Investigating the Effects of Moral Disengagement and Participation on Unethical Work Behavior

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Adam J. Barsky Gazi Islam Michael J. Zyphur Emily Johnson

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Investigating the Effects of Moral Disengagement and Participation on Unethical Work Behavior

Adam J. Barsky University of Melbourne

Gazi Islam Ibmec São Paulo

Michael J. Zyphur National University of Singapore

Emily Johnson University of North Carolina

ABSTRACT With massive corruption uncovered in numerous recent corporate scandals, investigating the reasons for unethical behavior in organizations has become a critical area of research for organizational scientists. This paper seeks to explain why people engage in unethical behavior by forcing on the use of rationalizations to justify egregious actions at work, termed moral disengagement. Further, we predicted that allowing employees to participate in setting performance goals would both decrease the incidence of unethical behavior as well as attenuate the relationship between moral disengagement and unethical behavior. Across two studies, a lab simulation and field survey, we developed a measure of moral disengagement for use with working adults, and tested our propositions. Hypothesized relationships between disengagement, participation, and unethical behavior were largely confirmed. Implications and future directions are discussed.

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Investigating the Direct and Interactive Effects of Moral Disengagement and Participative Goal-Setting on Unethical Work Behavior The literature linking individual differences and organizational factors to ethical decision making processes and behavior at work has developed substantially in the past two decades. Research has implicated individual differences such as personality factors (e.g., cognitive moral development; authoritarianism, locus of control), demographics (gender, age, nationality), values and beliefs; as well as contextual factors such as codes of conduct, ethical climate/culture, and rewards and sanctions as explanatory factors in individual wrongdoing (see O’Fallon & Butterfield , 2005 for a recent review). However, a number of important gaps in the literature remain. First, the individual difference research has not provided a compelling window into the cognitive processes employed when individuals decide to act in an unethical manner. As such, this paper takes an alternate approach to understanding unethical behavior by focusing on breakdowns in self-regulation as a common factor underlying the perpetration of high risk, harmful, deceitful or otherwise unethical acts at work. While this latter area is far less developed, we are beginning to see clues about the nature of moral thinking as it relates to moral behavior across a variety of disciplines. For instance, Bandura (1999) proposed the concept of moral disengagement, which refers to individuals’ selective disengagement of their moral self-sanctions which generally operate to keep behavior in line with moral norms, as a means by which people allow themselves to act in deviant ways. While this construct has shown promise as a factor underlying misbehavior among juveniles (e.g., Bandura, Barbaranaelli, Caprara & Pastorelli, 1996), and is growing in popularity in the social psychological literature on wrongdoing, it has yet to be integrated into mainstream business ethics research. Second, research has not tended to emphasize the interaction between the person and the situation as a cause of corruption (Loe et al., 2000). Organizational practices designed to promote productivity have come under scrutiny in recent years as cases of corruption in the popular literature have been tied to goal setting practices (e.g., overcharging in Sears’ automotive centers, Stevenson, 1992), and experimental research has begun to suggest that goal-setting may cause individual’s to engage in deception and other unethical behaviors (e.g., Schweitzer, Ordonez & Douma, 2004; Umphress, See, Barsky, Gogus, Ren & Coleman, 2005). In this paper, we will extend that literature as well, by suggesting that the manner in which goal-setting is conducted (extent to which individuals participate in the process) has implications for the extent to which failures in self-regulation though moral disengagement will lead to unethical behavior. Therefore, this manuscript is intended to contribute to the understanding of unethical behavior at work by (1) integrating the individual difference concept of moral disengagement into current business ethics theory, and (2) demonstrating how individuals’ moral disengagement may interact with the performance management prerogatives (i.e., allowing for participation in goal setting) at work to impact the perpetration of unethical behavior. To this end, the paper will unfold as follows. First, the nature of moral disengagement, and how it relates to unethical behavior at work is discussed, with a particular focus on how two mechanisms of moral disengagement are independently related to ethical behavior during the pursuit of performance goals. I then describe the first study in which is designed to develop a measure of moral disengagement and unethical behavior scales for use with working adults, and establish a relationship between moral disengagement and actual unethical behavior. Performance goal setting practices (i.e., participation) are linked to individuals’ willingness to engage in unethical behavior, and an argument is presented that participation may attenuate the effects of moral disengagement on the perpetration of unethical behavior. Finally, a second study

