Incumbent Stakeholder Management Performance and New Entry

Abstract

Instrumental stakeholder theory seeks to explain how managing stakeholders effectively can yield competitive advantage for incumbent firms. We extend instrumental stakeholder theory to explain and predict future competition operationalized as new entrepreneurial entries. Our study is among the first to empirically examine the relationships between aggregate stakeholder management performance and the entrepreneurial entries of individuals. Using a combined U.S. dataset from 2003 to 2013 from the Kinder, Lydenberg and Domini (KLD) Index, Compustat, and Kauffman’s Entrepreneurship Survey, we find support for three hypotheses. First, higher levels of stakeholder management performance are related to lower rates of entrepreneurial entry. Second, a curvilinear relationship exists between stakeholder management performance and entrepreneurial entry, where both low and very high stakeholder management performance increase entrepreneurial entry. Third, the greater the variance in stakeholder management performance across stakeholders, the more entrepreneurial entry. Our findings suggest that managing for stakeholders can help to avoid future competition. We add an entrepreneurship lens to the business ethics of stakeholder theory showing how incumbent stakeholder management performance shapes opportunities for entrepreneurs, a largely neglected stakeholder group.

Introduction

Stakeholder theory has been widely debated in the business ethics literature because “by substituting ‘stake’ for ‘share’, the very idea of non-shareholders having a ‘stake’ does normative work” (Parmar et al. 2010, p. 9). The normative character of the theory has led to greater attention and adoption over time with business ethicists mostly finding fluidity between stakeholder theory a variety of ethical frameworks (Laplume et al. 2008). Meanwhile, in parallel, strategy scholars developed instrumental stakeholder theories (Jones 1995; Jones et al. 2018), where the value of stakeholder relationships is assessed against corporate variables like financial performance (e.g., return on investment or sales growth). Most prior studies propose or find positive associations between ‘good’ firm behavior toward stakeholders and firm performance (e.g., Freeman et al. 2004; Harrison and Freeman 1999; Henisz et al. 2014; Hosseini and Brenner 1992; Tantalo and Priem 2016; Wang and Choi 2013).

Instrumental stakeholder emphasizes managing stakeholders fairly to generate competitive advantage (Harrison et al. 2010). Competitive advantage is widely expected to stem from the acquisition and coordination of unique bundles of resources (Barney 1991) that stakeholders possess, control, and provide (Barney 2018; Jones et al. 2018). While we learn much from prior research, to our knowledge no study using SMP has examined entrepreneurial entries as a dependent variable. Rather, the bulk of the focus has instead been on comparing the performance of existing firms. This is a significant gap in stakeholder theory and the broader business ethics literature because while a firm may appear to outperform rivals, the whole industry could be in decline, or experience rapid contraction or disruption, thanks to new sources of competition driven by entrepreneurial entries. Moreover, from a business ethics lens, the interplay between new entrants and incumbents broadens the trade-offs involved in the stakeholder theory logic.

New entry by entrepreneurs is an important source of future competition (e.g., Bower and Christensen 1995; Henderson and Clark 1990; Tushman and Anderson 1986) for firms and is often thought of as a social good because it leads to new jobs and economic development (Newbert 2003), or as path to personal autonomy and emancipation (Rindova et al. 2009). It calls into question whether excessive corporate longevity is even a good thing for society. Nonetheless, our study reinforces the instrumental part of stakeholder theory, while at the same time highlighting a paradox for the business ethics debate around stakeholder theory.

Drawing on instrumental stakeholder theory (Harrison et al. 2010; Jones et al. 2018), we hypothesize that when firms in a given industry have low or very high aggregate levels of SMP, they are collectively more likely to experience a greater number of entrepreneurial entries, suggesting a U-shaped relationship. Further, our interpretation of instrumental stakeholder theory suggests that when firms’ aggregate SMP is imbalanced (i.e., tilts too much in favor of a small proportion of stakeholders), they are also likely to experience more entrepreneurial entries. Instrumental stakeholder theory also has significant links with the corporation social responsibility (CSR) and corporate social performance (CSP) literatures, which often use the same measures as stakeholder researchers (e.g., Brower and Dacin 2020; Hillman and Keim 2001; Perrault and Quinn 2018; Sun et al. 2019). Many studies examining SMP (and CSP) use the KLD dataset (e.g., Brower and Dacin 2020; Luo et al. 2015; Perrault and Quinn 2018; Wang and Choi 2013). It covers large, medium and small-sized publicly traded U.S. firms and includes measures of community relations, workplace diversity, labor relations, environmental impact and product safety, and corporate governance, which are key indicators of stakeholder management. The concept of SMP refers to the degree to which a firm invests in each stakeholder group and is therefore conceptually similar to CSP (Wang et al. 2020).

CSP was developed as a measure of corporate social responsibility, which has been defined as attention to the interests of nonfinancial stakeholders (Flammer and Kacperczyk 2019). In contrast, SMP was developed in order to derive a measurable construct to capture what was nebulously called stakeholder management, which includes investors as key stakeholders (Freeman 1984). Like high CSP, high SMP indicates a preponderance of positive interactions with stakeholders and a dearth of negative interactions. We assume that the degree to which a firm’s interactions with a given stakeholder group are positive or negative reflects the amount of investment the firm has made in the relationship with that stakeholder group over time. Two potential differences with CSP and SMP operationalizations are: (1) we include corporate governance in SMP because it relates to a financial stakeholder (shareholders); and, (2) we exclude indicators of social performance unrelated or indirectly-related to stakeholder interests (e.g., divesting from tobacco or nuclear sectors).

We use the KLD data to get the average (median) level of SMP practiced in a particular context defined as a state/industry/year triple, along with the variance (standard deviation). We test the relationship between aggregate SMP and entrepreneurial entries of individuals from the Kauffman Foundation survey. We find support for our hypotheses where very low or very high SMP are both related to higher rates of entrepreneurial entry, even when controlling for other relevant factors. We also find that in industry contexts with higher SMP imbalance (i.e., exhibit high variance or standard deviation), firms experience more entrepreneurial entries.

