CHOICE OR PERCEPTION: HOW AFFECT INFLUENCES ETHICAL CHOICES AMONG SALESPEOPLE Susan Powell Mantel Sales representatives often face situations that require spontaneous decisions that can affect their competitive advantage, relationships with clients, and the bottom line. To foster ethical decisions, sales management must understand the situational and personal influences that shape the representative’s decisions. This paper describes an experiment that identifies contextual and personal influences on ethical decision-making. Findings suggest that a person who is in a positive (versus neutral) affect state will be less likely to be effected by heuristic biases and more likely to choose an ethical option (over a questionable alternative). Further, the dollar value at risk and the probability for success play a role in the ethical decisionmaking under certain conditions.
According to a survey of 1,324 workers including line employees, managers, and executives conducted by USA Today “48% of workers admit to unethical or illegal acts” (Jones 1997). Further, some of these same respondents attribute their ethical lapse to “good salesmanship.” Others attribute unethical choices to “competitive pressures” and “industry standards” (Sales and Marketing Management 1982). Recently, unethical decisions made by employees have caused bankruptcies and prosecutions in companies as diverse as Enron, WorldCom, and Qwest (Levinstein and Smith 2003; Roberts and Thomas 2002). The pressure toward unethical behavior may be even stronger among sales representatives. The pressure to meet quotas and compete successfully in relatively weak economic times may have caused an increase in unethical behavior among sales representatives toward employers, fellow salespeople, and even customers (Stewart 2003). Salespeople have been fired for submitting a renewal contract as “new business” in order to get increased commission. More than half of nearly 300 sales managers surveyed by Sales and Marketing Management said that their salespeople are more concerned about colleagues stealing their accounts or leads compared to three years ago, and 16 percent of those managers report that infighting and deception has caused problems with clients (Stewart 2003). Although “shady practices” may close more deals in the short run, relationships with customers and, ultimately, the bottom line of the business will suffer in the long run. Because sales representatives typically have personal interactions with clients and potential clients, their actions are more readily visible and unethical behavior can have profound
Susan Powell Mantel (Ph.D., University of Cincinnati), Associate Professor of Marketing, Kelley School of Business, Indiana University,
[email protected]. The author thanks David Reid, Ellen Pullins, and James Kellaris for help on an earlier draft of this manuscript.
effect on the public opinion of the company. When MetLife sales agents in Tampa, Florida, were accused of misrepresenting facts and selling inappropriate products worth about $11 million in premiums, the company had to respond to allegations of misconduct that affected the entire company, not just the Tampa office (Hartley 2004). Some would argue that the commission structure of compensation would encourage unethical behavior from sales representatives. In fact, Putnam Investments has dropped their practice of “directed commissions” (i.e., a practice that was designed to reward brokerage firms that sell large amounts of their funds) in order to eliminate the perception of unethical behavior (Hechinger 2003). In an experiment among insurance salespeople, however, no relationship was found between commission structure and the type of product recommended to a hypothetical couple (Cupach and Carson 2002). In other words, the sales representatives were no more likely to recommend a particular product when a high commission was associated with that product compared to the same product when a flat fee for sale (regardless of recommendation) was offered compared to no stated compensation package. Salespeople tend to be exuberant over the product that they are selling and may use mild exaggeration (i.e., “puffing”) in describing their product. The question is how much puffing is too much. It is because of the gray lines between acceptable business practices and potentially unethical behavior that the subject of ethics is currently under scrutiny in the press and the topic of academic study. This topic is important because each day salespeople must make ethical decisions that can affect their competitive advantage, their relationships with the clients, and the bottom line. Many situational variables appear to influence one’s ethical perspective (Brady and Hatch 1992). For example, personal-life standards are typically higher than work-life standards (Car 1968), competitive pressures or economic conditions could encourage unethical salesperson behavior Journal of Personal Selling & Sales Management, vol. XXV, no. 1 (winter 2005), pp. 43–55. © 2005 PSE National Educational Foundation. All rights reserved. ISSN 0885-3134 / 2005 $9.50 + 0.00.
