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“Demonstrating the Need for Effective Business Ethics: An Alternative Approach,” located on this week’s

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a 700- to 1,050-word analysis of the article. Include the following:

Describe the approach mentioned in the article.

Identify the strengths and weaknesses in the approach.

Explain how the approach mentioned in the article differs from other approaches for individual, ethical decision making.

Explain how ethical judgment and ethical behavior were represented in the article. What is the relationship between the two?

Describe possible individual ethical problems that may arise in the business environment, and explain how the approach mentioned in this article may apply to those situations.


your paper according to APA guidelines.

Business and Society Review 117:2 221–232
Demonstrating the Need for
Effective Business Ethics:
An Alternative Approach
Since the financial crisis, the malfeasance of business
leaders has been a recurring theme in the news, along
with calls for increased regulation and oversight. This
focus on the ethics of the business community raises a
concern about the ethics of those in business or going
into business. The ethics of business people and business students has been explored by a number of
researchers using survey techniques. We propose and
report the results of an alternative method for investigating unethical behavior by students. In a motivated
economic experiment with introductory level students,
we find that business students were almost twice as
likely to lie for a monetary reward as students in other
disciplines, demonstrating the need for effective business
Jason Childs is Associate Professor, University of Regina, Regina, SK, Canada. E-mail:
© 2012 Center for Business Ethics at Bentley University. Published by Blackwell Publishing,
350 Main Street, Malden, MA 02148, USA, and 9600 Garsington Road, Oxford OX4 2DQ, UK.
usinesses have received a remarkable amount of negative
press since the financial crisis. The conviction of Bernard
Madoff, the civil case against Goldman-Sachs for fraudulent misconduct, and the accusations of “robo-signing” foreclosures all contribute the public belief that those in business are
untrustworthy. Incidences of fraud have not been restricted to the
banking sector. The examples of Enron, WorldCom, and Parmalat
are still cited as evidence of unethical behavior in business. Public
reports of losses to employee theft and fraud, approximately one
trillion dollars in the United States alone (Association of Certified
Fraud Examiners), further harm the reputation of business.
The public perception begs the question: are those in the world
of business truly more prone to dishonesty than those in other
fields? A growing body of literature attempts to address this issue.
Direct surveys of business people are rare, but some have found
that dishonest behavior is not uncommon (Greeman and
Sherman 1999). Dishonesty in the workplace has been linked to
cheating in university and college (Lawson 2004; Nonis and Smith
2001; Simkin and McLeod 2010 p. 443; Sims 1993; Teixeira and
Rocha 2010), making surveys of students a viable alternative. As
researchers have more access to students, more work has been
done exploring the ethical behavior of students in business
schools and business programs; Day et al. (2010) and Brown and
McInerney (2008) both provided reviews of the existing literature.
In general, this research finds that academic dishonesty is
extremely common. In short, students cheat.
The ubiquity of cheating by students is a concern for both
academic institutions and future employers. If cheating is prominent in a program or institution, the reputation of the school falls,
reducing the value of the degree to potential students. Detecting
and preventing cheating is clearly in the best interest of any
academic institution. From the viewpoint of a future employer,
academic dishonesty is a concern as well. If a degree is obtained
through fraud, the employer cannot be certain that the applicant
actually has the skills the degree is supposed to indicate. This
would cause employers to demand more experience of job applicants. Of course, job experience tends to be associated with
demands for higher pay.
A natural starting place is to see if students differ by discipline
of study. Given the current attitudes portrayed in the media, it
makes particular sense to focus on business students. There is
disagreement in the literature about the relationship between field
of study and dishonesty. Some find that business students are
significantly more likely to engage in dishonest behavior than
students in other disciplines (Bernardi et al. 2004; Smyth and
Davis 2004). Other research has found no relationship between
dishonesty and field of study (Klein et al. 2007; Molnar et al.
2008; Smyth et al. 2009; Zopiatis and Karmbia-Kapardis 2008). If
business students are in fact more prone to dishonest behavior, it
will be in the best interest of business schools to take steps to
improve the ethics of business students both while they are
studying and later in life.
The studies cited earlier all report the results of unmotivated
