BE MORE SPECIFIC!: HOW A SPECIFIC RULE REDUCES
UNETHICAL BEHAVIOR OF AN EMPLOYEE.
Master thesis, MscHRM
University of Groningen, Faculty of Economics and Business
BE MORE SPECIFIC!: HOW A SPECIFIC RULE REDUCES
UNETHICAL BEHAVIOR OF AN EMPLOYEE.
ABSTRACT
Unethical behavior of employees could result in severe problems that are harmful for the organization. Recent scandals such as bribe and corruption at multinationals endorse the importance of ethics within organizations. Organizations try to prevent unethical behavior of employees by installing rules, policies and codes of ethics. This research examines if employees engage more in unethical behavior when they personally can gain a lot. We focus on how specific and general framed rules moderate the effect of personal gain on unethical behavior of employees. Unethical behavior, personal gain and rule framing are measured in an online questionnaire, amongst a sample of 92 employees of different organizations. A multiple regression analysis in PROCESS was used to examine the moderation effect of a specific rule. The results show that high or low personal gain has no effect on unethical behavior. The results do show a reducing direct effect of a specific rule (compared to a general rule or no rule) on unethical behavior of an employee.
BE MORE SPECIFIC!: HOW A SPECIFIC RULE REDUCES
UNETHICAL BEHAVIOR OF AN EMPLOYEE.
1. INTRODUCTION
Failures and accounting scandals at Enron and WorldCom, such as bribery, corruption, theft and fraud, highlight the importance of ethics to organizations and the potential problems of unethical behavior (Soltani, 2014; Carson, 2003). Organizations can be held responsible for the actions and behaviors of their employees, which resulted in a growing concern in business ethics over the last years (Adams, Tashchian & Shore, 2001). The importance of ethics is widespread amongst organizations around the world and 'ethics' is externally noticeable on organizations' websites, statements and incorporated in their strategies. Another reason for organizations to commit to ethics is that unethical behavior such as fraud could result in a fine for the organization, which can hurt the image and the financial position of the organization (Bishop, 2013).
As a reaction to the growing importance of ethical behavior for an organization, organizations implement compliance and ethics codes through training programs, legal compliance standards and special compliance officers (Treviño, den Nieuwenboer & Kish-Gephart, 2014; Weaver, 2004). Internally, organizations try to influence employees in making ethical decisions by providing clear guidelines such as ethics codes, rules and other policies (Terbrunsel & Smith-Crowe, 2009). These ethics codes and policies try to help prevent employees committing to unethical behavior, by guiding them what to do and what not to do and enhance ethical behavior (Treviño et al., 2014).
presence of a rule therefore becomes even more valuable. Previous research shows that the positive effect of rules on ethical behavior can be different when unethical behavior is influenced by other variables, such as an individual's incentives to behave unethically (Ford & Richardson, 1994). Carson (2003) endorses the importance of examining individual incentives, because employees behave more unethically when their self-interest if high and individuals can gain a lot when they engage in unethical behavior. If an employee is highly self-interested, schemes of payment and reward have a stronger effect to engage in unethical conduct, than when self-interest is low.
In order to stop and prevent this unethical behavior of employees, clear specific rules and guidelines regarding ethical behavior could be implemented (Carson, 2003). Rules exist in many different forms. In this research rules can be either specifically framed or generally framed. As a rule is specifically framed, the rule is enforceable and clear for an employee and there is less room to morally rationalize unethical behavior. As a rule is generally framed, the rule is less enforceable and less clear, because there is more room for an employee to morally rationalize unethical behavior. Formulating a rule either specifically or generally can therefore have advantages and disadvantages towards the moral rationalization of unethical behavior. Mulder, Jordan and Rink (2015) endorse the importance of how a rule is formulated, as a specific rule is preferable over a general rule and specific framed rules reduce the room for moral rationalization. This research focuses on how specific and general rules moderate the effect of personal gain on unethical behavior of employees. The conceptual model of this research can be found in figure 1. The research question for this study is:
"How does a specific rule moderates the effect of personal gain on unethical behavior of an employee?".
