actions (Hambrick and Mason, 1984). On top of that, several studies have pinpointed the importance of internal forces of the organization such as power and political structures, economies of scale, sunk cost, etc. in limiting decision-making actions. In the same vein, external forces to the organization such as competitors' reactions, bargaining power of suppliers, etc. has also been pointed as potential influencers to organizational strategic change (e.g. Lant et al., 1992). Regarding this research stream, managerial-, company- and industry-level factors should also be considered to understand strategic decisions. Hence, in our study we include control variables at the managerial-level, at the company-level and at the industry-level. At the managerial-level, we controlled for “TMT functional diversity” and “TMT educational diversity”. For its part, “TMT functional diversity” can influence TMT problem solving, decision-making processes and organizational performance by improving an organization's access to external information and attentiveness to various environmental sectors (Daft et al., 1988). Meanwhile, “TMT educational diversity” is used as an indicator of the variety of skills, cognitive processes and basic knowledge embedded in a managerial team (Boeker, 1997; Wiersema and Bantel, 1992), and may also influence the relationship between family ownership and a firm's financial strength (Bunderson, 2003). At the company-level, we controlled for the “size of the organization” (measured as operating income) as larger organizations usually have more organizational slack (Lavie et al., 2010) and lower probability of default than SMEs when using financial leverage (Cathcart et al., 2020), “age of the organization” (years that the organization has been functioning), because older organizations are characterized more strongly by consolidated routines and practices that hinder change and investment (Hannan and Freeman, 1989), and “prior financial strength” (preceding economic status of the firm), as earlier research states that slack can be used to engage in search behaviors and pursue strategic changes which could improve firm's long-term situation (Daniel et al., 2004).

Eventually, at the industry level, we incorporated “industry innovation intensity” (i.e. a firm's research and development expenses divided by its sales) to determine its average degree of innovation. We captured this variable as a proxy for environmental dynamism because it is closely related to survival and competitiveness in a particular sector (Covin and Slevin, 1989). In other words, the dynamism or hostility of an environment characterizes competence; technological, social, political and economic uncertainty; business climate and the level of opportunities for exploitation (Dyer and Mortensen, 2005; Donaldson et al., 2024).

Results

The values of the means, standard deviations and correlations for all variables included in the analyses are presented in Table 2. Our hypotheses on the effects of family ownership, a firm's context of activity and TMT characteristics on an organization's financial strength were evaluated using multiple hierarchical regressions in SPSS 20.0 (see Table 3). The variables were centered before the interaction terms were generated. Interaction analysis using the centering procedure is preferable for simpler analyses because it yields readily interpretable coefficients that are relatively free of multicollinearity. However, we also checked for the presence of multicollinearity in our analyses, finding variation inflation factors (VIF) of less than five for all parameters (analyses available from the authors on request).

Model 1 (Table 3) includes only the control variables. “Size of the organization”, “age of the organization” and “prior financial strength” at the company-level, “industry innovation intensity” at the industry-level and “TMT functional diversity” and “TMT educational diversity” at the managerial-level, as they may limit the ability of firms to adapt to the existing hostile and changing environment, thereby affecting the current strategic actions and performance of such firms (e.g. Lant et al., 1992; Villagrasa et al., 2024). These results highlight that firms' financial strength is higher in larger organizations (β = 0.392; p < 0.05), in organizations with prior elevated financial conditions (β = 0.452; p < 0.05) and in organizations that have higher levels of TMT functional diversity (β = 0.188; p < 0.1). Larger organizations are argued to be more efficient than smaller ones (Lo and Lu, 2006) and to dispose of more slack, which allows them to engage in more exploratory activities (Lavie et al., 2010) and to better analyze the processes of change (Boeker, 1997) leading to a lower likelihood of default (Cathcart et al., 2020). Similarly, prior positive financial strength is argued to increase the availability of resources for a firm, thereby providing certain slack that could be used to boost the adaptability and long-term performance of the firm. Finally, organizations with greater TMT functional diversity are associated with better information processing, problem solving, range of perspectives and assessment accuracy (Daft et al., 1988). Consequently, we establish that a company's financial strength is likely to increase in the presence of these variables.

