Abstract
Many countries have regulations that require firms to engage in minimum levels of corporate social (CS) activities in areas such as the environment and social welfare. In this paper, we argue that changes in a firm’s compliance with CS regulations are reflected in its reputation for corporate social responsibility (CSR), which affects the firm’s performance. The performance impacts depend on whether the firm’s CSR reputation in the current and prior periods is positive (i.e., the firm exceeds CS regulations), neutral (the firm meets CS regulations), or negative (the firm fails to comply with CS regulations). Our theoretical framework draws on the reputation literature and on the concepts of recency bias, which weights the present more heavily than the past, and negativity bias, which weights negative assessments more heavily than neutral or positive assessments. We test our hypotheses on a sample of 7317 banks over 1992–2007 where we compare a bank’s return on assets (ROA) with its current and prior compliance ratings under the U.S. Community Reinvestment Act. We find that changes in CSR reputation have predictable, asymmetric, and sizeable impacts on firm performance. For example, for an average bank with $1 billion in assets, gaining a positive CSR reputation translates into a rise in profits of 4.04%; gaining a negative CSR reputation results in a drop in profits of − 7.8%.
Similar content being viewed by others
Avoid common mistakes on your manuscript.
Introduction
Engaging in corporate social (CS) activities is a means by which firms can comply with accepted societal rules and exhibit appropriate business behavior. CS regulations are government policies that involve social issues such as human rights, minorities, or the environment, where firms are required to achieve a minimum standard of compliance. Governments can monitor compliance in various ways, for example, by requiring self-reports by firms, conducting audits, or issuing penalties for noncompliance.
When a government adopts a new CS regulation, firms may choose to either not meet, meet, or exceed the mandated level of CS activity. Prior researchers have studied the implications of compliance versus noncompliance with CS regulations (e.g., Doh et al. 2010). However, there has been little research on more complex situations where changes over time in a firm’s level of compliance with CS regulations are considered.
One important way that firms can differentiate themselves from one another within a group is by engaging in CS activities that “go above and beyond” government regulations, which McWilliams and Siegel (2001) define as corporate social responsibility (CSR). Public and private rating agencies often publish rankings of firms in terms of their compliance levels with government regulations, which are reported in the media. For example, firms that spend well above government-mandated levels are recognized as high performers on lists such as “the top 50 socially responsible corporations” (Maclean’s),Footnote 1 the “top 10 most socially responsible companies” (Frontstream),Footnote 2 and “the 10 companies with the best CSR reputations” (Forbes).Footnote 3 Such publicly available information enables stakeholders to build an assessment of a firm’s reputation in terms of its CS activities.Footnote 4 Thus, over time, a firm can develop a CSR reputation with its stakeholders where the firm is known for being a high or low performer in terms of its CS activities (Lange and Lee 2011).
Changes in CSR reputation can be measured in one of two ways: across different firms at the same point in time (cross-sectional change) or changes in one firm’s CSR reputation over time (time series or dynamic change). We know that stakeholders can react differently to firms that meet CS-mandated targets (Doh and Guay 2006; Doh et al. 2010), but we know little about the processes and performance outcomes of changes in CSR reputation.
In this paper, we examine the relationship between a firm’s financial performance (i.e., ROA) and changes in its CSR reputation. We hypothesize that changes in a firm’s CS activities are visible to stakeholders and affect the firm’s CSR reputation, which in turn affects firm performance. Our theory development draws on the reputation literature and incorporates insights from research on recency and negativity biases. The recency bias literature suggests that stakeholders should place more weight on current than on prior activities (Arnold et al. 2000). The negativity bias literature suggests that stakeholders should place more weight on negative than positive assessments (Elayan et al. 2016; Rozin and Royzman 2001; Zavyalova et al. 2016). We therefore anticipate that the level and direction of changes in a firm’s CSR reputation are likely to have asymmetric impacts on firm performance.
We test our arguments about changes in CSR reputation using a sample of domestic and foreign-owned banks in the United States over 1992–2007. We examine banks’ compliance with the Community Reinvestment Act (CRA), which encourages financial institutions to meet the credit needs of their local communities, especially low-income customers. Bank CRA ratings have been used in previous research on corporate social responsibility (Campbell et al. 2012; Simpson and Kohers 2002; Vitaliano and Stella 2006). We compare banks’ financial performance with changes in their compliance with the Community Reinvestment Act and find strong support for our arguments.
Our paper makes the following contributions. First, we contribute to the CSR literature by theorizing and empirically testing how changes in a firm’s CSR reputation affect its performance; our work builds on and extends prior work by Arlow and Gannon (1982), Barnett and Salomon (2006), Campbell et al. (2012) and Wei et al. (2017). Second, our study theorizes and shows that the performance impact of changing levels of CS activity depends on a firm’s prior level of CS activity, extending Doh et al. (2010). Third, our finding of an asymmetric effect of CS activity levels on firm performance adds to the literature on the performance implications of CSR (McWilliams and Siegel 2000, 2001; McWilliams et al. 2006). Fourth, our work contributes to work on recency bias (Arnold et al. 2000) and negativity bias (Rozin and Royzman 2001) by examining their effects on CSR reputation and firm performance. Lastly, our research speaks to the decades-old debate on the role of business in society (c.f., Arlow and Gannon 1982; Berle 1932; Dodd 1932) and offers practical implications for managers given the pervasiveness of CS regulations around the world (e.g., McWilliams et al. 2006).
Theory Development
CSR Reputation and Firm Performance
There has been extensive research on firm reputation (Fombrun 1996; Fombrun and Shanley 1990; Rao 1994; Pfarrer et al. 2010; Rindova et al. 2005; Roberts and Dowling 2002). Reputation and legitimacy are closely linked concepts (King and Whetten 2008); legitimacy reflects an organization’s conformity to a set of standards, and reputation reflects a firm’s differentiated status within its peer group (Doh et al. 2010). According to Bitetkine, “the sets of dimensions forming reputation and legitimacy often partially overlap, and the same dimension can be used to make legitimacy and reputation judgments” (2011, p. 160). Thus, reputation and legitimacy have similar determinants and implications, as well as processes for social construction. Indeed, reputation is socially constructed and is the result of the process of legitimation (Rao 1994).
Our theory development leverages the works of Bitektine (2011), Deephouse and Carter (2005), and Doh et al. (2010) to define three levels of CSR reputation, which we refer to as positive, neutral, and negative CSR reputation. A positive CSR reputation is gained by exceeding, a neutral CSR reputation by meeting, and a negative CSR reputation by not complying with CS regulations. In each case, stakeholders build their assessment of a firm’s CSR reputation from observing the firm’s activities relative to government-mandated levels of CS activities.
Many studies have focused on the firm performance implications of CSR activities. While the evidence is mixed, most research has concluded that high CSR performers have better firm performance, all else being equal (Arlow and Gannon 1982; McWilliams and Siegel 2000, 2001; Simpson and Kohers 2002; Orlitzky et al. 2003; McWilliams et al. 2006). Furthermore, other studies have shown that CSR activities appear to be positively correlated with better earnings forecasts (Lee 2017) and increased information disclosure (Jo and Kim 2008).
There are several positive effects on firm performance that can arise from being viewed by stakeholders as a socially responsive firm (Brammer and Pavelin 2006; Doh and Guay 2006). Social responsiveness can attract more investors (Day 2001) and enable superior CSR performers to enhance firm value (Jeong et al. 2018). In addition, since a firm reflects the personal characteristics of its top managers (Hambrick and Mason 1984), by engaging in CS activities, managers disclose their values, preferences, and biases, which can help to reduce information asymmetry between the company’s stakeholders and the firm. Also, information asymmetry is reduced because CS activities can be viewed as actions that reveal firm quality and attention given to stakeholder issues (Bitektine 2011).
We therefore expect that a positive CSR reputation should be positively associated, and a negative CSR reputation negatively associated, with firm performance, all else being equal. On the other hand, we view a neutral CSR reputation as paralleling Bitektine’s (2011) and Deephouse and Carter’s (2005) notion of “neutral” as capturing “unknown” or insufficient evidence of social responsiveness. A neutral CSR reputation implies that a firm has organizational legitimacy in the CSR domain but does not “outshine” its peers. A firm with a neutral CSR reputation therefore does not earn superior returns, and we do not expect any positive impact on firm performance from gaining a neutral CSR reputation.
Changes in CSR Reputation
Our underlying theoretical model assumes that a change in a firm’s level of government-mandated CS activity generates a change in the firm’s CSR reputation (a latent variable), which affects firm performance. We explore these linkages below.