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designed to both extend the findings from study 1 to a field setting, and demonstrate the interactive relationship between moral disengagement and participative goal setting is descbed. Ethical Decision Making Models While numerous definitions of unethical behavior exist in the literature, for the purpose of the current manuscript, we rely on Jones’ (1991) broad conceptualization of unethical behavior as reflecting any action that is “either illegal or morally unacceptable to the larger community” (Jones, 1991, p. 367). Over the previous two decades, a number of frameworks have been proposed as models for understanding the reasoning or decision-making processes underlying moral (or immoral) behavior (e.g., Rest, 1986; Trevino, 1986). Jones’s (1991) issue-contingent model is often cited as a comprehensive synthesis model of ethical decision-making (e.g., Street, Douglas, Geiger, & Martinko, 2001), and has been used to guide a number of theoretical and empirical studies (see Loe, Ferrell, & Mansfield, 2000). Jones’s (1991) model provides a useful heuristic framework for understanding the processes individuals go through when deciding to engage in ethical behavior. However, the model is incomplete in the discussion of reasoning processes that occur when individuals decide to act unethically. To fill this void, we will draw on Bandura’s (1999) social cognitive theory of moral disengagement and Sykes and Matza’s (1957) neutralization theory. The foundation of Jones’s (1991) model lies in Rest’s (1986) multi-stage model, whereby individuals are argued to move through a series of sequentially ordered steps during the course of making a decision to act ethically or unethically (e.g., Jones, 1991). In the first step, the terms “ethical recognition” and “moral awareness” are often used interchangeably in reference to individuals’ recognition that their decision or action will harm or help others, and that they have some volition in acting or making a decisio n. Once a problem is recognized as moral, decision- makers enter the second step wherein they reason that acting morally is warranted and, therefore, resolve to place moral concerns above other concerns. This process is referred to as establishing moral or ethical intent. The steps (i.e., ethical recognition, ethical judgment, and ethical intent) in ethical decision-making scenarios act as a script, which, when activated, ultimately increase the probability of ethical behavior. In addition, this decision-making script functions such that the activation of a prior step usually precedes the activation of future steps. Given that most research to date has focused on the ethical recognition component (e.g., Loe et al., 2000), we feel that focusing on additional cognitive processes that come into play, such as disengaging internal moral controls, is an important agenda for business ethics research. This is where we turn now. Moral Disengagement and the Use of Rationalizations This manuscript presupposes that most wrongdoers in organizations are psychologically “normal,” in the sense that they see themselves as fair, moral, and honest (Allison, Messick, & Goethals, 1989). Given that individuals typically imagine themselves as moral people, one would expect that, if a moral issue were recognized, then individuals would always attempt to act ethically to maintain a consonant self-image. However, this reaction is often not the case, as ethical recognition is often a necessary but insufficient condition for ethical behavior. A further process is also required, whereby individuals judge their behavior as acceptable and form an intention to behave in a given way (e.g., Bersoff, 2001). In attempting to explain deviant behavior among juvenile delinquents, Sykes and Matza (1957) asserted that most delinquents possess conventional values and are able to commit delinquent acts by subscribing to certain rationalizations that define such acts as situationally appropriate. Similarly, Bandura (1999) suggested, “the self-regulatory mechanisms governing moral conduct do not come into play unless they are activated, and that there are many psychosocial maneuvers by which moral self-sanctions are selectively disengaged from inhumane 3 13447

conduct” (p. 193). In other words, moral disengagement is predicated on the use of “psychological maneuvers,” which are consistent with the rationalizations described by Sykes and Matza (1957). Below, we will briefly discuss two rationalizations (i.e., moral justification and displacement of responsibility), and review evidence suggesting that rationalizations disrupt moral behavior by providing justification to morally disengage, and therefore, to act in an unethical manner. Although people may use a variety of rationalizations (see Ashforth & Anand, 2004 for a review), moral justification and displacement of responsibility are focused on here as both have been widely researched and have the clearest links to goal directed work behavior. Moral justification. Rationalizations facilitate moral disengagement by articulating reasons why the specific unethical acts are justifiable or excusable exceptions to the general normative rules (e.g., Ashforth & Anand, 2004). The first rationalization, moral justification, involves cognitive reconstruction of the behavior itself. That is, people often do not intend to engage in unethical behavior until they have justified to themselves the morality of their actions (e.g., Bandura, 1999). In this process, unethical behavior is made personally and socially acceptable by portraying it in the service of valued or moral purposes. This concept is similar to Sykes and Matza’s (1957) idea that people neutralize their wrongdoing by appealing to higher loyalties. That is, people construe that ethical norms have to be sacrificed for more important causes. Experimentally, Bandura et al. (1996) found that “moral reconstrual of harmful conduct by linking it to worthy purposes” (p. 364) was the most powerful predictor of detrimental activities (e.g., violence, lying). To the extent that individuals access moral justifications for their behavior, they are more likely to engage in behavior that would otherwise be considered normatively harmful or unethical. Hypothesis 1: Moral disengagement through moral justification is positively related to engagement in unethical behavior. Displacement of responsibility. A second commonly identified rationalization is displacement of responsibility (e.g., Ashforth & Anand, 2004). Researchers argue that people are most likely to form ethical intentions when they acknowledge that they have an agentive role in the ethical behavior to which they engage (e.g., Bandura, 1999). Thus, people may disengage their moral controls if they deny responsibility of their actions due to circumstances beyond their control. The circumstances may include such things as management orders, peer pressure, dire financial straits, existing precedent, that everyone else is doing it, that they play a small part, and so on (e.g., Greenberg, 1998). For example, employees of Beech-Nut, a company that sold a purely chemical cocktail advertised as baby formula to the public, reported that other companies were doing the same thing, and that their company was just following the pack (Welles, 1988). In essence, Beech-Nut employees denied their own culpability in the decision by suggesting that it was due to forces beyond their control. Empirical studies have demonstrated that, in fact, displacement of responsibility can interfere with individual’s intention to act ethically. For instance, in a laboratory study, Bersoff (2001) found that people were likely to take an “accidental” overpayment by an experimenter, unless the displacement of responsibility neutralization was made unavailable. This neutralization was made unavailable by asking subjects explicitly if they had received correct payment. Thus, to the extent that individuals displace responsibility for their actions away from themselves, they will be more likely to engage in questionable behavior at work. Hypothesis 2: Moral disengagement though displacement of responsibility is positively related to engagement in unethical behavior. Thus far, we have reviewed theory and research suggesting that unethical behavior may be the result of decision-making processes that involves rationalizing away the need to act 4 13447