In Model 2 (Table 3), we include the variable “family ownership” in order to evaluate the effect of family involvement in an organization on its financial strength. Our results indicate a direct positive significant effect (β = 0.243; p < 0.05) of this variable on an organization's financial strength. Hence, we support our baseline hypothesis or H1. This hypothesis is closely related to the distinct functioning of family firms compared to non-family firms and to the consideration that a family firm is an asset to be passed on to succeeding generations and is not a temporary income provider (Casson, 1999). In other words, family firms are not only a source of income but also a context for families' activities and the embodiment of their pride and identity (Meyer and Zucker, 1989), which make them invest more efficiently and carefully in their business (Gimeno et al., 1997) and employ financing forms with low probabilities of default (Anderson and Reeb, 2003).

We argue that this finding is in line with family firms' characteristics and peculiarities, such as higher risk aversion (Anderson and Reeb, 2003; Fang et al., 2021), higher efficiency (Daily and Dollinger, 1992; Fama and Jensen, 1983), greater cash levels (Jensen, 1986; Caprio et al., 2020), less dependence on debt as a form of financing (Jensen, 1986), willingness to continue in business (Gimeno et al., 1997), prioritization of firms' goals over those of individuals (McConaughy, 2000) and relevant investment in their firms in terms of financial investment, prestige and human capital (McConaughy et al., 2001), etc. This finding is also in line with the emotional component of family firms, which reflects in the preservation of the SEW that refers to the affective needs, such as the ability to exercise family control and the perpetuation of the family dynasty (Gomez-Mejia et al., 2007; Davila et al., 2023). Likewise, this argumentation may be reflected in the non-munificent context in which our sample is set, thereby (even) enhancing the effects of H1. In fact, in a resource-constrained environment, the financial robustness of these firms becomes even more critical, as such conditions may significantly impact their immediate prospects and long-term viability (Amato et al., 2023; Iwasaki, 2014).

In Model 3 (Table 3), “internationalization”, “diversification”, “TMT educational level” and “TMT average age” are introduced. However, none of these variables have a marginally significant effect on a firm's financial strength. Still, the variable “family ownership” keeps its direct positive significant effect showed in Model 2 (β = 0.266; p < 0.05), suggesting that during periods of global or international economic crisis, family firms' prospects are crucial to determine the financial status of a firm, contrary to the organization's scope of operation (represented in our study by the variables “internationalization” and “diversification”) or the characteristics of its key-role players (represented by the variables “TMT educational level” and “TMT average age”). Although we did not formally hypothesize such effects, this is not surprising given the maximization of the long-term orientation shown by these firms (Amato et al., 2023; Cathcart et al., 2020; Stein, 1988). In other words, Model 3 indicates that despite the (individual effect of the) context in which a firm operates or the characteristics of its TMT, family firms' inherent particularities overcome any other circumstances when explaining variations in firms' financial performance (Minichilli et al., 2010; Miroshnychenko et al., 2021).

In Model 4 (Table 3), we test for the interaction effect of “internationalization”, “diversification”, “TMT educational level” and “TMT average age” with the variable “family ownership” on an organization's financial strength. With this, we intend to interpret and contextualize H1.

In H2 and H3, we established that “internationalization” (H2) and “diversification” (H3) potentially minimize the risk of firms and increase their chances of (economic and financial) success due to their access to heterogeneous markets, which provides them bigger opportunities of growth and income (Sanchez-Bueno and Usero, 2014). Our results, however, indicate that there is no conditional significant effect between the first two interactions (“family ownership”*“internationalization” and “family ownership”*“diversification”) and firms' financial condition. Hence, we are unable to support H2 and H3, and this shows that the context in which a firm is embedded does not affect family firms' longer outlook for survival (and, therefore, their financial strength). There are potential explanations for these results. The first relates to the characteristics of this crisis period and its global influence. Hence, this time frame was characterized by a turbulent context in which organizations and customers faced a global recession that created a shared crisis in credit, mortgages and trust; high levels of uncertainty; raised variability; relative scarcity of all types of resources and the rupture of the production-employment-consumption wheel (International Monetary Fund, 2009). Consequently, despite operating in diverse businesses, sectors or markets, family organizations could not have experienced any difference due to the existent economic and financial homogenization during those years. The second could be related to the high cost of undertaking both strategies, which could generate a neutral influence on a firm's financial strength (Wagner, 2004), thereby resulting in a non-significant effect of these interactions.