Our contribution is to examine the antecedent relationship between firms’ aggregate SMP and entrepreneurial entries in a given industry context. We point out that pursuing an optimal level of SMP is a way for incumbents to reduce entrepreneurial entry. While prior studies have looked at related ideas like the stakeholder prioritization of entrepreneurs (Agle et al. 1999), none have directly hypothesized or measured entrepreneurial entries as a result of the collective SMP of incumbent firms. This also holds for the CSP literature, which has to date ignored how aggregate CSP influences entrepreneurial entry.

To our knowledge, this is the first study to hypothesize and empirically examine the relationships between aggregate SMP and entrepreneurial entries. This is important because firm-level studies comparing existing firms can only tell us about how the firms are doing in relation to each other, whereas entrepreneurial entries are key sources of disruptive, architectural, or competence-destroying innovations that can affect the performance of incumbent firms in an industry (e.g., Bower and Christensen 1995, Henderson and Clark 1990; Tushman and Anderson 1986). In addition, our findings provide yet another argument in support of active and balanced stakeholder management by incumbent firms, specifically to avoid future competition. This is relevant from a business ethics perspective because it emphasizes how the normative choices of incumbent managers drive entrepreneurial opportunities for potential new entrants, a previous neglected side of the ethical debate around stakeholder theory. It highlights the tension (competing mechanisms) between the desires for pro-social corporate governance and the vitality of the entrepreneurial ecosystem (Clarke and Holt 2010; Newbert 2003; Venkataraman 2002), which we highlight in the discussion section.

Our paper proceeds by reviewing the instrumental stakeholder theory literature, focusing on recent advances that provide the foundation upon which we develop our hypotheses. Next, we describe our dataset and methodology, followed by a description and interpretation of the results of our hypothesis tests. Finally, we discuss the implications of the study for the literature and future research, acknowledge study limitations and conclude.

Instrumental Stakeholder Theory

Instrumental stakeholder theory seeks to explain how managing stakeholders effectively can yield competitive advantage for firms. Jones et al. (2018) highlight knowledge transfer and information sharing enabled by effective stakeholder management as the source of competitive advantage. They argue that consistently managing for stakeholders produces a reputation for fairness. Harrison et al. (2010) argue that firms that develop a history of ‘fair play’ through consistent distributive, interactive, and procedural justice in its actions and decisions, may not only win the trust of their stakeholders, but stakeholders of these firms will develop expectations about being treated fairly in the future that will make them feel more comfortable about sharing valuable information that can be used or recombined with that of other stakeholders.

Stakeholders are likely to be more willing to share knowledge and resources with firms if they think they will benefit from the value created. According to Harrison, belief that a firm has a reputation for fair play may lead stakeholders to share information about their true utility functions rather than just sharing their bargaining positions. Firms that access information about their stakeholders’ utility functions may gain efficiency and innovation advantages. Close ties with stakeholders allow for sharing of information that provides opportunities for more efficient contracting because the firm is more likely to know what stakeholders really care about. Efficiency advantages come from the possibility of tailoring deals so that they cater to what stakeholders really need or want rather than what they officially say they want. Strong ties enable an exchange of information far beyond what is normally made available in bargaining. Actors that do not trust each other are not transparent about their true needs and abilities (Schnackenberg and Tomlinson 2016). In contrast, innovation advantages come from greater knowledge about possible new factors, products, or services existing within stakeholder networks and the economic potential created by their combinations (Tantalo and Priem 2016). Together, efficiency and innovation advantages are expected to boost firm’s performance both in the short run and in the long run. It also provides opportunities for creative construction or innovation because the firm is more likely to gain access to stakeholders’ tacit knowledge about opportunities. Recombining the tacit knowledge of stakeholders into new combinations is the work of a network whose central actors earn a reputation for fairness.

Nonetheless, another thread in the theoretical literature pertains to the possibility of overinvestment in stakeholders. Coff (1999) contends that knowledge-based assets are difficult to imitate because they are firm specific and involve social complexity and causal ambiguity. However, this also gives those stakeholders that possess the relevant tacit knowledge a great deal of bargaining power over the firm, which may reduce firm financial performance. Firms may also over-invest in stakeholders to try to maintain positive reputations (Jones et al. 2018). Bridoux and Stoelhorst (2014) propose that over-investment is particularly problematic given that some stakeholders are not reciprocators and suggest that non-reciprocators are better managed with arms-length arrangements rather than fairness-based stakeholder management. Further, Garcia-Castro and Francoeur (2016) find initial support for the idea that over-investment in some stakeholders can lower a firm’s financial performance.

Hypothesis Development

We have three hypotheses that we believe get at the core of the theoretical work laid out above. The first one posits a negative main effect for incumbent SMP on entrepreneurial entry. That is, higher aggregate SMP is related to lower entrepreneurial entry. The second hypothesis investigates the presence of a curvilinear relationship between incumbent SMP and entrepreneurial entry, where firms that invest too little or too much in stakeholders may face more entrepreneurial entries. Our third and final hypothesis posits that incumbent firms with high variance between their SMP across stakeholder types experience more entrepreneurial entries.

Stakeholder Management Performance and Entrepreneurial Entry

Incumbent firms that properly manage their stakeholders are already taking advantage of from stakeholder arbitrage opportunities because they listen to their stakeholders (i.e., the ones with the great ideas), thus leaving fewer gaps for new entrants to fill. Incumbents that manage for stakeholders develop trusting relationships that act as heuristics that reduce monitoring costs and increase information sharing (Jones et al. 2018). They also develop a reputation for fairness over time as stakeholders witness procedural and interactive justice on the part of the incumbent (Harrison et al. 2010). This positive reputation allows stakeholders to believe that they will be treated fairly in the future, which further encourages them to share knowledge about their utility functions (i.e., their true needs and abilities—the two key components of recombination). The incumbent that develops the positive reputation becomes a broker in the network of stakeholders in which they are a central actor (Rowley 1997). This favorable position allows the incumbent to access rich information from many stakeholders and to generate innovative new combinations.