morally. Next, we describe a managerial simulation study designed to develop a measure of moral disengagement and test the previous hypotheses. Study 1 Method Participants One hundred and sixty-four undergraduates were recruited from business (N=65) and psychology classes (N=99) at a private, Southern U.S. university. The sample was 61% female, with an average age of 19.2 years. While the stimulus materials used in the current study required individuals to assume the role of a business person, previous studies using the current in-basket exercise (e.g., Trevino & Youngblood, 1991) and similar exercises (e.g., Umphress, 2003) used psychology students successfully. Stimulus Material and Measures Participants were asked to play the role of “Pat Mason,” the National Sales Manager of Micrometer Electronics Inc., an electronics components manufacturing firm. First, participants were given background information in order to facilitate their role-playing exercise. Next, participants were presented with the first of three sections. The first section of the in-basket contained 16 items, including an organization chart, a company newsletter, and 14 letters, memos, or phone messages. Two of these decisions (placed 14th and 16th among the items) were ethical in nature. The other 11 decisions were included to mask the ethics focus of the study. Subjects were given 45 minutes to read through the in-basket and make decisions using a response form to record decisions after each message. Unethical Behavior. Unethical behavior was measured through two decision opportunities. The first decision was taken directly from the in-basket developed by Trevino and Youngblood (1990). In the first ethical decision opportunity, the parts decision, subjects responded to a memo from William Wyley, Vice-President of Production, in which he stated that he had decided to change the material used in a particular product component to save on production costs. He advised that customers should not be informed despite potential problems. Mason was informed that sales revenues would likely suffer a $500,000 loss if customers were informed of the change. Participants decided what to do, if anything, in response. The second ethical decision situation was adapted from an in-basket developed by Brief et al. (1996). Mason was asked to decide whether or not he/she wished to recognize the impending sales of a wiring system on this quarter’s financial statement even though the sale had not been completed. For each decision, participants were provided a response form that listed a number of options and instructed to choose one. The available options were coded a priori as ethical or unethical (an equivalent number of each) on the basis of criteria developed by Trevino and Youngblood (1991). In the parts situation, a decision not to inform customers was coded as unethical. In the financial reporting decision, participants could choose either to record the $750,000 gain on the current quarter, or wait for the sale to be completed before reporting the gain. A decision to record the gain in the current quarter was unethical because it entailed dishonestly reporting the company’s current financial situation (i.e., recording the sale of a wiring system before the sale actually occurred). Thus, each participant received a score of 0, 1, or 2, indicating the number of unethical decisions made. Unethical behavior scale/DV check. We checked the unethical behavior dependent measure to ensure that individuals were aware of the behaviors to which they had engaged (i.e., independent of judging the ethicality of the behaviors). That is, one manner of arguing for the validity of a measure is to show convergence in findings across operational definitions (e.g., Cook & Campbell, 1979). Specifically, a stronger case could be made that the decisions to 5 13447

deceive customers about new parts (i.e., the parts decision) and to fraudulently report financial information (i.e., the financial reporting decision) actually represent unethical behavior if a correspondence exists between making these decisions and a separate operational definition of unethical behavior (e.g., self-reported behavior). Therefore, participants were given an unethical behavior scale which included 12 items measured on a one to seven scale (where 1 = Never and 7 = More Than Ten Times) scale, and indicated how often they had performed each behavior while in the role of Pat Mason. Again, a significant correspondence between the number of unethical decisions made in the course of the simulation and the unethical behavior scale would indicate that the DV in the current study was, in fact, capturing unethical behavior. Twelve unethical behavior items were embedded among 22 filler items that were obtained from Brief and Motowildo’s (1986) description of prosocial organizational behaviors. The unethical behavior items were intended to assess deceptive work practices such as fraudulent financial reporting and misrepresentation of products and/or services. Items reflecting these facets of unethical behavior dimensions were chosen for two reasons. First, the items gauge dimensions of unethical behavior consistent with the operational definition of unethical behavior dependent variables in the current study. And second, deceptive work practices were discussed in the literature as a class of unethical behaviors that were particularly relevant to people’s pursuit of performance goals (e.g., Schweitzer, Ordonez, & Douma, 2004). Therefore, the same unethical behavior scale was used in Study 2 (discussed below) as a dependent measure. This method allowed us to maintain similarity between the two studies, which is important for the comparability of results, as well as to validate an instrument before taking it into the field. Five of the 12 unethical behavior items were taken from an unethical behavior scale originally developed and used by Umphress (2003). Examples of these unethical behaviors were “conceal information from the public that could be damaging to your organization” and “withhold negative information about your company’s product or services to customers and clients.” For use in the current study, the items were reworded so the unethical behavior would be more obviously personally beneficial. For instance, “damaging to your organizations” was replaced with “damaging to your performance on the job.” The remaining 7 items were taken from interviews with a Senior Vice President of Sales of a large international investment banking firm, and the Vice President of Investor Relations and Business Strategy of a large southwestern utility. In the current study, the unethical behavior scale showed markedly high internal consistency (a = .90). To check for dimensionality in the data, a principle axis factor analysis with varimax rotation revealed a dual factor solution, with the first factor accounting for 52.81% of the variance (eigenvalue = 6.24), and a second factor accounting for 12.81% of the variance (eigenvalue = 1.54). Despite the results of the factor analysis, several arguments can be made for conceptualizing the unethical behavior scale as a unitary factor. First, the two sub-factors are highly correlated (r = .60, or .69 dissattenuated for measurement error), suggesting that the two factors may be redundant. Second, the first factor extracted in the factor analysis explained greater than 52% of the variance, and a visual assessment of the scree plot shows a relatively small decrease after the first factor is explained. Third, previous studies using the same (e.g., Umphress, 2003) and similar unethical behavior scales (e.g., Smith-Crowe, Umphress, Brief, Tenbrunsel, & Chan, 2003) have used a single factor to represent unethical behavior. And, finally, within the current manuscript, no a priori rational was provided for why separate factors should function differently from one another. Since the unethical behavior scale in Study 1 is merely a check of the behavioral dependent variable, the level of specificity here may seem excessive. However, given that the 6 13447