Baseline Change
Reputation models assume “a tight coupling between past actions and future expectations” (Rao 1994, p. 30). Building on Rao (1994), we argue that a focal firm’s CSR reputation in the prior period should affect how stakeholders view its CSR reputation in the current period. To analyze whether and how changes in CSR reputation are related to firm performance, we therefore distinguish between a firm’s current and prior levels of CSR reputation. Accordingly, the three levels of CSR reputation (positive, neutral, and negative) produce four possible changes in CSR reputation: (1) Gaining a negative CSR reputation reflects a shift from compliance to noncompliance with CS regulations. (2) Losing a negative CSR reputation arises when a firm shifts from noncompliance to compliance with CS regulations. (3) Gaining a positive CSR reputation occurs when a firm shifts from compliance with to exceeding CS regulations. (4) Losing a positive CSR reputation reflects a change from exceeding to being compliant with CS regulations.
To understand the implications for firm performance of these four possible changes in CRS reputation, we look to decision-making models in information economics that incorporate beliefs based on previous actions and expected future actions (Weigelt and Camerer 1988). A central premise of our dynamic framework is that stakeholders are susceptible to recency and negativity biases. We discuss each bias in turn.
Recency Bias
The literature on recency bias assumes that decision makers are expected to collect and weigh all relevant information, current and past, when making decisions; however, current events are remembered and weighted more heavily than past events (Arnold et al. 2000; Reason 1990). The tendency to remember and give more weight to current events may have various causes including laziness and cognitive limitations.
Some studies assert that recency bias gets weaker with experience (Kennedy 1993; Messier and Tubbs 1994), but most scholars believe that recency bias persists in the presence of complex decision making. The belief adjustment model, which “explicitly accounts for order-effect phenomena as arising from the interaction of information processing strategies and task characteristics” (Hogarth and Einhorn 1992, p. 1), asserts that a decision maker’s current beliefs serve as an anchor and that a belief shift stems from new information (Arnold et al. 2000). The recency bias remains in the presence of heavy information load; that is, decision makers with high experience and more expertise exhibit a greater recency bias than their professional counterparts with less experience and lower expertise. Relatedly, Nofsinger and Varama (2013) found a recency effect in the behavior of individual investors, suggesting that if task complexity is high, recency bias is expected to persist.
Based on the recency bias literature, we assume that stakeholders give more weight to a firm’s current level than to its previous level of CS-mandated activity. Thus, the recency bias implies that evaluators (e.g., customers/network partners) pay attention to the direction of the firm’s change in CS-mandated activity but assign more weight to the current event than to a previous event regardless of the direction of change.
Negativity Bias
Prior research in psychology has shown that individuals experience a negativity bias (Hastie and Dawes 2001; Rozin and Royzman 2001), that is, “the tendency to experience negative events as more salient and diagnostic than positive changes, to give them more weight in judgments and assessments, and to respond to them more strongly” (Pfarrer et al. 2010, p. 1135). Furthermore, “negative events grow more rapidly in negativity as they are approached in space and time than do positive events” (Rozin and Royzman 2001, p. 298). The salience of negativity has been documented in the learning literature in that firms are more apt to learn from failures (Catino and Patriotta 2013; Madsen and Desai 2010).
Some scholars have argued that negativity bias may be buffered by a track record of positive activity. For example, psychology studies have concluded that the beliefs about performance are shaped by current reputation and are resilient to new negative information (Heider 1958; Kelley 1973; Pfarrer et al. 2010). Having a favorable track record makes negative information less problematic to evaluators because setbacks can be linked to many potential causes.Footnote 5 Rhee and Haunschild (2006) found, however, in their study of product recalls in the US automotive industry, that a good reputation can be an organizational liability when the firm suffers from a negative reputation event. The negativity bias effect was stronger and market penalty higher for firms with high positive reputations.
We infer, therefore, that evaluators (e.g., customers and network partners) pay attention to the direction of a focal firm’s change in CS-mandated activity but assign more weight to a negative event than to a positive or neutral event regardless of the time period.
Combining the Effects
Collectively these effects suggest that stakeholders consider both a focal firm’s current and prior levels of CS activity when assessing CSR reputation. Stakeholders should asymmetrically place more weight on current than prior events and on negative than positive events. This raises an important research question: What is the joint impact on CSR reputation of negativity and recency biases, and if the impacts are offsetting rather than reinforcing, which effect is likely to dominate? Our search of the relevant literature on negativity and recency biases found little discussion as to whether one effect would dominate the other and under what circumstances. We explore these issues below.
Losing/Gaining a Negative Reputation
We start by examining the directional impacts of gaining or losing a negative CSR reputation, that is, moving between compliance and noncompliance with CS regulations.
Losing a Negative CSR Reputation (NC → C)
We define losing a negative CSR reputation as implying that a firm has moved from being noncompliant (NC) with CS regulations in the prior period to being compliant (C) in the current period. Being noncompliant in the previous period has two implications: first, stakeholders have a positive perception of the firm now that it has achieved the minimum level of CS-mandated activity, and second, stakeholders in the previous period had a negative perception based on the firm not being compliant with CS regulations. Bosse et al. have argued that, in a stakeholder context, “third-party observers of an exchange will systematically reward or punish those they perceive fair or unfair” (2009, p. 449). If compliance with CS regulations is viewed as consistent with norms of fairness, stakeholders may reward such behavior based on norms of reciprocity (Bosse et al. 2009). Thus, we infer that the move from a negative to a neutral CSR reputation may provide some performance benefits for a firm relative to its rivals.
However, a firm is perceived to have a neutral CSR reputation if it satisfies or meets established compulsory standards (Bitektine 2011). A firm that merely complies with government regulations does not reveal any additional information beyond the legal requirement to its stakeholders regarding how the firm values its involvement in CS activities. Since a neutral CSR reputation is easy to replicate by other firms and not necessarily a valuable intangible resource (Barney 1991; Deephouse et al. 2017), the firm is unlikely to derive superior performance in the current period from mere compliance with government CS regulations.
In terms of the negativity bias, prior research has concluded that the information content of a particular behavior depends on the extent to which the behavior is linked to a particular trait category more than an alternative category. For instance, deviant behavior contains high information content because it is assumed that only deviant people engage in such behaviors, whereas positive behaviors can be conducted by everyone. Using a timely example, Lupfer et al. (2000) asserted that “denying help to a needy friend” (e.g., noncompliance with a CS mandate) is likely to be perceived more negatively than “helping a needy friend” (compliance with the mandate) is perceived positively. Thus, noncompliance with CS-mandated activity levels should receive more weight than compliance in the eyes of the firm’s stakeholders.
However, the recency bias should counteract the negativity bias at least to some extent. Since decision makers pay more attention to current events than to previous events, the firm’s current compliance with CS-mandated activity levels should receive more prominence than its previous noncompliance in the eyes of shareholders. Moreover, Chen and Lurie (2013) theorized and showed that time mitigates the effect of a negativity bias. Thus, the recency effect should dampen the negativity bias in the previous period.
In sum, losing a negative CSR reputation may send a positive signal to stakeholders; however, the negativity and recency biases work against one other, which should lead to there being no significant effect on firm performance. Thus, we hypothesize that:
Hypothesis 1a (NC → C)
Losing a negative CSR reputation does not affect firm performance.
Gaining a Negative CSR Reputation (C → NC)
Gaining a negative CSR reputation implies that the firm’s CS activity level changes from compliant (C) to noncompliant (NC) with CS regulations. By failing to comply with the law, the firm conveys not only a lack of benevolence for CS issues, but also a disregard for what is legally required. Noncompliance should therefore imply a negative CSR reputation with a negative impact on firm performance.
Note that there may be deliberate or unplanned reasons behind noncompliance. A firm may lack the requisite finances to put resources toward meeting the requirements; managers may believe that financial penalties incurred will be outweighed by the savings on resources that would otherwise be spent on achieving compliance; or the firm may have unexpectedly fallen short of expectations despite intentions to comply (miscalculation). Moreover, the underlying reasons may lie outside of the firm’s control, for example, a negative business cycle. It is therefore possible that reasons for the firm’s noncompliance, and the extent to which they are known and understood by stakeholders, may affect stakeholders’ views of the firm’s CSR reputation. Some studies have asserted that the impact of negative events on a firm can be buffered by its “reservoir of goodwill” (Zavyalova et al. 2016, p. 234) and that stakeholders may choose to blame events or actions outside of the firm’s control as causing the negative events.
Still, given that the firm does not meet the mandated level of CS activity in the current period, we anticipate that its current CSR reputation should be negative with a negative impact on the firm’s ROA. This assessment, however, does not account for recency and negativity biases, which are also likely to affect the firm’s CSR reputation and its performance.