Based on the prior literature on the upper-echelons theory (Hambrick and Mason, 1984), we have also hypothesized that TMT characteristics, and particularly “TMT educational level” (H4) and “TMT average age” (H5), influence the relationship between family ownership and firms' financial strength. H4 proposed that “TMT educational level” negatively moderates the existing relationship between family ownership and firms' financial strength. However, our results show a significant positive interaction effect (β = 0.781; p < 0.05; Table 3, Model 4). Nonetheless, before stating that our H4 is not supported, we should graphically represent this interaction (Preacher et al., 2007). Empirical academic evidence supports the idea that plotting data is essential before deciding if a hypothesis is supported. Thus, for instance Tukey (1977) argued that plotting data allows researchers to uncover patterns, spot anomalies, frame hypotheses and decide on subsequent analyses, highlighting that visualization is a critical step in understanding the underlying structure of the data. Similarly, Gelman et al. (2002) among others emphasize the benefits of graphical methods in hypothesis testing arguing that visualization aids in revealing insights that are not apparent through numerical summaries alone, thereby enhancing the robustness and credibility of the conclusions drawn from the data.

Thus, in Figure 2 we plot the effect of family ownership on firms' financial strength for high versus low TMT educational levels (note that high and low refers to mean ± one standard deviation). Figure 2 shows that the slope of the relationship between family ownership and a firm's financial strength is less pronounced for TMTs with lower educational levels than for TMTs with higher educational levels. Based on this observation, we make four main contributions. First, we can assume that the interaction of family firms with the level of education in a TMT is a better predictor of a firm's financial strength than only the family ownership. This leads us to point two, through which we understand the reason for the positive significant interaction obtained in Model 4 (Table 3), as the slope for highly educated TMTs is steeper than that for less-educated TMTs. Third, focusing on the difference between TMTs with high educational levels (represented by a dotted line) and low educational levels (represented by a continuous line), we can observe that the former (highly educated managers) generates lower levels of financial strength (reaching a lower value in the graph when comparing both the lines). Consequently, H4 would be supported. Finally, Figure 2 also helps corroborate what H1 and Model 3 (Table 3) proposed. H1 stated that family firms had greater levels of financial strength (as opposed to non-family firms). This can be observed in the divergence between the left (non-family firms; presenting low values of financial strength) and right part (family firms; showing high values of financial strength) of Figure 2. For its part, in Model 3 (Table 3) we suggested that family firms' prospects were crucial in determining the financial status of a firm, despite the specific features of an organization. In this instance, the absence of significant differences between family firms with a high versus low TMT educational level (see the right part of Figure 2) corroborates this assumption. Consequently, it appears that the intrinsic characteristics of family organizations and their SEW mitigate and obscure the negative impact that highly educated managers might have on a firm's financial robustness (a phenomenon observable in non-family firms).

To assess this interaction effect more systematically and comprehensively in the present study, we apply the Johnson–Neyman technique (note that, as prior research indicates, all variables must be standardized for this analysis). This tool acts as an extension of SPSS and can be run within the same statistical program after installing the corresponding plugin (see Preacher et al., 2007). As a differential aspect, this technique allows to define the regions in which the coefficient of family ownership is significantly positive or negative, conditional on the TMT's educational level. Hence, we find a different and richer approach to simple slopes captured by regular representations of conditional effects.

Figure 3 plots the conditional effect for the entire range of our moderating variable – TMT educational level – with a 95%-confidence band (full analyses are available from the authors upon request). The interaction effect will be significant when confidence intervals (represented by dotted lines in Figure 3) are either both above or both below zero – the former representing a positive conditional effect and the latter a negative one. To facilitate its understanding, we have drawn a vertical line representing the boundary of the region in which the interaction coefficient turns significant (at the 0.05-level).

Thus, based on the Johnson–Neyman technique, family ownership appears to have a positive effect on a firm's financial strength when its managers have high educational levels. Additionally, this positive effect seems to be the only significant range for the interaction, as the conditional effect turns insignificant (at the 0.05-level) when the TMT educational level reaches the value 44.62 (for the standardized variable), which would represent the half of the range of this variable approximately (see Figure 3). This suggests that only high TMT educational levels (as opposed to moderate or low levels of this variable) act as a (positive) moderator for the relationship between family ownership and a firm's financial strength.