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in many industries (Sales and Marketing Management 1982; Stewart 2003), and previous judgment and shifting points of reference seem to bias ethical judgments (Boyle, Dahlstrom, and Kellaris 1998). In fact, a sales manager’s reaction to unethical behavior differs based on the magnitude and likely consequences of the behavior and the salesperson’s overall sales level rather than the severity of the act (Bellizzi and Hite 1989). In addition, as many as 41 percent of sales managers report being willing to hire a salesperson who has engaged in an unethical behavior, depending on the manager’s personal moral philosophy (Sivadas et al. 2003). Given these situational and personal variations in judgment, it is not surprising that the literature has been inconsistent in its predictions of salesperson action in ethical and unethical situations or management reaction to that behavior. Large variances in ethical judgments have been found among marketing students (Dabholkar and Kellaris 1992) as well as experienced businesspeople (Chonko and Hunt 1985). Further, academic researchers have typically accepted these large variances and analyzed the data in relative terms rather than imposing an absolute norm. Many researchers (e.g., Bellizzi and Hite 1989; Boyle, Dahlstrom, and Kellaris 1998; Dabholkar and Kellaris 1992; Haley 1991; Kellaris, Boyle, and Dahlstrom 1994; Singhapakdi and Vitell 1991) have attempted to explain these large variances via situational or personal variables such as monetary implications, salesperson performance, gender, or organizational climate. Clearly, this research suggests that situational variables are as important as the behavior itself in determining the ethical evaluation of a business practice by marketing students, sales personnel, or sales management. Research in sales ethics has taken two tacks. Whereas one stream seeks to evaluate the moderating effects of the demographic characteristics of the person passing ethical judgment (Bass, Barnett, and Brown 1998; Haley 1991; Hoffman, Howe, and Hardigree 1991; Singhapakdi and Vitell 1991; Sivadas et al. 2003), the other focuses on the moderating effects of the situation itself (e.g., Bellizzi and Hite 1989). In addition, while commission structure, per se, may not encourage unethical recommendations (Cupach and Carson 2002), it seems that the inclusion or exclusion of monetary consequences and/or customer harm may influence perceptions (Dabholkar and Kellaris 1992). An interesting extension of this literature would be to look at how ethical information is processed given the internal state of the salesperson (i.e., their positive versus neutral affect). THE ROLE OF AFFECT ON SALESPERSON BEHAVIOR Popular lore suggests that a happy employee is a productive employee. The business press is littered with articles that sug-
gest that companies believe this and try to increase morale by giving employees a sense of ownership (Joyce 2004), fitness and recreational opportunities (Shreve 2004), employee discounts (White 1999), and achievable incentive programs (Bank Advertising News 1988). Within the academic literature, employee satisfaction and attitudes have been hypothesized to affect customer satisfaction in a positive manner by promoting helpfulness to others and enhancing problem solving capabilities (Rucci, Kim, and Quinn 1998). Within the sales literature, employee morale has had many interpretations. In some instances, it has been equated to job satisfaction (Churchill, Ford, and Walker 1976); in others, it has been defined as a direct result of job satisfaction (Benge and Hickey 1984). In organizational behavior literature, job satisfaction has been shown to be significantly and positively related to reported pleasant mood over a 16-day test period (Weiss, Nicholas, and Daus 1999). Both morale and job satisfaction have been defined as composite feelings about many job-related attributes (Churchill, Ford, and Walker 1976; Pestonjee, Singh, and Singh 1981). These feelings tend to vary over time (Weiss, Nicholas, and Daus 1999), depending on the salient attributes on any given day, but, over a reasonably short time frame, on average, they are believed to be fairly stable. Because morale and job satisfaction involve feeling states and attitudes, it is important to investigate the effect of these feelings and attitudes on decision-making and job performance. Positive affect is defined as a pleasant feeling state or good mood (Estrada, Isen, and Young 1994). Some researchers, particularly those in the area of organizational behavior, have looked at measured affect or mood (e.g., Staw and Barsade 1993; Staw, Sutton, and Pelled 1994; Weiss, Nicholas, and Daus 1999), whereas others, particularly those in the area of psychology, have looked at manipulated affect (for a review, see Isen 2000). In either case, positive affect has been shown to be positively related to increased creativity and flexibility in problem solving. Specifically, there is an abundant literature in social psychology and marketing (for a review, see Isen 2001) suggesting that positive affect (relative to neutral affect) is influential in improving the bargaining process and outcomes in face-to-face negotiations (Carnevale and Isen 1986), enhancing efficiency in complex tasks (Isen 1993; Isen and Means 1983), and increasing cognitive flexibility (Estrada, Isen, and Young 1994; Lee and Sternthal 1999). In addition, individuals who are in a pleasant mood are more likely to learn material or cue material from memory (Isen et al. 1978; Matlin 1989; Nasby and Yando 1982; Teasdale, Taylor, and Fogarty 1980). In the organizational behavior literature, measured positive mood has been shown to be related to better decision-making (Staw and Barsade 1993), positive job satisfaction (Weiss, Nicholas, and Daus 1999), and better supervisor evaluations (Staw, Sutton, and Pelled 1994). Thus,
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positive feelings (both manipulated and measured) appear to influence behavior potentially through storage, organization, and retrieval of cognitive information. Because individuals who are in a positive affect state tend to be more cognitively flexible (Isen 1990) and tend to be more likely to see “the big picture” (Isen 1989), a person in a positive (versus neutral) affect state should be more likely to spend time analyzing an ethical decision and to use more information in making that decision. Therefore, because they will be making more integrative decisions, individuals who are in a positive affect state should be more likely to notice the ethical issues and consider them when making their decision. The study of positive versus neutral affect rather than positive versus negative affect is relevant for several reasons. First, the research on affect suggests that there is an asymmetry between positive and negative affect. That is, negative affect (particularly sadness) is not the opposite of positive affect (Isen 2000). The literature suggests that people spontaneously use positive feelings as an aid to organize their thought process, but negative feelings have no effect on the organizational process (Isen 1985). Second, whereas positive affect tends to be unidimensional and predictable, negative affect can take many, very different forms (e.g., sadness, anger, depression). Therefore, affect