surveys. Given the conflicting results of this literature, an alternative method of assessing students’ propensity for dishonesty is
justified. We report the results of an economic experiment with
monetary incentives in which subjects were given an opportunity
to lie. In the experiment, business students were significantly
more likely to lie than students in all other disciplines.
In the next section, we make the case for an alternative method
of assessing students’ behavioral tendencies. We then present the
experimental design. This is followed by the results of the experiment. In the final section, we offer some discussion of the results
and their implications.
The existing literature on the likelihood of dishonest behavior
of students makes use of two different types of unmotivated
surveys. One approach is to ask students to report their own or
other’s dishonesty, generally in terms of academic cheating. This
approach has two limitations. First, there is no general definition
of cheating among students. For example, while some students
may consider sharing information about an assignment cheating,
others may simply view it as teamwork. A well-designed survey
can address this, but it does make the survey more complex and
time-consuming to complete. The larger limitation of this type of
survey is that it relies on honest reporting of dishonest behavior.
If business students are actually more honest than students in
other disciplines, and honesty includes survey responses, business students would appear to be less honest than others
because they told the truth about lying on a survey. For example,
if those business students who score highly on a test of Machiavellianism are more willing to admit to dishonest behavior, they
would appear to be more dishonest without actually being so.
This could explain the findings of Bloodgood et al. (2010) and
Tang and Chen (2008). This problem of honest reporting extends
to the other survey method, which asks students about their
attitudes toward dishonesty and cheating. The responses of students who are dishonest on a survey could indicate that they find
dishonesty objectionable even though they have no reservations
about taking such actions themselves.
Another weakness of the existing literature is that it focuses on
academic dishonesty. In the minds of students, academic dishonesty occurs at the expense of the course instructor. Students’
attitudes toward their instructors are potentially different from
their attitudes toward employers, other students, or future
clients. In existing studies of academic dishonesty, a difference
between business and nonbusiness students may arise due to
how different students view their instructors and their program.
This may play a part in explaining why students are found to be
more dishonest than practitioners (Teixeira and Rocha 2010).
Techniques developed in experimental economics offer an alternative to surveys. Instead of being asked whether or not they have
been dishonest, an experimental environment gives students an
opportunity to be dishonest in exchange for monetary gain. The
choices of students in this environment can be directly observed,
meaning the analysis is based on actual behavior rather than
self-reported actions.
There is a growing body of literature in both economics and
business that makes use of motivated experiments to further our
understanding of dishonesty. Mazar and Ariely (2006) and Mazar
et al. (2008) used a simple testing environment to explore the
internal rewards, social norms or self-concept, threshold explanation of cheating. Different groups of students were asked to find
pairs of numbers in matrices that summed to 10. The control
group received only the matrices and a sheet on which to report
the number of pairs found. Those in the treatment groups were
asked to perform short tasks1 before searching for pairs of
numbers and were provided with an opportunity to cheat. The
groups that were provided the opportunity to cheat reported
higher average scores than groups that did not have the opportunity to cheat. The increased scores are interpreted as evidence
cheating by the authors. While the treatments explored are interesting, this approach is limited by the fact that dishonesty can
only be inferred from aggregate behavior and not directly observed
at an individual level. Observing only group behavior makes it
difficult to determine the impact individual characteristics have
on dishonesty.
Another, arguably simpler, approach is based on a sender–
receiver environment initially used by Gneezy (2005). In this type
of experiment, one subject is shown a set of two payoffs. This
subject then sends a message (making them a sender) to the other
subject (the receiver) about the two payoffs. The message either
honestly identifies which payoff would yield the most money to the
receiver or is a lie. The direct observation approach avoids the
limitations of other methods.
This approach has been used to consider the relationship
between a number of factors and the propensity to lie. The original work (Gneezy 2005) examined the impact of different levels of
monetary incentives on lying. Dreber and Johannesson (2008),