focuses on both. This research examines whether a rule influences the effect of personal gain on unethical behavior and whether in the presence of a specific rule, the effect of personal gain on unethical behavior is reduced. Previous research (Cleek & Leonard 1998; Ford & Richardson, 1994) examined whether self-interest influences unethical behavior by using scenario and manipulation methods. This research is different than the previous research on rules and unethical behavior, because a different type of method is used. In this study, the correlation and regression of and between the variables is measured, in order to formulate predictions and test the relationship. This research contributes also in a practical way, because the results give recommendations for organizations on how to formulate rules, in order to reduce unethical behavior of employees. The results of this research indicate that a specific rule is more preferable above a general rule in order to reduce unethical behavior of employees. An organization should therefore install specific rules in order to foster ethical behavior of employees and counteract unethical behavior.
2. THEORETICAL FRAMEWORK 2.1 Unethical behavior
Jones (1991) defines unethical behavior as a process of unethical decision making, in which an individual behaves either illegal or morally unacceptable to the larger community. This unethical behavior can have a harmful effect on others, either for the organization, other individuals, or society as a whole (Jones, 1991). Treviño, Weaver and Reynolds (2006) defined unethical behavior as behavior that is contrary with norms in society. Lewis (1985) conducted a more specific definition of unethical behavior of an employee within an organizational context and defined unethical behavior as wrongdoing in specific situations within an organization.
In this research, I follow the definition of Lewis (1985), in which unethical behavior of an employee is considered as wrongdoing in an organizational context. This unethical behavior of employees can involve all kinds of negative behavior, such as theft, sabotage and misrepresentation in financial reports, which can result in severe negative outcomes such as contractor scandals, insider trading and bribing (Kish-Gephart, Harrison & Treviño, 2010; Barsky, 2011). There are a lot of different definitions of unethical behavior (Lewis, 1985; Kish-Gephart, Harrison & Treviño, 2010; Treviño, Weaver and Reynolds 2006), which are used in a lot of different contexts. In this research I follow the definition of Lewis (1985), because this definition is based on wrongdoing in an organizational context and therefore, more applicable for this research than other, more general definitions.
2.2 Personal gain
is influenced by the outcome expectancies of an employee. The outcome expectancies of ethical decision-making can differ if punishment, rewards or incentives are involved and personal gain might be an important outcome expectancy. Firstly, I explain the concept and definition of personal gain and the influence of personal gain on unethical behavior. Secondly, I explain and discuss how general and specific rules may effect the relation of personal gain on unethical behavior.
Personal gain is defined as the expected value of financial gain that is the outcome of the product of the magnitude of the gain (Jones, 1991; Treviño & Youngblood, 1990). In this research, personal gain is defined as the personal enrichment of an employee and the personal incentive to engage in unethical behavior. Personal gain can be described as the personal gain an employee can receive, as personal gain is based on rewards and on wage (Deckop, Mangel & Cirka, 1999). Personal gain reflects to the incentive which an individual can personally establish in committing to a particular unethical behavior or request of a client, peer or boss by committing to fraud, bribe or lying (Gneezy et al., 2013; Hegarty & Sims, 1978; Kish-Gephart et al., 2010).
employees can withhold negative information about their performance, in order to misrepresent actual performance in trying to gain a promotion within the organization.
Jones (1991) did research on the underlying ethical decision-making process of employees in organizations and proposed an issue-contingent model, in which employees are sensitive for personal incentives in a decision-making process. Gneezy et al. (2013) also researched ethical decision-making of individuals within an experiment. The first participant was assigned with a number, that had been send to the second participant. Participants could gain more money when their number was higher. Within this study, Gneezy et al. (2013) measured the unethical behavior ‘lying’. Their results show that an individuals’ tendency to lie increases when the gain of that lie is higher. Hegarty and Sims (1978) did laboratory experiments amongst 120 students, which were involved in marketing decision-making with the possibility of kickback payments to purchasing agents. Their results show that extrinsic rewards for unethical behavior, such as monetary rewards or other personal gain, significantly increased unethical decision behavior.