cannot be evaluated along a continuum forming the negative affect to positive affect dimension (Isen 2001b). For this reason, it is important to look at the positive/neutral dimension separately from the neutral/negative dimension. Further, the research looking at negative affect suggests that negative affect neither encourages nor discourages retrieval of information or elaboration. Conversely, the literature predicts that the positive/neutral dimension will have an effect on memory organization and retrieval. Therefore, it makes sense to look at this dimension for possible influences on ethical judgments. In addition, looking at the positive/neutral dimension is important not only from a theoretical perspective but also on a practical level. Managers may attempt to induce positive affect among their employees, and it is important to understand if those attempts are likely to influence behavior, creativity, and ethical decision-making. RISK AND UNCERTAINTY It has been shown that a person’s judgment process will be influenced by the framing of uncertainty and risk associated with a situation. Kahneman and Tversky (1979; Tversky and Kahneman 1987) propose prospect theory to explain this phenomenon and term this judgment bias the framing effect. Specifically, more risk-taking will occur under conditions of potential loss than under conditions of potential gain, causing a reversal of choice behavior based only on the wording used to describe the choice prospects. This seemingly irrational phenomenon has also been shown in relation to ethical
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decision-making within a marketing context (Kellaris, Boyle, and Dahlstrom 1994) as well as salesperson hiring decisions (Marshall, Stone, and Jawahar 2001). Kellaris, Boyle, and Dahlstrom (1994) show that MBA students with sales experience tend to choose the alternative predicted by prospect theory even when that alternative was less ethical than an alternative that offered an equivalent expected value. Still, the percentage that chose the unethical probable loss option was much lower than Kahneman and Tversky’s (1979) prospect theory would suggest, in which 70 percent of respondents consistently chose the probable loss situation over the smaller sure loss situation. Because positive affect has been shown to promote creativity and flexibility in decision-making, it would make sense that positive affect may be a moderator that helps some people to look past the risk position in the frame of the scenario (i.e., be less influenced by the framing effect), and evaluate the situation in relation to its relative ethical implications instead. Therefore, we expect that salespeople who are in a positive affective state to be more likely (than those in a neutral affective state) to choose the ethical solution regardless of the frame. In summary of this expectation, the following hypotheses are proposed: H1a: A salesperson who is in a positive affect state (compared to a neutral affect state) will be more likely to choose the ethical (rather than the unethical) option (i.e., main effect of affect). H1b: Affect will overwhelm the framing effect when ethical choice is presented against frame such that a salesperson who is in a positive (neutral) affect state will be more likely to choose the ethical (unethical) option when the ethical option is placed against frame. Research in prospect theory has looked at the effect of dollar value changes on the propensity to accept risk in situations of gain or loss (Hershey and Schoemaker 1980). It has been shown that preferences for the risky gain options and the less risky loss options decrease as the dollar amount became more positive or negative. For example, over 80 percent of the respondents preferred the risky alternative on the gain side and about 40 percent preferred the risky alternative on the loss side when the value of the safe alternative was ±$1. When the safe alternative was very high (±$10,000), however, the relative percentages were reversed (12 percent and 68 percent, respectively). In other words, the respondent’s propensity toward risk appears to depend not only on the direction of the gain or loss but also on the magnitude of the potential. Extrapolating from Hershey and Schoemaker (1980) results into the ethical choice among sales representatives, a logical hypothesis would suggest that salespeople will be more likely to engage in ethically questionable behavior when it is
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associated with a higher dollar value outcome compared to a lower dollar value. However, because positive affect is likely to encourage cognitive flexibility, it is reasonable to suspect that when the ethical choice is placed against frame (i.e., situated either as a sure loss or risky gain), those in the positive affect cell will be more likely to choose the ethical solution regardless of the gain or loss frame, and those in the neutral affect cell will be more likely to be influenced by dollar value. That is, they will choose the ethical choice for low dollar value option and the ethically questionable choice when the dollar value is high. Therefore, one would expect: H2a: There will be a main effect of dollar value such that a salesperson will be more likely to engage in an ethically questionable behavior when it is associated with a higher dollar value outcome than when it is associated with a lower value outcome. H2b: Affect will moderate the effect of dollar value such that when the ethical choice is presented against frame, a salesperson who is in a positive affect state will be more likely to choose the ethical option regardless of the dollar value, whereas those in the neutral affect state will be influenced by dollar value as stated in H2a. Similarly, Hershey and Schoemaker (1980) evaluate choices made between risky and certain alternatives with varying degrees of probabilities associated with the risky alternative. In their study, the probabilities vary from 0.001 to 0.2. The results suggest that respondents tend to be risk-averse when choosing between a small, sure gain and a risky, potential gain. As the probability increases for the risky gain to pay out, however, so does the propensity to choose that risky alternative. In the portion of their study dedicated to evaluating the effect of varying the probability of payout, Hershey and Schoemaker find that the preference for the risky gain alternative increases from 32 percent (0.001 probability) to 72 percent (0.2 probability). Therefore, as the chance of payout increases, so does the likelihood that salespeople would choose the risky alternative. Extrapolated into the ethical decision framework, these data would suggest that salespeople may be more inclined to engage in an ethically questionable activity as the probability of payout increases. In addition, it seems that the more creative mental processes induced by a positive affect state would moderate this contextual effect such that those who are in a positive affect state should be less likely to choose the unethical alternative at any given risk level, particularly when the ethical choice is presented against frame. H3a: The percentage of salespeople who would choose the ethically questionable (ethical) alternative will be higher at higher (lower) probabilities of payout.