In terms of the recency effect, according to the belief adjustment model, a revision to perceptions depends on the prior anchor and the nature of the information (positive or negative) used to make the revision. Information that refutes a prior belief will receive a weighting that is proportional to the strength of the belief—thus producing a more potent adjustment to a strong anchor than a weak one. Consistent with this view, Arnold et al. (2000) postulated that auditors will react more strongly to a new “going concern opinion,” which is recent and negative information. Thus, the recency bias should strengthen the negative impact of noncompliance in the current period.
In terms of the negativity bias, having a negative CSR reputation can significantly damage a firm’s relational ties and sustainability (Rhee and Valdez 2009). Even if no explicit financial penalties are attached to noncompliance with the law, a decentralized enforcement process relying on norms and rules can impose social and economic sanctions on the firm (Terlaak 2007). Without a reservoir of goodwill from prior CS activity, stakeholders are likely to stigmatize and shun a firm that gains a negative CSR reputation. Key stakeholders will react negatively by “lowering their quality of involvement, acting confrontationally toward management, demanding better contract terms, and/or detaching from the firm” (Rhee and Valdez 2009, p. 146). Prospective stakeholders may also abstain from associating with firms that gain negative CSR reputations. Such actions by current and prospective stakeholders are likely to affect negatively the firm’s financial performance. Moreover, the drop in CS-mandated levels from compliance to below compliance in and of itself is a negative event as it moves the firm from organizational legitimacy to being nonlegitimate. Rozin and Royzman (2001) have argued that there is greater potency associated with negative changes such that they produce a greater “objective magnitude” than positive changes. In sum, gaining a negative CSR reputation should be costly for the focal firm due to strained/detached relationships with current stakeholders and the inability to attract new stakeholders.
We therefore argue that both the recency and negativity biases should strengthen the negative impact of noncompliance in the current period, with the following implication:
Hypothesis 1b (C → NC)
Gaining a negative CSR reputation negatively affects firm performance.
In Hypothesis 1a, we predict that moving from noncompliance to compliance with CS regulations will have no significant impact on firm performance. In Hypothesis 1b, we predict that moving in the reverse direction, from compliance to noncompliance, will have a negative impact on firm performance. Combining the two hypotheses and looking at them in terms of their absolute values, we therefore anticipate that:
Hypothesis 1c (|NC → C|<|C → NC|)
The impact on firm performance of losing a negative CSR reputation is smaller in absolute terms than the impact of gaining a negative CSR reputation.
Gaining/Losing a Positive CSR Reputation
We now examine the directional impacts of gaining or losing a positive CSR reputation, that is, moving between meeting and exceeding CS regulations.
Gaining a Positive CSR Reputation (C → AC)
Gaining a positive CSR reputation implies that the firm has moved from meeting to exceeding government CS regulations. The achievement of an above-compliance rating in the current period should, all else being equal, generate a positive CSR reputation with a positive impact on firm performance. Stakeholders place more emphasis on the achievement of social responsiveness because it is difficult to replicate a valuable intangible resource that can be a source of competitive advantage (Barney 1991). Achieving social responsiveness helps build a favorable track record as a good corporate citizen with existing stakeholders and enables the firm to build new network relationships, especially with potential stakeholders that value corporate social activities that, in turn, enhance firm performance.
Looking at recency and negativity biases, the recency bias suggests that a current-period rating should be weighed more heavily by stakeholders than a previous-period rating. In addition, in neither time period does the firm face a negativity basis. Thus, the overall impact of gaining a positive CSR reputation should be a positive effect on firm performance.
Hypothesis 2a (C → AC)
Gaining a positive CSR reputation positively affects firm performance.
Losing a positive CSR reputation (AC → C)
Losing a positive CSR reputation is a negative change whereby a firm’s CS activities have declined from exceeding to meeting CS regulatory requirements. The firm’s compliance with CS-mandated levels in the current period should ensure that the firm maintains organizational legitimacy but does not distinguish itself from its peers and therefore does not achieve superior returns (Barney 1991; Deephouse et al. 2017). In addition, the recency effect should strengthen this assessment by stakeholders: the firm has a neutral CSR reputation with no impact on firm performance.
Since in neither time period is the firm noncompliant with CS regulations, we do not expect a negativity bias from the level of CS activity in either time period. However, it is still the case that the firm’s activity level has fallen from the prior to the current period, which may possibly be perceived negatively by the firm’s shareholders, as Rozin and Royzman (2001) have argued. On the other hand, scholars have shown that the beliefs about ability to perform are driven by past successful activities or past performance (Heider 1958; Kelley 1973). We infer from these studies that a firm with a favorable track record for CS activity that curtails its CS activity to the minimum required by law is likely to receive the “benefit of the doubt” (Love and Kraatz 2009, p. 321) from stakeholders. Moreover, even with the drop in CS activity levels, the firm remains compliant with CS regulations and therefore remains legitimate. Thus, we do not anticipate any negativity bias from the drop in CSR reputation in this case.
Putting these effects together, a firm is quick to accumulate benefits from gaining a positive CSR reputation, but slow to lose these benefits. Therefore:
Hypothesis 2b (AC → C)
Losing a positive CSR reputation does not affect firm performance.
In Hypothesis 2a, we predict that moving from compliance to above compliance with CS-mandated activity levels will have a positive significant impact on firm performance. In Hypothesis 2b, we predict that moving in the reverse direction, from above compliance to compliance, should not affect firm performance. Combining the two hypotheses and looking at them in absolute value terms, we anticipate that:
Hypothesis 2c (|C → AC|>|AC → C|)
The impact on firm performance of gaining a positive CSR reputation is larger in absolute terms than the impact of losing a positive CSR reputation.
Gaining/Losing a Negative CSR Reputation versus Gaining/Losing a Positive CSR Reputation
We further develop our dynamic framework by explaining the differential effects of changes in negative versus positive CSR reputation on firm performance. We extend Rozin and Royzman’s (2001) logic on space and time to losing a negative CSR reputation and gaining a positive CSR reputation. Gaining a positive CSR reputation underscores a firm’s social commitment and enhances its supply of goodwill for CS activity; losing a negative CSR reputation involves recollection of negativity in the prior period. Our predictions are more complex than those of Rozin and Royzman (2001) because we argue there are three effects involved in looking at CSR reputation in a dynamic context: the firm’s current and past levels of CS-mandated activity, recency bias, and negativity bias.
Moving “Up the Ladder” in CSR Reputation
We first consider “moving up” in CSR reputation; that is, we compare Hypothesis 1a, losing a negative CSR reputation (NC → C), with Hypothesis 2a, gaining a positive CSR reputation (C → AC). We predicted in Hypothesis 1a that losing a negative CSR reputation would not have a significant impact on performance; in Hypothesis 2a, we predicted that gaining a positive CSR reputation would positively affect performance. That is, if one conceptualizes a firm’s CS-mandated activity level as moving in steps from first noncompliance to compliance and then from compliance to above compliance with CS regulations, we predict the impact of the “second step” should be positive and larger than the “first step” in absolute terms. Thus:
Hypothesis 3a (|NC → C|<|C → AC|)
The impact on firm performance of losing a negative CSR reputation is smaller in absolute terms than the impact of gaining a positive CSR reputation.
Moving “down the ladder” in CSR Reputation
We now consider “moving down” in CSR reputation; that is, we compare Hypothesis 2b, losing a positive CSR reputation (AC → C) with Hypothesis 1b, gaining a negative CSR reputation (C → NC). In Hypothesis 2b, we hypothesized that losing a positive CSR reputation would have no impact on firm performance; Hypothesis 1b argued that firm performance would suffer when CSR reputation drops from neutral to negative. Comparing the two, in absolute terms, we predict that losing a positive CSR reputation should have a smaller impact on performance than gaining a negative CSR reputation. In other words, if we conceptualize this as “moving down the ladder,” the first step down from the top (AC → C) in absolute terms should have a smaller effect on firm performance than the second step (C → NC).
Hypothesis 3b (|AC → C| < |C → NC|)
The impact on firm performance of losing a positive CSR reputation is larger in absolute terms than the impact of gaining a negative CSR reputation.
Comparing Moves Away from Neutrality
Lastly, we compare the effects of gaining a positive CSR reputation versus gaining a negative CSR reputation.Footnote 6 Both events involve the firm being compliant with CS regulations in the prior period, implying the firm had organizational legitimacy and a neutral CSR reputation. We are therefore comparing the impact on firm performance, in absolute terms, of Hypothesis 1b, moving away from neutrality to above compliance (|C → AC|), with Hypothesis 2a, moving away from neutrality to noncompliance (|C → NC|).