2.3 Definition of rules
A way to counteract unethical behavior is to install rules and direct individuals in what they should do or should not do, in terms of ethical behavior (Lewis, 1985). Rules can be defined as the ethical infrastructure of an organization, in which policies and guidelines enhance ethical behavior of employees in organizations (Terbrunsel & Smith-Crowe 2009). An organization can therefore foster and influence ethical behavior of employees, by implementing policies and guidelines that positively influence employees' ethical behavior (Lewis, 1985).
In this research I define rules as guidelines on how to behave in an ethical manner, which are communicated by authorities, such as an organization or a government. As earlier discussed, rules are found in many different forms. Rules are most often expressed in codes of ethics, laws and policies (Michael, 2006; Sims, 2002). Rules occur in society as laws and policies for the main reason to shape social norms and thereby influence individuals' behavior (Cooter, 1998). Laws can prohibit unethical behavior of individuals such as theft, vandalism and physical abuse, by establishing social norms on how to behave (Sims, 2002). Cooter (1998) found that rules exist when a society or community agrees that individuals ought to behave in a particular way (social norms) and these norms actually affects what individuals do. On the other hand, rules can be a substitute for social norms and influence the behavior of individuals when clear social norms are missing (Tenbrunsel & Smith-Crowe, 2009).
(Weaver and Treviño, 1999). In setting and using rules, an organization can therefore foster an ethical working environment and reduce unethical behavior of employees.
2.4 Rule framing
In this research I will focus on the way rules are formulated within an organizational context, by defining rules into two main forms; general rules and specific rules. According Mulder et al. (2015) rules within an organization can be formulated and framed in either specific rules or general rules. Whereas specific formulated rules such as: 'Do not accept gifts from clients' and 'Do not take resources from the company home' are clear and enforceable but not extensive, general formulated rules such as: 'Do not engage in conflicting interests' are extensive, but not clear and enforceable (Mulder et al., 2015). This distinction between specifically and generally framed rules corresponds with research that examined the principles-based approaches versus rules-based approaches (Arjoon, 2006; Sama & Shoaf, 2005). In a rules-based approach, a clear, specific standard for ethical behavior is established, as in a principles-based approach, a broader general guideline is set.
and behaviors (Sama & Shoaf, 2005). Principles-based approaches can cover more situations and behaviors than rules-based approaches, but the limitation is that principles-based approaches are too broad in scope to cover specific behaviors of individuals (Arjoon, 2006).
Previous research of Mulder et al. (2015) suggests that the differences in formulation and the scope of a rule have different effects on ethical behavior. The specificity of a rule is therefore important to consider, because specific and general rules may have very different outcomes for ethical decision-making of employees, due to the room for moral rationalization (Weaver, 2004). Brown et al. (2011) describe moral rationalization as the mental maneuverings of an individual in the decision-making process of individuals, in which rationalization can enable individuals to reinterpret their unethical behavior as ethical. This rationalization process allows individuals to erect a psychological barrier, enabling them to justify their unethical behavior. Bandura et al. (1996) examined the role of moral rationalization in a study amongst students and found a positive relationship between reports of delinquent behavior and moral rationalization techniques, such as justification and displacement of responsibility. Moral rationalization can therefore have an increasing effect on unethical behavior, where individuals rationalize their behavior in order to justify their behavior.