Managing for stakeholders may also help to create barriers to entry and imitation, which can help to block rivals. In particular, the loyalty of stakeholders and reputation of the firm are both barriers for new entrants (Jones et al. 2018). Special knowledge of stakeholder utility functions represents information asymmetry disadvantages and causal ambiguity for potential entrants who do not have access to stakeholders’ utility functions or tacit knowledge (Cennamo et al. 2009). Moreover, managing for stakeholders may create barriers through path dependence (Mishina et al. 2012) because firms that develop trust early on may benefit from a chain of subsequent reciprocal actions and reactions making it difficult both for new entrants and for rivals that have underinvested in stakeholders to catch up (Weitzner and Deutsch 2019). A reputation for fairness creates a barrier to imitation for other firms (Jones et al. 2018), including barriers to entry for entrepreneurs. Stakeholders do not tend to share their secrets unless they first develop positive expectations about reciprocity (Harrison et al. 2010). Rivals with bad reputations as well as new entrants with no reputations, are thus at a significant competitive disadvantage.

New entrants may find it difficult to imitate the reputation-based advantage of incumbent firms. New entrants may seek out unique strategic alliances with stakeholders in order to enter the market (Pollack et al. 2017). However, new ventures tend to focus primarily on satisfying customers and financiers (Vitell et al. 2000), making it more difficult to present themselves as credible partners to other stakeholders. This is also consistent with the idea that new entrants suffer from a liability of newness where new firms lack a reputation with stakeholders. These problems are especially relevant when the market includes incumbents with path dependent relationships with stakeholders based on trust and reciprocity (Mishina et al. 2012). It takes consistent investment in stakeholders to gain a reputation for fair play, and most new entrants, especially small entrepreneurial firms may find it very difficult to compete. Most stakeholders may thus prefer to remain loyal to reputable incumbents rather than share sensitive information in bargaining with new entrants. For example, Flammer and Kacperczyk (2019) find that firms with higher CSP have fewer knowledge spillovers in the form of employees leaving to work for competitors or start spinout ventures of their own. Thus, holding other factors constant, we expect that:

Hypothesis 1

Higher levels of aggregate stakeholder management performance are associated with lower rates of entrepreneurial entry.

Overinvestment in Stakeholders and Entrepreneurial Entry

Our second hypothesis is an alternative and complement to the first because it predicts that over-investment in stakeholders can have a dark side, leading to a point whereby an additional increase in investment may start to degrade entry barriers (Harrison and Bosse 2013). That is, allocating too many resources to the maintenance of relations that do not pay off can be detrimental (Garcia-Castro and Francoeur 2016; Sun et al. 2019). We view over-investment as allocating resources to stakeholders who are not sufficiently relevant to actual business performance. This may occur for reasons including resource dependence, inertia, agency problems, network positioning, or political maneuvering (Coff 1999; Freeman 1984; Frooman 1999; Jensen 2002; Rowley 1997). For instance, overinvestment in community stakeholders appears to destroy firm value if it leads to a focus on social issues that are not strategically linked to competitive advantage (Freeman et al. 2004; Hillman and Keim 2001). Overly generous bargaining produces unprofitable loyalty whereby the incumbent is stuck with stakeholders that no longer provide value but is unwilling to sever the relationships because of the potential negative message that it could send to other stakeholders in the network (Jones et al. 2018).

A misfit between stakeholder and firm resources may generate conflict over time (Bundy et al. 2018). For example, to avoid looking opportunistic, a firm may be reluctant to lay off workers when others are willing to do the same job for less, or stick with a loyal supplier when another can provide the same input at a higher quality and efficiency. At the aggregate level, managerial fashions with non-stakeholder centric objective functions may catch on at the level of industries or across geographies. This momentum and its inertia is likely to cause the incumbent’s network information flow to become increasingly familiar and reduce the number of new combinations that can be generated (Gambeta et al. 2019; Harrison et al. 2010; Uzzi 1997), reversing some of the benefits of close ties.

For new entrants, incumbents’ overly generous bargaining and unprofitable stakeholder loyalty, both create opportunities. If incumbents receive a small proportion of potential industry earnings to be used as developmental resources and suffer from a stymied flow of opportunities, then they are less likely to be able to innovate. Unproductive stakeholder loyalty also hampers the ability of incumbents to make the strategic changes needed to benefit from environmental dynamism. For instance, Sun et al. (2019) suggest that over-investment in CSP can leave the firm with depleted resources. Old ties will prevent incumbents from spending significant resources on developmental initiatives that require alternative stakeholder networks, thus leaving more opportunities available in alternative networks to be exploited by newcomers. After all, incumbents tend to avoid innovations that destroy the competences of their existing stakeholder network (e.g., Tushman and Anderson 1986), and disruptive technologies that alienate their most profitable and demanding customers (Bower and Christensen 1995). It is also consistent with the stakeholder perspectives on entrepreneurship where entrepreneurs weave new networks of stakeholder relationships to create organizations (Greve and Salaff 2003).

In sum, while we continue to stand by our first hypothesis predicting that higher levels of incumbent SMP are likely to increase barriers to entry, we also acknowledge the potential for over-investment to create opportunities for innovative entry. Accordingly, we expect that very high and very low levels of SMP will be associated with more entries, leading to a curvilinear relationship.

Hypothesis 2

A curvilinear relationship exists between incumbent stakeholder management performance and rates of entrepreneurial entry.

Stakeholder-Resource Perspective and New Entry

Incumbents pay more attention to good relations with the stakeholders that matter more to their business activities linked to competitive advantage (Barney 2018). From an instrumental viewpoint, firms can afford ‘poor’ or contentious relations with those stakeholders who are peripheral to the core business, without adversely affecting their business operations. Barney (2018) suggests that a firm should invest generously in stakeholders that contribute resources to the firm’s unique self-reinforcing bundle that generates competitive advantage, and invest minimally in stakeholders that provide resources (tangible or intangible) that are neither rare nor hard to imitate. However, both Jones et al. (2018) and Wang and Choi (2013) point out the need for consistency because a lack of consistency can harm a firm’s reputation in the eyes of stakeholders. Similarly, De Roeck and Maon (2018) suggest that firms that practice inconsistent CSP (e.g., treating external stakeholders worse than internal stakeholders) may find themselves unable to reap the rewards of their effects, or may even be viewed as hypocritical (Scheidler et al. 2019).

An industry usually involves several firms competing for the support of customers, suppliers, investors, communities and other stakeholders. Each firm may employ a different strategy in order to compete. For instance, firms with a broad cost leadership strategy will cater to a different set of stakeholders than firms with a focused differentiation strategy. If firms adopt different strategies and a wide variety of strategies are present in an industry (e.g., all four of Porter’s generic strategies are in use), then we can expect that most stakeholders will receive attention from someone.

