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Heinze and Donoho                                                                                                                                                       Advances in Business Research 

2011, Vol. 2, No. 1, 16-26 
 

Sales Ethics: The Impact of Situational Factors on Gender Evaluation Differences 
 

Timothy Heinze, California State University, Chico 

Casey Donoho, California State University, Chico 
 

 

The number of sales positions is increasing, and the number of women in sales is growing. The current 
study seeks to understand gender-related ethical evaluations through testing responses to ethical 

situations in sales. Findings indicate that 1) women are less tolerant of ethical abuse in personal selling 
situations, 2) ethical evaluations do not vary based on situational outcomes, and 3) situations involving 
money, customers, and/or the companies that employ salespeople are evaluated with less ethical 

tolerance. Findings may be useful for pedagogical preparation and for the development of codes and 
training manuals within academia and industry.  
 

 

Growing at a 9% rate, sales careers remain a bright spot in today’s economy (Bureau of Labor 

Statistics, 2010). The number of women in sales and related occupations is also growing and is nearing 

the fifty-percent mark (Bureau of Labor Statistics, 2010). Despite the growth, ethical issues continue to 

haunt both public and private perceptions of sales (Luthy, 2007; Ramsey et al., 2007). Females are 

generally more sensitive to ethical issues in business, and, given the increased number of women in sales, 

research is required to better understand the specific ways in which males and females handle ethical 

scenarios in sales (O’Fallon and Butterfield, 2005). Prior studies have uncovered that 1) philosophical 

frameworks (moral idealism and relativism) impact ethical evaluations in sales, and 2) females are 

generally more idealistic than males (Donoho and Heinze, in press). However, philosophical framework 

divergence accounts for only a small portion of the variance in male/female sales ethics evaluations 

(Donoho and Heinze, in press).  

In a macro marketing ethics model, ethical evaluations are antecedent to decision making (Hunt and 

Vitell, 1986). This study moves prior research toward a more refined model through not only studying 

ethical evaluations, but also intentions. The latter constructs are tested via an experimental methodology 

in which unethical behavior and anticipated consequences are included within manipulated scenarios.  

The paper begins with a review of past research on ethics and gender-specific evaluations. Particular 

attention is paid to selling process evaluations, positive/negative outcome influences, monetary 

influences, and the effects of involved parties. A series of ethical experiments and scale responses is then 

conducted to determine and clarify varying gender responses. First, an updated version of the Personal 

Selling Ethics Scale (PSE-2) is used to replicate previously uncovered male/female evaluative differences 

related to ethical misconduct in personal selling situations. Second, a positive/negative outcome 

experiment tests the manner in which positive or negative consequences affect ethical evaluations. 

Finally, an experiment including money and affected parties studies the influence of money and involved 

parties on the relative ethical evaluations of each gender. The paper concludes by discussing the manner 

in which the findings may be useful in both academia and industry. The paper’s specific objectives are: 
 

1. Replicate previously uncovered differences in male/female personal selling ethics evaluations 

(Dabholkar and Kellaris, 1992; Donoho and Heinze, in press). 

2. Further the development of a gender/sales ethics model through studying the impact of situational 

factors (positive/negative outcomes, monetary involvement, affected parties) on gender-specific 

ethical evaluations. 

3. Suggest applications for use in both academia and industry. 
 

LITERATURE REVIEW AND HYPOTHESES 
 

Informing the current study are two streams of research. The first highlights the broad question of 

gender variation in ethical evaluations. The second reviews specific findings related to sales ethics 

evaluations.  

16 

 



Heinze and Donoho                                                                                                                                                       Advances in Business Research 

2011, Vol. 2, No. 1, 16-26 
 

17 
 

Ethical Evaluations and Gender 

 

Although early feminist researchers largely discounted the notion of innate gender differences (Grant, 

1988), research within the past 30 years has recognized innate gender variations (Pool, 1994; Smith and 

Rogers, 2000). The current sub-section reviews gender research centered on ethical evaluations. 

Both genders consider their own ethical standards as superior (Kidwell et al., 1987), but research 

indicates that males are generally more tolerant of ethical misconduct (Beu et al., 2003; Dobson and 

White, 1995; Gilligan, 1982). The gender evaluation divide has been criticized (Walker 1984; Sikula and 

Costa, 1994), but meta-reviews of ethical evaluation research generally support the contention that males 

are less ethically sensitive. For example, Collins (2000) reviewed forty-seven studies in the Journal of 

Business Ethics and found that few empirical analyses conclusively proved otherwise. Similarly, although 

half the studies (23 papers) reviewed by O’Fallon and Butterfield (2005) showed few evaluation 

differences, the remaining studies uniformly found men to be less ethically sensitive. Ford and 

Richardson (1994) reviewed fourteen studies and found a gender evaluation difference in half the studies. 