Erat and Gneezy (2011), and Childs (2012) examined lying by
gender. None of the preceding work has considered the relationship between the chosen field of study and lying. We use this
sender–receiver environment to examine the relationship between
field of study and willingness to lie.
The experimental environment is almost identical to that used by
Gneezy (2005).2 Individuals in separate rooms were paired with an
unknown partner. Subjects in one room were assigned the role of
sender and those in the other room the role of receiver. The
sender sees two different payoffs: one labeled A and the other B.
For half the senders, A offered a payoff of ($15, $5), $15 for the
sender and $5 for the receiver, while B offered a payoff of ($5,
$15). For the remaining senders, the payoffs were A ($5, $15) and
B ($15, $5).
In presenting these payoffs to the senders, two forms were
used. The first, the gains treatment, was identical to treatment
three by Gneezy (2005) in which all payoffs are framed as gains.
In the second form, the losses treatment, senders were initially
endowed with a voucher for $20, and the payoffs were framed as
losses. While there was a difference in framing, the net payoffs in
both forms were identical.
The sender then chooses one of two message to send his or her
partner; either “Option A will earn you more money than option
B” or “Option B will earn you more money than option A.” A lie is
defined as a message the sender knows to be inaccurate.3 Therefore, when the payoffs shown to the sender were actually A ($15,
$5), B ($5, $15) sending the message “Option A will earn you more
money than option B” is a lie.
After having received a message from the sender, receivers
choose which payoff both will receive. The receivers must make
this choice with no information other than the sender’s message.
After choosing their message or selecting payoffs, the subjects
were asked to complete a brief survey. In this survey, the subjects
were asked to identify their major and faculty of study.
The experiment was conducted with 200 students, 100 senders
and 100 receivers, recruited from introductory economics classes
at a Western Canadian university. The composition of the selfreported fields of study is consistent with the class records. The
experiment was originally designed to consider the impact of
framing on lying.4 In this article, however, we focus only on the
relationship between faculty of study and behavior. All participants remained anonymous to their partners. The actions of three
subjects were dropped from the analysis for poor understanding
of the instructions.
The results of the experiment are shown in Figure 1.
In total, 55 of 97 (57 percent) subjects sent incorrect messages
with 38 of 54 (70 percent) business students and 17 of 43
Frequency of Lying by Faculty of Study and
PorÆŸon of Subjects Lying
(40 percent) nonbusiness students lying.5 This difference is statistically significant (P value 0.002).6 It is possible that students in
different faculties reacted to the framing differently. The frequency
of lying was higher for both groups in the loss treatment, increasing from 20 of 31 (64.5 percent) to 18 of 23 (78 percent) business
students (P value 0.274) and from six of 19 (31.5 percent) to 11
of 24 (46 percent) nonbusiness students (P value 0.342). The
observed difference between subjects based on field of study is
statistically significant regardless of treatment (P = 0.024 in the
gains treatment and P = 0.022 in the losses treatment).
Given that lying is only profitable if the false information is
believed, it is also important to consider trust. The actions of
three receivers are not included in this analysis as they did not
identify their faculty of study. From a receiver’s point of view,
there is no difference between the treatments so the actions of
all the receivers were pooled. Twenty-four of 35 (69 percent)
business students trusted the messages they received and chose
the recommended action, whereas 46 of 62 (74 percent) nonbusiness students trusted their senders (P value 0.553). Though
not statistically significant, a lower level of trust by business
students is reasonable given their greater propensity to lie.
Lying, particularly employee theft and fraud, is a major problem
for both businesses and regulators, costing American businesses
an estimated $994 billion in 2008 (Association of Certified
Fraud Examiners n.d.). In addition to the costs of internal theft
and fraud, the business community around the world has seen
several high-profile cases of dishonesty (Goldman-Sachs) and
outright fraud (Bernard Madoff) in recent years. The Sarbanes–
Oxley Act illustrates the increase in regulation that can occur in
response to high-profile instances of dishonesty by business
Given the explicit costs of dishonest dealing and the likely costs
of increased regulation and oversight, businesses are rightly concerned with reducing dishonesty in the workplace. In order to
reduce dishonesty, it must be understood. Many researchers have
demonstrated a link between dishonest behavior as students and
malfeasance in professional life (Lawson 2004; Simkin and
McLeod 2010, p. 443; Sims 1993; Teixeira and Rocha 2010).
The next logical step is to understand the nature and motives