In Hypothesis 1b, we predicted that moving from compliance to noncompliance should negatively affect firm performance. In Hypothesis 2a, we predicted that moving from compliance to above compliance should positively affect performance. The recency bias in both cases favors the firm’s current CS level; the negativity bias strengthens the current level for Hypothesis 1b, but not for Hypothesis 2a. Although the recency bias suggests that exceeding CS regulations will produce goodwill with stakeholders, the recency bias coupled with the negatively bias suggests that stakeholders will weigh a recent negative outcome more heavily than a recent positive one (Rozin and Royzman 2001); thus, we hypothesize that:
Hypothesis 3c (|C → NC|>|C → AC|)
The impact on firm performance of gaining a negative CSR reputation is larger in absolute terms than the impact of gaining a positive CSR reputation.
Empirical Analysis
Data and Sample
We test our hypotheses on data from the U.S. banking industry. Extensive government regulations in this industry make the relationship between firm compliance with government regulations and firm performance particularly relevant, because going above compliance with government regulations is one way a firm can differentiate itself from its peers. The banking industry sample has also been utilized in many empirical studies in management (e.g., Campbell et al. 2012; Dietz et al. 2004; Kim and Miner 2007; Miller and Eden 2006).
The most important CS regulation in the U.S. banking industry is the U.S. Community Reinvestment Act (CRA). The CRA, which was passed in 1977 and updated in 1995 and 2005, is designed to incentivize banks to help meet the credit needs of lower income areas in which they operate a branch (Federal Reserve Board 2008). The Act requires that banks meet the needs of all communities, including lower- and moderate-income areas, without jeopardizing the safety and soundness of bank operations (Johnson and Sarkar 1996).Footnote 7 All banks in the United States, domestic and foreign, are normally audited and rated every 2–3 years by U.S. government agencies. Banks that meet CRA requirements are rated as “Satisfactory”; those that exceed the requirements are rated as “Outstanding,” whereas those that fail to meet requirements are rated as “Unsatisfactory.”Footnote 8
Because bank CRA ratings are based on independent assessments by federal government agencies (e.g., Federal Reserve Board, Federal Deposit Insurance Corporation, and Office of the Comptroller of the Currency), their CS activity levels can be considered credible and reliable, unlike self-reports of CS activities. The ratings and full reports are released publicly shortly after the final report is submitted to the respective agency, which provides greater consistency in exposure compared with most firm-level corporate social activities. It is also important to note that the CRA does not force firms to undertake an undue amount of risk or put any pressure on individual institutions to exceed the expectations set forth by the Act.
CRA ratings of banks are publicly available for download from the Federal Financial Institutions Examination Council’s (FFIEC) website. In addition, each bank must maintain and update its public file with specific information about its CRA performance, including the bank’s most recent evaluation and disclosure reports. Banks must also provide consumers with contact information where they can comment on the bank’s CRA performance.Footnote 9 Many banks are now publishing annual CSR reports that include information on their CRA ratings.
We infer from Gates and Villanueva (2014) that CRA ratings are viewed by stakeholders as an important indicator of a bank’s responsiveness to local community issues and concerns. For example, the Charlotte Business Journal announced that Bank of America’s reputation was severely damaged when its CRA rating dropped to “Satisfactory” from “Outstanding” (O’Daniel 2014). Taylor and Silver (2009) note that banks often issue press releases announcing “Outstanding” CRA ratings but avoid publicizing low CRA ratings because they can adversely affect a bank’s supply of goodwill.
Each CRA rating is based on a US federal government agency’s assessment of the bank’s CS activities in three areas (lending, investment, and service activities) over the period since the bank’s previous CRA rating. The three components are weighted 50%, 25%, and 25%, respectively, to determine an overall CRA rating. (See Online Appendix for details.) A bank’s overall CRA rating in any period is a lagged variable because it evaluates a bank’s activities over the past rating period (years t − 1 and t − 2). To confirm the assessment lag, we examined several CRA reports, all of which stated that the assessment period preceded receipt of the CRA rating. All other data were obtained from the Reports of Condition and Income (Call Reports) maintained by the Federal Financial Institutions Examination Council and available through Wharton Research Data Services.
Our sample includes bank entities located in Metropolitan Statistical Areas (MSAs) in the United States. MSAs are the most commonly used geographical boundaries in studies of commercial banks (Amel and Rhoades 1988; Barnett et al. 1994; Miller and Eden 2006). Our unit of analysis is the local bank entity (i.e., the subsidiary at the local MSA level, as opposed to the parent institution at the regional or national level). The number of CRA ratings received by a bank varies from a minimum of one rating to a maximum of 12 ratings, with an average of 3.5 CRA ratings per bank. Our final sample consists of 7317 banks that received at least two CRA ratings for a total of 25,732 firm-year observations over 1992–2007. If a bank received the same CRA rating in two consecutive periods, we code the rating change as zero for the hypothesized variables.
Measures
Dependent Variable
We measure firm performance as return on assets (ROA), which is the most commonly used measure of bank performance in research in management (e.g., Barnett et al. 1994; Mehra 1996) and finance (e.g., Bonin et al. 2005).
Independent Variables
Our independent variables capture positive and negative changes in a bank’s CS-mandated activity levels. Because a CRA rating in year t reflects the bank’s level of CS-mandated activities in the previous 2 years, our independent variables automatically lag our dependent variable ROA by 1–2 years. Note that our model does not capture the “announcement effect” of a CRA rating (which would require an event study around the specific date that the CRA rating was announced), but rather the impact of prior CS activity levels on current firm performance.
Losing a negative CSR reputation is a dummy variable that equals one if a bank moves from a noncompliant CRA rating in the prior period to a satisfactory CRA rating in the next period, zero otherwise. Gaining a negative CSR reputation is a dummy variable that equals one for moving from a satisfactory CRA rating in the prior period to a noncompliant CRA rating in the next period, zero otherwise. Gaining a positive CSR reputation is a dummy variable that equals one when the bank moves from a satisfactory CRA rating in the prior period to an outstanding CRA rating in the next period, zero otherwise. Losing a positive CSR reputation is a dummy variable that equals one if a bank moves from an outstanding CRA rating in the prior period to a satisfactory CRA rating in the next period, zero otherwise.
Control Variables
We included several controls that may affect bank performance or failure, following Miller and Eden (2006). Market size is based on the natural log of deposits in the metropolitan statistical area (MSA). Market share is the ratio of a bank’s deposits to total deposits in the MSA in each year.
In terms of firm characteristics, bank size was used as a control for the bank’s relative market power; this variable was calculated as the natural logarithm of total assets (in thousands of dollars). Net loan losses, calculated as annualized net loan charge-offs (adjusted for recoveries) as a percentage of the bank’s average total loans (Barsade et al. 1997), was used to control for the bank’s lending performance. Expense ratio was included to control for the bank’s cost efficiency in a given year. It was calculated as the annual ratio of interest and noninterest expenses to total average assets. Following Kim and Miner (2007), we included charter type (“federal charter” = 1; “state charter” = 0). We included foreign ownership (“foreign owned” = 1; “domestic” = 0) to control for the possibility that foreign banks face greater adversity than domestic banks in the local market due to liability of foreignness (Zaheer 1995).
Initial positive CSR reputation is a dummy variable equal to one if a focal firm had an outstanding CRA rating the first time we observe that firm in our sample, zero otherwise. Initial negative CSR reputation is a dummy variable set to one if a focal firm has a noncompliant CRA rating the first time we observe that firm in our sample, zero otherwise. We include these measures to take account of our baseline argument that social responsiveness (the firm’s going “above and beyond” CS-mandated activity levels) is positively related to firm performance.
Finally, we included year dummy variables to control for fluctuations in macroeconomic conditions and general industry performance, and any other time-dependent variation (such as regulatory policy change). Inclusion of time dummy variables also effectively deals with contemporaneous correlation (Certo and Semadeni 2006). Due to outliers, we winsorized firm performance, net loan losses, and expense ratio at 99%.
Analysis
Because we have panel data, we used the xtreg command in STATA 14 with firm fixed effects and robust standard errors, which is more conservative than a random effects model. Since the CRA evaluation is not completed each year, we only include sample years in which the CRA rating was available for a given firm (every 2–3 years).
Results
Table 1 presents summary statistics and correlations. Multicollinearity diagnostics for Model 2, which contains all main effects, show that the highest individual VIF value is 1.77 (a year dummy variable) and the mean VIF value is 1.27. These values are well below the generally accepted threshold of 10 (Neter et al. 1990), indicating that multicollinearity should not affect our results.
