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Abstract

Organizational slack is associated with various positive effects on the organization. By focusing on slack’s cushioning property, which shields the firm from external adversities, this article discusses how slack can also mute important external stimuli for problemistic search and increase adverse self-enhancement effects when an organization performs below aspirations. We use panel data on publicly traded firms to test how shareholder voice affects problemistic search and how slack negatively moderates this relationship. We also show that problemistic search suffers more in self-enhancing firms as a firm’s slack increases. We contribute to the behavioral theory of the firm by unfolding the negative side of slack and demonstrating how differentiation between internal and external coalition perspectives unfolds new sides of this concept.

JEL Classification: L20, M10

Keywords

Performance feedback problemistic search self-enhancement shareholder voice slack

1. Introduction

Organizational slack is a foundational concept in the behavioral theory of the firm (Mount et al., 2024), which, according to Cyert and March, “permit[s] the business firm to make decisions with inconsistent goals” (Cyert and March, 1963). The positive properties of organizational slack have drawn significant attention from scholars who suggested that slack increases organizational learning (Argote et al., 2021), reduces conflict (Levinthal and Rerup, 2021), intensifies search (Baum et al., 2005; Chen, 2008; Greve, 2003a; Posen et al., 2018), and enhances organizational change (Kuusela et al., 2017). Organizational slack also acts as a “cushion” (Cyert and March, 1963) by stabilizing the firm through reduction of goal conflict (Mount et al., 2024) and absorption of variability of the firm’s environment (Bradley et al., 2011). However, such a cushioning effect might also inhibit external stimuli, such as shareholder voice, for organizational search and change since slack would allow the firm to ignore critical external feedback rather than attend to it. Also, a cushion from external coalitions might galvanize murky internal practices, such as self-enhancement, which also inhibit problemistic search (Jordan and Audia, 2012) when a firm performs below aspirations. It follows that slack’s “cushioning” property may cause a negative side effect, which has not been addressed by the literature so far. Hence, in this article, we address the following research question: Does the cushioning property of slack have a negative side effect on the firm’s ability to search, when firm performance falls below aspirations?

Scholars of the behavioral theory of the firm distinguish between problemistic search (Posen et al., 2018), which is triggered by firm performance below aspirations, and slack search (Greve, 2003b; Levinthal and March, 1981), which occurs when an organization performs above its aspirations. Existing empirical evidence suggests that organizational slack increases organizational search for all performance bandwidth (Chen and Miller, 2007; Greve, 2011), or when the firm performs below aspirations only (Cao et al., 2024; Tyler and Caner, 2016). Kuusela et al. (2017) also show that the search behavior of firms with low slack differs from that of firms with high slack such that slack decreases the propensity of divestment and increases the propensity of acquisitions in firms performing below aspirations. In addition, the behavioral theory of the firm (Cyert and March, 1963) suggests that slack has a cushioning effect but provides little insight into how such an effect impacts organizational search. Thus, both the theory and existing evidence suggest that the role of slack in search and learning processes is rather complex.

This article draws attention to the controversial role that slack plays in problemistic search, when on one hand, it supports innovation and search, but on the other, it shields the firm from adversities and the need to respond to negative feedback and be accountable to external stakeholders. We pose that high slack may also protect self-enhancing managers within the firm and mute the voice of external coalition members. Hence, it is crucial to examine the potential drawbacks of the cushioning property of slack and whether there are factors that motivate problemistic search that are actually inhibited by organizational slack and negative factors that are motivated by slack. An example of a company whose accumulated slack is associated with the decline in innovation is Apple Inc. The company has been criticized for making only incremental changes in its new products, and as Petro (2019) points out, “at its core, Apple is no longer innovative.” At the same time, Apple topped the list of S&P 500 firms as the company with the highest cash in hand (Krantz, 2021). And while Apple performs well, it is clear that the company has high-slack resources and is reluctant to listen to stakeholder concerns about its innovativeness.

Building on literature related to performance feedback (Audia and Greve, 2021; Keil et al., 2023; Kotiloglu et al., 2021) and self-enhancement (Kostopoulos et al., 2023; Levinthal and Rerup, 2021) as well as Hirschman’s (1970) idea of voice as the articulation of critical opinions by organizational affiliates, we explain the negative side effects of slack through distinguishing between internal and external coalition members and argue that along with shielding a firm from external adversities, slack also shields internal coalition members from the communication and accountability to external coalition members. Following Hirschman (1970), we define shareholder voice as the expression of critical opinions by the shareholders about an organization in decline. Hirschman constructs voice as a political instrument through which stakeholders can pressure the firm to change, and as an alternative to economic choice between staying and exiting from the relationship with the firm. We exploit the idea that external coalition members, such as shareholders, motivate firms to increase problemistic search in order to adapt to adversities, and further pose that slack will reduce such external stimuli. We are particularly concerned with organizational search during performance shortfalls, which is known as problemistic search (Posen et al., 2018), for two reasons. First, problemistic search is critical for organizational survival (Posen et al., 2018) as it demonstrates organizational ability to adapt to the changing environment. Second, adverse effects of self-enhancement are particularly sensible during performance shortfalls as symbolic acts of self-enhancement substitute for actual organizational adaptiveness to negative feedback (Audia and Brion, 2007; Jordan and Audia, 2012). In this study, we define self-enhancement as a firm’s action intended to present the firm’s performance as better than it actually is.

Empirically, we examine situations where firms engage in problemistic search in response to performance declines and further test how slack negatively moderates the effect of shareholder voice and self-enhancement on problemistic search. We predict that firms cushioned from the environment by high slack will have stronger adverse effects from self-enhancement on problemistic search and weaker positive effects from shareholder voice on problemistic search.

We test our respective set of hypotheses using 11 years of panel data on publicly traded US firms, assembled from shareholder proposals, accounting restatements, ownership, and financial databases. Our main thesis is that organizational slack reinforces the position of internal coalition members and mutes the voices of external or peripheral coalition members in organizational search processes. Slack not only stabilizes the firm (Cyert and March, 1963) but it also partially blocks organizational change by limiting external and peripheral stimuli for organizational search, hence potentially narrowing the search itself. The major contribution of this article is that it unfolds the negative side of slack in organizational search. This article also shows that an embrace of external coalition perspectives on the behavior of the firm allows us to rethink and understand better how old organizational theory concepts, such as slack, work and unfold new unusual sides of these concepts.

2. Theory and hypotheses

2.1. Problemistic search and slack

March and Sutton (1997) saw organizational performance as a powerful predictor of organizational actions. Both firms on organizational level (Cyert and March, 1963; Gaba and Joseph, 2013) and individual members of organizational coalitions (Hu et al., 2023; Mithani and O’Brien, 2021) monitor and react to organizational performance relative to aspirations, or performance feedback (Audia and Greve, 2021). Firm performance below the aspired level is deemed to be a problem (Cyert and March, 1963) and, hence, requires search for a solution, or problemistic search (Posen et al., 2018). Problemistic search is a necessary, though not sufficient, condition for organizations to recover from performance decline, in both absolute and relative terms, and needed for their long-term survival.

Organizational studies emphasized the importance of slack resources in organizational ability to activate problemistic search (Mount et al., 2024). According to Cyert and March (1963), slack is some sort of surplus resource that a firm has and that exceeds a firm’s usual needs. In times of adversity, slack is a much needed resource that helps the firm to experiment and search for solutions more intensely. For instance, slack enhances exploration (Zhang et al., 2023) and acquisition (Iyer and Miller, 2008) by firms performing below aspirations, fosters innovation during downsizing (Ramdani et al., 2021), increases reliability of risky expenditures (Lu et al., 2023), and enhances proactive search behavior (Jiao et al., 2020). Because slack helps firms to sustain adversity, Cyert and March (1963) suggest that slack acts as a cushion between the firm and the external environment.