Gaps in stakeholder investment manifest at the industry level where some stakeholder groups are essentially neglected by all, or nearly all, incumbents. The gaps left by incumbents create opportunities for new entrants that develop strategies that cater to the marginalized stakeholders (Venkataraman 2002). We see it when startups like Uber and Airbnb nurture a whole new pool of previously neglected suppliers (car owners and homeowners), or when marginalized customers latch onto lower performing, but affordable products like Netflix and Youtube. We see it when mistreated communities push for local internet service provision; when neglected small businesses adopt open source software solutions, or when ignored environmentalists protest and campaign for legislation favoring green (local) businesses, or when the crowd supplies funding to entrepreneurs who could not obtain capital from traditional sources. Thus, we expect that:

Hypothesis 3

The larger the variance in stakeholder management performance across stakeholders, the higher the rate of entrepreneurial entry.

Methods

Sample and Data

We use and combine three datasets in our analysis. First, we use the KLD database to measure SMP (Coombs and Gilley 2005; Garcia-Castro and Francoeur 2016; Hillman and Keim 2001). We note that KLD has also been used to measure corporate social performance (CSP), however, we believe it is more appropriate to measure SMP. When used to measure CSP, KLD-based measures often include social issues that are not directly related to stakeholders (e.g., avoiding investment in tobacco or weapons—see Hillman and Keim 2001), or exclude non-financial stakeholders (Flammer and Kacperczyk 2019). Nonetheless, we include a robustness check for the above interpretations.

The KLD data is compiled by an independent rating service using annual surveys, companies’ annual and quarterly reports and proxy statements, as well as external data sources including media reports about corporate behavior. This data is the most widely used and best source for SMP outcomes (Hillman and Keim 2001), contrasting with other measures of stakeholder management that examine manager’s dispositions and cognitions about their stakeholders (e.g., Greenley and Foxall 1997). Second, we collect the data on entrepreneurial entries from the annual Kauffman Entrepreneurship Survey (KES) reported on the Kauffman Foundation website. The KES data provides comprehensive information about new business creation activities in the U.S. Third, the financial data used for control variables comes from the Compustat North America database.

The sample period of this study is from 2003 to 2013. Prior to 2003, the KLD database only covered 1100 U.S. companies. In 2003, KLD coverage was expanded to the 1000 largest U.S. firms and 2,000 firms with smaller market capitalizations. Our sample period thus starts in 2003 to ensure that the measurement of SMP captures a wide range of firms in the economy. After 2013, SMP scores cannot be computed for many firms due to the large number of missing observations. Our sample period thus ends in 2013.

Our industry classification is primarily based on the structure in the KES database. The KES data divides the industries into 14 industry sectors, including Agriculture, Mining, Construction, Manufacturing, Wholesale & Retail Trade, Transportation & Utilities, Information, Financial Activities, Professional & Business Services, Educational & Health Services, Leisure & Hospitality, Other Services, Public Administration, and Armed Forces. According to the industry description in the KES database, we then map the corresponding SIC codes to Compustat in order to construct industry-level variables. We drop the industry of Armed Forces in the analysis due to lack of observations in Compustat.

Dependent Variables

We use the percentage of individuals starting a new business among all observations in a given year, industry, and state to measure the extent of entrepreneurial entries (Entrep%). For instance, there are seven new entrepreneurial entries out of 65 total observations in year 2011, state 43 and industry 1. The Entrep% equals 10.77% (= 7/65). The Kauffman survey asks a large sample of individuals whether or not they created a business in the last month. More specifically, following the methodology of Fairlie (2014), the entrepreneurship number is counted as individuals who do not own a business in the first survey month, but start a business in the following month with fifteen or more hours worked. The range in ages for these individuals was 20–64. Similar to Fairlie (2014), we also excluded observations with allocated labor force status, class of worker, and hours worked variables. We note that our measure of entry does not count new corporate ventures, nor does it capture industry reclassifications.

Independent Variables

The KLD database provides evaluations of companies’ SMP based on a binary rating for each item of strengths and concerns along seven dimensions, including community, human rights, employee relations and diversity, governance, environment, and product issues. Conceptually, these dimensions map onto relations with particular primary stakeholder groups (Harrison and Freeman 1999; Waddock and Graves 1997). Human rights, diversity and employee relations all relate to the relationship of firms and their employees. Environmental relations and community relations measure dimensions of a firm’s relationship with communities. Customer relationship can be estimated from product safety issues. Suppliers may also be considered to the extent that diversity issues report on dealings with minority-owned suppliers (Hillman and Keim 2001). Corporate governance issues indicate relations with shareholder and measure executive compensation and reporting transparency (Kang 2015).

When a firm conducts a good deed (a harm), which is listed as a strength (concern) indicator, it gains (loses) one point. If there is no event related to a strength or concern, it is coded as zero. Prior studies (e.g., Deng et al. 2013) argue that it is inappropriate to compare aggregate scores across years and dimensions because the number of strength and concern indicators changes substantially over the years. To mitigate this drawback, we follow Deng et al. (2013) and construct an aggregate SMP measure by dividing the scores by the total number of strengths and concerns as follows:

$$Aggregate \,{SMP}_{i,t}= \frac{\sum Strength \,{scores}_{i,t}}{{N (Strength \,scores)}_{i,t}}-\frac{\sum Concern \,{scores}_{i,t}}{N{\left(Concern \,scores\right)}_{i,t}}$$

(1)

We also compute the SMP score at the individual stakeholder level. We use the aggregate SMP scores in our main tests and use the individual stakeholder SMP scores to explore the stakeholder-level implications. To measure the level of SMP, we take the median value of Aggregate SMP for a given year, industry and state. For example, if there are 5 firm-level observations in a given year/industry/state context, with scores of 0.15, 0.33, 0.45, 0.68, and 0.77, then the median at the context-level is 0.45. The median value is used and not the mean because it is not affected by outliers in the sample observations.

We compute a standard deviation measure of SMP scores among seven stakeholder groups to proxy for the extent of the imbalances in the stakeholder management within firms (Imbalance (Std_SMP)). Similarly, we take the median value of Imbalance (Std_SMP) of observations categorized for a given year, industry, and state.