same unethical behavior scale is used as the primary dependent variable in study 2, assessing the psychometric properties of the scale in the current study is critical. Given the justifications provided above for considering unethical behavior as a general construct, and given the similarly in the relationships between each subfactor and all study variables (thus providing redundant information), the unethical behavior scale will be assumed to represent a single construct. This issue will be returned to in Study 2. The unethical behavior scale appeared to have validity as a measure of unethical behavior, as the number of unethical decisions made by participants was significantly correlated with responses to the unethical behavior scale (r = .43, p < .01). The fact that individuals who made unethical decisions in the simulation received higher scores on the unethical behavior scale indicated that people were aware of the behaviors they engaged in, even if they did not recognize the ethicality of their behaviors. This implies that the unethical behavior scale could be acceptable to use in a non-experimental design as well (such as Study 2 described below), given that the scale appeared to represent recall of actual behavior. Moral Disengagement. Using a priori theoretical categories of rationalizations, Bandura et al. (1996) developed a moral disengagement scale that measured the propensity to use rationalizations for violence and delinquency among schoolchildren. Items in the original measure tapped eight mechanisms (e.g., rationalizations) of moral disengagement: (a) readiness to construe injurious conduct as serving righteous purposes, (b) rendering harmful activities benign by advantageous comparison, (c) using morally neutral language to describe harmful activities, (d) disowning responsibility for harmful effects by displacement or (e) diffusion of responsibility, (f) minimizing the harmful effects of one's detrimental conduct, (g) devaluing those who are maltreated, and (h) attributing blame to them (e.g., Bandura, 1999; Bandura et al., 1996). To cite some examples, “If people are careless where they leave things it is their own fault if they get stolen” was one of the items measuring attribution of blame to the victims. The item “Kids cannot be blamed for misbehaving if their friends pressured them to do it” measured displacement of responsibility. “Some people deserve to be treated like animals” measured proclivity for dehumanization (Bandura et al., 1996). For the purposes of the current study, a modified version of the moral-disengagement scale was created. The current scale includes items exclusively pertaining to the rationalizations discussed in the introduction (i.e., moral justifications and displacement or diffusion of responsibility). In addition, the detrimental activities and social context embedded in each item were modified to be relevant for working adults and to refer to activities in which the individual could have engaged during the course of the in-basket. That is, while the original items referred to detrimental activities such as physically injurious conduct, verbal abuse, deception, and theft, the current items refer specifically to deception. Similarly, the social context in the original scale was modified from referring to educational, familial, community, and peer relations to refer to organizational and supervisory relations. For example, an original moral justification item stated “It is alright to fight to protect your friends,” and the modified item read: “It is alright to stretch the truth to protect your company.” An original displacement of responsibility item stated “Kids cannot be blamed for misbehaving if their friends pressured them to do it,” and was modified to state “Employees cannot be blamed for wrongdoing if they feel that their boss pressured them to do it.” The moral disengagement scale consisted of 13 items rated on a 7-point Likert-type scale (1 = Strongly Disagree to 7 = Strongly Agree) indicating the degree to which participants had the following thoughts while in the role of Pat Mason. As discussed above, moral disengagement was conceptualized to be a construct composed of rationalizations that allow an individual to 7 13447

disengage their internal moral controls by (a) justifying unethical behavior in moral terms (i.e., moral justification) and (b) displacing responsibility for the behavior to an external agent (i.e., displacement of responsibility). To assess factor structure, a principle axis factor analysis with varimax rotation was conducted on the data. The first step in a factor analysis, once the initial eigenvalues are extracted, is to determine which factors should be retained for rotation. Selecting the correct number of factors to retain requires setting criteria for retention based on the eigenvalues generated in the exploratory factor analysis. The approach used to select factors for rotation was parallel analysis, which estimates what eigenvalues one would expect by chance alone given a specified number of items and participants (see Kaufman & Dunlap, 2000). Some researchers have argued that parallel analysis offers a more practical solution than Kaiser’s rule, as the number of items in a given scale influences the likelihood that an eigenvalue will exceed 1 (Bacon, 2001). The parallel analysis indicated that, given 13 items and 164 participants, the first factor should have an eigenvalue over 1.50, and the second factor should have an eigenvalue over 1.37, and the third factor should have an eigenvalue over 1.27. Given this criteria, the factor analysis extracted and rotated two factors with eigenvalues of 4.06 and 1.67 respectively. In addition to the parallel analysis, the scree plot was visually inspected to determine if a third factor was present. Indeed, the remaining 11 factors that were extracted appeared to form a relatively discontinuous group (i.e., scree) from the first two factors. The rotated factor loadings are reproduced in Table 1, and show a pattern of loadings largely consistent with the original theoretical rational for the dimensions of moral disengagement. For instance, the four items (i.e., items 1, 8, 10, & 14) written to reflect moral justification (e.g., “It is alright to exaggerate the truth to keep your company out of trouble,” item 14) loaded on a single factor with high internal consistency (alpha = .82). In addition, the items written to reflect displacement of responsibility (e.g., “Employees are not at fault for wrongdoing if their boss puts too much pressure on them to perform at work,” item 18) loaded on a second factor, with the exception of items 2, 7, and 16 which did not load on either factor. Two items (items 11 and 13) displayed cross-loadings on the first factor; however, the cross-loadings were substantially lower than the loading on the second factor. Therefore, a six item scale measuring displacement of responsibility was created using items 4, 5, 11, 13, 15, and 18, which had an internal consistency estimate of .71. Results Descriptive statistics and intercorrelations are presented in Table 2. As predicted, both moral disengagement through moral justification and displacement of responsibility were significantly related to unethical behavior. However, the magnitude of the relationships was quite different, with moral justification strongly related (r = .34, p < .01) and displacement of responsibility only weakly related (r = .15, p < .05) to unethical behavior. When both variables were simultaneously entered into a regression equation predicting unethical behavior, the effect of moral justification on unethical behavior changed very little (ß = .33, t = 4.12, p <.01), while the effect of displacement of responsibility dropped to near zero (ß = .01, t = .12, ns). Thus, the sub-dimensions do not explain independent variance, as moral justification appears to account for virtually all of the variability in unethical behavior. The significance of this finding will be returned to as a discussion point in the following section. Discussion Consistent with previous theorizing on the subject (e.g., Bandura, 1999), moral disengagement through moral justification and displacement of responsibility was significantly related to individuals’ propensity to make unethical decisions. We believe that this represents a 8 13447