H3b: Affect will interact with probability such that when the ethical choice is presented against frame, a salesperson who is in a neutral affect state will be influenced by the decision biases stated in H3a. Conversely, a salesperson who is in a positive affect state will be more likely to choose the ethical option at any given probability level. Further, given the increased propensity for choosing the higher payout alternative when either dollar value or probability are manipulated, it would seem reasonable that dollar value and probability would interact such that when the dollar value is low, the propensity to choose the ethical option should be driven by the probability of payout. Conversely, when the dollar value is high, the propensity to choose the ethical option will be moderate. H4a: For low dollar value decisions, salespeople will be more likely to choose the questionable alternative when the probability of payout is high (versus low). H4b: For high dollar value decisions, the propensity to choose the ethical option will be moderate. METHODOLOGY Overview The purpose of this study is to investigate differences in ethical judgment among salespeople in two employee affect states (positive versus neutral). These differences will be investigated under conditions of varying degrees of risk and uncertainty under both situations of potential gain and potential loss using a 2 (affect) × 2 (frame) × 2 (risk) × 2 (dollar value) betweensubjects design. This experiment was executed via self-administered questionnaires mailed to the homes of randomly selected sales representatives identified via a purchased mailing list. Ethical Decision Scenario The scenario used for this study was adapted from Kellaris, Boyle, and Dahlstrom (1994). The scenario was created such that respondents choose between an ethically questionable (yet not illegal) option and a more ethical option. The frame of the scenario is operationalized such that the expected value and risk probability are objectively equivalent. The manipulations within the scenario are counterbalanced so that the ethical choice is in either the risky choice position or the sure (but lesser value) alternative. The specific scenario is depicted in Table 1, with all manipulations presented within brackets. Each respondent was exposed to only one version of the scenario. It is important to note that all alternatives are objectively equivalent, both between versions of the scenarios and between choices within each given scenario. For example, a 25 percent chance of getting both jobs is equivalent to a 75 per-
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Table 1 Scenario Descriptions Background Information You are a salesperson and are bidding for two jobs from one firm. Within the industry, some salespeople use “backdoor selling” (i.e., salesperson calls directly on the operations manager). Because the operations manager is the final consumer, this backdoor selling tactic is often effective, especially when competition is heavy. Whereas backdoor selling is not illegal, the client company has a policy that all purchases be executed through the purchasing department. Therefore, if the backdoor selling tactic is identified, the purchasing department could stop an otherwise sure sale. Given the circumstances described below, please indicate what you would do. Treatments You have estimated that, given the amount of competition for both jobs, you have a [25/75/10/90] percent chance of getting/losing] both jobs totaling [$32,000/80,000] if you go [through the purchasing department/directly to the operations manager]. Assume your estimate is accurate. However, your contacts inside Tri-State Trucks tell you that going [directly to the operations manager/through the purchasing department] with the bid will guarantee you [getting the smaller (dollar value*) job/losing the larger (dollar value*) job]. Risk and Dollar Value Manipulations
Combined Value of Two Jobs
Probability of Getting Both (percent)
Value of Lesser Job
Value of Greater Job
$32,000 $32,000 $80,000 $80,000
10 25 10 25
$3,200 $8,000 $8,000 $20,000
$28,800 $24,000 $72,000 $60,000
cent chance of losing both jobs. Further, a 25 percent chance of getting both jobs (worth a total of $32,000) has the same expected value of a guarantee of getting only the smaller ($8,000) job. The fact that “backdoor selling” is perceived as less ethical was shown by Kellaris, Boyle, and Dahlstrom (1994). The risk and rewards were also manipulated within the scenario to test H2–H4. The values of risk and reward are depicted in Table 1. Independent Variables Independent variables that were manipulated in this study include affect, frame, position of the ethical option, dollar value, and probability of payout. Salesperson Affect Manipulation To ensure that a positive or neutral affect is the currently active state of the respondent during the experiment, respondents were randomly assigned to affect conditions. Half of the participants were assigned to the positive affect group and received a questionnaire that began by asking the participants to recall their most recent positive work-related event. The questionnaire read: “Please take a moment to think about your most recent exciting, work-related accomplishment. This could be a recent promotion, a large, unexpected sale or any other exciting, work-related event.” The remaining respon-