(Mulder et al., 2015). When an organization installs a general rule, which tells employees not to engage in conflicts of interests, employees can reason that accepting a gift does not mean that they engage in conflicts of interests. When, on the other hand, an organization installs a specific rule, which tells employees to not accept gifts from clients, employees have less room to interpret the specific rule and therefore, there is less room to morally rationalize accepting the gift (Mulder et al., 2015). The studies of Mulder et al. (2015) show that specific framed rules reduce unethical behavior more than general rules do, because there is less room for moral rationalization. An employee will have more room for moral rationalization when there is a general rule, because general rules are not that clear and are not enforceable.
2.5 Influence of personal gain on unethical behavior may depend on rules
As previously described, personal gain can increase unethical behavior, but the main question in this research is if the relation between personal gain and unethical behavior is effected by rules. Despite all of the aforementioned interventions of organizations (rules, codes of ethics and policies) in order to prevent unethical behavior, Carson (2003) argues that employees remain sensitive for incentives, even in the presence of a rule. Hegarty and Sims (1979) found that in the existence of an organizational ethics policy, the influence of rewards and personal gain on unethical decision behaviors significantly reduced.
As general framed rules give more room for moral rationalization, an employee can morally rationalize his or her unethical behavior. An employee can therefore morally rationalize unethical behavior, especially if there is a lot to gain by showing the unethical behavior. General framed rules make the process for moral rationalization less difficult, because the rules have a more broad scope and there is more room to argue around it (Hegarty & Sims, 1979). Specific framed rules make the process of moral rationalization more difficult, because the rules about what to do and what not to do are clearer and there is less room to argue around it. For example, within the presence of a specific rule such as: "do not drive in excess of 65 miles an hour on expressways", an individual has less room to argue around it than in the presence of a general rule such as: "do not drive at an excessive speed on expressways" (Mulder et al, 2015). Thus, in the presence of a specific room, an individual has less room to morally rationalize his or her unethical behavior, because specific rules are scoped more precisely in how an individual should behave.
specific rule is clearer and thus, gives individuals less room for motivated reasoning, because the frameworks of the rule are more specific.
To examine the conceptual model in figure 1 and measure the effect of rules on the relation between personal gain and unethical behavior, the following hypotheses will be conducted:
Hypothesis 1: Personal gain increases unethical behavior of an employee.
Hypothesis 2: A specific rule reduces unethical behavior more than no rule or a general rule does.
Hypothesis 3: The presence of a rule reduces the effect of personal gain on unethical behavior of an employee.
Hypothesis 4: A general rule will moderate the effect of personal gain on unethical behavior.
Hypothesis 5: A specific rule will reduce the effect of personal gain on unethical behavior.
Hypothesis 6: A specific rule will reduce the effect of personal gain on unethical behavior stronger than no rule or a general rule.
Figure 1: Conceptual model.
Specific Rule
Personal gain Unethical
behavior (-)
3. METHOD 3.1 Design and participants
The aforementioned conceptual model and the underlying hypotheses are tested in an online survey. Data was collected through mobilizing the researcher's network and approaching people personally on the street or by phone and by using snowball sampling. People were asked to engage in a study about rules and behavior in the workplace. Upon agreement, participants received a link towards to the survey by e-mail or personal message on LinkedIn. Participation was voluntary and participants could quit any time during the survey. One of the participants was randomly chosen to win a homemade apple pie.
The sample (N = 92) consists of Dutch employees that work for different companies and in different sectors in the Netherlands. Different sectors were represented, such as education (13,5%), finance (11,7%) and healthcare (8,1%). Average tenure was 6.44 years. Average age is 33.94 years, with a gender distribution of 55% female and 45% male.
3.2 Procedure
Firstly, some demographic questions were asked. Secondly, the independent variables rules and personal gain were measured. Lastly, the dependent variable was measured by using a self-report of unethical behavior.
3.3 Measures
Rules
Concerning the rules that exist in organizations the survey measures the presence of rules within the organization and the type of these rules.
Existence and clarity of rules
The existence of rules is measured using a three point Likert-scale, participants could choose between "Yes", "No" and "do not know". The items that are used are: "In the organization I work for, there is an integrity code" and "In the organization I work for, there is a code of conduct regarding behavior" (α = .61). The 14 participants that choose "do not know" are left out of the analysis of the existence of a rule.