contribution to the ethics literature, albeit a minor one. That is, while moral disengagement through the use of rationalizations is implicitly (e.g., Rest, 1987) or explicitly (e.g., Bandura et al., 1996; Sykes & Matza, 1957) central to most model of ethical decision-making, organizational researchers have yet to examine the construct empirically. Therefore, this paper may provide some important findings regarding the nature of moral disengagement in organizational behavior. First, the factor structure of the moral disengagement scale corresponded to the theoretical dimensions specified in the original scale developed by Bandura et al. (1996). That is, items tapping moral justification, or rationalizations that reconstrue misbehavior as moral, tended to cluster together, and items related to displacement of responsibility tended to cluster together. Second, we suggested that moral disengagement may represent a unitary construct, with moral justification and displacement of responsibility as alternate mechanisms through which this may take place. However, given the results of Study 1, treating moral disengagement as a general factor does not appear to be appropriate. Instead, moral disengagement though moral justification and moral disengagement though displacement of responsibility, appear to operate differently, and should be assessed independently. This is, consistent with studies suggesting that individuals seek to appear “moral” (Batson, Thompson, & Seuferling, 1997), justifying the morality of a harmful or deceitful act seems to be substantially more important, in terms of releasing an individual to engage in the behavior, than simply appearing “not responsible.” Given that we have demonstrated a link between moral disengagement and unethical behavior in the simulation study described above, a number of important questions must be addressed. First, to what extent do the results generalize to a working population? As with all simulation based studies using college students, the issues of external validity is an important one. Second, what are the boundary conditions for the relationship? Specifically, what contextual factors may limit the availability of rationalizations, or attenuate the force of peoples’ disengagement on their tendency to engage in unethical behavior at work? In the next section, we attempt to address both of theses questions with a second field study. Indeed, we extend our reasoning to the performance management domain, where some preliminary evidence has suggested that goal-setting and reward initiatives may have an impact on ethical work behavior (Schweitzer et al., 2004). Here we argue that the way in which goals are set (i.e., the extent to which they are set participatively) may have an impact on ethical behavior directly, and also may attenuate the relationship between moral disengagement and unethical behavior. Study 2 Worker participation in decision-making, such as the setting of organizational or work related task goals, has historically been an important variable in the organizational behavior and human resource management literatures. The particular method of goal-setting that has received the majority of research interest is whether goals are set in a top-down or “autocratic” manner, or made with subordinate participation (e.g., Erez, Earley, & Hulin, 1985; Latham, Erez, & Locke, 1988; Latham & Marshall, 1982; Latham, Steele, & Saari, 1982; Latham, Winters, & Locke, 1994; Leana, Locke, & Schweiger, 1990). Participation is defined as joint decision-making (Locke & Schweiger, 1979) or as influence-sharing between hierarchical superiors and their subordinates (e.g., Mitchell, 1973). Theoretically, researchers have argued that allowing subordinates to participate in setting goals affects performance by enhancing employees’ commitment to, and satisfaction with, the performance goals (e.g., Cotton, Vollrath, Froggartt, & Lengnick-Hall, 1988; Dachler & Wilpert, 1978; Miller & Monge, 1986). However, researchers continue to debate the utility of participative decision making, with several researchers suggesting that no clear link has been established between worker participation and such organizationally relevant criteria as employee commitment (to the goal or to the organization), 9 13447

persistence, or productivity (e.g., Strauss, 1982; Wagner, 1994). If this were true, than involving workers in management may be relegated to a social or charitable objective a firm may wish to pursue, rather than an important practice for organizational functioning. This manuscript takes a different angle, and suggests that organizations may consider allowing employees to participate in setting goals as a means of reducing the likelihood of unethical behavior without abandoning a proven motivation tool of setting performance goals. One problematic issue with setting performance goals at work is that setting a goal focuses individuals on achieving that goal, and work related behavio rs are subsequently evaluated by the goal recipient based on this criteria (i.e., that the behavior will help achieve the goal), and other criteria (e.g., ethicality) are disregarded. However, the likelihood that individuals will pay attention to ethical considerations may be affected by whether they are involved in the decision- making process. Specifically, when a person is simply assigned a goal, evaluation of the available behavioral options is focused primarily on goal achievement. That is, since the goal has already been set, all subsequent consideration of behaviors is made through the lens of the preexisting- goal. However, when an individual is involved in setting the goal, the consideration of behavioral options likely begins before the goal is set, and therefore may include other aspects besides effectiveness for goal attainment. Consistent with Latham and Steele’s (1983) assertion that participation in decision-making can lead to the development of strategies to accomplish the task, involvement in the decision-making process allows individuals to think more broadly and strategically about behavioral options before an objective is specified. This additional consideration, specifically towards ethical issues, would otherwise have been ignored or blocked out if the performance goal was simply assigned. Therefore, individuals who participate in goal- setting are more likely than those who are assigned performance goals to recognize the ethicality of their behaviors, thereby decreasing the likelihood that unethical behavior will occur. At least two studies can be considered supportive of this position. First, Latham et al. (1994) found that allowing for participation in goal-setting had the function of increasing the amount of task strategizing in which participants engaged. In describing how the Latham et al. study was developed, Latham (2001) recounts that “I had foolishly forgotten the final conclusion…that participation can increase understanding of what is required to perform the task. The participants in the [participation] condition asked far more questions than did those in the assigned condition” (p. 5). Consistently, an increased understanding or consideration of the behaviors required by a performance goal is likely to facilitate the recognition that some behaviors have a moral flavor. Thus, instead of the tunnel vision produced by assigned goal- setting, participation can encourage active evaluation of the process by which the goal may be accomplished, and thereby enhance ethical recognition. Secondly, Ludwig and Geller (1997), in a fascinating study on injury control among pizza delivery drivers, found that participative goal-setting produced increases in behaviors targeted by the intervention (e.g., turn signal and safety belt use), as well as increases in behaviors not directly targeted by the goal-setting (e.g., intersection stopping). The authors concluded that participative goal-setting can function to activate internal or personal norms governing behavior, thereby activating behaviors that are functionally related to goal achievement, even if not specified by the goal. Consistently, the activation of internal or personal norms can have an additional effect of enhanced ethical consideration of behaviors not specified by a performance goal. Taken together, the Latham et al. (1994) and Ludwig and Geller (1997) suggest that participation may increase the ethical recognition of employees exposed to performance goal- setting.