Changes were made to the KLD database over the years such as adding/removing indicator variables, with the most significant being in 2010. MSCI acquired RiskMetrics, the parent company of KLD in that year, and there were so many changes that 2010 and subsequent years are not comparable to any of the previous years. To address these concerns, we have adjusted the numbers of indicators in each year in computing Aggregate SMP and also controlled year fixed effects in all the regressions, which largely mitigate the concern on the inconsistency of indicators across years in the KLD database.

Control Variables

We include several additional variables in the regression analyses. The control variables are as follows. Log gross domestic product per capita (LogGDP_per) for the U.S. by year, as we expect that entrepreneurial entries will be more difficult during years with sluggish economic conditions. Gini_coef, income inequality measured by Gini Coefficient for a state in a given year, because income inequality has been linked to increased necessity entrepreneurship (Xavier-Oliveira et al. 2015). These two variables are obtained from the website of the World Bank.¹Firm Size, median value of the natural logarithm of total assets for a given industry and year, because concentrated industries are expected to pose greater barriers to entry (Demsetz 1982). Profitability, median value of the ratio of net income to book value of assets for a given industry and year, because new entrepreneurs may be attracted to industries with high profitability level and fill the gaps (Eaton and Lipsey 1980; Rosenbaum and Lamort 1992). Investment Intensity, median value of capital expenditure divided by total assets for a given industry and year, because if the industry requires substantial investment, as reflected in higher investment intensity, it will discourage some entrepreneurial entries by individuals due to larger barriers of capital investment and their limited access to external funds (Ho and Wong 2007). Sales growth, the median value of sales growth rate from year t − 1 to year t, for a given industry and year, because munificent industries are expected to attract more entrepreneurial entries (Rosenbaum and Lamort 1992). We list a summary of variable definitions in Appendix A.

Estimations

We use pooled ordinary least squares (OLS) regressions to examine the relationship between entrepreneurial entries and the level of SMP. Our baseline regression is as follows:

$$Entrep\%=\alpha +{\beta }_{1}{\text{SMP}}\,{\text{ Measures}}+{\text{Controls}}+{\varepsilon }_{i,t}$$

(2)

where Entrep% is the dependent variable measuring the extent of entrepreneurial entries; SMP Measures refer to Aggregate SMP, individual stakeholder SMP scores, or imbalance in individual stakeholders of SMP; and Controls are the control variables discussed above. All independent variables are lagged by 1 year to mitigate potential endogenous concerns (i.e., dependent variable uses the year t value and the independent variables are measured using year t − 1 value). In addition, we include year fixed effects to control for minor variations in SMP measurement due to indicator changes in the KLD database across different years, and use robust standard errors to correct for interdependence among observations.

Results

Descriptive Results

We report the sample descriptive statistics and correlation matrix in Table 1. We find that the average (median) yearly entrepreneurial entry level is 0.41% (0.22%). The average (median) Aggregate SMP score is − 0.22 (− 0.21). The negative Aggregate SMP values suggest that incumbent firms have room to improve their stakeholder management, and thus, may open opportunities for entrepreneurial entries to fill the gap. The Pearson correlation matrix shows that the entrepreneurial entry level (Entrep%) and Aggregate SMP are negatively and significantly correlated. The mean value of Imbalance (Std_SMP) is 0.16. The correlation between Entrep% and Imbalance (Std_SMP) is 0.08 and significant at the 5% level, suggesting that larger deviations in SMP are associated with more entrepreneurial entries. We explore these relationships further in the following multivariate analysis.

Table 1 Descriptive statistics and correlation matrix

Main Results

The empirical results on H1 are presented in Table 2. The coefficients of Aggregate SMP is negative and statistically significant (β = – 0.11, p = 0.018). The coefficient of Aggregate SMP suggests that one standard deviation (SD) increase in Aggregate SMP is associated with a 0.052 decrease in the percentage of entrepreneurial entries (Entrep%). It is an economically significant impact because one SD increase in Aggregate SMP is associated with a 12.6% decrease in the percentage of entrepreneurial entries, on average. As shown in Table 1, the standard deviation of Aggregate SMP is 0.47, and the mean value of Entrep% is 0.41. The percentage decrease in Entrep%, 12.6%, is calculated as 0.47 × 0.11/0.41. This result, therefore, provides support for H1 where the higher SMP of incumbents the fewer entrepreneurial entries.

Table 2 Empirical results of Hypothesis 1

To alleviate endogeneity concerns, we apply the instrumental variable (IV) regression and use the political affiliation of the state where the firm is located as the IV. The rationale is that prior studies suggest democratic-leaning states spend more on SMP than Republic-leaning states (Di Giuli and Kostovetsky 2014). Specifically, we measure the political affiliation of a state in the prior presidential election; Democratic is a dummy variable that equals 1 if the Democratic Party attained majority of votes in the presidential election before year t in the state where the firm is located, and 0 if it was the Republican Party. The data on past election results is from Dave Leip’s Atlas of U.S. Presidential Election.

In the first stage regression, we use Aggregate SMP as the dependent variable and the instrumental variable Democratic and control variables in Eq. 2 as explanatory variables. We obtain the predicted value of Aggregate SMP from the first stage regression and then re-estimate Eq. 2 by replacing Aggregate SMP with the predicted value in the second stage regression. The results are reported in Table 3. We find that in the first stage regression, the coefficient of Democratic is positive and significant at the 1% level, consistent with the expectation that firms in democratic-leaning states spend more on SMP than firms in Republican-leaning states. The F statistic is 34.8, which is larger than the critical value (16.38) at the 10% level for the Stock-Yogo weak IV test. Therefore, we reject the null hypothesis that Democratic is a weak instrument. In the second-stage regression, the predicted Aggregate SMP is negatively and significantly associated with Entrep%, consistent with the results reported in Table 2.

Table 3 Endogeneity: IV regressions

We test H2 and report the empirical results in Table 4. H2 predicts that the opportunity of entrepreneurial entries not only exists under low levels of SMP, but also exists under very high levels of SMP. We find that the coefficient of Aggregate SMP is negative and significant (β₁ = − 0.12, p = 0.013), while the coefficient of the square term is significantly positive (β₂ = 0.11, p = 0.002). Thus, our regression results are consistent with the prediction of H2 and show a curvilinear relationship between incumbent stakeholder management and entrepreneurial entries.