Similar findings emerged in Weeks et al., (1999) review of ethical evaluation research. Although each 

review uncovered a substantive number of studies with no gender evaluation differences, the remaining 

studies uniformly demonstrated less ethical sensitivity on the part of males. Male evaluations were less 

ethically sensitive across a range of issues, from sexual ethics to double standards to social concerns 

(Smith and Oakley, 1997; Vermeir and Van Kenhove, 2008). 

 In sales, specific gender evaluation differences have been studied using Dabholkar and Kellaris’ 

(1992) personal selling ethics scale (PSE). The PSE presents an array of ethical situations and asks 

respondents to identify the degree to which they feel the situation is ethical. In the original PSE, 

statistically significant gender differences emerged in four sales scenarios (Kellaris and Dabholkar, 1989). 

Evaluation differences have also emerged in a wide variety of subsequent studies using the PSE (Donoho 

et al., 1998, Donoho et al., Swenson, 2003). An updated version of the PSE, referred to as the PSE-2 

(Donoho and Heinze, 2011), is used to test ethical evaluation differences in the current study. In light of 

prior research and in order to provide a basis for the current study, the following hypothesis is proposed: 
 

Hypothesis 1: Females will be less tolerant of unethical behavior in sales ethics dilemmas than males. 
 

Sales Ethics Evaluations and Gender 

 

Providing a foundation from which to better understand the divergence in male/female sales ethics 

evaluations, Donoho and Heinze (in press) examined the evaluative effects of moral idealism and 

relativism. The two perspectives flow from Hunt and Vitell’s (1986) general theory of marketing and can 

offer a nuanced view of ethical gender variation (Schminke, 1997). Idealistic perspectives view activities 

as either moral or immoral, regardless of the consequences associated with the activity. Actions can be 

judged by universal principles as either right or wrong. Relativistic, or utilitarian, frameworks propose 

that actions and resulting consequences cannot be separated. Therefore, the relative morality of an action 

is dependent on the action’s effects. 

Although Donoho and Heinze (in press) found that males and females possess moderately disparate 

ethical frameworks, they also uncovered that idealism and relativism accounted for less than 9% of the 

variance in gender-related sales ethics evaluations. Additional factors behind evaluative disparity are 

clearly present and may include the presence of money and the parties that are affected by the action. 

Dabholkar and Kellaris’ (1992) original PSE study uncovered that the presence of money in a sales 

situation heightens ethical sensitivity. Likewise, Donoho and Heinze (2011) conducted a content analysis 

of recent sales material and found that the nature of involved parties (i.e. customers, company, 

competitors) is an important variable. Therefore, the following hypotheses are proposed in order to further 

explore moral frameworks, monetary involvement, and affected parties: 
 

Hypothesis 2: Both males and females will be less tolerant of sales dilemmas whose outcomes are 

negative than with sales dilemmas whose outcomes are positive. 



Heinze and Donoho                                                                                                                                                       Advances in Business Research 

2011, Vol. 2, No. 1, 16-26 
 

18 
 

 

Hypothesis 3: Both males and females will be less tolerant of sales dilemmas which directly involve 

money than with scenarios that do not directly involve money. 
 

Hypothesis 4: Both men and women will be less tolerant of ethical misconduct in sales ethics 

dilemmas that affect the following parties in the following order (a. Customers, b. Company, c. 

Competitors). 
   

Hypothesis 5: Ethical sensitivity (as measured by the PSE-2) will influence experimental ethical 

evaluations. 
 

Method 

 

To replicate prior findings regarding ethical evaluative disparity and to examine associated factors, the 

current study administered a scale questionnaire and conducted two experiments. The scale questionnaire 

consisted of an updated version of Dabholkar and Kellaris’ (1992) personal selling ethics scale. The new 

scale is referenced as the PSE-2 (see Donoho and Heinze, 2011). It presents 20 ethical dilemmas related 

to the personal selling process. The scale was used as a gender divide replication device, and results were 

compared with prior utilizations of the scale (Dabholkar and Kellaris, 1992, Donoho and Heinze, in 

press).  