Since a firm consists of coalitions, both internal and external (Mithani and O’Brien, 2021), slack is also needed to make payments to the coalition members to ensure that they remain with the firm. Hence, slack is a factor in organizational politics that holds the firm together; however, it is mainly in control of the management team, which reinforces managerial perception of control over the firm and its environment (Schwarz et al., 2020). However, effects of slack on the firm are nuanced. Slack benefits generalist firms more than the specialists (Kim and Rhee, 2022). Also, while slack’s abundance is usually positive for the firm, slack scarcity is a problem as it constrains a firm’s adaptability and innovativeness (Ramdani et al., 2021). Effects of slack on the firm vary depending on the type of slack (Lu et al., 2023; Mount et al., 2024; Yang and Jiang, 2023). For organizations, slack works differently for different search behaviors (Jiao et al., 2020), enhancing search when firm behavior is proactive and suppressing search when the behavior is reactive. Yet, it is managerial proactiveness that is rewarded by the slack resources, while other coalition members may be muted by the slack’s cushion.

2.2. Shareholder voice and problemistic search

Although firms are a bundle of coalitions, existing literature has focused mostly on internal coalition members who respond to performance feedback (Audia and Greve, 2021), yet the role of external coalition members in performance feedback has been understudied. Selected works emphasize that external factors such as customer concentration (Zhong et al., 2020), institutions (Greve and Teh, 2018), external rankings (Sharkey and Bromley, 2015), and media pressure (Shipilov et al., 2019) are factored into performance feedback and organizational search processes. Park et al. (2024) highlight how firms use external search to look for ideas. Yet, behavioral theory of the firm has overlooked shareholder voice (Hirschman, 1970), that is feedback from the shareholders, despite the evidence from the literature on shareholder activism (Denes et al., 2017; Foss et al., 2021; Goranova and Ryan, 2015) that shareholders take an active role in organizational decision-making. In this article, we look at shareholders as a specific group of external coalition members and theorize that shareholders, collectively, as external members of the goal-setting coalition, trigger problemistic search when performance falls below their aspired level.

Shareholder involvement in organizational behavior has been overlooked by management research or deemed passive (Mithani and O’Brien, 2021; Jensen and Meckling, 1976). Yet, Cyert and March (1963) mention stockholders as members of the goal-setting coalition while Greve and co-authors (Audia and Greve, 2021; Greve and Teh, 2018) advocate that organizational goals can be imposed externally. Cyert and March (1963: 88) also mention that “search behavior can be initiated by an exogenous event.” Hence, we should not ignore the presence of shareholders in the coalition concerned with organizational performance goals. Zhang and Greve (2019) look at how directors’ backgrounds impact organizational decisions under a performance shortfall. In this article, we focus on shareholders as a collective class of external coalition members. While there is significant variation in the behavior of individual shareholders with respect to the focal firm, we acknowledge that by design of the shareholder ownership rights, shareholders collectively should be systematic in their responses to variance in organizational performance.

In the stream of research on voice in organizations, Hirschman (1970, 1974); suggests that shareholders can give feedback to the firm through raising their voice when organizational performance deteriorates. Indeed, Karpoff et al. (1996) show that shareholders submit more shareholder proposals when a firm is not making a profit. Hence, voice as a form of feedback might trigger organizational search and change. Cyert and March (1963) note that the amount of search depends on the amount of motivation for search, and shareholder voice should enhance such motivation of the firm’s managers. Therefore, we anticipate that when a firm’s performance falls below aspirations, shareholder voice will motivate problemistic search.

Hypothesis 1 (H1). Shareholder voice is positively associated with problemistic search when a firm performs below aspirations.

2.3. The muting side effect of slack

In contrast with the behavioral theory of the firm, which saw slack as a factor of stability and innovation (Cyert and March, 1963; Levinthal and March, 1981), Hirschman thought of slack as a barrier from the critical voice of different stakeholders (Hirschman, 1970). While external stakeholders, such as shareholders, may give feedback to the firm whose performance deteriorates, the firm may listen to such external signals or ignore them (Hirschman, 1970). Hirschman further suggests that organizations with high slack are more likely to ignore external feedback. The cushioning effect of slack (Bourgeois 1981; Cyert and March, 1963) allows a gap between actual and potential organizational response to adversity.

However, it is not clear whether an organization’s own negative performance feedback should be considered to be such an adversity. This would not be a problem if organizations were oriented exclusively toward problem-solving, but as Audia and Greve (2021) suggest, organizational response to negative performance feedback is not necessarily straightforward and is refined through preferences and beliefs of the managers (Cao et al., 2024; Choi et al., 2019), who are an internal part of the organizational goal-setting coalition. Managers with high self-enhancement can ignore negative feedback on certain goals by reorienting attention to more favorable outcomes on other goals (Jordan and Audia, 2012). Power can be a good predictor of high self-enhancement (Audia and Greve, 2021), and high slack gives an organization some power to ignore the environment, including the pressure from external coalition members. High slack may also reinforce managers’ belief that they are on the right track (Chambers et al., 2024) and make them attend to external stimuli reluctantly.

Jordan and Audia (2012) further suggest that self-enhancement is a behavioral choice of internal decision-makers in contrast to the informed external observer. Hence, while we argued earlier that shareholders stimulate problemistic search, slack allows internal decision-makers to resist such external stimuli and respond to performance below aspirations with less search than they could potentially engage in. While slack can boost improvisation and learning, this article suggests that slack filters external stimuli, and therefore slack-driven learning might be gravitating toward the preferences of internal coalition members. This suggests that the positive effect of shareholder voice on problemistic search, which we theorized earlier, will be muted in firms with high slack.

Hypothesis 2 (H2). Slack negatively moderates the direct relationship between shareholder voice and problemistic search during negative performance feedback, such that an increase in slack will reduce the positive effect of shareholder voice on problemistic search when the firm performs below the aspirations.

2.4. Slack and adverse effects of self-enhancement

While slack could inhibit external stimuli for problemistic search and organizational change, we further discuss how the cushioning property of slack could intensify adverse internal processes that hinder problemistic search, such as self-enhancement. We theorized earlier that slack not only protects the firm from external adversities, but it also shields internal coalition members from the voice of external coalition members. The behavioral theory of the firm (Cyert and March, 1963) posits a firm as a political organization (March, 1962) where coalitions of groups and individuals cluster around goals. The membership in these coalitions, however, is not limited to those individuals or groups that fit within the formal boundaries of the organization. But internal members of the coalition have more control over an organization than external members (Eisenhardt, 1989; Jensen and Meckling, 1976). Hence, when external voice is muted, it is prudent to assume that the weight of internal coalition members in organizational decision-making increases further.

Internal coalition members, such as managers, are often reluctant to engage in risky problemistic search and are often oriented toward self-enhancement (Jordan and Audia, 2012; Levinthal and Rerup, 2021). When firms self-enhance such that they draw a positive image of themselves regardless of their actual performance, such firms will be less likely to engage in problemistic search when their performance deteriorates. We further extend this idea by suggesting that by cushioning the firm from external influence, slack would reinforce the negative effect of self-enhancement on problemistic search as external influence on high-slack firms will be weaker. Audia et al. (2022) discuss such external influence as they portray investors as audiences who exercise pressure on the senior managers of a firm. The authors further show that powerful managers care less about external evaluations as their power allows them to ignore shareholder pressures. High slack manifests an organization’s high past performance (Cyert and March, 1963), and past performance manifests future managerial power (Daily and Johnson, 1997); therefore, we can assume that organizational slack is an indicator of managerial power.