The clarity of the rules is measured using a seven point Likert-scale, (1 = totally disagree, 7 = totally agree These items are: "I am aware of the rules of ethical conduct within my organization", "in the organization I work for, there are rules considering behavior" and "the rules on ethical behavior within my organization are clearly communicated" (α = .88). Emphasis on rules
The emphasis of rules was measured with eight statements (Appendix A), conducted from Victor and Cullen’s (1988) Ethical climate questionnaire, using a seven point Likert-scale, (1 = totally disagree, 7 = totally agree). Victor and Cullen (1988) used these two subscales in order to measure rules and policies. An example of one of the eight items is: "In this company, the law or ethical code of their profession is the major consideration" (α = .83). Rule specificity
amongst three statements on a seven point Likert-scale, (1 = Very specifically framed, 7 = Very generally framed). An example of one of the three items is: "The rules within the organization I work for are.." (α = .96).
The last item aimed to distinguish between no rules, specific rules and general rules. Participants were asked whether the rules within their organization are more specific, general or that there are no rules. The question was: "If you have to choose what is most appropriate for the organization you work for, what would you choose?", with response categorical answers: "Within my organization, there are almost no rules", "The rules within my organization are mostly general" and "The rules within my organization are mostly specific".
Personal gain
Personal gain was measured with ten items (appendix C), using a seven point Likert-scale, (1 = totally disagree, 7 = totally agree). The performance-pay Link measures personal gain, from the original study of Deckop, Mangel, & Cirka (1999). An example item is: "In my organization, people have little respect for employees who do not perform much". The first six items are the original items of Deckop et al. (1999), the other four items are self-made (α = .71). The factor-analysis on these ten items showed an acceptable determinant of .03 and thus, no factors were deleted from the measurement.
Unethical behavior
4. RESULTS
Correlations
Correlations are displayed in table 1. This table shows that I did not find a main effect of personal gain on unethical behavior (r = .14, p = .19), because there is no significant correlation, thus hypothesis 1 is not supported. To measure the differences between a specific versus a general rule, dummy variables were created. The general rule dummy contains the general rule (= 1), which is contrasted with no rule (= 0), controlled for a specific rule (= missing value). The specific rule dummy contains a specific rule (= 1), which is contrasted with no rule (= 0), controlled for a general rule (= missing value). The main effect of rules on unethical behavior is divergent: the presence of a rule marginally increases unethical behavior (r = .15, p = .07), as a specific rule (dummy) has no significant direct effect on unethical behavior (r = -.24, p = .12). The effect of the clarity of the rule (r = -.28**, p = .01) is stronger and significant.
M SD 1 2 3 4 5 6 7
1. Rule presence 1.55 .68
2. Clarity of the rules 5.00 1.51 -.27**
Hypothesis 2 suggested a difference between the effect of no rule, a general rule and a specific rule, on unethical behavior. There was a marginal significant difference between rules as determined by a one-way ANOVA (F (2,90) = 2.99, p = .06). To examine these differences, a pairwise comparison was made. Pairwise comparisons showed that unethical behavior was significantly lower under the presence of a specific rule (M = 1.40, SD = .40) compared to no rule (M = 1.67, SD = .64, p = .40) and the general rule (M = 1.70, SD = .63, p = .05). There was no statistically significant difference between no rule and a general rule (p = .98). The post-hoc differences are displayed in table 2.
Mean difference Differences No rule General Rule
Specific Rule
-.04 .26
1.67ab
General rule No Rule Specific Rule
.04 .30*
1.70b
Specific rule No Rule General Rule
-.26 -.30*
1.40a
* p < .05, Note: means with different superscripts significantly differ.
Table 2: pairwise comparisons and post-hoc differences of no rule, general rule, specific rule on unethical behavior.