 Following testing of the gender divide via the PSE-2, the study adapted an experiment from Tanner et 

al., 2009. The experiment was designed to examine the relative effects of utilitarian/relativistic factors on 

ethical evaluations. Using ethical evaluation as the dependent variable, the study reviewed two 

independent variables. The first was ethical behavior within the scenario (ethical or unethical), and the 

second was the outcome/consequence of the situation (positive or negative). The experimental situation 

and four experimental cells can be found in Exhibit 1. 
  

  

The second experiment was designed to examine the relative evaluative influences of monetary 

involvement and affected parties. Ethical evaluation was the dependent variable. The first independent 

variable was monetary involvement (money directly involved or not directly involved), and the second 

independent variable was the affected party (company, customer, or competitor). The experimental 

situation can be found in Exhibit 2. Respondents were asked to use a 7-point scale (“1” = very unethical; 

“7” = very ethical) to rate the ethical acceptability of the situation.  

 

Exhibit 1: Experimental Scenario 

  

Ethical/Unethical Behavior by Positive/Negative Outcome 
 

Scenario: Salesperson X graduated from college and went to work for Patman Paper Company, a provider of office supplies.  The 

salesperson had recently been married and life was good.  Sales were slow initially, and after 6 months, the salesperson had only sold 
80% of quota.  A brief meeting with the sales manager indicated that this was unacceptable performance and may result in 

termination. What bothered Salesperson X was there was an account worth 30% of quota just waiting for a deal to be made. 

 
Entertaining clients is not unusual for Salesperson X, especially for breakfast and lunch. The meeting with the Buyer went well and 

the Salesperson got a small order, but not enough to make quota. “There’s a lot more where that came from,” winked the Buyer to the 

Salesperson. An attractive person, the Buyer leaned over and put a hand on the Salesperson’s knee. “What do you say we head over to 
O’Malley’s for happy hour and talk it over?”  

 
Ethical/(Unethical) Behavior: The Salesperson replied, “My spouse is expecting me home for dinner soon, but how about if we meet 

for breakfast in the morning to discuss the rest of the order?”  (Salesperson X agreed to go to the bar and drank and danced with the 

Buyer until the wee hours of the morning.) 
 

Positive/(Negative) Outcome 

 

Positive/(Negative) Response: The Buyer agreed and the next morning placed a large enough order for the Salesperson to exceed 

quota by a generous amount. (The Buyer did not place the large order with the Salesperson as originally suggested.  Shortly thereafter, 

the Salesperson was terminated.) 



Heinze and Donoho                                                                                                                                                       Advances in Business Research 

2011, Vol. 2, No. 1, 16-26 
 

19 
 

 

Data Collection and Sample Characteristics 
 

Part of an on-going, multi-sample, multi-questionnaire study at medium-sized U.S. university in the 

west, the current study administered the PSE-2 to 669 undergraduate business students at two western 

universities. The experiments, conducted separately, netted 491 usable responses. The PSE-2 and 

experiments were administered using the survey/quiz function of the WebCT/Blackboard learning system. 

The multiple surveys took less than 30 minutes to complete and were a voluntary, extra credit assignment.  

Table 1 presents sample characteristics. Males comprised 58% of the sample. The 18-24 age range 

represented 87% of the sample. Most respondents were juniors (45.0%) or seniors (51.5%). Thirty-five 

percent were marketing majors. Seventy-six percent had 3 or more years of work experience, and only 

24% had 3 or more years of sales experience. Almost 40% had no sales experience. The sample generally 

represents today’s traditional, undergraduate business student enrolled in upper division classes. 
 

Table 1: Sample Characteristics by Gender (n = 491) 
 