In both cases, whether managerial power is high or organizational slack is high, we can see that such organizations rely less on external evaluations and pressures (Audia et al., 2022). Empowered by high slack, self-enhancing managers will care less about the need to respond to negative performance feedback and will take less risk in an attempt to change the firm. By bringing into the spotlight the perspectives on internal and external coalition members, we can see how organizational slack, which is situated within and controlled by the focal organization, weakens the influence of external coalition members and increases the power of internal ones. As managers of high-slack firms are prone to self-enhancement (Jordan and Audia, 2012), we can expect stronger negative effects of self-enhancement on problemistic search, as external controls on such firms will be less effective. Hence, our third hypothesis is the following:

Hypothesis 3 (H3). Slack positively moderates the inverse relationship between self-enhancement and problemistic search during negative performance feedback, such that an increase in slack will increase the negative effect of self-enhancement on problemistic search when a firm performs below aspirations.

3. Data and methods

3.1. Sample

Our theoretical focus requires data on external and internal members of the goal-setting coalition as well as firm-level information in order to distinguish data on external shareholder voice, internal self-enhancement, organizational search, and slack, as well as other relevant parameters. Publicly traded firms can be a sufficient source of the required data. Hence, to test our hypotheses, we assembled panel data on firms included in the S&P 1500 index over the period 2006–2016. We combined data from different sources, including Institutional Shareholder Service (ISS), Audit Analytics, and Bloomberg and Capital IQ. Since we are concerned with shareholder voice and operationalize it using data on shareholder proposals, we identified 855 firms from the ISS database whose shareholders submitted proposals during the analyzed time frame. Following Hu et al. (2023), we dropped firms from banking, insurance and financial services industry (Standard Industrial Classification [SIC] codes starting with 6), regulated utilities (SIC codes starting with 49) and unclassified firms (SIC codes starting with 99), which reduced our sample to 674 firms. Also, since we needed to construct aspiration levels relevant for the shareholders, we collected lists of peer firms from Bloomberg, and because for some firms, these data were not available, our sample was further reduced to 469 firms. Finally, some of our observations had missing data, and these incomplete observations were dropped during the estimation process. Thus, our final data sample included 4405 firm-year observations for 454 firms over the period 2006–2016 (see Table 1 for details).

Table 1.

Summary statistics.

Variable		M	SD	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)	(9)	(10)	(11)	(12)	(13)	(14)	(15)
R&D % of Sales	(1)	4.42	17.48	1
CapEx % of Sales	(2)	11.02	26.57	−0.02	1
Performance below social aspirations	(3)	0.03	0.07	0.24*	−0.03	1
Performance below historical aspirations	(4)	0.03	0.30	0.01	−0.00	0.09*	1
Performance above social aspirations	(5)	0.04	0.31	−0.00	−0.01	−0.05*	−0.01	1
Performance above historical aspirations	(6)	0.02	0.30	0.01	−0.01	−0.01	−0.01	0.94*	1
Shareholder proposals	(7)	0.71	1.47	−0.01	−0.03*	−0.00	−0.01	0.02	−0.00	1
Self-enhancement	(8)	0.15	0.35	0.00	−0.03	0.04*	0.00	−0.01	−0.01	−0.01	1
Slack absorbed	(9)	19.09	16.36	0.22*	−0.16*	0.10*	−0.00	−0.00	−0.02	−0.05*	0.02	1
Slack available	(10)	2.24	3.43	0.07*	−0.01	0.01	0.01	0.00	0.01	−0.02	0.06*	−0.01	1
Slack potential	(11)	19.26	222.04	−0.00	−0.01	0.01	0.00	−0.00	0.00	0.01	0.01	0.03*	0.01	1
Assets	(12)	19.83	50.16	−0.01	−0.01	−0.03	0.00	0.01	−0.02	0.44*	−0.02	−0.04*	−0.04*	−0.01	1
Employees	(13)	0.04	0.12	−0.04*	−0.08*	−0.05*	−0.01	0.00	−0.01	0.25*	−0.03	−0.00	−0.08*	0.01	0.39*	1
Debt	(14)	4.88	20.26	−0.01	0.00	−0.02	−0.00	−0.00	−0.01	0.27*	−0.01	−0.01	−0.03*	−0.01	0.85*	0.26*	1
Age logged	(15)	3.91	0.79	−0.13*	−0.14*	−0.08*	0.00	0.01	0.01	0.07*	−0.05*	−0.04*	−0.07*	−0.00	0.14*	0.12*	0.08*	1
Ownership concentration	(16)	0.37	0.34	−0.01	−0.02	0.03*	0.00	−0.01	−0.01	−0.09*	0.00	0.01	0.02	−0.01	−0.13*	0.13*	−0.08*	−0.06*

Total number of observations = 4405; M = mean; SD = standard deviation.

If p-value < 0.05.

3.2. Variables

Problemistic search is our dependent variable. We measured problemistic search as research and development (R&D) to sales ratio of the year (t + 1) following performance feedback in year t. There has been some criticism of R&D as a measure of problemistic search because reported R&D poorly measures organizational risk-taking (Bromiley et al., 2017) and scarce attempts to use capital investments (Arrfelt et al., 2013; Audia and Greve, 2006) or marketing expenses (Vissa et al., 2009), or the combination of R&D, capital and marketing expenses (Zhang and Gong, 2018) to measure search or change in organizations. Despite these criticisms, R&D search has been the most widely used measure of problemistic search (Posen et al., 2018). R&D may not be risky (Bromiley et al., 2017), but the original behavioral theory of the firm (Cyert and March, 1963) does not require problemistic search to be risky. Nevertheless, a performance shortfall may indicate a resource constraint, and an increase in R&D under such a condition should reflect an organizational effort to find a solution for the problem of poor performance. Hence, we believe that using R&D to sales ratio is appropriate for studying problemistic search. In the section “Additional analysis” we also tested our hypotheses using an alternative three factor measure (Lim and McCann, 2014).

Shareholder voice is measured as the number of shareholder proposals submitted for the forthcoming annual general shareholder meeting. The submission of shareholder proposals is a streamlined way for shareholders to publicly voice their disagreement with a firm’s management (Denes et al., 2017) and puts external pressure on the firm. Shareholder proposals are accumulated throughout the year and considered annually during the annual shareholder meeting. Hence, the annual amount of shareholder proposals represents a convenient cumulative measure of voice. Shareholder proposals are heterogeneous, and are mostly concerned with corporate governance and compensation issues, and some proposals also include suggestions about other aspects of organizational matters, such as operations and strategy, that may relate to performance feedback. However, Environmental, Social and Governance (ESG) proposals are subject to broader environmental dynamics and institutionalization of ESG practices (Rutherford and Huennekens, 2013) rather than reactions to performance feedback; hence, we excluded ESG proposals from our measure of shareholder voice. While we used total shareholder proposals to measure shareholder voice, we did not account for voting on shareholder proposals (Audia et al., 2022) because the voting power of the proponent of the proposal would bias the proxy measure.

Self-enhancement is coded as a dummy variable equating to 1 if the firm was self-enhancing during the calendar year and zero otherwise. Self-enhancement occurs when firms portray themselves in front of audiences in a positive manner trying to create a better image of themselves (Jordan and Audia, 2012; Levinthal and Rerup, 2021). One example of self-enhancement is overstating financial results, such as earnings, in annual financial statements. It is not uncommon for firms to restate their financial results in the future and firms do so for multiple reasons, the most important of which is US Securities and Exchange Commission (SEC) investigations (Karpoff et al., 2017). Hence, we assume that the negative restatement of corporate earnings is an indicator of self-enhancement; such a restatement shows that the firm originally portrayed a positive image of itself and then had to adjust this and reduce backdated earnings at a future date. We accessed Audit Analytics’ extensive database on financial restatements of publicly traded firms and collected data on negative earnings restatements as a proxy of corporate self-enhancement. Audit Analytics provides the most comprehensive record of corporate financial restatement events (Karpoff et al., 2017), indicating whether restatement was negative or not. Hence, if a firm’s reported earnings for the year 2006 were restated downward in any of the subsequent years, we assigned “1” to the self-enhancement dummy variable for the year 2006 and “0” otherwise. Unfortunately, while Audit Analytics indicates whether the profit restatement was positive or negative, the database often misses the actual amount of restatement, as these amounts were available for only 7.3% of the restatements.