dents were asked to “think about your workday last Wednesday (if you did not work last Wednesday, use another recent normal workday).” Each group was asked to write a summary of the day in one or two sentences and then write down the first five words that come to mind when thinking of the day. This manipulation is similar to those that have been used in the past to induce positive and neutral affect by having respondents read (versus not read) a “happy, warm” story (Batra and Stayman 1990), watch (versus not watch) a comedy film clip, receive (versus not receive) an unexpected bag of candy, or make word associations for positive (versus neutral) words (Isen 2000). Manipulation Check To verify this manipulation, the words written down by the salesperson were examined for consistency with the “average day” and “accomplishment” direction. The open-ended responses were coded as positive, negative, or neutral by two independent coders who were naive to the conditions to which the subjects were assigned. The two coders produced a high interjudge reliability, with 96 percent of the codes matching across judges. Discrepancies were resolved by discussion. Next, the codes were compared to the assigned cell to ensure that those in the positive affect cell recorded predominantly positive descriptions and those in the neutral cell recorded predominantly neutral descriptions. Those respondents whose
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attributes were not consistent with the requested affect state (5 respondents) and those who did not provide the written description (34 respondents) were excluded from the sample, because it could not be determined that the affect induction was successful or even implemented. In total, 39 subjects were excluded for noncompliance on this instruction. Frame Manipulation Following the procedure used by Hershey and Schoemaker (1980), each respondent was presented with either a gain or loss scenario. The independent variable, frame, was coded with a zero if the respondent saw the loss scenario and a one if the respondent saw the gain scenario.
Table 2 Cell Sample Sizes Sample Size Affect Positive Affect Neutral Affect Probability of Payout High Probability (25/75) Low Probability (10/90) Dollar Value at Risk Low ($32,000 total value) High ($80,000 total value) Frame of the Scenario Loss Gain
134 156 139 151 134 156 152 138
Position of the Ethical Option The ethical choice was counterbalanced between the “risky” alternative and the “sure thing.” According to prospect theory (Kahneman and Tversky 1979), subjects are more likely to choose the “safe” alternative in the gain scenario and the “risky” alternative in the loss scenario. Therefore, the “position of the ethical option” variable was coded as zero when the ethical choice matched frame (i.e., either the risky alternative in the loss scenario or the sure thing in the gain scenario) and coded as one when the ethical choice was against frame (i.e., either the sure thing in the loss scenario or the risky choice in the gain scenario). Dollar Value The dollar value variable was coded as either zero if the subject saw the low dollar value ($32,000) scenario or one if the subject saw the high dollar value ($80,000) scenario. Probability of Payout The probability variable was coded as zero if the subject saw the low probability of payout option (10 percent chance of gain/90 percent chance of loss) and a one if the subject saw the high probability option (25 percent chance of gain/75 percent chance of loss). Subjects and Design Sales representatives were recruited to participate in the study via a purchased national mailing list. Of the 1,500 questionnaires mailed, 46 were returned undeliverable, 5 recipients of the survey called to say that they were ineligible to participate because they were not sales representatives, and 329 were returned, giving a return rate of 22.7 percent. This response rate is similar to other studies using a mailed questionnaire (e.g., Weeks et al. 2004). The total number of questionnaires returned
was reduced due to the mood manipulation check and four were removed because they did not answer the choice question. Therefore, 286 questionnaires were used in the analysis. An analysis of early and late responders showed no significant difference in results between those that responded early and those that responded late, suggesting that nonresponse bias is not an issue for this sample. Further, the returned questionnaires were divided relatively evenly among the 16 cells of the experimental design, suggesting that there is no differential response bias across cells. Table 2 provides specific cell sizes for each manipulation. About half of the returned questionnaires (139) had the ethical choice in the position that matched the frame of the scenario (i.e., the sure, but smaller gain or the risk of a larger loss). The rest (147) had the ethical choice in the position that did not match the frame of the scenario (i.e., the chance of a larger gain or the sure, but smaller loss). The sample was about 78 percent male (224) and 21 percent female (60), with two respondents declining to give gender information. The ages ranged from 22 to 71, with both a mean and a median of 41 years of age. On average, the respondents have worked for their companies about 9 years and have about 14 years of sales experience. The respondents represented 14 different industries, such as manufacturing, transportation, communication, consumer products, wholesale, business services, and so on. The distribution of these demographic variables did not differ significantly across cells, suggesting that random assignment, which is implicit in the experimental design, successfully controlled for the potential effects of these demographic variables. Questionnaire and Measurement A letter of introduction along with a questionnaire was sent to each potential respondent. The letter explained the purpose of the study and assured confidentiality of the responses.