 Male Female Total   

 Count Percent Count Percent Count Percent Chi-Sq. p 

Age       11.457 .022 

20 or younger 49 17.3 54 26.0 103 21.0   

21-22 137 48.4 105 50.5 242 49.3   

23-24 56 19.8 25 12.0 81 16.5   

25-34 35 12.4 17 8.2 52. 10.6   

35+ 6 2.1 7 3.4 13. 2.6   

Class Standing       2.315 .510 

Fresh/Soph 8 2.8 6 2.9 14 2.9   

Junior 121 42.8 100 48.1 221 45.0   

Senior 153 54.1 100 48.1 253 51.5   

Graduate 1 0.4 2 1.0 3 0.6   

Major       9.811 .133 

Accounting 19 6.7 19 9.1 38 7.7   

Info. Systems 21 7.4 5 2.4 26 5.3   

Economics 1 0.4 0 0.0 1 0.2   

Finance 20 7.1 10 4.8 30 6.1   

Management 50 17.7 37 17.8 87 17.7   

Marketing 100 35.3 72 34.6 172 35.0   

Other 72 25.4 65 31.3 137 27.9   

Work Experience       12.949 .044 

0 17 6.0 20 9.6 37 7.5   

1 23 8.1 8 3.8 31 6.3   

2 26 9.2 22 10.6 48 9.8   

3 37 13.1 18 8.7 55 11.2   

4 58 20.5 46 22.1 104 21.2   

5-9 97 34.3 85 40.9 182 37.1   

10+ 25 8.8 9 4.3 34 6.9   

Sales Experience       16.145 .013 

0 118 41.7 75 36.1 193 39.3   

1 67 23.7 39 18.8 106 21.6   

2 42 14.8 31 14.9 73 14.9   

3 21 7.4 18 8.7 39 7.9   

4 14 4.9 25 12.0 39 7.9   

5-9 14 4.9 19 9.1 33 6.7   

10+ 7 2.5 1 0.5 8 1.6   

Total 283 57.6 208  491 42.4   

Exhibit 2: Experimental Scenario 
  

Money Directly Involved (not directly involved) by 
  

Party Affected (Customer, Company, Competitor) 

 
Salesperson C was involved in a certain practice that might be questionable. The practice involved (did not involve) money in a direct 

way. The main party affected by C's action was a customer (company, or competitor). 



Heinze and Donoho                                                                                                                                                       Advances in Business Research 

2011, Vol. 2, No. 1, 16-26 
 

20 
 

Results 
 

 PSE-2 Results. Analyzing responses to the PSE-2 allowed for confirmation of Hypothesis 1 (see Table 

2 for description of all 20 PSE-2 ethical dilemma scenarios). Gender differences clearly exist in the PSE-2 

scale, and this finding confirms and mirrors the findings of prior studies (Dabholkar and Kellaris, 1992; 

Donoho and Heinze, 2011). Gender Table 2 presents the results. A MANOVA of the 20 PSE-2 scale 

items by gender was conducted, resulting in significant gender differences (Wilks’ Lambda = 2.651,        

p = .000).  Individual ANOVAS revealed that 6 scale items (offer monetary bribe to buyer, inflate 

expense report, sneak vacations on company time, sneak vacations on company time, false promises used 

to close sale, cheating on the bidding process and charging customers different prices) were responsible 

for the rejection. All six items were viewed as less ethical by females (p < .05). Additionally, the mean for 

all 20 PSE-2 items was significantly lower for females than for males (F = 3.83, p < .033). Thus, females 

are less tolerant of ethical misconduct in sales than are males.  
  

Table 2: Gender Differences in the PSE-2 Scale (1 = very unethical, 7 = very ethical) 
 

PSE PSE2 Ethical Scenarios Male SError Female SError F Sig. F 

1 Offer monetary bribe to buyer 2.74 .07 2.52 .08 4.76 .029 

2 Steal from competitor at trade show 1.95 .06 1.82 .07 1.97 .161 

3 Inflate expense report 2.61 .07 2.18 .08 18.48 .000 

4 Sneak vacations on company time 2.55 .07 2.29 .08 6.62 .010 

5 Conflict of interest with company (moonlighting) 3.33 .09 3.15 .10 1.98 .160 

6 Lavish entertaining 3.71 .08 3.50 .09 2.99 .084 

7 Cheating on sales contest 2.43 .07 2.30 .08 1.75 .186 

8 False promises used to close sale 2.31 .06 2.13 .07 4.32 .038 

9 Cheating on bidding process 4.02 .08 3.77 .09 3.99 .046 

10 Fear exploitation used to close sale 4.04 .08 4.10 .09 0.23 .630 

11 Frequent flyer abuse 3.22 .09 3.26 .10 0.81 .777 

12 Information leaks about one customer to another 2.95 .07 2.89 .08 0.39 .535 

13 Withholding information to customer about product 3.90 .07 3.70 .08 3.29 .070 

14 Defamation of a competitor 3.58 .07 3.48 .08 1.02 .314 

15 Tying agreement 3.46 .08 3.42 .09 0.13 .715 

16 Charging customer different prices 3.93 .09 3.44 .10 14.30 .000 

17 Puffery 5.11 .08 5.20 .09 .56 .457 

18 Reciprocity 4.42 .08 4.63 .09 2.95 .086 

19 Special Treatment 4.48 .08 4.61 .09 1.00 .318 

20 Scarcity (excessively limited choice) 3.59 .08 3.63 .09 0.11 .745 

PSE-2 PSE-2 Mean (of all scale items) 3.42 .03 3.30 .04 4.580 .033 

 MANOVA (Wilks’ Lambda) PSE-2 20 scale items by Gender 2.651 .000 

Cronbach Alpha = .802 

 