Table 4 Empirical results of Hypothesis 2

Following Lind and Mehlum (2010) and Haans et al. (2016), we further provide additional robustness checks to confirm the presence of the U-shape. Lind and Mehlum (2010) suggest that it is important to ensure that the relationship is decreasing (increasing) at low (high) levels within the data interval. Following their 3-step framework, we check and show that: (1) the quadratic term is significantly positive; (2) the slopes are significantly negative at the lower end and significantly positive at the higher end of SMP values; (3) the turning point of the U-shape is well within the SMP data range (results are not tabulated here for brevity). Therefore, we can safely claim the presence of the U-shape.

We also conduct a per stakeholder analyses to examine our results for H2. Our above results are based on aggregate SMP scores, which is constructed with strengths and concerns along seven dimensions, including community, corporate governance, employee relations, diversity, environment, human rights and product issues. We check if the curvilinear relationship between entrepreneurial entries and each dimension of stakeholder management still holds and report the regression results in Table 5. The results show that the curvilinear relationship holds under four (environment, human rights, governance and product issues) out of seven stakeholders. We interpret this to mean that where incumbents under- or over-manage the environment, human rights, shareholders, and product safety, they can stimulate new entries. We still observe positive and significant coefficients for the square term of Aggregate SMP for diversity and employee relations, and the coefficients on Aggregate SMP are positive but not significant—this suggests that managing diversity and employee relations may not elicit a negative main effect on new entry. Community relations on the other hand has a significant negative main effect but non-significant positive quadratic effect—suggesting that firms cannot over-manage communities.

Table 5 Individual stakeholders tests of Hypothesis 2

Finally, we test H3, which predicts that larger deviations in SMP are associated with more entrepreneurial entries. To test this hypothesis, we compute a standard deviation measure of SMP among seven stakeholder groups to proxy for the extent of the imbalances in the stakeholder management within firms. A higher value of standard deviation represents greater differences in managing different stakeholders. We expect to observe a significantly positive coefficient on Imbalance (Std_SMP). Our regression results as shown in Table 6 are consistent with the prediction of H3. We find that the coefficient on Imbalance is significantly positive (β = 0.88, p = 0.008 in column (1)) without including SMP and its square term and remain significantly positive after including these additional variables, with β = 0.71 and p = 0.049 in column (2). In column (1), the coefficient of Imbalance suggests that one SD increase in the stakeholder imbalance is associated with 0.088 increase in the percentage of entrepreneurial entries, which implies 21.5% increase in Entrep% on average. More specifically, the mean value of Entrep% in our sample is 0.41. The SD of Imbalance (Std_SMP) is 0.10. The 0.088 increase in Entrep% represents 21.5% of the mean value of Entrep%. In sum, our empirical findings in Tables 2, 3, 4, 5 and 6 collectively show support for our three hypotheses that relate SMP and the extent of entrepreneurial entries.

Table 6 Empirical results of Hypothesis 3

An Alternative Explanation?

It is possible that there is an alternative explanation for our findings. Incumbents with good stakeholder management practices are likely to have strong financial performance, which leads to lower new entries. To alleviate the concern that our result is driven by financial performance, we conduct a two-stage regression. In the first stage, we regress Entrep% on median profitability and then use the residual as the dependent variable in the second stage. The purpose of doing this exercise is to isolate the direct effect of profitability on entrepreneurial entry, and use the residual to examine the linkage between SMP and entrepreneurial entry. The regression results in the second stage are very similar to those reported in Tables 2, 3, 4, 5, and 6, suggesting that our results are not driven by this explanation (Tables are not reported here for brevity but are available upon request).

Time Period Robustness Check

Due to the changing number of indicators available, we perform a robustness check using the sample of 2003–2009 (the period before MSCI made substantial change to KLD data). We repeat all the tests with this subsample and the results for H1, H2 and H3 remain robust (results are not tabulated here for brevity). There is only one minor exception in the test of H2; the coefficient of Aggregate SMP is insignificant, while the coefficient of Aggregate SMP square remains significantly positive as expected. Accordingly, these additional tests allowed us to confidently include KLD data from 2010, 2011, 2012, and 2013 in our sample.

Consistent Stakeholder Management Robustness Check

To further examine if the stakeholder management is a consistent corporate policy, we check the correlation between Imbalance (Std_SMP), 1-year lag value of Imbalance (Std_SMP), and 2-year lag value of Imbalance (Std_SMP). The correlation coefficient between Imbalance (Std_SMP) and 1-year lag is 0.485 (significant at 0.001 level), and the correlation coefficient between Imbalance (Std_SMP) and 2-year lag is 0.339 (significant at 0.001 level), both of which are considered moderate level correlations. The autocorrelation of Std_SMP suggests consistency in stakeholder management. In an untabulated analysis, we further add Imbalance (Std_SMP) and the two lag variables of Imbalance (Std_SMP) in the regression model (2) as a step-wise design. The two lag variables are both significantly positive, while the coefficient of Imbalance (Std_SMP) is smaller than in the main results of Table 6, and the p value is slightly larger than 10%. It suggests that Imbalance (Std_SMP) in the past 3 years all have impacts on new entry, showing consistent stakeholder management.

Corporate Social Performance Robustness Check

As we mentioned in the introduction section, SMP and CSP are inter-related threads in the management literature, often both using KLD as their main source of data. The constructs are often operationalized in the same way, however, it is worthwhile to examine how our results hold up with two modifications accommodating different interpretations of corporate social performance. First, following Flammer and Kacperczyk (2019), we modified our measure of SMP to exclude corporate governance because it relates to shareholders. Using this version, the results for Aggregate SMP, SMP-squared, and SMP variance remain the same. Second, we add five indicators of social performance unrelated or indirectly-related to stakeholder interests (e.g., exposure to alcohol, tobacco, gambling, firearms, nuclear power, and military contracting), or what Hillman and Keim (2001) called social issue performance. Again, the results remain robust for SMP, and SMP-squared, though we could not calculate SMP variance properly due to changes in the social issues measured each year. Overall, the results appear robust to broader interpretations of CSP.