To estimate our hypotheses about side effects of Slack, we used separate measures for absorbed, available, and potential slack (Bourgeois, 1981; Chen, 2008). Absorbed slack was measured as general administrative and marketing expenses to sales ratio; available slack as current assets to current liabilities ratio; and potential slack as market capitalization to earnings ratio (Bourgeois, 1981: 38). Since we are studying the moderating effect of slack on shareholder voice, we need to acknowledge that shareholders are the source of equity resources for the firm; hence, some measures of slack, particularly potential slack, which measures the firm’s potential to attract new financial resources (Bourgeois, 1981), may not adequately represent the “cushioning” effect of slack that is of primary interest to us. Hence, in our regression model, we separately interacted our three measures of slack with shareholder voice and self-enhancement. In the additional analysis, we also tested our hypotheses using the combined measure of slack (Chen, 2008).

As a performance measure, we used return on assets (ROA). Despite the common critique that such a measure is too broad (Audia and Greve, 2021), in the case of shareholders, the use of ROA is justified by the role profitability plays in stock valuations. As Greve and Teh (2018) suggest, financial goals of a firm are often informed externally; hence, we believe that the choice of ROA as the financial goal in studying the effects of shareholder voice and slack in this study is justified.

This article is concerned with how slack interacts with shareholder voice and managerial self-enhancement when performance falls below aspirations; hence, we followed the literature (Kim et al., 2015) and calculated separate measures for historical and social aspirations. Historical aspirations (HA) are derived from a firm’s past performance and, according to Greve (2003b), are measured as the exponentially weighted sum of past performances using the formula below. Following Greve (2003b), we changed the weighting parameter (α) by the increments of 0.1 and picked α = 0.2, which yields the regression model with the highest explanatory power (lowest Akaike Information Criterion [AIC] value) and allocates high weight to more recent historical performance in the historical aspiration measure.

H A_{t} = (1_α) * R O {A_{t}}_{_1} + α * H {A_{t}}_{_1}

(1)

{SA}_{t} = \frac{\sum P e e r f i r m s R O A_{t}}{n u m b e r o f p e e r s}

(2)

We calculated the social aspirations (SA) measure as the average current ROA of the defined list of peer firms from Bloomberg’s relative valuation (RV) function. Since we are concerned with shareholder voice, we needed to select peers that are specific to the shareholders of the firms. Unlike managers, whose mobility is constrained by the formal contracts with an organization and who follow both historical and social aspirations (Kacperczyk et al., 2015), shareholders often form investment portfolios and monitor firm performance in relation to the firm’s peers based on relatedness rather than on formal SIC code.

We used the Bloomberg terminal to pull out lists of peer firms from Bloomberg’s RV function.¹ Relative valuation or multiples method is the common equity valuation technique and the most efficient predictor of share price (Liu et al., 2002). This method requires a selection of the group of comparable firms, whose performance indicators are then used in the valuation of the focal firm (Liu et al., 2002); accordingly, the lists of firms used in relative valuation would be the best match for measuring social aspirations of the firm from the shareholder perspective. We also contacted the Bloomberg terminal support team and were instructed that Bloomberg forms lists of peers based on the similarity of product and geographical structure of revenues. The Bloomberg terminal is currently the world’s largest financial data provider with 32.5% market share (Stafford, 2019). We also tried to collect lists of peer firms from analyst reports of large investment banks, such as Credit Suisse and JPMorgan, that are available through the Mergenta database; however, we found Bloomberg’s coverage of publicly traded firms to be more comprehensive compared to investment banks’ research coverage, as mid- and small-tier firms are rarely covered by the equity research analysts, or in many cases, the coverage is brief and does not disclose detailed relative valuation with the list of peer firms, which is our primary interest. After extracting the lists of peers for the firms in our sample, we collected ROAs of these peers and averaged them to come up with the social aspirations measure.

Ultimately, the difference between our firm performance measure (ROA_t) and its respective SA_t and HA_t aspiration was taken to measure performance relative to aspiration. As per Greve (2003b), we used the spline function to separate performance below aspirations and performance above aspirations. Since in our research design we use three-way interactions, which are difficult to interpret, and since performance below aspiration would be negative according to the applied approach, we multiplied performance below historical aspirations (PbHA) and performance below social aspirations (PbSA) by –1, to make the values of these measures positive and ease the interpretation of the interaction terms.

3.2.1. Controls

Ownership concentration should be controlled for when studying shareholder proposals, since firms with concentrated ownership might have weaker responses to such proposals. Hence, as a measure of ownership concentration, we calculated a Herfindahl-Hirschman Index based on stock ownership data pulled from Capital IQ for the top 10,000 shareholders of each firm. We also used total assets and number of employees as measures to control for firm size from the financial and human resources (HR) perspectives. Logged value of the number of years since founding was used as a measure of firm age.

3.3. Model specification

To test our hypotheses, we ran a series of System Generalized Method of Moments (GMM) regression models (Arellano and Bond, 1991; Blundell and Bond, 1998) in STATA. The System GMM model allows us to use lagged values of the dependent variable as predictors while also controlling for firm and year fixed effects. We used two-way System GMM regression with robust standard errors to account for heteroscedasticity concerns, and orthogonal deviations to account for gaps in unbalanced panel structure (Arellano and Bover, 1995). Also, we considered all variables as potentially endogenous and allowed the use of their lagged values as instruments. Such instrumentation allows us to isolate the own effect of the variables from the group effects and the effects of other variables, which deals with potential multicollinearity problems. We also made a separate test for multicollinearity and found that the Variance Inflation Factor (VIF) values for the parameters of interest do not exceed 1.3.

The correctness of the choice of instruments in our model and the effectiveness of dealing with autocorrelation was further confirmed by Hansen’s J test (model 7 in Table 2, b = 203.08, p-value = 0.37) and the Arellano-Bond autocorrelation test (model 7 in Table 2, b = 0.02, p-value = 0.98) as the respective null hypotheses about the validity of instruments and absence of autocorrelation in the chosen model were supported. In general, both the Hansen test and the second-order autocorrelation test results were satisfactory for all the models in Table 2.

Table 2.

System GMM regression models of search.