Table 3: Means Ethical Evaluation by Gender of Salesperson and Gender 
 

  PSE 7 PSE 9 PSE 2 PSE X 

Male Male Salesperson 2.48 4.21 2.27 4.17 

 Female Salesperson 2.64 4.17 2.28 4.14 

 Total 2.57 4.19 2.27 4.16 

      

Female Male Salesperson 2.37 3.82 2.22 4.37 

 Female Salesperson 2.38 4.13 2.07 3.96 

 Total 2.38 3.98 2.15 4.18 

      

Total Male Salesperson 2.43 4.05 2.25 4.25 

 Female Salesperson 2.53 4.15 2.19 4.06 

 Total 2.48 4.10 2.22 4.17 

      

PSE Scale Male 2.43 4.02 1,95 n/a 

Items Female 2.30 3.77 1.82 n/a 

 

Additional analysis utilizing the PSE-2 was also conducted to determine the competence of the PSE-2 

in predicting how current student respondents will make ethical evaluations in their future industrial 

careers. Four scenarios were chosen based on their representation of the full ethical spectrum. Results (see 

Table 3 above) indicated that the gender of the salesperson did not significantly affect ethical evaluations. 



Heinze and Donoho                                                                                                                                                       Advances in Business Research 

2011, Vol. 2, No. 1, 16-26 
 

21 
 

Overall, ethical sensitivity was significantly related to each scenario, and therefore, the PSE-2 scale mean 

is a good predictor of how “future managers” will make their ethical evaluations. 

Note: PSE-7, 9, and 2 are “repeats” from the actual scale modified for gender. The PSE-2 scale was 

part of Survey 1, and the gender manipulation was Part of Survey 2.   

Experiment 1 Results. A manipulation check of the first experiment indicated that the ethical and 

unethical scenarios were clearly evaluated as different (F = 35.3, p = .000). To test H2 (both males and 

females will be less tolerant of sales dilemmas whose outcomes are negative than with sales dilemmas 

whose outcomes are positive), a series of tests was conducted.  

 First, it was hypothesized that scenarios with positive outcomes would be evaluated as more ethical 

than scenarios with negative outcomes. This hypothesis was not confirmed (F = 1.2, p = .279). However, 

there was an interaction effect between ethical/unethical behavior and outcome (F = 8.2, p = .004). For 

the ethical behavior scenario, the scenario was considered more ethical if there was a negative outcome, 

while for the unethical behavior, the scenario was considered more ethical if there was a positive 

outcome.  

 Second, it was hypothesized that females would evaluate the scenarios as less ethical than males. The 

hypothesis was confirmed (F = 10.4, p = .001) and was followed by a test of the hypothesis that ethical 

evaluation would be lower for respondents who have lower PSE-2 mean scores (ethically sensitive). Tests 

results confirmed this hypothesis (F = 10.4, p = .001).  

 Next, in line with the Hunt & Vitell (1986) model of marketing ethics, it was hypothesized that ethical 

evaluations are positively related to ethical intentions. Ethical intentions were measured via two questions 

that addressed 1) personal ethical intentions regarding the situation and 2) the relative degree to which the 

situation fell within accepted social norms. Results confirmed the hypothesis (males r2 
=.392, females r

2 
= 

.621, total r
2 
= .522). Ethical evaluations are positively related to ethical intentions. Likewise, social norm 

evaluations are positively related to social norm ethical intentions (males r
2 
= .208, females r

2 
= .149, total 

r
2 

= .297). Finally, personal ethical evaluations have a larger effect on ethical intentions than do social 

norm evaluations (Males: norm eval std. beta = .244, personal ethical eval std. beta = .499; Females: norm 

eval std. beta = .373, personal ethical eval std. beta = .519; Total: norm std. beta = .277, personal ethical 

evaluation std. beta = .537). For females, the “normative” effect is larger (42% = .373/.892) than for 

males (33% = .244/.743), indicating that females are more prone to take the views of others into 

consideration when making their own ethical evaluations.  
  