This analysis is rather interesting, as it complements our prior findings, suggesting that when managers have low levels of education, the relationship between family ownership and a firm's financial strength is not significant. This suggests that managers with little training leverage less (and thus their firms have higher levels of financial strength) despite belonging to a family or non-family firm, and for that reason, significant differences in their firms' financial strength do not exist.

However, when managers are highly educated, the financial strength of family firms is greater than the one of non-family firms. As previously mentioned, we argue that such differences could be explained by family firms' inherent ability to invest more efficiently (Daily and Dollinger, 1992; Fama and Jensen, 1983), take less risk-averse options (Anderson and Reeb, 2003), rely less on debt (Jensen, 1986) and look for higher continuity of the firm (Gimeno et al., 1997), which would reduce and compensate for the negative effect of highly educated managers on non-family firms' financial strength.

In H5, we proposed that the “TMT average age” positively moderates the existing relationship between family ownership and a firm's financial strength. Nevertheless, contrary to what is proposed in H5, we find a marginally significant negative interaction effect (β = −1.719; p < 0.1; Table 3, Model 4). However, as in the previous case, we graphically represent this interaction effect to facilitate its interpretation and verify its impact. In Figure 4 we plot the effect of family ownership on firms' financial strength for high versus low levels of TMT average age (note that high and low refers to mean ± one standard deviation). The slope of the relationship between family ownership and a firm's financial strength is less pronounced for TMTs with a higher average age than for TMTs with a lower average age. Like in the previous moderation analysis, we can make four main contributions. First, we can assume that the interaction of family firms with TMT's average age is a better predictor of a firm's financial strength than only the family ownership. Second, we can comprehend the roots of the negative significant interaction obtained in Model 4 (Table 3), as the slope for “older” TMTs is less positive than that for “younger” ones. Third, we can also identify that “older” managers (represented with a dotted line) generally generate higher levels of financial strength than managers with lower average age (represented with a continuous line) when comparing both the lines in the graph – note that due to the nature of both characteristics (TMT educational level and TMT average age), this situation will be contrary to that obtained for high versus low educational levels of TMTs. Consequently, H5 would be supported. In the last place, Figure 4 can also help confirming what H1 and Model 3 (Table 3) advocated. H1 proposed that family firms had greater financial strength (as opposed to non-family firms). This can be observed in the divergence between the left (non-family firms; holding low values of financial strength) and right part (family firms; showing high values of financial robustness) of Figure 4. Meanwhile, in Model 3 (Table 3), we determined that family firms' prospects were decisive in outlining the financial status of a firm, despite the specific features hold by the company. In this case, the lack of differences depicted among family firms with a high versus low TMT average age (see the right part of Figure 4) supports this assumption. Therefore, it seems that (again) family firms' inherent particularities and SEW overcomes and blurs any other characteristic present in the firm or its managers when explaining variations in firms' financial performance (Minichilli et al., 2010; Miroshnychenko et al., 2021).

Like prior analysis, to enhance the comprehension of this interaction we also applied the Johnson–Neyman technique. Nevertheless, this statistical analysis showed no significant areas for the entire range of our moderating variable (full analyses are available from the authors upon request). This result is not surprising because if we look at the outcome provided by Model 4 (Table 3), we may observe that the interaction among these variables is (only) marginally significant (β = −1.719; p < 0.1). Similarly, when we plot it in Figure 4 we cannot identify significant differences between the two lines either (i.e. among high versus low values of the variable). Hence, the use of the Johnson–Neyman technique enriches our analysis, helping us understand the weaknesses presented by this particular conditional effect.

Additional analyses and robustness checks

To delve deeper into our findings, we conducted supplementary analyses and robustness checks. Initially, we explored whether certain control variables, like “TMT functional diversity” and “TMT educational diversity”, could act as moderators in our model. Our data partially supported this notion, with an existent significant correlation between “TMT educational level” and “TMT educational diversity” (ρ = 0.370; p < 0.05; Table 2). However, when we assessed these variables as moderators, replacing “TMT educational level” and “TMT average age” with “TMT functional diversity” and “TMT educational diversity”, no significant conditional effects were observed on family firms' financial strength (analyses available upon request). Moreover, this adjustment reduced the model's robustness from an adjusted R-squared of 0.562 to 0.476, affirming the superiority of our original model.