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Hypothesis 3: Participation in goal setting will be negative related to unethical behavior, such that increased opportunity to participate in setting task goals will lead to less unethical behavior on the part of the goal recipient. Participation and Moral Disengagement In addition to the impact of participation on ethical behavior at work, participative goal- setting may have a substantive effect on the relationship between moral disengagement and unethical behavior. This reasoning is predicated on two arguments. First, participation in the goal setting process may interfere with individuals’ disengagement of their internal moral controls by limiting the availability/usefulness of rationalizations for wrongdoing. In particular, moral disengagement is limited through participation by increasing an individual’s accountability for their actions. That is, assigning performance goals for employees may be perceived as an implicit order to act in an unethical manner, thus displacing the responsibility from the individual to the superior or organization. Simon (1945) asserted that “‘authority’ may be defined as the power to make decision which guides the actions of another” (p. 125). The superior exercises his or her authority by framing and transmitting decisions with the expectation that the subordinate will accept the decision. However, Simon noted that the implementation of authority requires no a priori command. Instead, the “rule of anticipated reactions” holds, whereby subordinates may and are expected to ask themselves “what would my superior wish me to do in these circumstances” (e.g., Friedrich, 1937). An individual on the receiving end of an assigned performance goal may feel that he/she was ordered to engage in immoral behavior, even if no explicit order was given. If individuals feel “ordered,” they may simply displace the responsibility for their actions on their superior, thus freeing them to act in whatever way they see fit. In contrast, when a goal is participatively set, the employee takes on some amount of accountability for the decision, and can no longer simply attribute the goal to their boss. By extension, the responsibility for the actions employees take to achieve their performance goals cannot be easily displaced to superiors, given that the employee was partially responsible for the level and/or type of performance goal set. Second, as discussed above, participation may have the effect of increased task strategizing (e.g., Latham et al., 1994). The increased use of strategizing with regard to behavioral options to achieve the goal may attenuate the impact of rationalizations such as moral justification and displacement of responsibility on behavior. Specifically, to the extent that an individual derives behavioral options through being involved in the decision making process, they may use less personal discretion in deciding what behaviors to engage in to achieve their performance goal. Thus, while an individual may rationalize wrongdoing, the previously participatively derived (and presumably legitimate) behavioral strategies may override an individual’s likelihood to choose an illegitimate course of action. Given the previous arguments, we propose the following two hypotheses: Hypothesis 4a: Participation in goal setting and moral justification will interact to predict Unethical Behavior, such that participation will attenuate the relationship between moral justification and unethical behavior. Hypothesis 4b: Participation in goal setting and displacement of responsibility will interact to predict Unethical Behavior, such that participation will attenuate the relationship between displacement of responsibility and unethical behavior. Method Sample For the current study, 111 participants were recruited from two sources: (a) professional MBA (PMBA) and executive MBA (EMBA) classes at a private, Southern U.S. university, and 11 13447

(b) a professional association of purchasing managers. One requirement for inclusion in this study was that individuals were employed at the time of the survey administration. Of the 111 initial participants, 83 reported that they were currently employed. One individual reported only working 3 hours per week, and therefore, was dropped from analysis. The remainder of the participants worked at least 15 hours per week, with an average of 44.4 hours/week. Individuals were told specifically that their participation was completely voluntary. Given the nature of the sample for the current study, participants held a variety of different jobs. The sample was primarily male (64%), with 42% identifying themselves as supervisors or managers, and 6 individuals identifying themselves as business owners. In addition, all responses were confidential and only utilized for research purposes. Measures Participation in Goal-setting. The participation in goal-setting scale (hereafter referred to as the participation scale) was designed to assess the extent to which people participated in setting their performance goals at work. The items for the goal-setting method scale were taken from the GSQ (Locke & Latham, 1984) and contained items related to choice of goals (i.e., item 2: “My boss lets me have some say in deciding what my performance objectives will be”; and item 3: “I do not have any input in deciding what my performance goals will be [reverse coded]”), involvement or voice in the process of setting goals (i.e., “My boss works with me to come up with my performance goals”; and item 5: “My boss tells me what my performance objectives are without consulting me [reverse coded]”). The measurement properties of the scale were assessed in the current study, and indicated that the scale was highly reliable (a = .83) and a single factor solution was extracted from a principle axis exploratory factor analysis (eigenvalue = 3.29) explaining 65.87% of the variance. A second factor had an eigenvalue of only 0.61, far below the second factor eigenvalue of 1.09 estimated by parallel analysis. Consequently, all 5 items were retained and averaged to form a scale where higher scores indicated greater participation in goal-setting. Moral Disengagement. The moral disengagement scale used in the current study is described in detail in Study 1. In the current study, the instructions were altered such that participants were asked to report the extent to which they experienced a list of thoughts while in their current job. Consistent with Study 1, moral disengagement items were subjected to a principle axis exploratory factor analysis with varimax rotation to assess factor structure. Initial extraction showed four factors with eigenvalues greater than 1, however only two factors appeared visually distinct from the other factors though inspection of a scree plot, and exceeded the criteria for retention and rotation derived from parallel analysis. In addition, when all four factors were rotated, the third and fourth factor did not explain meaningful variance or provide interpretable factor loadings. Thus, two factors were retained and rotated, with the first factor explaining 35% of the variance (eigenvalue = 4.59) and the second factor explaining 12% of the variance (eigenvalue = 1.57) in the item responses. While the rotated factor loadings were not identical to the loadings in Study 1, the pattern of loadings was largely consistent, with a factor related to moral justification and a factor related to displacement of responsibility present. Given the low sample size in the current study, and the resulting instability in factor loadings, one would not expect an exact reproduction of factor structure. Therefore, given the similar pattern of results, and to remain consistent across studies, a 4 item moral justification subscale (a = .72) and a 6 item displacement of responsibility subscale (a = .77) was created using the items specified in Study 1. Taken together with the results of Study 1, a creating a scale score to reflect a general moral disengagement factor did not appear appropriate. Therefore, moral disengagement is conceptualized for the remainder of this 12 13447