Table 4: Means Ethical Evaluation by Behavior (Ethical, Unethical) and  

Outcome (Positive, Negative) (1=strongly disagree, 7=strongly agree) 
 

Male Positive Outcome Negative Outcome Total 

Ethical Behavior 4.94 5.26 5.11 

Unethical Behavior 3.96 3.49 3.76 

Total 4.42 4.45 4.43 

    

Female Positive Outcome Negative Outcome Total 

Ethical Behavior 4.37 5.31 4.68 

Unethical Behavior 2.87 2.85 2.86 

Total 3.72 3.66 3.69 

 

Table 5: ANOVA Ethical Evaluation by Behavior (Ethical, Unethical) and Outcome (Positive, Negative) 
 

Source df Mean Square F Sig Eta squared 

Corrected Model 8 53.7 18.8 .000 .238 

Ethical/Unethical Behavior 1 320.7 112.0 .000 .189 

Positive/Negative Outcome 1 3.36 1.2 .279 .002 

Behavior by Outcome 1 23.5 8.2 .004 .017 

Gender by Behavior 1 10.2 3.6 .059 .007 

Gender by Outcome 1 5.7 2.0 .159 .004 

Gender by Behavior by Outcome  .4 0.1 .707 .000 

Gender 1 29.9 10.4 .001 .021 

PSE-2 Mean 1 33.1 11.6 .001 .023 

 



Heinze and Donoho                                                                                                                                                       Advances in Business Research 

2011, Vol. 2, No. 1, 16-26 
 

22 
 

Table 6: Regression: Intentions by Ethical Evaluations 

Dependent Variable: SEXH3 I would act in the very same way 

Independent Variables: 

SEXH I consider the action very ethical 

SEXH2 Most people consider the action very ethical 

PSE-2 Sales Ethics Scale (Ethical Sensitivity) 

(1=strongly disagree, 5=strongly agree) 
 

 Adj. R2 F Sig. F Std Beta t p 

Males .418 112.2 .000    

I consider the action very ethical                                                 .499 9.3 .000 

Most people consider the action very ethical    .214 4.0 .000 

       

Females  .686 265.7 .000    

I consider the action very ethical    .519 9.9 .000 

Most people consider the action very ethical    .373 7.1 .000 

       

Total  .563 406.8 .000    

I consider the action very ethical    .537 15.1 .000 

Most people consider the action very ethical    .277 7.8 .000 

 

Table 7: Regression Intentions by Ethical Evaluation Personal and Social Norm 
 

I would act in the same way Adj. R2 F Sig.F Std eta t p 

Males: I consider the action very ethical                                              .392 201.5 .000 .628 14.2 .000 

Females: I consider the action very ethical .621 398.3 .000 .789 20.0 .000 

Total:  I consider the action very ethical .522 690.1 .000 .723 26.3 .000 

Most people would act in the same way Adj. R2 F Sig.F Std eta t p 

Males: Most people consider the action very ethical                                            .208 165.3 .000 .456 12.9 .000 

Females: Most people consider the action very ethical .149 55.5 .000 .390 7.5 .000 

Total:  Most people consider the action very ethical .297 103.1 .000 .547 10.2 .000 

 

In summary, results associated with Experiment 1 (see Tables 4-7 above) indicate that ethical 

evaluations were not different in the positive or negative outcome conditions (p-.235), females evaluated 

the scenario as less ethical than their male counterparts (p = .001), and the experimental factors explained 

about 21% of the variance in ethical evaluations. 

 Experiment 2 Results. Experiment 2 was conducted to test H3 (both males and females will be less 

tolerant of sales dilemmas which directly involve money than with scenarios that do not directly involve 

money) and H4 (both men and women will be less tolerant of ethics situations that affect the following 

parties in the following order (a. Customers, b. Company, c. Competitors)).  

 Results indicate that scenarios in which money is directly involved are viewed as less ethical than 

those in which money is indirectly involved (F = 5.6, p = .019). Likewise, it was partially confirmed that 

scenarios in which customers are affected are viewed as less ethical than those in which the company or 

the competition is affected (F = 7.5, p = .001). However, pairwise comparisons showed that the difference 

lies between customer/company and competitors, but not between customers and company. In the 

scenario in which money was directly involved, females ordered their evaluations in the hypothesized 

manner (customers, company, competitors).  

 Second, females were found to evaluate the scenarios as less ethical than males (F = 9.9, p = .003).  