Variables / Model #	1	2	3	4	5	6	7
Sh.Voice × PbSA (H1)	−51.02* (26.83)	62.11*** (23.17)	7.14(11.28)	9.37(13.27)	17.18(27.31)	−31.98(21.83)	57.65*** (21.61)
Sh.Voice × PbHA (H1)	−1.98(7.08)	−64.44** (30.27)	6.04(14.73)	−10.57(10.97)	−39.98(34.86)	−2.12(5.69)	−63.54** (28.83)
Sh.Voice × PbSA × Slack Absorbed (H2)		−1.77*** (0.52)		−1.65*** (0.61)			−1.82*** (0.62)
Sh.Voice × PbSA × Slack Available (H2)		−24.46** (11.13)			−24.04* (13.41)		−21.58* (11.09)
Sh.Voice × PbSA × Slack Potential (H2)		−0.42(0.31)				−0.58(0.47)	−0.48(0.35)
Sh.Voice × PbHA × Slack Absorbed (H2)		2.95** (1.40)		1.94* (1.08)			3.23*** (1.22)
Sh.Voice × PbHA × Slack Available (H2)		22.68** (10.24)			27.36(19.86)		17.95(11.66)
Sh.Voice × PbHA × Slack Potential (H2)		0.17(0.17)				−0.24(0.25)	0.30(0.23)
Self.E × PbSA × Slack Absorbed (H3)			−7.04*** (2.37)	−7.08** (2.97)			−6.00*** (2.28)
Self.E × PbSA × Slack Available (H3)			−42.21(31.58)		−67.79* (37.32)		−24.72(24.62)
Self.E × PbSA × Slack Potential (H3)			−0.22(0.25)			−0.07(0.36)	−0.74** (0.32)
Self.E × PbHA × Slack Absorbed (H3)			6.15** (2.45)	5.46(3.51)			4.87* (2.80)
Self.E × PbHA × Slack Available (H3)			17.76(24.40)		42.36(39.88)		7.22(25.92)
Self.E × PbHA × Slack Potential (H3)			−0.01(0.16)			−0.47(0.43)	0.23(0.30)
R&D/Sales Lagged (t–1)	0.49*** (0.12)	0.26** (0.12)	0.26** (0.13)	0.24* (0.14)	0.47*** (0.10)	0.63*** (0.08)	0.26** (0.13)
Perf. Below Social Aspir. (PbSA)	212.61* (114.84)	−148.61** (67.15)	−161.02*** (57.96)	−39.25(61.15)	−72.78(74.35)	139.15(97.56)	−161.00** (57.05)
Perf. Below. Histor. Aspir. (PbHA)	−1.78(3.870)	68.39** (30.48)	36.70* (20.86)	2.71(3.83)	128.38* (77.73)	−8.19(7.44)	64.85* (36.31)
Perf. Above. Social Aspir.	29.11(21.85)	11.99(10.59)	12.85(11.56)	0.72(10.43)	42.10(27.95)	8.83(9.98)	12.99(10.39)
Perf. Above. Histor. Aspir.	−34.25(23.88)	−16.47(10.78)	−16.22(11.90)	−5.24(9.70)	−47.26(30.00)	−12.84(12.01)	−18.39(11.45)
Self-Enhancement	4.58** (1.95)	2.40(2.64)	−2.73(2.66)	−1.70(2.35)	1.98(2.11)	1.17(1.29)	−2.49(2.80)
Self-E. × PbSA	−127.4** (52.74)	−86.13(59.52)	249.5** (114.49)	153.59(122.31)	38.49(86.46)	−84.95** (42.00)	163.35(99.84)
Self-E. × PaHA	−49.64* (28.79)	−5.81(53.09)	−173.02(121.64)	−143.44** (71.11)	−97.02(99.43)	−3.82(20.66)	−133.06(109.97)
Shareholder voice	0.68(0.76)	−0.51(0.91)	−0.70(0.64)	−0.42(0.63)	−0.40(0.73)	0.01(0.49)	−0.30(0.96)
Slack Absorbed	0.53(0.38)	−0.05(0.13)	0.03(0.11)	−0.06(0.14)	0.52(0.37)	0.24(0.24)	−0.05(0.16)
Slack Available	0.15(0.14)	0.44(0.55)	−0.26(0.49)	0.07(0.08)	0.11(0.71)	0.11(0.13)	0.41(0.60)
Slack Potential	−0.00(0.01)	−0.01(0.02)	−0.02(0.02)	0.00(0.00)	0.00(0.00)	−0.11(0.09)	−0.030(0.04)
Sh.Voice × Slack Absorbed		0.01(0.03)		0.02(0.04)			0.01(0.04)
Sh.Voice × Slack Available		−0.14(0.18)			−0.11(0.17)		−0.11(0.16)
Sh.Voice × Slack Potential		0.00(0.01)				0.05(0.04)	0.00(0.02)
PbSA × Slack Absorbed		6.32*** (1.45)	6.39*** (1.49)	7.02*** (1.52)			6.38*** (1.43)
PbSA × Slack Available		49.17*** (17.96)	48.03* (25.71)		103.66** (43.67)		54.69** (23.54)
PbSA × Slack Potential		0.41(0.35)	0.27(0.25)			0.99(0.81)	0.76(0.49)
PbHA × Slack Absorbed		−0.48(1.27)	−1.21(1.01)	−0.84(1.14)			−1.50(1.39)
PbHA × Slack Available		−37.85** (18.11)	−18.42(11.73)		−74.22* (44.82)		−32.08(21.53)
PbHA × Slack Potential		−0.02(0.19)	−0.07(0.11)			0.59(0.54)	−0.34(0.26)
Self.E × Slack Absorbed			0.10(0.13)	0.16(0.14)			0.17(0.16)
Self.E × Slack Available			0.30(0.48)		0.31(0.58)		−0.06(0.47)
Self.E × Slack Potential			0.03(0.03)			0.09(0.07)	0.05(0.04)
Assets	0.04* (0.02)	0.04*** (0.02)	0.04*** (0.02)	0.03*** (0.01)	0.05* (0.03)	0.02(0.02)	0.04** (0.02)
Employees	−4.92(4.09)	−3.09(2.25)	−3.30(2.82)	−4.15(2.65)	−2.91(3.40)	−1.79(2.74)	−2.62(2.76)
Debt	−0.08* (0.04)	−0.07*** (0.03)	−0.06** (0.03)	−0.06** (0.02)	−0.09* (0.048)	−0.04(0.03)	−0.07** (0.03)
Age	0.71(1.17)	−0.18(0.38)	0.02(0.37)	0.09(0.50)	−0.03(0.91)	0.44(0.83)	−0.15(0.44)
Ownership concentration	0.70(1.50)	−0.07(0.37)	−0.48(1.28)	−0.45(1.75)	0.32(1.39)	0.51(2.09)	−0.70(0.99)
Constant	−16.15(12.80)	1.39(2.26)	1.41(2.55)	1.01(2.07)	−10.50(10.35)	−6.98(8.50)	2.15(2.80)
Hansen J test	233.85	226.26	209.62	213.89	227.16	379.82	203.08
Hansen J test p-value	0.26	0.16	0.42	0.47	0.24	0.26	0.37
Autoregression 2 test	−0.81	−0.81	−0.76	−0.54	−0.94	−0.84	0.02
Autoregression 2 test p-value	0.42	0.42	0.45	0.59	0.35	0.40	0.98
Chi² test	1424	19,722	20,900	25,850	1496	5786	23,270

PbSA = Performance below Social Aspirations (positive); PbHA = Performance below Historical Aspirations (positive).

Robust standard errors in parentheses; 4405 Observations; 454 IDs.

***

p < 0.01; ** p < 0.05; * p < 0.1.

4. Findings

As seen from Table 2 (model 1), our H1 about the positive impact of shareholder voice on problemistic search was not supported because in the absence of the interaction terms with slack, the test result was nonsignificant when performance was below historical aspiration (b = –1.98, p-value = 0.78) but negative and marginally significant when performance was below social aspiration (b = –51.02, p-value = 0.08), suggesting that shareholder voice could be a source of conflict and negatively impact problemistic search.

As seen from Table 2 (model 7), for our H2 and H3, we found opposite effects for performance below social aspirations and performance below historical aspirations. Also, as we anticipated, the interaction terms with absorbed and available slack were more consistent and significant than the interaction terms with potential slack. This confirms our assumption that, as potential slack is subject to shareholder discretion, it does not exhibit the negative effects associated with absorbed and available slack.

Our model shows that when firms performed blow social aspirations, the three-way interaction terms of shareholder voice, absorbed slack, and performance below social aspirations (b = –1.82, p-value = 0.004), as well as three-way interaction of self-enhancement, absorbed slack, and performance below social aspirations (b = –6.00, p-value = 0.01) were negative and significant, supporting our H2 and H3. We can also see consistency of these results across models 2 to 6 in Table 2, with partial control for other interaction terms, further supporting the robustness of the findings. We also found robust and consistent support for our H2 using available measure of slack, also showing that when the firm performs below social aspirations and shareholders raise their voice, available slack decreases the amount of problemistic search (b = –21.58, p-value = 0.05).