Subsequently, we investigated the interchangeability of “TMT educational level” and “TMT educational diversity.” Employing “TMT educational diversity” as a moderator and “TMT educational level” as a control variable, we found that family ownership positively influenced firms' financial strength (β = 0.222; p < 0.05). However, no significant conditional effects were detected on “TMT educational diversity,” “internationalization,” or “diversification.” Despite this, “TMT average age” retained its negative conditional effect (β = −1.995; p < 0.1), albeit marginally. Yet, this adjustment diminished the model's robustness from an adjusted R-squared of 0.562 to 0.515, reaffirming the superiority of our original model (full analysis available upon request).

Lastly, we examined the impact of removing “TMT educational level” entirely from our model, substituting it with “TMT educational diversity” as a moderator. Despite the existing correlation between these variables mentioned above (ρ = 0.370; p < 0.05; Table 2), this adjustment did not significantly alter the prior additional findings. Hence, family ownership remained significant (β = 0.222; p < 0.05), with (again) no notable conditional effects on “TMT educational diversity,” “internationalization,” or “diversification.” However, “TMT average age” continued to exhibit a marginally negative conditional effect (β = −1.989; p < 0.1). Moreover, this adjustment slightly reduced the model's representativeness, as the adjusted R-squared decreased from 0.562 to 0.525 (full analysis available upon request). Subsequent analyses, wherein only “TMT educational diversity” was removed from the control variables, yielded similar results, underscoring the robustness and suitability of our chosen variables.

Additionally, we evaluated the appropriateness of the span of time covered by our dependent variable (analyses available from the authors on request). As mentioned in the theoretical framework section, in our study we chose to assess firms' financial strength as an average of the years 2008–2009. We did so and did not consider the economic fortitude of a single year (e.g. only assessing the year 2008 or 2009) for two main reasons. First, scholars and international reports jointly consider both years as a turning point of the Spanish and international crises (Instituto de la Empresa Familiar, 2022; International Monetary Fund, 2009). Second, due to single-year assessment may contain specific variations that could affect the veracity and feasibility of our study. Nevertheless, despite these concerns and for the sake of robustness, we executed two independent regressions in which firm's financial strength was evaluated individually in 2008 and in 2009. Although on the same expected line, the results obtained here were slightly less convincing than those reported in Table 3. For instance, this situation may be observed in the results obtained when using firm's financial strength only for the year 2008 as a dependent variable. Here, family ownership presented the following (poorer) results: β = 0.130, p < 0.05 (vs prior results: β = 0.243; p < 0.05). Regarding moderating variables, we found less powerful results in this model. Hence, for example, the moderation effect of “TMT educational level” (“family ownership”*“TMT educational level”) was found to present a lower effect both in terms of the effect size and significance level as compared with the reported one (β = 0.610; p < 0.1 vs prior results: β = 0.781; p < 0.05). Likewise, similar results were obtained using firm's financial strength only for the year 2009. Thus, we can widely confirm that poorer results are obtained using single-year analyses.

Discussion

In this study, we show that family firms' inherent particularities and embedded SEW counts more on the firms' financial strength than any other characteristics or circumstances of these firms, either related to an organization's scope of operation (e.g. internationalization or diversification of a firm) or to the characteristics of its key role players (e.g. TMT educational level or TMT average age). In other words, we provide evidence to prove that the financial strength of family businesses is similar (and higher than that of non-family firms), whether they operate in just one country or in many of them, whether they focus their attention on a single industry or on several ones and whether they have TMTs with certain types of characteristics.

In fact, we prove that when one variable such as TMT educational level could potentially reduce firm's financial robustness due to their will to leverage more, their better ability to deal with ambiguity, complexity and their greater openness to change (Calabrò et al., 2021; Herrmann and Datta, 2005); family firms' inherent ability to invest more efficiently (Daily and Dollinger, 1992; Fama and Jensen, 1983), hold higher cash levels (Caprio et al., 2020), take less risk-averse options (Anderson and Reeb, 2003), rely less on debt (Jensen, 1986) and look for higher continuity of the firm (Gimeno et al., 1997), would “activate” and compensate for the negative effect of highly educated managers on financial strength. Hence, in this situation there would be significant differences among family and non-family firms (which will leverage more, and thus will hold poorer levels of financial strength) due to the functioning of this “automatic regulation system” which would adjust the behavior of the family corporations.