Graph 1: Differences on unethical behavior, between no rule, general rule and specific rule.
Hypothesis 3 proposed that the presence of a rule moderates the effect of personal gain on unethical behavior. To test the effect of the presence of a rule, a hierarchical regression analysis with model 1 in PROCESS was conducted. The presence of a rule, unethical behavior and personal gain are standardized. The overall model is not significant (F (3,89) = 1.69, p = .17, R2 = .05). Thus, as table 3 shows, the presence of a rule does not significantly moderate the effect of personal gain. Therefore, the presence of a rule does not moderate the effect of personal gain and hypothesis 3 is not supported.
Moderation model, DV = unethical behavior, moderator = presence of a rule
β SE p LLCI ULCI
Personal gain .11 .07 .10 -.02 .25
Presence of a rule .17 .09 .07 -.02 .35
Interaction (Personal gain * presence of a rule). .02 .09 .28 -.15 .19
Hypothesis 4 posted that a general rule moderates the effect of personal gain on unethical behavior. To test the effect of a general rule, a hierarchical regression analysis with model 1 in PROCESS was conducted. Within this analysis, unethical behavior and personal gain are standardized and the dummy variable general rule was used. Thus, the general rule condition is contrasted against the no rule condition and controlled for the specific rule condition. The overall model was not significant (F (3,55) = .61, p = .61, R2 = .04). As table 4
shows, a general rule does not significantly moderate the effect of personal gain on unethical behavior. Thus, I did not find a moderation effect of a general rule on personal gain and unethical behavior and therefore, hypothesis 4 is not supported.
Moderation model, DV = unethical behavior, moderator = general rule (dummy)
β SE p LLCI ULCI
Personal gain .13 .12 .31 -.12 .38
General rule -.08 .31 .81 -.70 .55
Interaction (Personal gain * general rule). -.16 .32 .61 -.79 .47
Table 4: Moderation model.
Moderation model, DV = unethical behavior, moderator = specific rule
β SE p LLCI ULCI
Personal gain .09 .11 .39 -.13 .32
Specific rule -.37 .30 .23 -.98 .25
Interaction (Personal gain * specific rule). -.22 .31 .49 -.83 .41
Table 5: Moderation model.
Hypothesis 6 posted that a specific rule versus a general rule differently moderate the effect of personal gain and unethical behavior. To test the differences between the effects of a specific versus a general rule, a hierarchical analysis with model 1 in PROCESS was conducted. Within this analysis, unethical behavior and personal gain are standardized and a new dummy variable general rule was created, in which the specific rule condition (= 1) was contrasted against the general rule condition (= 0), controlled for the no rule condition (= missing value). The overall model was marginally significant (F (3,79) = 2.62, p = .06, R2 = .09). As table 6 shows, the interaction between personal gain and a specific versus a general rule is not significant and therefore, hypothesis 6 is not supported. The main effect of a specific rule versus a general rule is significant (β = -.30, p = .01). This was also explained within table 2, in which unethical behavior is significantly lowered under the presence of a specific rule, compared with a general rule.
Moderation model, DV = unethical behavior, moderator = specific versus general rule
β SE p LLCI ULCI
Personal gain .08 .09 .41 -.11 .27
Specific rule versus general rule -.30 .12 .01 -.54 .06 Interaction (Personal gain * specific versus
general rule).
5. DISCUSSION 5.1 Hypotheses and findings
The main goal of this research was to examine whether and how a specific rule moderates the effect of personal gain on unethical behavior. This study aimed to contribute to the literature on these topics, by investigating the role of a specific rule as a moderator. In a field study, I examined whether a specific rule moderates the effect of personal gain on unethical behavior, with the expectation that when a specific rule is installed, the effect of high personal gain on unethical behavior reduces. Thus, I expected that when an organization installs a specific rule, rather than a general rule or no rule, the increasing effect of personal gain on unethical behavior of employees is reduced. Comparing the expectations and the results, I can conclude that the findings contain more non-results than actual results, the next paragraphs will discuss and explain the most important non-results and results.