Table 2 presents the results from the fixed effects GLS regressions. Model 1 includes only the control variables. Most controls are statistically significant. Perhaps the most important of the controls for our analysis is initial CSR reputation. Model 1 shows that initial positive CSR reputation enhances firm performance, whereas initial negative CSR reputation is negatively related to performance, relative to the baseline case of an initial neutral CSR reputation, as we anticipated. These findings provide strong evidence of the impact of initial CSR reputation on firm performance, which aligns with assertions made by Brammer and Millington (2008) and, in turn, explains some of the mixed results in prior studies.
Model 2 introduces the main effects. The control variables for initial CSR reputation retain their significance and size, again demonstrating the strong correlation between firm performance and a bank’s initial CRA rating. Hypothesis 1a predicted that losing a negative CSR reputation does not affect firm performance. According to Cohen and Cohen (1983), a hypothesis of no effect can be supported if statistical power (1 − β) is high, and the relationship is found to be trivial. In the presence of high statistical power, failing to reject the null suggests that no nontrivial relationship exists (Cohen 1990). We rely on general approximations of a medium effect size as outlined by Cohen (1992). Thus, setting α = 0.05, power = 0.95 (β or Type II error = 0.05)Footnote 10 with 28 predictors (including year dummy variables), the minimum sample size required to detect a small effect is a sample size of 718. Since our sample size exceeds 25,000 observations, we conclude that since the coefficient for losing a negative CSR reputation is not statistically significant in Table 2. Therefore, we have support for Hypothesis 1a.
Hypothesis 1b predicted that gaining a negative CSR reputation negatively affects firm performance. The coefficient for gaining a negative CSR reputation (β = −0.198; p < 0.05) is negative and statistically significant, providing support for Hypothesis 1b.
Hypothesis 1c argued that the effect on firm performance of gaining a negative CSR reputation is stronger, in absolute terms, than the effect of losing a negative CSR reputation. The difference between these coefficients is statistically significant (χ2 = 4.66; p < 0.05), which supports Hypothesis 1c.
Hypothesis 2a predicted that gaining a positive CSR reputation has a positive effect on firm performance. In Model 2, the coefficient for gaining a positive CSR reputation is positive and statistically significant (β = 0.102; p < 0.001), providing support for Hypothesis 2a.
Hypothesis 2b predicted that losing a positive CSR reputation has no effect on firm performance. Following the same argument as for Hypothesis 1a, we conclude that losing a positive CSR reputation has no meaningful statistical effect on firm performance, supporting Hypothesis 2b.
Hypothesis 2c is based on a comparison of Hypotheses 2a and 2b. We predicted that the effect on firm performance of gaining a positive CSR reputation (Hypothesis 2a) would be stronger than the effect of losing a positive CSR reputation (Hypothesis 2b). The results indicate that the difference in absolute values of the respective coefficients is statistically significant (χ2 = 4.90; p < 0.05), which supports Hypothesis 2c.
Next, we examine the magnitude of changes across different changes in CSR reputation. Hypothesis 3a, which we refer to as “moving up the ladder in CSR reputation,” compares the relative impact on firm performance of, first, moving from noncompliance to compliance and, second, moving from compliance to above compliance, with CS regulations. Hypothesis 3a predicted that the impact on firm performance, in absolute terms, of losing a negative CSR reputation should be smaller than the impact of gaining a positive CSR reputation. However, the absolute value of the coefficient for losing a negative CSR reputation is not statistically different from the absolute value of the coefficient for gaining a positive CSR reputation (χ2 = 0.55; p < 0.46), implying no empirical support for Hypothesis 3a. Thus, the size in absolute terms of the two “upward steps” in terms of their correlation with firm performance is roughly the same so that their difference is not significant. The mathematical reason for this result is clearer when we look at the means and standard errors for the two effects. Our statistical test looks at the difference between the two means (standardized betas), which are not significantly different, and ignores the standard errors. Thus, the lack of significance for losing a negative CSR reputation, which is due to the mean being small relative to the standard error, is not relevant for this comparison.
Hypothesis 3b, which we refer to as “moving down the ladder in CSR reputation,” compares the relative impact on firm performance of two steps: the first step, moving from above compliance to compliance (Hypothesis 2b), and the second step, moving from compliance to noncompliance (Hypothesis 1b), with CS regulations. Hypothesis 3b predicts that the impact of losing a positive CSR reputation should, in absolute terms, be larger than the impact of gaining a negative CSR reputation. The absolute value of the coefficient for gaining a negative CSR reputation is greater than the absolute value of the coefficient for losing a positive CSR reputation (χ2 = 4.56; p < 0.05), supporting Hypothesis 3b.
Lastly, Hypothesis 3c, which we refer to as “moving away from a neutral CSR reputation,” posited that gaining a negative CSR reputation should have a stronger impact on performance than gaining a positive CSR reputation. Our results show that the absolute value of the coefficient for gaining a negative CSR reputation is not significantly greater than the absolute value of the coefficient for gaining a positive CSR reputation, which shows no support for Hypothesis 3c (χ2 = 1.32; p < 0.25). In both situations, in the prior period the firm is merely compliant with CS regulations. In the second period, in one situation the firm moves above CS-mandated levels and in the other situation the firm moves down to noncompliance. Empirically, our results show no statistical difference between the size of these two “steps” in absolute terms. This suggests either that the negativity bias, in absolute terms, must be relatively small or that the gain from going “above and beyond” mandated CS compliance levels must be relatively large.
The comparison of our hypotheses with our empirical work is summarized in Table 3.
Extended Analysis
Reverse Causality
Because reverse causality might confound our results, we created a lagged performance variable as an independent variable. We used gaining a positive CSR reputation, as the dependent variable. Because this dependent variable is dichotomous, we used year dummies, a foreign dummy, and firm controls (e.g., firm size) as explanatory variables with xtprobit in STATA. The coefficient on lagged firm performance was not statistically significant. We repeated the analysis for losing a positive CSR reputation, losing a negative CSR reputation, and gaining a negative CSR reputation, respectively. For each estimate, the coefficient on lagged performance is not significant. As such, reverse causality appears to have no effect in our study.
Liability of Foreignness
As we probe deeper to understand the asymmetric effects of CSR reputation changes, we note that foreign banks achieve lower performance than domestic banks. The coefficient on foreign ownership in Table 2 is negative and marginally statistically significant in Model 2 (β = − 0.388; p < 0.10). This result is consistent with liability of foreignness (LOF) theory whereby foreign firms suffer from unfamiliarity, discriminatory, and relational hazards arising from institutional distance and a lack of embeddedness in the host country (Eden and Miller 2004; Miller and Parkhe 2002; Wu and Salomon 2016; Zaheer 1995). Activities such as adopting local best practices and engaging in CSR can help reduce LOF and improve embeddedness (e.g., Campbell et al. 2012).
In effect, we need to consider all three biases: recency, negativity, and foreignness. Drawing on LOF theory, we argue that the foreignness bias should be strongest when the foreign subsidiary is not compliant with CS regulations and weakest when the foreign subsidiary exceeds CS regulations in the host country.
Losing a negative CSR reputation, as we have defined and measured the variable, implies having been noncompliant with CS regulations in the prior period. We expect that foreign subsidiaries are penalized more by local stakeholders for being foreign if they lack compliance with CS regulations in the prior period. Thus, we expect foreignness to moderate the relationship between losing a negative CSR reputation and firm performance, in that the relationship between losing a negative CSR reputation and firm performance is more negative (i.e., stronger) for a foreign firm than for a domestic one.
Gaining a negative CSR reputation, as we have defined and measured it, implies that the bank moves from compliance with CS regulations in the previous period to noncompliance in the current period. Even though negativity bias affects all firms that gain a negative CSR reputation, the foreignness bias suggests that foreign firms should be punished more by local stakeholders for gaining a negative CSR reputation. That is, we expect foreignness strengthens the negative relationship between gaining a negative CSR reputation and firm performance.
In an extended analysis, the coefficient for foreign ownership * losing a negative CSR reputation was negative and marginally significant (p < 0.10), suggesting the foreign-owned firms do incur somewhat greater costs to losing a negative CSR reputation than domestic firms. However, the coefficient for gaining a negative CSR reputation was not statistically significant.
We also expect the foreignness bias to be weaker for foreign firms that comply with CS regulations; thus, foreign firms are unlikely to differ from domestic firms with respect to gaining or losing a positive CSR reputation. The coefficients for foreign ownership * gaining a positive CSR reputation and foreign ownership * losing a positive CSR reputation were not significant.