Additionally, as we proved our assumptions during the non-munificent period of 2008–2009, we can state that family firms' perspectives and idiosyncratic characteristics seem to keep dominating their behavior also during crisis periods, prevailing in this manner over other particularities. This argument is supported by Claessens et al. (2000), who assert that the challenges faced by firms during turbulent periods are not merely the result of external shocks but rather that these difficulties were evident well before the crisis, contending that the risky financial policies adopted by these firms beforehand are the true factors that rendered them vulnerable.

Therefore, we suggest that family firm owners should maintain their hard-to-duplicate capabilities or what some scholars call “familiness” (Habbershon and Williams, 1999) to achieve their desirable transgenerational sustainability (Calabrò et al., 2021). But similarly, we argue that their better financial position should place them in a privilege position to receive economic support from public administrations. As a kind of reward for its duties performed as a company and as deserving of (the scarce) public resources. These companies positively impact the economy by being less likely to downsize compared to non-family businesses (Sanchez-Bueno et al., 2020). Additionally, family firms typically exhibit greater responsibility toward their employees and the environment. Besides, their unique ownership structures enable them to make swift decisions and respond to changes and crises more rapidly and with less bureaucracy than their non-family counterparts (Kraus et al., 2020).

Contributions

With this study, we contribute to the extant literature in several ways. First, this paper contributes to the family firm literature by offering insights into the nuanced dynamics between family and non-family firms during economic downturns, specifically examining their financial strength when different strategic options are pursued and when firms are managed by different type of managers. As highlighted by the literature, further studies about the specific idiosyncratic characteristics of family firms and its relationship with the environment are awaiting further study (Miroshnychenko et al., 2021). Therefore, our research tries to deepen into this matter shedding light on the implications for financial policy and support mechanisms.

Second, our research also attempts to extend prior findings on investment appropriateness in family firms, a topic that is of substantial practical and scholarly interest (De Massis et al., 2013). Literature argues that innovation input is lower in family firms than in non-family firms, however some colleagues demonstrated that this lower input level does not translate into a lower output level (Duran et al., 2016). On the contrary, family firms are particularly quite well-suited to efficiently use their resources (e.g. Carney, 2005; Sirmon et al., 2011) and thus to reach a higher innovation output compared to non-family firms, despite the former' limited level of innovation input. Both results seem to be caused by the same set of family firm idiosyncrasies (Duran et al., 2016). Thus, wealth concentration implies specific attitudes toward risk and uncertainty which usually lowers the number of financial resources dedicated to innovation projects that are a priori more uncertain. However, at the same time it also motivates family owners to monitor the efficiency of the innovation process to further reduce such uncertainty and increase its productivity. For its part, although the focus on non-financial goals disincentivizes family owners to raise external money and thus limits their innovation input, the existence of non-financial goals in these firms (alongside financial ones), also leads to the development of certain capabilities, tacit knowledge and network access over time, which ultimately augment the innovation process, in a sort of resource orchestration mentioned by the literature (Sirmon et al., 2011). Consequently, innovation will drive the future development of such firms by fostering competitive advantage, enhancing efficiency and enabling the creation of new products and services, thereby ensuring sustained growth and adaptability in a dynamic market environment (Duran et al., 2016), therefore confirming the appropriateness of investing in this type of companies (De Massis et al., 2013).

Third, since the seminal study of Hambrick and Mason (1984) on the upper-echelons perspective, research on TMTs has developed itself into one of the most prominent areas in the management research field (Menz, 2012). TMTs, defined as the group of managers consisting of the CEO and those managers that directly report to the CEO (Boeker, 1997), are widely recognized as one of the most imperative decision-making units in organizations. Likewise, this stream of research has emphasized the relevance of these actors in monitoring environmental conditions and modifying organization's strategies to maintain satisfactory alignments between both (Villagrasa et al., 2018). In addition, in the context of family firms, TMTs are argued to be even more responsible for strategic decisions (e.g. Habbershon and Williams, 1999; Gedajlovic et al., 2004). Thus, following this line of investigation, scholars have convincingly argued (and repeatedly found) that managers and their characteristics matter in affecting strategic decision-making processes, and, in turn, organization-level outcomes. In line with this body of work, we anticipate that the relationship between family ownership and firm's financial strength may be influenced by the characteristics of their managers. More particularly, we drive our attention on analyzing the influence of their educational level and average age; and expect an opposite effect between both variables. However, our results suggest that under some circumstances where the future viability of the firm may be called into question family inherent behavior or “common (family) sense” can be activated and compensate potential deviations from the family goals. Future scholars might try to tease out these multilevel effects by for instance investigating different other features of the TMT among family and non-family firms.