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Table 3 Logistic Regression Results (N = 286) Dependent Variable: Choice (1 = Ethical Choice, 0 = Questionable Choice) Model 1
Variable
Coefficient (odds ratio)
Constant Frame
–0.135 (0.87)
Model 2
Wald-statistic (p-value)
Coefficient (odds ratio)
10.79 (0.001) 0.304 (ns)
Affect
Model 3
Wald-statistic (p-value) 3.121 (0.07)
0.510 (1.66)
4.196 (0.04)
Frame × Affect Model Chi-Square [df] Percent Correct Predictions Pseudo R2 (Nagelkerke)
0.304 [1]
(ns)
62.6 0.001
Respondents were asked to choose between two alternatives. Whereas one alternative is ethically questionable (i.e., backdoor selling), the other is presented as ethical (i.e., direct contact through the purchasing department). The outcome variable, choice, was coded as a 0/1, with 0 representing the ethically questionable choice and 1 representing the ethical choice. ANALYSIS H1a predicts that a salesperson who is in a positive (versus neutral) affect state will be more likely to choose the ethical option than the ethically questionable option. To test this hypothesis, a logistic regression model (Long 1997) was run on the choice variable (coded as 0 = unethical choice and 1 = ethical choice), with affect and frame as independent variables. Three models were tested: (1) frame alone, (2) affect alone, and (3) affect, frame, and affect × frame interaction (see Table 3). The first model (Table 3, Model 1) is not significant (chisquare[1] = 0.304, ns, r2 = 0.001), suggesting that frame alone is not a good predictor of choice. The second model (Table 3, Model 2) is significant (chi-square[1] = 4.252, p = 0.04, r2 = 0.02), and predicts 63 percent of the responses correctly. The coefficient of the affect variable has a Wald-statistic of 4.196 (p = 0.04), and the “odds ratio” suggests that participants who are in a positive affect state are 1.7 times more likely to choose the ethical alternative over the ethically questionable alternative compared to those in a neutral affect state. In fact, 70 percent of the respondents in the positive affect condition chose the ethical alternative compared to only 57 percent of those in the neutral affect condition (see Figure 1). A third
Coefficient (odds ratio)
4.252[1] 62.6 0.020
(p = 0.04)
0.030 (1.0) 0.825 (2.28) –5.33 (0.59) 5.951[3]
Wald-statistic (p-value) 1.485 (ns) 0.009 (ns) 4.680 (0.03) 1.097 (ns) (p = 0.114, ns)
62.6 0.028
model was run to rule out the interaction of affect and frame (see Table 3, Model 3). While affect remains significant (Waldstatistic = 4.680, p = 0.03), neither frame, nor the interaction affect × frame are significant. In fact, the overall model is best with affect as the only predictor variable (Model 2 versus Model 3). Therefore, H1a is supported. To test H1b, an analysis examined the likelihood that the ethical choice was chosen against frame. That is, was the positive affect group more likely than the neutral affect group to choose the ethical choice when the ethical choice was in the position that prospect theory would predict as the unlikely choice (i.e., the sure choice for the loss scenario, or the risky choice for the gain scenario)? A logistic regression was run on the 147 subjects who were presented a scenario where the ethical choice was against frame. Again, three logistic regression models were run (see Table 4). The most parsimonious models are presented as Models 1 and 2. The first includes only the variable that specifies the frame of the presented scenario (gain versus loss). The results from Model 1 indicate that frame by itself is not a good predictor of ethical choice (model chi-square[1] = 0.416, ns, r2 = 0.004). The results from Model 2 (using affect as the only independent variable) indicate that affect is a good predictor of ethical choice (chisquare[1] = 7.593, p < 0.01, r2 = 0.07). Affect has a coefficient of 0.992 with a Wald-statistic of 7.197 (p = 0.007). In addition, when affect and frame are included together (along with their interaction), the resulting model is not a better predictor (chi-square[3] = 8.356, p = 0.04, r2 = 0.076), and the only predictor that is significant is affect (Wald-statistic = 5.22, p = 0.02; see Table 4, Model 3). Therefore, Model 2 was used for the remainder of the analyses. The “odds ratio” for the
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Figure 1 Percent of Subjects Choosing the Ethical Option
Table 4 Logistic Regression Results (N = 147) Only Include Cells Where Ethical Choice is Positioned Against Frame Dependent Variable: Choice (1 = Ethical Choice, 0 = Questionable Choice) Model 1
Variable
Coefficient (odds ratio)
Constant Frame
0.225 (1.2)
Model 2
Wald-statistic (p-value)
Coefficient (odds ratio)
4.96 (p = 0.02) 0.415 (ns)
Affect
Model 3
Wald-statistic (p-value) 1.24 (ns)
0.992 (2.7)
7.20 (p < 0.01)
Frame × Affect Model Chi-Square [df] Percent Correct Predictions Pseudo R2 (Nagelkerke)
0.416 [1]
(ns)
66 0.004