Finally, H5 was confirmed. The PSE-2 was found to be a good predictor of ethical evaluations in 

Experiment 2 (F = 57.7, p = .000).   

In summary, Experiment 2 results (see Tables 8-10 below) indicate that respondents evaluate 

situations involving money as less ethical than situations in which money is not directly involved 

(p<.062). Additionally, situations that affect customers or the company are evaluated as less ethical than 

situations that affect competitors. Females evaluate the scenario as less ethical than their male 

counterparts (p = .001), and the experimental factors explained approximately 5% of the variance in 

ethical evaluations. 

 

 



Heinze and Donoho                                                                                                                                                       Advances in Business Research 

2011, Vol. 2, No. 1, 16-26 
 

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Table 8: Means Ethical Evaluation by Money Involved and Party Affected 
 

Male Customer Company  Competition Total 

Money Directly Involved 2.96 2.74 3.43 3.04 

Money Not Directly Involved 3.26 3.28 3.41 3.32 

Total 3.1 3.02 3.42 3.18 

     

Female Customer Company  Competition Total 

Money Directly Involved 2.23 2.69 3.11 2.66 

Money Not Directly Involved 2.75 2.65 3.13 2.81 

Total 2.51 2.67 3.12 2.73 

 

Table 9: ANOVA Ethical Evaluation by Money Involved and Party Affected 
 

Source df Mean Square F Sig Eta squared 

Corrected Model 12 11.9 8.4 .000 .173 

Money Involved (directly, not directly) 1 8.0 5.6 .019 .012 

Party Affected (Company, Customer, Competitor) 2 10.7 7.5 .001 .030 

Gender by Money Involved  .4 .3 .570 .001 

Gender by Party Affected  1.7 1.2 .303 .005 

Money Involved by Party Affected  2.3 1.6 .206 .007 

Gender by Money Involved by Party Affected  2.5 1.8 .170 .007 

Gender  13.0 9.9 .003 .019 

PSE-2 Mean  82.6 57.7 .000 .108 

      

 

DISCUSSION, LIMITATIONS, AND RECOMMENDATIONS 
 

PSE-2 
 

Overall conclusions confirm prior findings (Dabholkar and Kellaris, 1992; Donoho and Heinze, in 

press), indicating that females are often less tolerant of ethical misconduct in the sales arena. In the 

current study, females were more sensitive across the 20 situational items in the PSE-2 and in two small 

experiments that manipulated several ethical factors.   

 Although the current study merely confirmed prior gender evaluation research utilizing the Personal 

Selling Ethics Scale (Dabholkar and Kellaris, 1992; Donoho and Heinze, 2011), it did additionally 

demonstrate the scale’s ability to predict ethical evaluations. The utility of the scale is therefore markedly 

increased for those within academia and industry.  
 

Experiment 1 
 

 The model associated with Experiment 1 explained approximately 24% of the variation in ethical 

evaluation, with the ethical/unethical behavior factor explaining a larger portion of the variation. If ethical 

behavior is in question, both males and females evaluated negative outcomes as more ethical than positive 

outcomes. Rescheduling the appointment for the next morning was evaluated as quite ethical, and being 

fired for doing the right thing was evaluated as more ethical than making the sale. Therefore, both females 

and males “rewarded” ethical behavior when it was accompanied by a known, negative outcome. 

 However, with the unethical behavior in Experiment 1, the outcomes did not affect female evaluations. 

Conversely, male evaluations were affected. Males viewed the unethical scenario as less ethical when 

associated with a negative outcome than when associated with a positive outcome. An explanation could 

be the impact of relativism/utilitarianism. Prior research on moral frameworks and sales evaluation 

indicates that males are more relativistic/utilitarian than females (Donoho and Heinze, in press). Since 

females lean toward moral idealism in sales scenarios (Donoho and Heinze, in press), the positive or 

negative outcomes associated with Experiment 1 did not pragmatically influence their judgment of the 

relative morality of the action. However, relativistic males were more likely to color their ethical 

evaluations based on situational outcomes.  

 Limitations associated with Experiment 1 include the unrealistic fact that the “consequence” of the 

described action was known with 100% probability. In “real-life” situations, consequences have unknown 



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probabilities and weights must be determined by the individuals making the evaluation (Hunt and Vitell, 

1986).  

 Second, confounding variables may have colored responses. For example, the description of the “new” 

spouse may have unintentionally increased ethical sensitivity.   