Restricted Sample
We also took a closer look at the winsorized (99%) dependent variable. A histogram showed a substantial number of observations at the tails of the ROA distribution, especially for banks with noncompliant ratings. Hence, we re-estimated the results with a sample that excluded observations at the tails. These results were qualitatively similar to the reported results with one exception. The coefficient for losing a negative CRS reputation was 0.000 (n.s.) and the coefficient for gaining a positive CSR reputation changed from 0.10 to 0.11. The test of the difference in absolute values reveals statistical significance at the 0.078 level, which would indicate weak support for Hypothesis 3a. This is important to note since our test of power revealed that our sample size was more than adequate.
Practical Implications of Our Results
Lastly, we investigated the substantive or practical significance of our results, specifically, the impacts on bank profitability of gaining a positive CSR reputation (Hypothesis 2a) and gaining a negative CSR reputation (Hypothesis 1b). To quantify the performance impacts of these changes in CSR reputation, consider a bank with $1 billion in assets. Gaining a positive CSR reputation (C → AC) translates to a $1.02 million increase in earnings after tax, which represents 4.04% of mean profits for the representative bank. Alternatively, gaining a negative CSR reputation (C → NC) results in a $1.98 million decrease in after-tax earnings, which equals − 7.8% of mean profits. Thus, the impacts of changes in a bank’s CSR reputation have substantive, meaningful, and asymmetric financial impacts in terms of bank profitability.
Discussion and Conclusions
This paper explores the concept of change in CSR reputation with respect to corporate social (CS) activities of banks. Our study addressed the link between changes in CSR reputation and performance by distinguishing between firms that gain (lose) a positive CSR reputation and those that gain (lose) a negative CSR reputation. We theorized and showed that among the pool of firms that comply with CSR regulations, gaining a positive CSR reputation can differentiate them from firms that merely comply. Our evidence of changes in CSR reputation extends prior work by Barnett and Salomon (2006). Our use of the reinforcing and offsetting effects of recency and negativity biases provided evidence that stakeholders asymmetrically weigh a firm’s positive/negative changes and current/non-current corporate social activities. This aspect of our study contributes to research on reputation, corporate social responsibility, and firm financial performance (e.g., Doh et al. 2010) and to work on recency and negativity biases.
In the paper, we developed a dynamic framework to explain how the changes of a firm’s responses to government-mandated levels of CS activity affect its reputation and performance. We argued that the impacts depend on the following factors: (1) the firm’s current and prior levels of CS-mandated activity relative to CS regulations, where moving from noncompliance to compliance to above compliance is generally and positively related to CSR reputation and firm performance; (2) the recency bias, which weights current activity more heavily than prior activity; and (3) the negativity bias, which weights noncompliance more heavily than compliance or above compliance with CS regulations. The overall impact on how stakeholders view a firm’s CSR reputation and the impact on firm performance depends on how these three factors play out in different situations.
We further develop our dynamic framework by explaining differential effects of changes in negative versus positive CSR reputation on firm performance. We can extend Rozin and Royzman’s (2001) logic on space and time to losing a negative CSR reputation and gaining a positive CSR reputation. Gaining a positive CSR reputation underscores a firm’s social commitment and enhances its supply of goodwill for CS activity; losing a negative CSR reputation involves recollection of negativity in the prior period.
Our results are generally consistent with these three factors. We found that movements toward compliance with CS regulations had no significant impact: losing a negative CSR reputation (NC → C) and losing a positive CSR reputation (AC → C) were both nonsignificant. Firms with a neutral CSR reputation are legitimate but do not achieve superior returns (Barney 1991; Deephouse et al. 2017).
On the other hand, we found that movements away from compliance with CS regulations did affect firm performance: gaining a negative CSR reputation (C → NC) was negatively related to firm performance, whereas gaining a positive CSR reputation (C → AC) was positively related to firm performance. When we compared the relative sizes of the two movements in absolute terms, we found no statistically significant difference. However, there was a substantive difference in terms of average bank profitability. For a bank with $1 billion in assets, gaining a positive CSR reputation generated a 4.04% increase in bank profits, whereas gaining a negative CSR reputation was associated with a drop of 7.8% in bank profits. Thus, changes in a bank’s CSR reputation can have substantive and meaningful financial impacts for the firm in terms of profitability.
We also found that the relative sizes of the two steps in “moving up the ladder” (from NC → C and then from C → AC) were not significantly different in terms of their impact on firm performance. The relative sizes of the two effects in “moving down the ladder” (from AC → C and then from C → NC), on the other hand, had a clear negative impact on performance. Moving into noncompliance clearly was costly for the firm.
The extant literature on reputation tends to have a static view—comparisons of firms with positive reputations versus others. However, the present study showed that firms can achieve a positive CSR reputation and then lose it or gain a negative CSR reputation and then lose it. As such, the present study’s integration of the reputation and CSR literature with recency and negativity biases opens the door to new research opportunities involving studying reputation and firm performance in a dynamic setting.
One possible issue in our study is that the sample involves an action that may involve more risk—providing loans to lower income customers. Firms may charge higher interest rates to compensate for greater risk of defaults. If our findings reflected only the risk-return tradeoff, then a positive effect on firm performance from gaining a positive CSR reputation should have revealed a symmetric result for losing a positive CSR reputation. Since we found support for Hypothesis 1c, however, the risk-return argument does not hold because it ignores how current and potential stakeholders view these CS actions.
Our paper offers managerial implications. For the U.S. banking industry, even though there are no explicit penalties attached to failure to comply with the Community Reinvestment Act, our results consistently show that transgressors are punished as reflected in their lower financial performance. Going voluntarily beyond government-mandated levels of social activities enables firms a performance bump and a reservoir of goodwill with stakeholders. Yet if firms lose social responsiveness, the reservoir of goodwill seems to prevent a corresponding performance drop.
In terms of policy implications, the Community Reinvestment Act represents a good example of a diluted regulation (also see Bradford 2004) adopted under the pressure of socially concerned NGOs and community organizations, as noncompliance does not lead to a penalty by the regulator. However, our findings focusing on stakeholders’ view demonstrate the benefits and penalties of compliance and outstanding CRA rating even when the regulations might be diluted (Bradford 2004).Footnote 11 For instance, one way in which transgressors are punished is through the inability to expand or to acquire other banks. However, this punishment is probably inconsequential for the many banks in our sample that do not need to establish more branches or subsidiaries or acquire other banks. Instead, we suggest that an informal system of sanctions can help punish “rogue banks,” consistent with the reputation literature (Fombrun 1996).
There are some limitations to our study. First, while our sample includes U.S. banks and U.S. affiliates of foreign commercial banks, our data are for a single country and a single industry, which raises the question of generalizability to other settings and to other types of corporate social activity. One benefit of examining changes in CSR reputation in a single-industry/country context is that it limits firm heterogeneity and thus increases confidence in the internal validity of our results. We contend that our framework is generalizable to other social activities, industries, and countries; however, future research needs to examine this assertion.
A possible limitation also pertains to the CRA ratings. As we show in Appendix A, the regulators use a continuous variable to compute the lending (0–12 points), investment (0–6 points), and service (0–6 points) components and then add them together to obtain a bank’s total CRA points; however, CRA ratings are based on a range of CRA points. We point out that the specific numerical CRA points are not provided in a bank’s publicly disclosed Community Reinvestment Act Performance Evaluation, so stakeholders see only the CRA ratings, not the points. For some studies, a continuous variable is preferred to a categorical one. However, in the management literature, researchers have focused on whether a firm has complied with CSR regulations, but not by how much a firm exceeds or falls short of the next CSR rating category. Hence, our use of categories for CRA ratings is justified.
Another possible limitation is that the context of our study involves only three possible outcomes (meeting, exceeding, or noncompliance with CS regulations) in one issue area (CRA regulations). Other researchers may want to consider the performance impacts of firms having different ratings in different CS areas or consider a CS area where the ratings are more fine-grained. Relatedly, it is conceivable to a firm to change from noncompliance to exceeding CS regulations, and vice versa. That said, we do not examine these changes because they are generally rare; moreover, there were no cases in our sample. Because of their rarity, research on these changes could use qualitative methods (e.g., Balmer 2010), which represents an opportunity for future research.
Our results may also be affected by changes in the external environment. When the economy is strong, firms have more resources for CSR than in a weak economy where the high opportunity cost may dampen CSR spending. By restricting our sample time period to 1992–2007, we avoided the 2008 financial crisis reducing the likelihood of confounds. We also controlled for macroeconomic variance over time with year dummy variables. Still, future studies may want to explicitly include environmental predictors. We infer from Bitektine and Haack (2015), for example, that external environment changes can have important effects on firm’s CSR reputation.
Our study provides additional opportunities for research. For example, future research might examine local differences in isomorphic pressures between domestic and foreign-owned firms, as our extended analysis shows that there may be different thresholds for foreign-owned firms with respect to positive and negative CSR reputations. Further analysis of differences across foreign affiliates would also be useful.