Another possible explanation for this problem is that the overall scores on unethical behavior were also low and there was not much variance in the answers. This problem could be caused by the fact that unethical behavior was measured using survey questions, in which respondents could indicate how often they behaved in an unethical way, over the past twelve months. Zuber and Kaptein (2013) examined unethical behavior in the workplace and the differences in frequencies using self-reports versus observer-reports. They found that observer-reports show higher frequencies and variance of unethical behavior than self-reports, indicating that researchers should use observer-reports rather than self-reports. Moreover, self-reports could entail social desirable answers, because respondents will underreport unethical behavior, when they perceive an item within a survey as more unethical (Zuber & Kaptein, 2013; Jones, 1991). Therefore, the non-results of the effect of personal gain on unethical behavior could be influenced by the low variance within the self-reports on unethical behavior and the possibility that employees may misperceive personal gain within their organization.
Mulder et al. (2015), as an employee has less room to morally rationalize unethical behavior when there is a specific rule present. Installing a specific rule can help the organization to reduce unethical behavior of employees, because employees have less room for motivated reasoning and have less room to morally rationalize behavior that is unethically (Kunda, 1990).
5.2 Theoretical implications
5.3 Practical implications
Despite the fact that most of the results are non-results, this research can contribute in a practical way, because the results that I did find, give recommendations for organizations. The results of this research indicate that a specific rule is more preferable above a general rule in order to reduce unethical behavior of employees. In order to counteract unethical behavior in the workplace, organizations should implement specific rules that are clear and enforceable. General rules cover more general situations, but this research shows that there is no difference between the effect of no rule and a general rule on unethical behavior of an employee.
The differences between the main effect of a specific rule, a general rule and no rule, can be explained by the understanding that within the presence of a general rule or no rule, there is more room for moral rationalization and motivated reasoning than in the presence of a specific rule. Under the presence of a general rule or no rule, individuals can morally rationalize their unethical behavior by justifing their behavior, using motivated reasoning (Kunda, 1990). Therefore, a specific rule reduces unethical behavior of an employee more than a general rule or no rule, because there is less room for moral rationalization and motivated reasoning.
5.4 Limitations and future research
This current research has some strengths, which include the finding of a direct effect of a specific rule on unethical behavior. Nevertheless, this current research is limited by different factors, including the non-results and the fact that this research does not have a lot of power. In this paragraph the most important limitations are discussed and combined with recommendations for further research.
As earlier discussed, the main limitation of this research is the fact that I did not find evidence that personal gain can increase unethical behavior of an employee. The main issue that caused this non-result is the fact that the power of this research is low, because I did not collected enough respondents. Moreover, due to the low amount of respondents, the variance of unethical behavior and personal gain was low. Future researchers should use observer-reports in order to solve the problem of the low variance of unethical behavior and personal gain (Deckop, Mangel & Cirka, 1999; Zuber & Kaptein, 2013). Using observer-reports rather than self-reports, the problem of social desirable answers will be diminished, given that observer-reports do not underreport unethical behavior (Zuber & Kaptein, 2013).
Another limitation of this research is that I did not examine the effects of moral rationalization (Mulder et al., 2015) as part of the unethical decision-making process. Future research could further investigate the role of moral rationalization, in order to describe and interpret the underlying unethical decision-making process better. Moral rationalization could be measured using a scenario study, in which participants are presented with either a general or a specific rule, after which moral rationalization and unethical behavior is measured. Measuring moral rationalization plays an important role in the decision-making process of individuals. For future research it might be interesting to examine how moral rationalization is influenced under the presence of a specific or general rule.
6. CONCLUSION
This research aimed to answer the following research question: "How does a specific rule moderates the effect of personal gain on unethical behavior of an employee?".