 Finally, Experiment 1 was gender neutral. Most respondents likely assumed that the buyer was a 

member of the opposite sex, and this assumption could influence responses. Future studies should include 

a follow-up question in which respondents are asked to identify their assumptions regarding the buyer’s 

gender.   
 

Experiment 2 
 

The second experiment clarified evaluative differences related to important factors such as the 

presence of money and the nature of the involved parties. As expected, the presence of money increases 

evaluative stringency. Likewise, the involved party increases ethical sensitivity to the situation, with 

situations involving customers and the company being evaluated with less tolerance. Overall, females 

were shown to be less tolerant of ethical misconduct than were males. 
 

Recommendations 
 

 Although prior research indicates that moral idealism and relativism are not the only drivers behind 

male/female evaluative differences (Donoho and Heinze, in press), the influence of these variables is still 

strongly felt. Gender differences in Experiment 1 can be partially, yet plausibly, explained by gender-

related moral stance variation. Experiment 2 added additional factors by which the overall model is 

strengthened. Nevertheless, the importance of moral frameworks remains and should be considered as a 

key component in academic and corporate ethical sales training.   

The study’s first recommendation moves beyond gender and highlights the importance of including 

ethical sales training in both academia and industry. The overall mean PSE-2 score (males, 3.42; females 

3.30) indicate that today’s students have fairly tolerant evaluations of ethical misconduct in sales. Most 

PSE-2 scenarios involve serious ethical breaches, but respondents averaged an evaluation that fell 

between “somewhat unethical” and “neither unethical nor ethical.” This average response indicates that a 

large percentage of respondents are tolerant of ethical misconduct in sales.  

The study’s second implication concerns the use of morally idealistic frameworks in sales training. 

Regardless of gender, individuals who favor idealistic frameworks exhibit increased ethical sensitivity. 

Idealistic approaches also provide a foundation from which to discuss situational factors such as the 

presence of money or variation in the involved parties. Therefore, encouraging idealistic orientations may 

increase the likelihood of positive ethical responses to ethically questionable sales scenarios. Teachers 

and training managers can incorporate idealistic perspectives through using ethical codes or practical 

representations of ethical codes (e.g. PSE-2). 

Third, situational and relativistic perspectives should also be included in training since there are a 

large number of individuals (especially men) who hold these perspectives (Donoho and Heinze, in press). 

These orientations can be addressed through reviewing situational variables (such as the presence of 

money or the unique party involved) within the context of ethically idealistic frameworks. In this manner, 

relativists can be introduced to the utility and necessity of idealistic frameworks.   

Finally, additional work is required to develop a truly comprehensive model of ethical sales 

evaluations and gender. The current paper highlights important elements of the model, but further 

research is still required. 
 

CONCLUSION 
 

Despite the growth in sales and the increasing number of women in sales-related occupations, ethical 

issues continue to negatively color public and private perceptions of sales. Since females are generally 

more sensitive to ethical issues in business, the current study reviewed ethical evaluations variations 



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through testing gender responses to ethical situations in sales. The Personal Selling Ethics Scale (PSE-2) 

was used to confirm gender-related evaluative differences toward ethical misconduct in personal selling 

situations. Second, a positive/negative outcome experiment tested the manner in which positive or 

negative consequences affect ethical evaluations. Finally, an experiment including money and affected 

parties studied the influence of money and involved parties on the relative ethical evaluations of each 

gender. Findings indicated that 1) women are less tolerant of ethical abuse in personal selling situations, 

2) ethical evaluations do not vary based on situational outcomes, and 3) situations involving money, 

customers, and/or the companies that employ salespeople are evaluated with less ethical tolerance. 

Findings may be useful for pedagogical preparation and for the development of codes and training 

manuals within academia and industry.  
 

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Tim Heinze is an assistant professor of marketing at California State University, Chico. He received his 

Ph.D. in organizational management with an emphasis in marketing from Capella University. His current 

research interests include sales ethics, Generation Y marketing, and impression management. He has 

published in Journal of Marketing Education, Research in Consumer Behavior, Journal of Business & 

Economics Research, and others. 
 

Casey Donoho is an associate professor of marketing at California State University, Chico. He received 

his Ph.D. in marketing from University of Oregon. His current research interests include sales ethics, 

marketing case research, and sales education pedagogy. He has published in Journal of Business 

Research, Journal of Marketing Education, Journal of Services Marketing, Case Research Journal, and 

others.  