study as operating at the level of the mechanism by which an individual disengages. That is, the moral disengagement through moral justification and moral disengagement through displacement of responsibility appear to be the relevant conceptual and operational variables. Unethical Behavior. The same 12-item unethical behavior scale used as a dependent measure check in Study 1 was used as the DV in Study 2. Participants were asked to indicate on a scale from one to seven (where 1 = Never and 7 = More Than Ten Times) how often they had performed a list of behaviors since they began their current job. Consistent with Study 1 results, the scale displayed acceptable internal consistency (a = .78), and a single factor solution using principle axis factor analysis. Results Descriptive statistics and correlations are reported in Table 2. Hypotheses 1 and 2 were tested by examining the bivariate relationship between the mechanisms of moral disengagement (i.e., moral justification and displacement of responsibility) and unethical behavior. As evident in Table 2, both mechanisms were significantly related to unethical behavior, although moral justification showed a slightly stronger effect (r = .36, p < .01) than displacement of responsibility (r = .29, p < .05). However, consistent with Study 1, when unethical behavior was regressed on moral justification and displacement of responsibility together, the independent effects were drastically different. That is, while moral justification remained a strong predictor of reported unethical behavior (ß = .29, p<.05), the independent effect of displacement of were responsibility on unethical behavior was substantially diminished (ß = .11, ns). Therefore, once again, when individuals disengage their moral and social controls through moral justifications, the use of alternate rationalizations to morally disengage (i.e., displace responsibility to one’s supervisor) does not appear to elicit more unethical behavior. Support for the third hypothesis was inferred by examined the bivariate relationship between the participation scale and the unethical behavior scale. This analysis was conducted only the sub-sample of participants who were exposed goal-setting at work. The null hypothesis was rejected, as a significant correlation (r = -.34, p < .05) was observed between paticipation and unethical behavior, indicating that individuals who responded more affirmatively to items asking if they were allowed to participate in setting performance goals were less likely to report engaging in unethical behaviors at work. To test the fourth hypotheses, a moderated regression analysis (e.g., Cohen & Cohen, 1983) was conducted to assess whether the magnitude of the relationship between moral disengagement and unethical behavior varied across levels of participation. Moderated regression analysis is conducted by comparing a reduced regression model composed of an equation regressing the dependent variable (i.e., unethical behavior) on both the independent variables (i.e., moral justification and displacement of responsibility respectively) and the moderator (i.e., participation), with a complete model that includes the independent and moderator variables and a cross-product term representing the interaction of IV and the moderator. As shown in Table 3, participation significantly moderated the moral justification ? unethical behavior relationship, but did not moderate the displacement of responsibility ? unethical behavior relationship. Therefore, hypothesis 4a was supported, while hypothesis 4b was not. To elucidate the significant findings, a plot of the significant interaction is presented in Figure 1. Discussion The results from Study 2 replicate the findings from study 1 to a working field sample, and extend the reasoning to incorporate the influence of contextual factors as well. As predicted, both moral justification and displacement of responsibility were significant predictors of unethical behavior, although once again displacement of responsibility does not appear to add much additional information. In addition, participation in goal-setting was shown to decrease the 13 13447

likelihood of unethical behavior, which represents the first such finding in the organizational literature. Perhaps most interesting, while moral justifications tended to increase in the reported incidences of unethical behavior, this was only true when employees did not feel that they had the opportunity to participate in setting their performance goals at work. As such, participation may have value as both a predictor and buffer for individuals to act ethically at work. The second study was not without it’s limitations as well. First, while cross-sectional data does not provide adequate control for causal or directional statements, the link between moral disengagement and reported unethical behavior is provocative. In the general discussion, we will return to this point, but for now it is worth recognizing that mechanisms for moral disengagement and unethical behavior may have a reciprocal relationship. That is, while rationalizing wrongdoing may make unethical behavior more likely, engaging in unethical behavior may entice individuals to justify their actions to make their behavior more palatable (e.g., Bandura, 1999). As long as unethical behavior is conducted without repercussions, this cycle may continue unabated. Second, the measurement of unethical behavior was generic and, therefore, may not have applied equally across occupations. For example, an unethical behavior measure for car salespeople may look different than an unethical behavior measure for project managers, given that each group has more or less opportunity to engage in a given set of behaviors. One potential solution would be to study a single occupation and develop an idiosyncratic measure composed of unethical behaviors specific to that occupation. Alternatively, a measure of unethical behavior based on a well developed construal of the unethical behavior construct would have much greater utility. Unfortunately, the organizational and psychological literatures lack even a generally accepted taxonomic structure for domains of unethical behavior. While Warren (2003) and other researchers have attempted to specify the domains of employee deviance, unethical behavior remains a rather amorphous construct, embodying a variety of socially unacceptable behaviors. However, the consistency in the findings across studies is at least encouraging that the measures tapped the appropriate constructs. General Discussion The results regarding the mechanisms moral disengagement are provocative for future research, both as in terms of conceptualizing the variables and understanding how disengaging one’s moral controls may influence one’s propensity to act unethically. The findings related to the differential impact of moral disengagement facets on unethical beahvior has important implications for understanding why (a) an individual might engage in an egregious act, and (b) where an organization seeking to reduce such acts may target an intervention. For instance, as the United States is stunned by images of American soldiers brutalizing Iraqi prisoners (e.g., Glanz, 2004), many question whether the soldiers engaged in their criminal behavior because they felt that their superiors were ultimately responsible (although they were apparently not given specific orders to abuse the prisoners) or because they felt that their brutality had a just and moral rational (i.e., derive information to save American lives). If the former is the case, then investigators should look to a breakdown in accountability in the chain of military command. However, if the latter is the case, as this dissertation would suggest, than one must look to the ideological climate that would allow for such acts to be morally justified (i.e., leaders of the organization making clear that any action that saves American lives is morally justifiable). In addition, given that organizational researchers have shown that providing justifications for wrongdoing can influence other types of organizationally undesirable behaviors such as discriminatory behaviors (e.g., Brief et al., 2000), establishing a connection between rationalizations for moral disengagement and unethical conduct is a reasonable next step. Indeed, the availability of rationalizations may be amenable to change, thereby providing an avenue for 14 13447