Interestingly, when firm performance fell below historical aspirations, our model showed the reverse of the hypothesized relationships. It appears that under negative feedback relative to historical aspirations and pressure from the shareholder voice, the firms will search more when absorbed slack is high (b = 3.23, p-value = 0.01). Similarly, with marginal significance, this positive effect of absorbed slack (b = 4.87, p-value = 0.08) was seen for self-enhancing firms. However, this effect was not consistent across models 2 to 6 in Table 2.

The effect of absorbed (b = 6.38, p-value = 0.000) and available slack (b = 54.69, p-value = 0.02) on problemistic search when firms performed below social aspirations was positive and significant (see model 7 in Table 2), in line with the prior literature (Chen and Miller, 2007; Greve, 2003a). Hence, this work does not challenge the earlier knowledge about organizational slack, but rather complements it by showing the complex nature of this organizational parameter.

We also plotted the interaction effects of slack with shareholder voice and self-enhancement, respectively. As seen in Figures 1 to 4, the relationship between performance below aspirations and problemistic search affected by shareholder voice and self-enhancement changes across the levels of slack resources. When slack is low, such relationships are minimal, but they become more pronounced as slack increases. For instance, at a high level of absorbed slack and low shareholder voice (Figure 1), 1 standard deviation (SD) increase in performance below social aspiration increases problemistic search by 224%; however, as shareholder voice becomes high (1 SD above the mean), problemistic search increases by only 49%. Similar effects of available slack can be seen in Figure 2, where under high levels of slack, the amount of problemistic search in response to performance below social aspirations increases by 255% when such negative performance feedback increases by 1 SD under the condition of low shareholder voice, but as shareholder voice becomes high, the increase in search drops to only 61%. Similarly, absorbed slack alters the relationship between search and performance below social aspiration under the presence of self-enhancement (Figure 3). Non-self-enhancing firms with high slack have 124% increase in search in response to an increase in performance below social aspiration by 1 SD, but such relationship drops to only 31% for self-enhancing firms. Interestingly, as Figure 4 shows, a high level of absorbed slack reverses the relationship between performance below historical aspirations and slack from negative (–247%), when shareholder voice is low, to positive (+361%), when shareholder voice is high (1 SD above the mean).

Figure 1.

Relationship between performance below social aspiration and search moderated by shareholder voice and absorbed slack.

Figure 2.

Relationship between performance below social aspiration and search moderated by shareholder voice and available slack.

Figure 3.

Relationship between performance below social aspiration and search moderated by self-enhancement and absorbed slack.

Figure 4.

Relationship between performance below historical aspiration and search moderated by shareholder voice and absorbed slack.

4.1. Additional analysis

In the post-estimation analysis, we performed additional steps to further verify our findings. First, we tested our hypotheses using a combined measure of slack, following Chen (2008), as an average of the standardized measures of absorbed, available and potential slack (see Appendix 2). With such a measure of slack, we still could not find support for H1, yet we found robust and consistent support for H2 and H3, when firm performance was below social aspirations. Yet, the coefficients of the three-way interaction terms were nonsignificant when firm performance was below historical aspirations.

Second, due to the potential risk of model misspecification, we also tested our hypotheses using the generalized estimation equations (GEE) method (see Appendix 3). GEE represents a class of robust estimators used with panel data (Lim and Audia, 2020) and allows us to account for covariance misspecification and for unobserved differences between the firms. Also, GEE estimation is appropriate when there are variables included in the model, such as shareholder proposals in our case, which are relatively stable over time (Kolev and McNamara, 2022). Unlike with System GMM regression, in the GEE regression model, we did not instrument independent variables using their historical values; however, we controlled for the lagged dependent variable given that organizational search has some inertia. As required by the estimation procedure, for our GEE models, we indicated Gaussian distribution, identity link function, and an exchangeable correlation structure. Overall, the results of our GEE models were in line with our main model for interaction terms with absorbed slack.

Third, we tested our hypotheses using the alternative measure of search. One of the proxy measures of problemistic search is the firm’s risk-taking (Greve, 1998; Hu et al., 2023). We calculated the firm’s risk-taking following Lim and McCann, (2014) as the average of standardized ratios of R&D/Sales, Capital expenditures/Sales, and long-term debt/Sales in t + 1. However, measuring search through risk did not yield consistently significant results, although the signs of the estimated coefficients of the three-way interaction terms were in line with prior estimations.

Also, since the majority of performance feedback studies use industry codes to determine peer firms, in the additional analysis, we also constructed social aspirations using 4-digit SIC codes. However, we could not find support for our hypotheses when peer firms were selected using this method. We assume that selection of peer firms based on formal criteria, such as the SIC code, rather than based on the similarity of the businesses, might yield a less precise measure of social aspiration (Luger, 2023). For instance, Airbus would not be selected as a peer firm for Boeing based on SIC codes because Airbus is incorporated in Europe and is not subject to US industry classification. Yet, Airbus is Boeing’s major competitor on the global market, and Bloomberg includes Airbus in the list of Boeing’s peers.

Moreover, we estimated our main model using more commonly used debt to equity ratio as a measure of potential slack (Bourgeois, 1981), and we found the results similar to our main model.

Finally, slack can also be nonfinancial (Wang et al., 2016; Bentley and Kehoe, 2020), and the original work of Cyert and March (1963) considered available staff resources as a source of slack. For example, Lecuona and Reitzig (2014) study how HR slack increases search for novel solutions. Hence, we also calculated HR slack as employees to sales ratio and interacted it with the measures of shareholder voice and self-enhancement to check for potential effects of nonfinancial slack on problemistic search. However, we could not find any significant results for this measure of slack using our System GMM model.

5. Discussion

5.1. Contributions and future research directions

This article makes several contributions to the behavioral theory of the firm (Cyert and March, 1963; Gavetti et al., 2012) and performance feedback studies (Audia and Greve, 2021; Greve, 2003b). First, it takes a critical view of slack in organizations, showing that slack amplifies a firm’s character—whether positive or negative. Although slack fosters innovation in organizations, this effect can diminish in firms characterized by self-enhancing management or those challenged by their shareholders. Slack’s cushioning property can serve as a source of stability (Cyert and March, 1963) but also as a source of rigidity (Leonard-Barton, 1992). Moreover, while slack (particularly available and absorbed slack) can increase problemistic search, our findings suggest that it hinders externally motivated problemistic search while potentially supporting internally motivated problemistic search. Exploring this tension between internally and externally motivated search falls beyond the scope of this article and thus requires further investigation.

Second, this article challenges Cyert and March’s (1963) assumption that slack is not political and that it is not in managers’ interest to increase slack. In their behavioral theory of the firm, Cyert and March (1963) present slack as a surplus of certain resources that the dominant coalition members share to “quasi-resolve” conflict and fulfill their claims. However, this article shows that internal coalition members may be more inclined to accumulate slack resources to gain independence from external stakeholders, rather than share these resources with them.

From this, three questions emerge:

It would be interesting to examine whether slack is also used for internal corporate politics. Scholars have studied the nuances of performance feedback in multi-business corporations (Gaba and Joseph, 2013; Hu et al., 2017), and considering the political side of organizational slack could further complement such research.

Since slack is not politically neutral, the semi-resolution of conflicts within coalitions is not automatic, and the mere presence of high slack does not guarantee that coalition members will satisfy their claims. Other conditions must coexist with slack to stabilize the firm.

The use of slack in internal versus external coalition politics warrants further reconciliation of the behavioral theory of the firm (Cyert and March, 1963; Gavetti et al., 2012) with both resource dependence theory (Pfeffer and Salancik, 1978) and agency theory (Eisenhardt, 1989; Jensen and Meckling, 1976), which address the power relationships between external and internal stakeholders.