Limitations and future research avenues

Like any study, ours has limitations that can set the stage for future research avenues. First, literature does not agree about how to define “family ownership” (Chrisman et al., 2005). Scholars should start their research with a common definition of family involvement in the firm to be able to distinguish family firms from the ones that are not (Sharma and Chrisman, 1999). Besides, traditional definitions of family businesses have been rather fragmented, paying attention to some different individual components of a family involvement in the business such as ownership, governance, management or transgenerational succession (Chua et al., 2012). Consequently, scholars have serious problems making these components homogenous and attempting to reconcile all of them in their investigations. Thus, the observation that firms with “similar” family involvement may or may not be considered family or non-family firms due to the existence of those imprecise components yielded that some colleagues tried to define family businesses theoretically. Two approaches stood out mainly: the involvement approach and the essence approach. The involvement approach is based implicitly on the belief that a mere family involvement is sufficient to consider a firm a family business. Meanwhile, the essence approach is based on the belief that family involvement must be proved and therefore is a necessary but insufficient condition; hence, family involvement must be directed toward behaviors that produce certain distinctiveness before a firm can be considered a family firm. In other words, two firms may not both be identified as family businesses if one of them lacks the intention, vision, “familiness” and/or behavior that constitute the essence of a family business. Our study uses this approach, providing a clear definition of what can be and cannot be considered a family business. However, we measure it as a dummy variable, and not as a continuous variable as proposed by recent research with which much more accurate results could be obtained (Chua et al., 2012). Therefore, our results although relevant and significant for the family firm literature, must be viewed carefully because we do not properly distinguish between the degree of family involvement.

Second, related to the previous point and following Astrachan and Shanker (2003) research, scholars could further analyze in the future the differences between dichotomous and continuous way of assessing family involvement within an organization. This idea would allow literature to dig into the definition of family businesses and would help to clarify an issue that is still open to debate. Differences should be identified and explained through both theory and practice. Additional research could also retest some prior studies to depict differences caused by “real” family firm involvement.

Third, due to the importance of family firm values in this type of companies' behaviors and results, an interesting trajectory for future research would be to capture the drivers of the preservation of such “familiness”. Thus, we argue that a more in-depth understanding of the concept and its intricacies would increase the explanatory value of family firm-oriented research.

Finally, prior research has revealed that “familiness” represent a highly heterogeneous group with different levels of family involvement and emotional attachments to the family firm (Berrone et al., 2012). That is to say, “familiness” is argued not to be something homogenous. However, most studies have supposed that each family member holds a relative equal level to the family firm, therefore generating an overall degree of family involvement of this firm (Miller and Le Breton-Miller, 2014). Recent studies oppose this, showing that the level of emotional attachment to the family firm differs not only between family members (Berrone et al., 2012) but also among non-family members, who can possess even stronger emotional endowments to the family firm than the proper family members (Miller and Le Breton-Miller, 2014). It would be interesting for future researchers to scrutinize these differences. Additionally, we argue that different levels of “familiness” among decision-makers of a firm can result in fundamental differences of opinion about the course of action and strategies followed by the firm, and thus increase the likelihood of relational tensions that may therefore hamper the correct functioning of the firm. A fruitful research avenue would be to firstly test the existence of these differences, and secondly check whether the potential friction and conflicts originated from such dissimilarities in family involvement may actually affect the quality of the decisions made by a management team. In fact, firm leaders not only have a substantial say in resource-allocation decisions (Hambrick and Mason, 1984) but also monitor and direct the usage of those resources, creating the conditions for the subsequent implementation of the strategies (Duran et al., 2016). Therefore, the existence of tensions among them could impede the implementation of the agreed-upon terms.

In sum, we view our study as illustrative rather than definitive and hope to encourage further replication in samples with different width, applicability and considerations, aspiring to pave the way for future research and to inspire fellow scholars.