combating unethical behavior at work. For example, moral justifications such as “If an employee needs to stretch the truth to do their job, they cannot be blamed for lying” (item 8) could be countered by executives who emphasize the priority of honest business dealing over increasing revenue. Finally, if rationalizations cannot be changed, at least the impact of moral disengagement on future behavior can be minimized. Consistent with the emerging trend in organizational research to study outcomes other than employee productivity and organizational effectiveness (see Griffin & O’Leary-Kelly, 2004 for a series of chapters dealing with the “dark side” or organizational behavior), we chose to study the effects of the widespread organizational practice of participative goal-setting through the lens of workplace ethics rather than the lens of firm profitability. As such, we further demonstrated that the method of managing performance through participatively setting goals may limit the effect of individuals’ rationalizations on their willingness to act unethically. Taken together, our findings suggest that individual reasoning and judgment are central to, but not solely responsible for, misbehavior in the workplace. While this paper may raise more questions than it answers, we see it as a step in the right direction. As widespread corporate and political corruption is uncovered on an almost daily basis, understanding the individual, contextual, and interactive predictors of unethical behavior at work has become, more than ever, an important agenda for organizational scientists.

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TABLE 1 Factor loadings for Moral Disengagement Scale

Item F1 F2

Moral Justification 14. It is alright to exaggerate the truth to keep your company out .80 of trouble. 10. If it helps you do your job, it is alright to deceive clients or .75 customers. 1. It is alright to stretch the truth to protect your company. .74 8. If an employee needs to stretch the truth to do their job, they .71 cannot be blamed for lying. Displacement of Responsibility 18. Employees are not at fault for wrongdoing if their boss puts .69 too much pressure on them to perform at work. 4. Employees cannot be blamed for wrongdoing if they feel that .64 their boss pressured them to do it. 11. If an employee perceives that his/her company wants him/her to do something unethical, it is unfair to blame the employee .31 .51 for doing it. 13. Employees cannot be blamed for exaggerating the truth when .34 .50 all other employees do it. 15. It is unfair to blame an employee who had only a small part in .45 the harm caused by a company’s actions. 5. If employees engage in unethical behavior at work, it is their .32 boss’s fault. 16. If employees are not going to be disciplined, they should not

be blamed for wrongdoing. 7. An employee who only suggests breaking rules should not be

blamed if other employees go ahead and do it. 2. An employee should not be blamed for the wrongdoing done on

behalf of the organization

Initial Eigenvalue Estimate 4.04 1.67

% of Variance Accounted For 31.09 12.87

Note: N = 164. Factor loadings less than |.30| are not shown.

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TABLE 2 Means, Standard Deviations and Intercorrelations of Variables Used in Study1 and Study 2

Mean Mean SD SD Variable 1 2 3 4 Study 1 Study 2 Study 1 Study 2

1. Unethical Behavior 0.62 1.49 0.69 0.67 (.78) - .34** .15*

2. Participation in a - 5.54 - 1.16 -.34* (.83) - - Goal-Setting [.82] 3. Moral Justification 2.74 2.24 1.17 0.95 .36** b -.14 a .44** (.72)

4. Displacement of b a b [.71] Responsibility 2.92 2.64 .93 1.04 .29* -.15 .63** (.77)

Note. Study 1 correlations are above the diagonal. N = 164 for all Study 1 correlations. Study 2 correlations are below the diagonal. N= 59 – 80 for all Study 2 correlations. Reliabilities for Study 1 are in brackets on the diagonal, reliabilities for Study 2 are in parentheses on the diagonal. a = correlations computed on N = 59; b = correlations computed on N = 80. * = p < .05; ** = p < .01.

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TABLE 3

Summary of Moderated Regression Analysis Predicting Unethical Behavior Variable ?R2 b SE Reduced Model .23** Participation .34** .08 Moral Justification -.29* .07 Complete Model .08** Participation .33** .07 Moral Justification -.33** .06 Participation X Moral -.31** .06 Justification

Reduced Model .24** Participation -.28* .07 Displacement of .36** .07 Responsibility Complete Model .04 Participation -.28* .06 Displacement of .32** .07 Responsibility Participation X Displacement of -.21 .05 Responsibility

Note. N = 59. Moderation is evidenced by significant change in R2 in the complete model, or a significant parameter estimate for the interaction term in the complete model. * p < .05; ** p < .01.

21 Moral Disengagement 22

FIGURE 1

Participation X Moral Justific

2.50

2.00

1.50

Participation high med low

Unethical Behavior 1.00

0.50

0.00 low med high Moral Justification ·