We also uncovered some intriguing empirical findings that underscore the need for further investigation into the roles of slack and shareholder voice in the performance feedback mechanism. First, we did not find support for H1, which posited that shareholder voice would increase problemistic search when a firm performs below aspirations. Instead, the coefficients for the interaction between shareholder voice and performance below social aspirations in model 1 (Table 2) were negative and marginally significant (b = –51.02, p-value = 0.08). This suggests that shareholder voice may act as a source of conflict — rather than a stimulus — by potentially disrupting a firm’s ability to search. Yet, because our current empirical setting cannot fully address the outcomes of such shareholder pressure, we note, as Posen et al. (2018) emphasize, that the effectiveness of problemistic search remains an important yet understudied area.

Furthermore, when testing H2 and H3 under conditions of performance below historical aspirations, our results run counter to our theorizing and differ from those related to performance below social aspirations. Indeed, historical and social aspirations appear to influence the firm in distinct ways (Kim et al., 2015), sending different signals to both internal and external stakeholders. Underperformance relative to historical aspirations may indicate a stronger crisis, whereas underperformance relative to social aspirations may signal missed opportunities. These divergent interpretations could trigger different forms of shareholder voice, potentially explaining the inconsistency in our findings.

Nevertheless, our theory found more robust and consistent support for performance below social aspirations in the main model (Table 2), the model with combined measure of slack, and the GEE model (Appendix 2 and 3). This pattern suggests that vicarious learning from performance gaps relative to social aspirations (Beckman and Lee, 2020) may provoke a different kind of organizational learning and lead to distinct outcomes compared with historical aspiration gaps. Moreover, our findings indicate that organizational politics can be particularly intense when firms perform below social aspirations, whereas a firm falling below its historical aspirations may exhibit greater internal unity.

Nevertheless, as evident from Figures 1 to 4, our estimations show that high levels of slack would still be associated with high levels of search, whereas when slack is low, organizational search is bleak. So, firms need to plan for some slack to be able to confront the adversities. Yet, this study also demonstrates that high slack is more nuanced and often comes with its own politics.

Finally, while this article empirically tests these theoretical concepts using shareholders as an example of external coalition members, more research is needed on other stakeholders such as suppliers, consumers, regulatory institutions, communities, and activists. Future studies could explore how these actors, each with unique forms of influence, shape organizational responses to performance feedback.

5.2. Implications for practitioners

Our study has important implications for both managerial practice and shareholder oversight, as it highlights the multifaceted role of slack resources. While managers generally prefer to have surplus resources at their disposal, an overabundance of such slack can create an echo chamber, reinforcing internal beliefs and downplaying valuable external advice. Consequently, managers in high-slack firms should devote extra effort to carefully considering and interpreting signals from external stakeholders. In turn, shareholders and boards should scrutinize information provided by high-slack firms and adopt a more activist stance, recognizing the heightened risks of self-enhancement and shareholder voice deflection in these organizations.

Our findings also suggest that firms and shareholders need to further work on the effective governance mechanisms that should mitigate self-enhancing behavior inside the firm and build a bridge for the dialogue between internal and external coalition members, to further improve the use of firm’s slack resources.

5.3. Limitations

Measurement error is a significant limitation of this article, particularly in the measurement of shareholder voice, problemistic search, and self-enhancement. According to the behavioral theory of the firm (Cyert and March, 1963) and shareholder studies (Karpoff et al., 1996), stockholders exert pressure on firms to promote organizational change when performance deteriorates. However, shareholder proposals can target individual or symbolic goals unrelated to firm performance. Proposals are cumulative, and individual proposals vary in support and impact, making them a limited measure of shareholder voice. Despite this, proposals are a costless method available to all shareholders, prioritizing them over other, less accessible methods. Shareholder proposal data is zero-inflated (Goranova et al., 2017), as some firms negotiate issues informally rather than allow formal proposals, rendering our measure conservative.

Organizational search occurs in multiple domains (Agrote et al., 2020; Posen et al., 2018), so measuring search by only examining R&D is another limitation. R&D expenses are often underreported (Blagoeva et al., 2020; Koh and Reeb, 2015; Koh et al., 2018; Seru, 2014) and omit nonfinancial search behaviors, making this measure overly conservative.

To measure self-enhancement, we rely on financial restatements, which may not fully capture corporate self-enhancement since not all acts of self-enhancement lead to restatements. Thus, our measure is conservative, and an alternative might show more variance. We could only measure self-enhancement as a binary variable, as only 7.3% of restatements indicated the actual restated amount. Full data on financials would allow for a more fine-grained measure.

Our empirical test is limited to US publicly traded corporations, making findings less generalizable. US firms are protected from minority shareholder pressures (Bebchuk and Fried, 2006), potentially resulting in a weaker response to shareholder voice compared to other organizations or jurisdictions, adding conservatism to our findings.

Finally, we focus on one financial performance goal, ROA, while recent research suggests organizations pursue multiple goals simultaneously (Gaba and Greve, 2019; Levinthal and Rerup, 2021). Using only one performance goal is a limitation, as shareholders may prioritize different goals based on their temporal orientation.

6. Conclusion

Prior research has highlighted various positive effects of slack on firms. By examining the cushioning property of slack, we begin our investigation by asking whether slack can negatively affect a firm’s ability to search when performance falls below aspirations. We theorize and empirically demonstrate that high levels of slack can reduce problemistic search either when the firm’s managers engage in self-enhancement or when the firm’s shareholders exert pressure. Furthermore, we argue that shareholders are factored into the performance feedback mechanism by means of shareholder voice. Overall, this article underscores the complex nature of organizational slack and stimulates further discussion about the political dimensions of this organizational phenomenon.

Key practical and research implications:

• Slack resources provide organizations with the resilience to endure adversity and the flexibility to explore opportunities for value creation. However, as our research demonstrates, the effects of organizational slack are non-linear. The accumulation of slack resources is associated with shifts in organizational politics and changes in the firm’s relationships with external stakeholders. This highlights the need for organizational scholars to examine the accumulation and utilization of slack resources through a political lens. While most of the studies focused on slack as economic factor, there is also a political dimension to it.

• Our research also reveals that high levels of organizational slack reduce firms’ susceptibility to external shareholder influence. This scenario can be problematic, as it diminishes the external control needed to mitigate agency problems within organizations. This insight presents an opportunity to integrate agency theory with the behavioral theory of the firm, enabling a broader study of shareholders’ roles within the context of firm behavior.

• Additionally, high slack fosters conditions for managerial self-enhancement, making organizations less responsive to negative performance feedback. For practitioners, particularly those involved in corporate governance, this finding underscores the importance of closely monitoring high-slack firms. Their surplus resources can contribute to a self-centered organizational mindset, warranting greater oversight and strategic attention.

• Lastly, our measures of self-enhancement and social aspirations from the shareholder perspective provide novel and useful tools for the future management and organizational studies.

Footnotes

Appendix

Appendix 3.

GEE regression model of search.