Figures

Figure 1

Research model

Figure 2

Interaction of “TMT educational level” and “family ownership” on “firm’s financial strength”

Figure 3

Coefficient of “family ownership” conditional upon “TMT educational level”

Figure 4

Interaction of “TMT average age” and “family ownership” on “firm’s financial strength”

Table 1

Descriptive statistics and correlation matrix

Description	Value	Percentage
Total firms sampled	1,000	100%
		(55% family vs 45% non-family)
Filled questionnaires received	190	19%
Questionnaires removed for reasons of incompleteness	7	0.7%
Total valid questionnaires	183	18.3%
Firms without complete information (objective and subjective data)	46	4.6%
Total questionnaires used in this study	137	13.7%
		(57.66% family vs 42.34% non-family)

Source(s): Authors’ own creation

Table 2

Descriptive statistics and correlation matrix

Measures	Mean	s.d.ˆ	1	2	3	4	5	6	7	8	9	10	11	12
Dependent variable
1. Firm's financial strength	579.08	139.59	1.00
Independent variable
2. Family ownership	0.60	0.49	−0.104	1.00
Moderators
3. Internationalization	36.14	29.95	−0.251*	−0.076	1.00
4. Diversification	3.03	2.28	−0.095	−0.220*	0.075	1.00
5. TMT educational level	70.09	42.16	0.064	−0.069	0.078	0.095	1.00
6. TMT average age	42.54	6.36	0.029	−0.064	0.175	0.191	−0.135	1.00
Control variables
7. Size of the organization	31,820.67	72,234.13	0.461**	0.066	−0.011	0.378**	0.209**	0.140	1.00
8. Age of the organization	37.20	28.18	−0.027	0.271**	0.153	−0.011	0.088	0.286**	−0.023	1.00
9. Prior financial strength	620.35	134.03	0.412**	−0.116	−0.291*	−0.218*	0.063	−0.028	0.400**	−0.009	1.00
10. Industry innovation intensity	1.22	0.7736	0.032	−0.053	0.071	0.190	0.239***	0.021	0.041	0.008	0.058	1.00
11. TMT functional diversity	0.7375	0.1203	0.064	−0.003	−0.183	−0.054	−0.001	0.050	0.003	0.159	0.059	0.185**	1.00
12. TMT educational diversity	0.3765	0.2283	−0.031	−0.152	0.063	0.012	0.370**	0.056	0.142	−0.056	−0.244*	0.120	0.003	1.00

Note(s): N = 137

*p < 0.1; **p < 0.05; ***p < 0.01 (two-tailed)

ˆs.d. stands for standard deviation

Source(s): Authors’ own creation

Table 3

Results of the linear regression analysis

Measures	Model 1 Control variables	Model 2 Independent variable	Model 3 Direct effects	Model 4 Interaction effects
Controls
Size of the organization	0.392**	0.350**	0.322	0.414**
Age of the organization	0.132	0.045	0.060	0.175
Prior financial strength	0.452**	0.547***	0.558***	0.487**
Industry innovation intensity	0.076	0.123	0.171	0.182
TMT functional diversity	0.188*	0.279***	0.299**	0.354***
TMT educational diversity	−0.013	0.057	0.092	0.168
Main effect
Family ownership		0.243**	0.266**	1.345
Moderators
Diversification			0.033	−0.049
Internationalization			−0.106	−0.108
TMT educational level			−0.026	−0.516**
TMT average age			0.006	0.136
Interaction terms
Family ownership*Internationalization				−0.009
Family ownership*Diversification				−0.086
Family ownership*TMT educational level				0.781**
Family ownership*TMT average age				−1.719*
R-squared	0.541	0.578	0.588	0.651
Adjusted R-squared	0.495	0.531	0.508	0.562
R-squared change	0.541***	0.037**	0.010	0.063**
F-value	16.221***	16.526***	9.826***	9.547***

Note(s): N = 137

Dependent variable: Firm's financial strength

Standardized coefficients are shown; *p < 0.1; **p < 0.05; ***p < 0.01 (one-tailed)

Source(s): Authors’ own creation

Notes

1. In Spain, where our dataset belongs to, family firms represent 88.8% of the companies (1.1m of them). Currently, they create 67% of all the private employment, with a total of more than 6.58m jobs, and are responsible for 57.1% of the GDP of the country’s private sector (Instituto de la Empresa Familiar, 2022).