I did not find evidence an effect of personal gain on unethical behavior, which could be caused by the limitations in variance and self-reports. I did find evidence for a direct reducing effect of a specific rule on unethical behavior; compared to a general rule or no rule, unethical behavior of an employee is reduced under the presence of a specific rule. Organizations therefore can counteract unethical behavior of employees by installing a specific rule. Reducing unethical behavior of employees is important for organizations, because unethical behavior could cause severe problems such as fines, which can hurt the image and the financial position of the organization (Bishop, 2013). Future research should examine the non-results, using observer-reports amongst more respondents, in order to make the results more powerful. Moreover, to avoid common source bias, future researchers should gather data amongst two different employees of the same organization. If these limitations are solved, conclusions and recommendation are more powerful. For now, I can recommend organizations to "be more specific" in setting and installing rules.
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APPENDIX A
Ethical Climate Questionnaire (ECQ), Victor and Cullen (1988)
7 - point Likert scale: 1 = Totally disagree, 2 = mostly disagree, 3 = somewhat disagree, 4 = agree/disagree, 5 = somewhat agree, 6= mostly agree, 7 = totally agree.
Original instruction: We would like to ask you some questions about the general climate in your company. Please answer the following in terms of how it really is in your company, not how you would prefer it to be. Please be as candid as possible, remember, all your responses will remain strictly anonymous.
2. Law and Code
(PC) People are expected to comply with the law and professional standards over and above other considerations.
(PC) In this company, the law or ethical code of their profession is the major consideration. (PC) In this company, people are expected to strictly follow legal or professional standards. (PC) In this company, the first consideration is whether a decision violates any law.
3. Rules
(PL) It is very important to follow the company's rules and procedures here. (PL) Everyone is expected to stick by company rules and procedures. (PL) Successful people in this company go by the book.
APPENDIX B Rule frame specificity Explanation of general and specific rules:
Specific rules are clear and enforceable, an example of a specific rule is: 'Do not accept gifts
from clients'.
General rules have a broad scope and are not clear and enforceable, an example of a general
rule is: 'Do not compete in conflicts of interests'.
Questions:
Seven point Likert-scale: 1 = Very specific, 2 = Mostly specific, 3= Somewhat specific, 4 = Specific/General, 5 = Somewhat general, 6= mostly general, 7 = very general. 1. The rules within the organization I work for are:
2. The rules I have to deal with are: 3. The rules I have to follow are:
APPENDIX C
Performance-pay Link (Deckop, Mangel & Cirka 1999).
Rate the following items on a 7-point scale: 1= Totally disagree, 2 = Mostly disagree, 3 = Somewhat disagree, 4 = agree/disagree, 5 = somewhat agree, 6 = mostly agree, 7 = totally agree.
- Increased productivity means higher pay for employees.
- My individual performance actually has little impact on any incentive pay reward. (*reversed-coded)
- My performance actually has little impact on my salary. (*reversed coded) - In my organization, employees who perform well get promoted.
- In my organization, people have little respect for employees who do not perform much.
- In my organization, I'm in trouble if I'm not performing well. Self made items, according to the items above:
APPENDIX D
Unethical Deception Scale (Barsky, 2011)
1. Conceal information from the public that could be damaging to your performance. 2. Report financial data inappropriately to make it seem you are performing your job better than you are.
3. Conceal information from your supervisor that might be detrimental to your performance. 4. Withhold negative information about your products or services from customers and clients. 5. Exaggerate the truth about financial information (e.g., revenue, losses, budget, etc.) to make your performance look good.
6. Exaggerate the truth about your company's products or services to customers and clients. 7. Misrepresent the truth to the internal auditor to help make your finances (e.g., revenue, losses, budget, etc.) look good.
8. Fail to inform customers or clients of important changes to your products or services 9. Misrepresent financial data to your customers, clients, or shareholders.
10. Understate losses or expenditures to make your department's financial situation look better.
11. Misrepresent the truth to your supervisor to help make your finances (e.g., revenue, losses, budget, etc.) look good.