Our results raise the question of whether a firm can do “too much of a good thing,” that is, engage in such excessive CS activities that evaluators and stakeholders view its actions as risky and foolhardy. Under these circumstances, we would expect the firm’s excess CS activities to generate social responsiveness but be accompanied by a negative performance impact. In our CRA banking dataset, the rating system indicates only whether a bank achieves an “Outstanding” rating so there may be considerable variance in CS activity levels within the “Outstanding” group of banks. In a study of 137 savings banks and thrifts in 1998, Vitaliano and Stella (2006, p. 235) found that the average additional cost of achieving an “Outstanding” CRA rating was $6.547 million or 1.2% of total costs compared with a “Satisfactory” rating, which the authors call the “shadow price of CSR.” Despite these costs, the authors argued that the impact on firm performance may still be positive if the additional benefits outweighed additional costs.
We conjecture that if we were able to examine banks’ expenditures on CS activities, there may indeed be a curvilinear relationship between activity levels and financial performance. This idea is supported by empirical evidence showing that the relationship between corporate philanthropy (a type of CSR) and financial performance is best captured by an inverse U-shaped curve (Wang et al. 2008). Barnett and Salomon (2006), in their study of mutual funds involved in socially responsive investing, also find a curvilinear relationship. Further research on this topic is also warranted.
Corporate social (CS) regulations are a useful context for studying changes in CSR reputation. We explored how changes in a firm’s CSR reputation asymmetrically affected its performance. Our results confirm the importance of recency, negativity, and foreign biases on a firm’s CSR reputation and performance and the asymmetrical impacts of losing and gaining a negative CSR reputation. Our research underlines the need for scholars to employ a dynamic perspective to advance the research field on firm reputation.
Notes
We acknowledge that the actions that result in gaining a positive CSR reputation may be driven by altruism or other motives. At no point do we attempting to distinguish the actual motives of corporate leaders, which are difficult to observe, if not virtually impossible to distinguish. Rather, we focus on a firm’s observable investment in corporate social activities and institutional actors’ perceptions of the focal firm’s actions.
We acknowledge prior studies of autobiographical memory reveal evidence of a fading effect bias, in which people more quickly forget negative experiences than positive ones (Ritchie et al. 2006), this effect is unlikely in a professional setting with high task complexity.
Note we do not compare movements toward a neutral CSR reputation (that is, compliance with CS regulations) because we hypothesize in both cases (H1a and H2b) that the impact should be nonsignificant.
We therefore do not consider the case where a firm spends so far in excess of CS regulations that evaluators and stakeholders view its behavior as unsafe and unsound. In such a case, the firm would be socially responsive but its excessive behavior would have a negative reputation effect.
There are two noncompliant categories, “Needs to improve” and “Substantial noncompliance.” The second was issued so rarely that we combined them into the “Noncompliant” category.
Setting α (the probability of Type I error) and β (the probability of Type II error) equal to .05 means that the probability of our not finding a significant effect when it is actually present is equal to the probability of incorrectly rejecting the null.
Goldman-Carter (1992) discussed diluted regulations with respect to a different CSR domain – environmental protection.
References
Amel, D., & Rhoades, S. (1988). Strategic groups in banking. Review of Economics and Statistics, 70, 685–689.
Arlow, P., & Gannon, M. (1982). Social responsiveness, corporate structure, and economic performance. Academy of Management Review, 7(2), 235–241.
Arnold, V., Collier, P., Leech, S., & Sutton, S. (2000). The effect of experience and complexity on order and recency bias in decision making by professional accountants. Accounting and Finance, 40, 109–134.
Balmer, J. M. T. (2010). The BP Deepwater Horizon debacle and corporate brand exuberance. Journal of Brand Management, 18, 97–104.
Barnett, M., & Salomon, R. (2006). Beyond dichotomy: The curvilinear relationship between social responsibility and financial performance. Strategic Management Journal, 27, 1101–1122.
Barnett, W., Greve, H., & Park, D. (1994). An evolutionary model of organizational performance. Strategic Management Journal, 15, 11–28.
Barney, J. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17, 99–120.
Barsade, S., Koput, K., & Staw, B. (1997). Escalation at the credit window: A longitudinal study of bank executives’ recognition and write-off of problem loans. Journal of Applied Psychology, 82, 130–142.
Berle, A. (1932). For whom corporate managers are trustees: A note. Harvard Law Review, 45, 1365–1372.
Bitektine, A. (2011). Toward a theory of social judgments of organizations: The case of legitimacy, reputation, and status. Academy of Management Review, 53, 151–178.
Bitektine, A., & Haack, P. (2015). The “macro” and the “micro” of legitimacy: Toward a multilevel theory of the legitimacy process. Academy of Management Review, 40, 49–75.
Bonin, J., Hasan, I., & Wachtel, P. (2005). Bank performance, efficiency and ownership in transition countries. Journal of Banking and Finance, 29, 31–53.
Bosse, D., Phillips, R., & Harrison, J. (2009). Stakeholders, reciprocity, and firm performance. Strategic Management Journal, 30, 447–456.
Bradford, C. S. (2004). Does size matter? An economic analysis of small business exemptions from regulation. Nebraska:University of Nebraska, College of Law, Faculty Publications.
Brammer, S., & Millington, A. (2008). Does it pay to be different? An analysis of the relationship between corporate social and financial performance. Strategic Management Journal, 29, 1325–1343.
Brammer, S., & Pavelin, S. (2006). Corporate reputation and social performance: The importance of fit. Journal of Management Studies, 43, 435–455.
Campbell, J., Eden, L., & Miller, S. R. (2012). Multinationals and corporate social responsibility in host countries: Does distance matter? Journal of International Business Studies, 43, 84–106.
Catino, M., & Patriotta, G. (2013). Learning from errors: Cognition, emotions and safety culture in the Italian Air Force. Organization Studies, 34, 437–467.
Certo, S. T., & Semadeni, M. (2006). Strategy research and panel data: Evidence and implications. Journal of Management, 32, 449–471.
Chen, Z., & Lurie, N. (2013). Temporal contiguity and negativity bias in the impact of online word of mouth. Journal of Marketing Research, 50, 463–476.
Cohen, J. (1990). Things I have learned (so far). American Psychologist, 45, 1304–1312.
Cohen, J. (1992). A power primer. Psychological Bulletin, 112, 155–159.
Cohen, J., & Cohen, P. (1983). Applied multiple regression/correlation analysis for the behavioral sciences. Erlbaum: Hillsdale, NJ.
Day, D. (2001). Assessment of leadership outcomes. In S. Zaccaro & R. Klimoski (Eds.), The nature of organizational leadership (pp. 384–410). San Francisco: Jossey-Bass.
Deephouse, D., Bundy, J., Tost, L. P., & Suchman, M. (2017). Organizational legitimacy: Six key questions. In R. Greenwood, C. Oliver, T. Lawrence & R. Meyer (Eds.), The SAGE handbook of organizational institutionalism (2nd edn., pp. 27–54). Oxford: Sage.
Deephouse, D., & Carter, S. (2005). An examination of differences between organizational legitimacy and organizational reputation. Journal of Management Studies, 42, 329–360.
Dietz, J., Pugh, S., & Wiley, J. (2004). Service climate effects on customer attitudes: An examination of boundary conditions. Academy of Management Journal, 47, 81–92.
Dodd, E. (1932). For whom corporate managers are trustees? Harvard Law Review, 45, 1145–1163.
Doh, J., & Guay, T. (2006). Corporate social responsibility, public policy, and NGO activism in Europe and the United States: An institutional-stakeholder perspective. Journal of Management Studies, 43, 47–73.
Doh, J., Howton, S., Howton, S., & Siegel, D. (2010). Does the market respond to an endorsement of social responsibility? The role of institutions, information and legitimacy. Journal of Management, 23, 1461–1485.
Eden, L., & Miller, S. R. (2004). Distance Matters: Liability of foreignness, institutional distance and ownership strategy. In M. Hitt & J. Cheng (Eds.), The evolving theory of the multinational firm. Advances in International Management. Amsterdam: Elsevier.
Elayan, F., Li, H., Liu, Z., Meyer, T., & Felton, A. (2016). Changes in the covalence ethical code, financial performance and financial reporting quality. Journal of Business Ethics, 134, 369–395.
Federal Reserve Board. (2008). Community reinvestment act. http://www.federalreserve.gov/dcca /cra/.
Fombrun, C. (1996). Reputation: Realizing value from the corporate image. Boston: Harvard Business School Press.
Fombrun, C., & Shanley, M. (1990). What’s in a name? Reputation building and corporate strategy. Academy of Management Journal, 33, 233–258.