affect coefficient (Model 2) is 2.7 with a 95 percent confidence interval of [1.3, 5.6]. This suggests that those who are in a positive affect state are almost three times more likely than those in a neutral affect state to choose the ethical option when it is presented against frame, regardless of whether the option is presented as a gain or a loss (see Figure 2). This provides support of H1b. H2a predicts that a salesperson should be more likely to engage in ethically questionable behavior when it is associated with higher dollar value outcome than when it is associated with a lower value outcome. H2b suggests an interaction between affect and dollar value when ethics is placed against
Coefficient (odds ratio)
7.593 [1] 66 0.070
p < 0.01
0.395 (1.4) 1.222 (3.3) –0.452 (0.64) 8.356 [3]
Wald-statistic (p-value) 0.026 (ns) 0.761 (ns) 5.22 (p = 0.02) 0.371 (ns) p = 0.04
66 0.076
frame. To test these hypotheses, logistic regression models were run on choice with dollar value and affect as the independent variables. There was no statistical main effect of dollar value on choice (chi-square[1] < 0.1, ns) when tested by itself on the entire sample, and no main effect or interactive effect involving dollar value when tested along with affect among those who viewed a scenario in which the ethical solution was against frame. Consistent with H1, the only main effect in this model is affect (Wald-statistic = 6.8, p = 0.009) and the model is significant (chi-square[3] =8.757, p = 0.03, r2 = 0.08), with 66 percent of the responses correctly predicted. Therefore, H2 is not supported.
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Figure 2 Ethical Choice Against Frame (N = 147)
H3a and H3b investigate the main effect of probability for payout and the interaction between affect state and probability. In order to test these hypotheses, a logistic regression was run on choice with probability alone (see Table 5, Model 1) and with probability and affect together (see Table 5, Model 2). There is no main effect of probability when included by itself (chi-square[1] = 2.47, ns, r2 = 0.02). However, when probability is included along with affect as independent variables (see Table 5, Model 2), the results indicate that a main effect of affect (odds ratio = 2.9, Wald-statistic = 8.2, p = 0.004) and a marginal main effect of probability (odds ratio = 0.5, Wald-statistic = 3.4, p = 0.06). The overall model is significant (chi-square[2] = 11.08, p = 0.004, r2 = 0.10), and the model predicts roughly 69 percent of the responses correctly. These results show that salespeople in a positive affect state are almost three times more likely to choose the ethical option (74 percent to 81 percent choose ethical choice). Conversely, the neutral affect state salespeople choose the ethical alternative only about 44 percent of the time when the probability of payout is high (25 percent) and 62 percent of the time when the probability of payout is low (see Figure 3). H4 predicts an interaction between dollar value and probability of payout. The logistic regression includes independent variables of dollar value, probability, and affect, as well as the interaction between dollar value and probability (Table 5, Model 3). The results partially support the hypothesis. The data show a main effect of affect (Wald-statistic = 8.46[4], p = 0.004) and the interaction between dollar value and probability is also marginally significant (Wald-statistic = 2.68[4], p = 0.10). The overall model shows good predictive power (chi-square[4] = 13.8, p = 0.008, r2 = 0.124). The pattern of
responses is consistent with the hypothesis. The low dollar value option ($32,000) elicits extreme responses, with 78 percent of respondents choosing the ethical alternative when the probability of payout is lower (10 percent likely) and only 53 percent of the respondents choosing the ethical alternative when the probability of payout is higher (25 percent likely). The high-value alternative ($80,000) elicits responses that are more moderate, with close to 65 percent of respondents choosing the ethical alternative regardless of the risk level associated with the described alternative (see Figure 4). CONCLUSIONS This study examines how personal and situational variables influence the ethical judgment of salespeople. The data show that ethical judgment can be strongly influenced by the affective state of the salesperson. Specifically, salespeople in a positive affect state (compared to a neutral affect state) are almost two times more likely to choose the ethical solution overall and almost three times more likely to choose the ethical solution when it is positioned against frame. This suggests that positive affect allows the salesperson to look past the situational factors (i.e., frame) and make the more ethical choice. Absolute dollar value does not seem to influence the likelihood of an ethical choice either by itself or in conjunction with affect. The probability of payout, on the other hand, appears to influence the likelihood of an ethical choice among salespeople in neutral affect states (i.e., they are more likely to choose the questionable alternative when the probability of payout is higher). Further, the probability of payout interacts with dollar value such that a low dollar value scenario with a
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Journal of Personal Selling & Sales Management Table 5 Logistic Regression Results (N = 147) Only Include Cells Where Ethical Choice is Positioned Against Frame Dependent Variable: Choice (1 = Ethical Choice, 0 = Questionable Choice) Model 1