Discussion

We found that balanced SMP significantly reduced entrepreneurial entry. Our findings suggest that incumbent firms should carefully manage their investments in stakeholders if they seek to avoid providing opportunities for future competitors. This is an important contribution to the business ethics literature given its heavy use of stakeholder theory focused on the advantages of stakeholder management for incumbent firms, but not considering the broader societal implications of corporate longevity in terms of the prospects for future independent entrepreneurs. It counterbalances the evidence from past studies that have generally observed only a positive relationship between high SMP and firm performance (Henisz et al. 2014). Considering new entrants is important given its well-regarded status (e.g., Newbert 2003; Rindova et al. 2009) and the fact that they are expected to be the main source of competence-destroying (Tushman and Anderson 1986) and disruptive/architectural innovations (Bower and Christensen 1995; Henderson and Clark 1990) with the potential to reshape industries.

Insights for Business Ethics Research

Venkataraman (2002) suggested that, left to its own devices, self-interested capitalism would lead to great imbalances and inequities. He suggested a fourth mechanism of redistribution in entrepreneurship; whereas previous scholars had focused on the redistributive role of the moral manager who allocates generously to stakeholders, the bargaining process that ensures that stakeholders that contribute important resources get their due, or the institutional regulation of the legal system and trial lawyers. Like these three mechanisms, entrepreneurship redistributes wealth by taking income streams from incumbents and sharing them with a new set of stakeholders (see also Newbert 2003). However, entrepreneurs redistribute by creating goods and services that attract marginalized stakeholders—Venkataraman call them victimized stakeholders—away from incumbents. Many of these products continue to improve and become qualitatively superior and start to displace incumbencies (see also Bower and Christensen 1995).

The incumbent firm is an intervention that resolves some stakeholder conflicts, and so is the entrepreneurial startup. Entrepreneurship is a market mechanism to resolve inequities (Brenner 1987) caused by the failure of the other three mechanisms. In this paper, we focus on the relationship between the moral manager and entrepreneurial entry. Venkataraman’s analysis implies that there should be a trade-off between these two mechanisms because they are substitutes for each other. This is consistent with the observation that entrepreneurs often have moral (read redistributive) motives for starting their ventures (Clarke and Holt 2010; Newbert 2003). If the moral manager does too good a job of resolving conflicts, then naturally, the entrepreneur will find fewer meaningful gripes to resolve. However, this should not be taken as an endorsement of immoral management, rather, it suggests that moral management is the right path for incumbents and entrepreneurs alike. We simply highlight how the market for startups resolves stakeholder conflicts that incumbent managers fail to resolve. This is similar to takeover threats that regulate agency problems.

We should make clear that we do not discount the role of the institutional environment, which is key to ensuring that the entrepreneurial mechanism can function (Venkataram 2002). Nor do we downplay the role of the bargaining process itself—though we note that the moral manager reallocates resources less shrewdly than might be expected from a purely resource-based perspective (Barney 2018) because of the imperative of maintaining a reputation for fair play among stakeholders (Jones et al. 2018). Therefore, the moral manager and bargaining mechanisms may not be split from each other cleanly. We also highlight the potential for extremely high levels of stakeholder investment to encourage entry. Overly generous bargaining can leave a firm without the wherewithal to respond to changing environments. Thus, we are left with the implication that some moderate level of moral (read redistributive) management is the way to go, perhaps checked by the survival imperative.

Study Implications and Connections to Prior Research

The curvilinear relationship suggests that incumbent managers can go wrong in two ways when it comes to managing stakeholders, not doing enough, and doing too much. This implies an equilibrium point where investing more in stakeholders starts to pay negative returns in terms of provoking new entries.

The notion of too much of a good thing resonates with a current trend in the broader business ethics literature. Brieger et al. (2019) find that too much focus on CSR can encourage employee addiction to work, perhaps leading to burnout and unwanted employee mobility. Since we focused on aggregate SMP, the implications go even further toward identifying sources of industry ossification to account for the lack of response exhibited by many firms facing environmental changes. Perhaps, it was their imbalanced approach to stakeholder management that led to their new competitors. Our study suggests new insights that help explain why comparing incumbent performance is not likely to capture the role of innovation through entrepreneurial entry. Incumbent rivals may be affected by many of the same power relationships and loyalties. For example, the automotive manufacturing industry in the U.S. is nearly universally unionized, with the notable exception of Tesla Motors, which is a new entrant that has to date avoided worker unionization. Thus, incumbencies may develop similar constraints over time and may tend to invest heavily in the same stakeholders. This is especially true when there is coordination between those organizing independent firms (e.g., the United Automobile Workers). Thus, future models examining how SMP affects firm performance, should also consider the role of innovation as exogenous shocks caused by autonomous actors, which can bring about a whole new generation of products to a host of new markets.

We further investigated the U-shaped curve for each stakeholder group independently with the results presented in Table 5. We contend that we have provided a macro-perspective to an arising stream of CSR research that addresses domain specific effects. There were also two important insights in these results that contribute to an emerging focus on domain-specific (micro) stakeholder management or corporate social responsibility (e.g., De Roeck and Maon 2018; Scheidler et al. 2019). First, the size of the significant coefficients (as we can say little about the insignificant coefficients) suggested that the curvilinear relationship was not equally applicable to all stakeholder types. This meant that the equilibrium point was stakeholder-specific, where too much (little) value for one stakeholder may not be too much (little) for another. Second, four out of seven stakeholders had a significant negative main effect and a significant positive quadratic effect, suggesting that the curvilinear relationship with entrepreneurial entries did not apply to all stakeholders. However, our data tells us that firms in our sample can over-invest in the environment (communities), human rights (employees), corporate governance (investor), and product issues (customers), resulting in more entrepreneurial entries. Taken together, these results question the common assumption that more is better, and it appears that for SMP too much more can be detrimental, resulting in an increased number of future competitors. Further, in our data, firms could not overinvest in the community stakeholder. Future research can probe deeper into the stakeholder specific equilibrium points including which stakeholders, industries and countries does the curvilinear relationship occur and which does it not.

Our results for Hypothesis 3 support the idea that incumbents with a high degree of imbalance, as measured by the standard deviation of their SMP scores by stakeholder group, create opportunities for new entrants. It suggests that industries with many imbalanced firms may offer significantly more opportunities to new entrants because incumbents in such industries are unlikely to develop the close social ties for stakeholder resources combinations and contract efficiencies. This points to several avenues for future research into the causes of imbalance. There may be an opportunity to consider causes of imbalance due to the knowledge structures inherent in the stakeholder resources for example.