Gates, C., & Villanueva, M. (2014). Community Reinvestment Act: Developing a strategy for success. Consumer Compliance Outlook, third quarter.
Goldman-Carter, J. (1992). Wetlands classification: A tool for protection or abandonment? Duke University Environmental Law & Policy Forum, 94–105.
Hambrick, D., & Mason, P. (1984). Upper echelons: The organization as a reflection of its top managers. Academy of Management Review, 9, 193–206.
Hastie, R., & Dawes, R. (2001). Rational choice in an uncertain world: The psychology of judgment and decision making. Thousand Oaks: Sage.
Heider, F. (1958). The psychology of interpersonal relationships. New York: Wiley.
Hogarth, R., & Einhorn, H. (1992). Order effects in belief updating: The belief-adjustment model. Cognitive Psychology, 24, 1–55.
Jeong, K.-H., Jeong, S.-W., Kee, W.-J., & Bae, S.-H. (2018). Permanency of CSR activities and firm value. Journal of Business Ethics, 152, 207–223.
Jo, H., & Kim, Y. (2008). Ethics and disclosure: A study of the financial performance of firms in the seasoned equity offerings market. Journal of Business Ethics, 80, 855–878.
Johnson, S., & Sarkar, S. (1996). The valuation effects of the 1977 Community Reinvestment Act and its enforcement. Journal of Banking & Finance, 20, 783–803.
Kelley, H. (1973). The processes of causal attribution. American Psychologist, 28, 107–128.
Kennedy, J. (1993). Debiasing audit judgment with accountability: A framework and experimental results. Journal of Accounting Research, 31, 231–245.
Kim, J.-Y., & Miner, A. (2007). Vicarious learning from the failures and near-failures of others: Evidence from the U.S. commercial banking industry. Academy of Management Journal, 50, 687–714.
King, B., & Whetten, D. (2008). Rethinking the relationship between reputation and legitimacy: A social actor conceptualization. Corporate Reputation Review, 11, 192–207.
Lange, D., & Lee, P. (2011). Organizational reputation: A review. Journal of Management, 37, 153–184.
Lee, D. (2017). Corporate social responsibility and management forecast accuracy. Journal of Business Ethics, 140, 353–367.
Love, E., & Kraatz, M. (2009). Character, conformity, or the bottom line? How and why downsizing affected corporate reputation. Academy of Management Journal, 52, 314–335.
Lupfer, M., Weeks, M., & Dupuis, S. (2000). How pervasive is the negativity bias in judgments based on character appraisal? Personality and Social Psychology Bulletin, 26, 1353–1366.
Madsen, P., & Desai, V. (2010). Failing to learn? The effects of failure and success on organizational learning in the global orbital launch vehicle industry. Academy of Management Journal, 53, 451–476.
McWilliams, A., & Siegel, D. (2000). Corporate social responsibility and financial performance: Correlation or misspecification? Strategic Management Journal, 21, 603–609.
McWilliams, A., & Siegel, D. (2001). Corporate social responsibility: A theory of the firm perspective. Academy of Management Review, 26, 117–127.
McWilliams, A., Siegel, D., & Wright, P. (2006). Corporate social responsibility. Journal of Management Studies 43, 1–18.
Mehra, A. (1996). Resource and market-based determinants of performance in the U.S. banking industry. Strategic Management Journal, 17, 307–322.
Messier, W., & Tubbs, R. (1994). Recency effects in belief revision: The impact of audit experience and the review process. Auditing: A Journal of Practice & Theory, 13, 57–72.
Miller, S. R., & Eden, L. (2006). Local density and foreign subsidiary performance. Academy of Management Journal, 49, 341–355.
Miller, S. R., & Parkhe, A. (2002). Is there a liability of foreignness in global banking? An empirical test of banks’ x-efficiency. Strategic Management Journal, 23, 55–75.
Neter, J., Wasserman, W., & Kutner, M. (1990). Applied linear statistical models Chicago: Irwin.
Nofsinger, J., & Varma, A. (2013). Availability, recency, and sophistication in the repurchasing behavior of retail investors. Journal of Banking & Finance, 37, 2572–2585.
O’Daniel, A. (2014). Bank of America hit with downgraded Community Reinvestment Act rating. Charlotte Business Journal, November 14.
Orlitzky, M., Schmidt, F., & Rynes, S. (2003). Corporate social and financial performance: A meta-analysis. Organization Studies, 24, 403–441.
Pfarrer, M., Pollock, T., & Rindova, V. (2010). A tale of two assets: The effects of firm reputation and celebrity on earnings surprises and investors’ reaction. Academy of Management Journal, 53, 1131–1152.
Rao, H. (1994). The social construction of reputation: Certification contests, legitimization and the survival of organizations in the American automobile industry. Strategic Management Journal, 15, 29–44.
Reason, J. (1990). Human error. Cambridge: Cambridge University Press.
Rhee, M., & Haunschild, P. R. (2006). The liability of good reputation: A study of product recalls in the US automotive industry. Organization Science, 17.1, 101–107.
Rhee, M., & Valdez, M. (2009). Contextual factors surrounding reputation damage with potential implications for reputation repair. Academy of Management Review, 34, 146–168.
Rindova, V., Williamson, I., Petkova, A., & Sever, J. (2005). Being good or being known: An empirical examination of the dimensions, antecedents, and consequences of organizational reputation. Academy of Management Journal, 48, 1033–1049.
Ritchie, T., Skowronski, J., Wood, S., Walker, W., Vogl, R., & Gibbons, J. (2006). Event self-importance, event rehearsal, and the fading effect bias in autobiographical memory. Self and Identity, 5, 172–195.
Roberts, P., & Dowling, G. (2002). Corporate reputation and sustained superior financial performance. Strategic Management Journal, 23, 1077–1093.
Rozin, P., & Royzman, E. (2001). Negativity bias, negativity dominance and contagion. Personality and Social Psychology Review, 5, 296–320.
Simpson, W. G., & Kohers, T. (2002). The link between corporate social and financial performance: Evidence from the banking industry. Journal of Business Ethics, 35, 97–102.
Strategic implications. Journal of Management Studies, 43, 1–18.
Taylor, J., & Silver, J. (2009). The Community Reinvestment Act: 30 years of wealth building and what we must do to finish the job. In P. Chakrabarti, D. Erickson, R. Essene, I. Galloway & J. Olson (Eds.), Revisiting the CRA: Perspectives on the future of the Community Reinvestment Act. Boston: Federal Reserve Banks of Boston and San Francisco).
Terlaak, A. (2007). Order without law? The role of certified management standards in shaping socially desired firm behaviors. Academy of Management Review, 32, 968–985.
Vitaliano, D., & Stella, G. (2006). The cost of corporate social responsibility: The case of the Community Reinvestment Act. Journal of Productivity Analysis, 26, 235–244.
Wang, H., Choi, J., & Li, J. (2008). Too little or too much? Untangling the relationship between corporate philanthropy and firm financial performance. Organization Science, 19, 143–159.
Wei, Z., Shen, H., Zhou, K., & Li, J. (2017). How does environmental corporate social responsibility matter in a dysfunctional institutional environment? Evidence from China. Journal of Business Ethics, 140, 209–223.
Weigelt, K., & Camerer, C. (1988). Reputation and corporate strategy: A review of recent theory and applications. Strategic Management Journal, 9, 443–454.
Wu, Z., & Salomon, R. (2016). Does imitation reduce the liability of foreignness? Linking distance, isomorphism, and performance.’. Strategic Management Journal, 37, 2441–2462.
Zaheer, S. (1995). Overcoming the liability of foreignness. Academy of Management Journal, 38, 341–363.
Zavyalova, A., Pfarrer, M., Reger, R., & Hubbard, T. (2016). Reputation as a benefit and a burden? How stakeholders’ organizational identification affects the role of reputation following a negative event. Academy of Management Journal, 59, 253–276.
Acknowledgements
An earlier version of this paper was presented at the annual meetings of the Academy of Management. We thank Joanna Tochman Campbell for her research assistance, and the editors and anonymous reviewers at the Journal of Business Ethics for their helpful comments, while retaining the responsibility for any errors or omissions.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
Stewart R. Miller, Lorraine Edenand Dan Li declares that they have no conflict of interest.
Electronic supplementary material
Below is the link to the electronic supplementary material.
Rights and permissions
About this article
Cite this article
Miller, S.R., Eden, L. & Li, D. CSR Reputation and Firm Performance: A Dynamic Approach. J Bus Ethics 163, 619–636 (2020). https://doi.org/10.1007/s10551-018-4057-1
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10551-018-4057-1