Variable
Coefficient (odds ratio)
Constant
Model 2
Wald-statistic (p-value)
Coefficient (odds ratio)
0.083 (ns)
Model 3
Wald-statistic (p-value) 3.88 (0.05)
Dollar Value Probability
0.551 (1.7)
2.48 (ns)
–0.679 (0.507) 1.076 (2.93)
2.47
(ns)
11.08 [2]
Affect
3.42 (0.06) 8.08 (0.004)
Probability × Dollar Value Probability × Affect Model Chi-Square [df] Percent Correct Predictions Pseudo R2 (Nagelkerke)
66
68.7
0.023
Coefficient (odds ratio)
0.10
(p = 0.004)
0.653 (1.9) –0.101 (0.904) 1.116 (3.0) –1.21 (0.297) 9.739 [4]
Wald-statistic (p-value) 0.465 (ns) 1.45 (ns) 0.040 (ns) 8.467 (0.004) 2.686 (0.10) (p = 0.05)
68 0.124
Figure 3 Ethical Choice (N = 147)
low chance of payout tends to elicit the highest percentage of ethical choices (70 percent). Conversely, a low dollar value scenario with a high chance of payout elicits a low percentage of ethical choices (55 percent), as does the high dollar value scenario with either a high or a low chance of payout (60 percent to 65 percent). This suggests that monetary outcome influences the likelihood of choosing ethical alternatives, but that positive affect may moderate that to some extent.
This research is important because it provides another piece to the puzzle that can help to show managers how to promote ethical decisions among the sales force. The experimental design complements previous survey research to suggest how positive affect can encourage cognitive flexibility and allow sales representatives to see past a strong bias (i.e., framing) to choose the ethical alternative even when it is positioned against frame.
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Figure 4 Ethical Choice (N = 147)
LIMITATIONS AND DIRECTIONS FOR FUTURE RESEARCH It is important to note that certain features of this study may impose limits on the generalizability of the findings. For example, the controlled experiment is both a benefit and a limitation. The benefit is represented by the random assignment to cells inherent in an experimental design. This allows for control over many variables that would be potential confounds in a survey study (e.g., gender, age, individual compensation program, success against quota, etc.). That is, all other things being equal, any given individual is equally likely to be assigned to any cell. Thus, the experimental design controls for possible confounds to the study. The limitation relates to the presentation of the scenario and manipulation of affect inherent in an experimental design. Because only one scenario was used to evaluate the ethical choice, one might argue that elements of the scenario might have caused the results. However, a version of this scenario has been used in the past (Kellaris, Boyle, and Dahlstom 1994) and has been shown to be perceived as either ethical (selling to the purchasing department) or questionable (backdoor selling). Similarly, the manipulation of affect is necessary in an experimental design in order to assure that the participants can be assigned randomly to the two affect cells. This study looks at positive versus neutral affect rather than positive versus negative affect. As stated previously, positive/ neutral affect dimension is appropriate because it conforms to previous literature and because it provides a managerially relevant context (e.g., assessing the value of positive affect inducing actions by management). However, because salespeople may be in a negative (rather than a neutral or positive)
mood from time to time, future research should investigate the consequences of negative affect on decision-making. These types of affect manipulations have been used regularly and successfully in psychology but they are just now being accepted in the sales literature. Although some researchers have shown a connection between measured mood and manipulated affect (Staw and Barsade 1993; Staw, Sutton, and Pelled 1994; Weiss, Nicholas, and Daus 1999), most research in sales has looked at mood or salesperson morale within a survey instrument. An extension to this research could look at the relationship between measured mood and manipulated affect as it relates to ethical decision-making. The important contribution of this research is to supplement the survey research in the area of sales by testing the ethical choices among experienced salespeople in a controlled experiment. Future research on this subject could also investigate possible methods by which management can influence positive affect on a daily basis among the sales force. By doing so, managers may be able to create an environment to encourage cognitive flexibility and thus encourage ethical decisionmaking in the field. REFERENCES Bank Advertising News (1988), “Incentives can Boost Sales, Morale, Consultant Claims,” 12, 33 (April 25), 7. Bass, Ken, Tim Barnett, and Gene Brown (1998), “Ethical Ideology and Ethical Judgment Regarding Ethical Issues in Business,” Journal of Business Ethics, 13 (June), 469–480. Batra, Rajeev, and Douglas M. Stayman (1990), “The Role of Mood in Advertising Effectiveness,” Journal of Consumer Research, 17 , 203–214.
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