Variables / Model #	1	2	3	4	5	6	7
Sh.Voice × PbSA (H1)	−5.65 (4.67)	23.85*** (8.91)	5.64 (4.74)	21.09*** (7.85)	7.55 (6.20)	−5.61 (4.76)	26.09*** (9.34)
Sh.Voice × PbHA (H1)	2.10 (2.19)	−8.55 (6.40)	−0.92 (2.94)	−9.80 (7.10)	−15.26 (12.68)	1.94 (2.46)	−12.73 (8.27)
Sh.Voice × PbSA × Slack Absor. (H2)		−1.27*** (0.47)		−1.36*** (0.45)			−1.33*** (0.46)
Sh.Voice × PbSA × Slack Avail. (H2)		−2.48(1.89)			−6.87(5.40)		−2.48(1.87)
Sh.Voice × PbSA × Slack Potent. (H2)		−0.03(0.03)				−0.01(0.02)	−0.03(0.03)
Sh.Voice × PbHA × Slack Absor. (H2)		1.18** (0.56)		1.16* (0.65)	0.74 (0.52)		1.27** (0.61)
Sh.Voice × PbHA × Slack Avail. (H2)		−0.28(1.20)			2.80(3.17)		0.51(1.41)
Sh.Voice × PbHA × Slack Potent. (H2)		0.01(0.02)			−0.03(0.03)	0.01(0.04)	0.00(0.02)
Self.E × PbSA × Slack Absorb. (H3)			−2.57** (1.19)	−2.33*** (0.83)			−2.04** (0.83)
Self.E × PbSA × Slack Avail. (H3)			−5.77(8.75)		−8.91(8.65)		−1.90(6.98)
Self.E × PbSA × Slack Potent. (H3)			−0.01(0.03)			−0.06(0.06)	−0.04(0.06)
Self.E × PbHA × Slack Absorb. (H3)			0.40(0.80)	−0.73(0.94)			−0.56(0.89)
Self.E × PbHA × Slack Avail. (H3)			3.45(4.45)		2.68(5.06)		1.58(4.44)
Self.E × PbHA × Slack Potent. (H3)			−0.02(0.02)			0.04(0.06)	−0.01(0.04)
R&D/Sales Lagged (t–1)	0.88*** (0.03)	0.36* (0.18)	0.39** (0.18)	0.32* (0.19)	0.84*** (0.04)	0.88*** (0.03)	0.33* (0.18)
PbSA	18.97(15.01)	−81.93** (33.79)	−69.20* (35.44)	−73.53*** (28.24)	−19.41(18.20)	19.41(15.54)	−89.28** (34.76)
PbHA	−0.05(0.14)	1.63(4.98)	5.38(5.60)	3.07** (1.38)	9.24(10.51)	−0.19(1.23)	3.07(5.39)
Perf. Above. Social Aspir.	4.13(4.60)	5.04(4.44)	5.07(4.64)	4.89(4.31)	4.74(5.33)	4.16(4.65)	4.87(4.25)
Perf. Above. Histor. Aspir.	−4.25(4.72)	−5.33(4.48)	−5.35(4.68)	−5.19(4.36)	−4.92(5.48)	−4.27(4.77)	−5.15(4.29)
Self-Enhancement	−0.10(0.26)	0.73(0.51)	−0.64(0.60)	−1.10* (0.61)	0.39(0.46)	−0.05(0.24)	−0.85(0.59)
Self-E. × PbSA	0.62(9.80)	−50.66** (23.84)	31.85(22.68)	24.72(16.27)	19.66(17.15)	−0.58(10.32)	21.37(20.63)
Self-E. × PbHA	0.88(7.94)	19.80(15.98)	−1.05(15.52)	28.01(19.20)	−7.22(14.01)	2.05(8.35)	20.77(17.28)
Shareholder voice	0.11(0.11)	−0.11(0.16)	−0.20* (0.11)	−0.02(0.12)	0.30(0.24)	0.10(0.09)	−0.12(0.15)
Slack Absorbed	0.02*** (0.01)	0.11*** (0.04)	0.10*** (0.04)	0.09*** (0.03)	0.03** (0.01)	0.02*** (0.01)	0.10*** (0.03)
Slack Available	0.045(0.03)	−0.14(0.11)	−0.02(0.13)	0.01(0.03)	−0.02(0.11)	0.05(0.03)	−0.05(0.13)
Slack Potential	−0.00(0.01)	−0.00(0.00)	−0.00(0.00)	−0.00(0.00)	−0.00(0.00)	−0.00(0.00)	−0.01(0.01)
Sh.Voice × Slack Absorbed		−0.01(0.01)		−0.01(0.01)	−0.02(0.01)		−0.01(0.01)
Sh.Voice × Slack Available		0.05(0.05)			0.03(0.03)		0.04(0.04)
Sh.Voice × Slack Potential		0.00(0.00)			0.00(0.00)	0.00(0.00)	0.00(0.00)
PbSA × Slack Absorbed		4.83** (1.90)	4.39** (2.02)	5.26*** (1.92)			5.12*** (1.87)
PbSA × Slack Available		9.47(6.33)	9.12(9.45)		18.92(15.54)		8.04(7.75)
PbSA × Slack Potential		0.03(0.04)	0.03(0.03)			−0.04(0.04)	0.07(0.06)
PaHA × Slack Absorbed		−1.91** (0.75)	−1.39** (0.69)	−1.51** (0.68)	0.05(0.17)		−1.57** (0.67)
PaHA × Slack Available		1.36(2.47)	−1.50(2.85)		−5.69(6.44)		0.13(2.59)
PaHA × Slack Potential		−0.01(0.02)	−0.00(0.02)		0.04(0.05)	0.01(0.09)	−0.01(0.05)
Self.E × Slack Absorbed			0.06* (0.03)	0.07** (0.04)			0.06* (0.03)
Self.E × Slack Available			−0.00(0.14)		−0.11(0.13)		−0.06(0.14)
Self.E × Slack Potential			0.01(0.00)			−0.00(0.01)	0.01(0.01)
Assets	0.00(0.00)	0.01* (0.01)	0.02** (0.01)	0.01* (0.01)	0.01** (0.00)	0.00(0.00)	0.01* (0.01)
Employees	−0.22(0.28)	−2.34* (1.27)	−2.19* (1.14)	−2.15* (1.25)	−0.56(0.36)	−0.22(0.27)	−2.20* (1.18)
Debt	−0.00(0.01)	−0.02(0.01)	−0.02* (0.01)	−0.01(0.01)	−0.01(0.01)	−0.00(0.01)	−0.02(0.01)
Age	−0.15(0.00)	−1.67** (0.01)	−1.57** (0.01)	−1.05** (0.52)	−0.17** (0.08)	−0.08(0.07)	−1.01** (0.48)
Ownership concentration	−0.28(0.19)	−0.40(0.41)	−0.39(0.41)	−0.48(0.48)	−0.23(0.16)	−0.28(0.19)	−0.41(0.44)
Constant	−0.40(0.54)	1.63* (0.94)	1.26(0.80)	4.78** (2.40)	0.36(0.44)	−0.19(0.60)	4.76** (2.29)

Robust standard errors in parentheses; 4405 Observations; 454 IDs.

***

p < 0.01; ** p < 0.05; * p < 0.1.

Acknowledgements

The authors are grateful to the editorial team and two anonymous reviewers for their constructive feedback on this manuscript, and to Mark Zbaracki, Simon Parker, Lee Watkiss, Nicolai Foss, and participants of Strategic Management Society Conference and Carnegie School of Organizational Learning Academy for the valuable comments on the earlier versions of this research.

Final transcript accepted 6 March 2025 by Miles Yang (Deputy Editor)

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was supported by the Insight Grant from the Social Sciences and Humanities Research Council of Canada.

ORCID iD

Sergii Nevmerzhytskyi

Notes

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The silence of the slacked: The negative side effect of slack on problemistic search

Abstract

Keywords

1. Introduction

2. Theory and hypotheses

2.1. Problemistic search and slack

2.2. Shareholder voice and problemistic search

2.3. The muting side effect of slack

2.4. Slack and adverse effects of self-enhancement

3. Data and methods

3.1. Sample

3.2. Variables

3.2.1. Controls

3.3. Model specification

4. Findings

4.1. Additional analysis

5. Discussion

5.1. Contributions and future research directions

5.2. Implications for practitioners

5.3. Limitations

6. Conclusion

Key practical and research implications:

Footnotes

Appendix

Acknowledgements

Funding

ORCID iD

Notes

References