Implications for CSP

Given there are many overlaps between the SMP and CSP literatures, and the way that CSP is measured is often similar or the same as how SMP is measured (Brower and Dacin 2020; Luo et al. 2015; Perrault and Quinn 2018), we ran two robustness checks accounting for varying operationalizations of CSP. The results suggest that the concepts develop herein are robust to both narrower (Flammer and Kacperczyk 2019) and broader interpretations of CSP, yielding implications for a broader literature examining corporate social performance. For example, Sun et al. (2019) found an inverted-U shaped curve describing the relationship between CSP and firm performance. Similarly, Feng et al. (2018) find an inverted U-shaped curve between ethical management of employees and employee creatively.

Implications for Entrepreneurship Research

Our results are relevant for incumbent firms seeking to maintain a competitive advantage by limiting future competition. However, our results also have implications for entrepreneurship researchers working on opportunity recognition and exploitation themes (e.g., Burns et al. 2016). For example, the process of customer discovery (Blank 2012) can be viewed as a rapid substitute for deep embedded exposure to stakeholder groups—to gain knowledge about their utility functions and gain their support. Customer discovery is one of “the ways individuals might make cognitive contact with opportunities prior to their actualization” (Ramoglou and Tsang 2016, p. 410). Future research might investigate how entrepreneurs solve the information asymmetry problems inherent in competing with stakeholder managing incumbents. Perhaps entrepreneurs should focus on opportunities in markets where incumbents take more of a shareholder return maximization perspective (Freeman et al. 2004; Friedman 1962; Jensen 2002; Parmar et al. 2010) because the information asymmetry advantages of the incumbents in such contexts should be significantly muted. Alternatively, perhaps activist entrepreneurs may be able to unravel incumbents’ reputations for fairness by constructing new narratives that paint them in a less favorable light (Dey and Mason 2018; Rindova et al. 2009). Alternatively, new entrants may develop new frames that give themselves greater legitimacy vis-à-vis incumbents (Hiatt and Carlos 2019).

Limitations

Our study has from some empirical limitations. First, although new entry can come from diversifying incumbents, our data was limited to entrepreneurial entries by individuals. For instance, cross-boundary disruptors like Apple that started in one industry, then moved into other industries (e.g., music). Future researchers may be able to find ways to include these types of cases in their analyses. Similarly, while employee spinouts are captured in our sample, we could not parse them out to test if spinout founders have access to greater network resources. We would expect that startups founded by teams of ex-employees of the same parent firm to be better able to take with them the stakeholder knowledge resources (i.e., utility functions) and the relationships and reputations that sustain access to this tacit knowledge about needs and abilities. This helps to answer another question in the literature about what type of knowledge spinout founders take with them from their parent firms. It seems that the key knowledge would be the utility functions of parent firm stakeholders. Future research could examine if the type of parent firm culture (stakeholder or shareholder oriented), has an impact on the ability of spinouts to form in the first place. Recent research suggests that CSP can reduce knowledge spillovers via spinouts (Flammer and Kacperczyk 2019). If spinout firms are embedded in firms with opportunistic organizational cultures they may be less likely to gain special access to parent firm stakeholder utility functions. By contrast, spinout founders embedded in parent firms that manage for stakeholders may gain access to stakeholder utility functions and may thus be better able to make new combinations from knowledge of the true needs and abilities of stakeholders. Alternatively, it seems that being able to hire or partner with individuals that have access to important tacit knowledge in an industry is vital. It would be interesting to see if tacit knowledge transfers from stakeholders accrue to employees and founders in the same way.

Second, we accept the biases of the KLD data set. Relying on primarily public data and targeting primarily publicly listed and more visible firms, the KLD data do not give a very representative and comprehensive view of the total population of firms. In particular, more covert types of stakeholder influences and relationship management remain outside the purview of the dataset. This clearly constrains the generalizability of our study results. Our SMP variables are constructed using data from the KLD database, which has its own limitation indicating that we need to exercise caution in explaining the results. For example, Chatterji et al. (2016) suggest that KLD and other corporate social rating agencies (such as Asset4, FTSE4Good, Innovest, DJSI) may apply different criteria in assessing rated firms.

Third, we acknowledge the possibility of reverse causation. While we lagged our dependent variable by 1 year to control for this, the possibility cannot be completely eliminated. For instance, Flammer (2015) and Dupire and M’Zali (2018) found that firms increased their investment in corporate social responsibility in response to increased product-market competition. Similarly, it is possible that incumbents may increase their investments in marginalized stakeholders in response to a wave of new entrepreneurial entries. For example, many taxi companies now offer the same electronic service level as Uber.

Conclusion

We extend instrumental stakeholder theory to explain entrepreneurial entry. This is in contrast to prior studies that have primarily compared the performance of rival incumbents and looked for competitive advantage derived from stakeholder management practices. Our findings provide yet additional empirical support for the active management of stakeholders, and, in particular, that failure to balance SMP can lead to a significant increase in entrepreneurial entry. This research is timely and important given that entrepreneurial entrants are increasingly viewed as key sources of innovations leading wealth redistribution, economic development and emancipation.

Appendix A: Variable Definitions

Variable	Definition
Entrep%	The percentage of entrepreneurship among all observations in a given year, industry, and state
Aggregate SMP	$Aggregate \,{CSR}_{i,t}= \frac{\sum Strength \,{scores}_{i,t}}{{N (Strength \,scores)}_{i,t}}-\frac{\sum Concern \,{scores}_{i,t}}{N{\left(Concern \,scores\right)}_{i,t}}$ We take the median value of Aggregate SMP of a particular group of observations to measure the level of stakeholder management for a given year, industry, and state
Imbalance (Std_SMP)	Median value of the standard deviation of SMP scores by stakeholder groups of observations categorized for a given year, industry, and state
Firm size	The median value of the natural logarithm of total assets for a given industry and year
Profitability	The median value of the ROA, the ratio of net income to total assets for a given industry and year
Investment intensity	The median value of the ratio of capital expenditures to total assets for a given industry and year
Sales growth	The median value of sales growth rate from year t − 1 to year t, for a given industry and year
LogGDP_per	GDP per capita of U.S. for a year
Gini_coef	Income inequality measured by Gini Coefficient for a state in a given year