of students when they engage in dishonesty. This question has
generated a wealth of literature. One of the recurring themes is
whether or not students in business have a higher propensity to
act dishonestly than others. If business students are in fact more
likely to be dishonest, much can be gained by focusing on the
ways in which business students differ from students in other
faculties and programs.
The existing literature on academic dishonesty reports mixed
results. Some demonstrate that business students are in fact
more dishonest or are more accepting of dishonest behavior (Bernardi et al. 2004; Smyth and Davis 2004), while others have
found no difference between students in different faculties (Klein
et al. 2007; Molnar et al. 2008; Smyth et al. 2009; Zopiatis and
Karmbia-Kapardis 2008).
The method of acquiring data on dishonesty binds all these
studies together. These studies use surveys of students as their
data source. This relies on students to honestly tell their professors that they have in fact engaged in academic dishonesty.
Surveying students in this way could lead to findings that are the
reverse of actual behavior. Groups of students that were in fact
more honest about cheating on the survey would be seen as more
dishonest than other students. Surveys of attitudes toward dishonesty are illuminating in their own right but are subject to the
same concern.
The focus on academic misconduct creates another confounding factor. Students generally believe that the victims of cheating
or plagiarism are their instructors and not fellow students or
society in general. Some researchers have considered exactly this
sort of factor in considering the impact of teaching vignettes on
students’ attitudes (Day et al. 2010) and found that the characteristics of the instructor have an impact on students’ attitudes
toward dishonesty. In one extreme case, the instructor facilitated
cheating by students (Jones and Spraakman 2011). The victim of
fraud, particularly in the manipulation of financial reports, is
often an anonymous public. Therefore, if the characteristics of the
instructor are central to academic cheating, the individual characteristics that lead to academic misconduct may not be accurate
predictors of professional misconduct despite the correlation
between the types of misconduct.
Instead of surveys, economic experiments with monetary incentives can be used to explore dishonest behavior. Mazar and Ariely
(2006) and Mazar et al. (2008) used a simple search task to
provide subjects with an opportunity to lie to increase their monetary payoff. While individual actions were not directly observed,
they did observe an increase in aggregate reported successes
when the subjects had the opportunity to cheat. The authors
found that a number of factors have an influence on cheating,
such as signing an ethics code statement, writing down the Ten
Commandments, etc. However, the inability to observe individual
choices makes this environment unsuited to researching the
impact of individual characteristics on dishonesty.
We use another experimental environment, originally developed
by Gneezy (2005), to explore the link between chosen field of
study and dishonest behavior. In this environment, individual
subjects have an opportunity to increase their payoffs by lying to
an anonymous partner. We discover that those subjects who
identified themselves as business students are significantly more
likely to lie than those in any other discipline.
There are a variety of ways in which business students could
differ from those in other disciplines. For example, individuals
who are more motivated by money may be more likely to pursue
a business degree than others. Business students could also be
more competitive by nature, leading to their being more likely to
make choices that improve their payoffs at the expense of others,
whether or not those choices involve lying (Hurkens and Kartick
2009). Further, business students may be more Machiavellian
than those in other disciplines, and this willingness to pursue an
end may explain the observed difference.
The subjects in this experiment were recruited from introductory classes in economics. The business program at the university
in question requires that students take an ethics class in their
third year of study, meaning that the majority of business students had not completed an ethics course. Thus, this experiment
does not provide a basis for assessing the effectiveness of the
required ethics course, only the need for it. By allowing researchers to directly observe dishonest behavior in response to known
motivation, future work can explore the impact of these factors
and others, such as taking an ethics course, on a subject’s
directly observed propensity to lie.
1. The extra tasks were things such as listing 10 books they had read
in high school, listing the Ten Commandments, signing an honor code
statement, and so on.
2. Full details and experimental instructions are available from the
3. This definition approximates the definition of fraud.
4. While the framing did have an impact on the frequency of lying, the
frequency of lying is not statistically significant different (two-sided
Pearson chi-square P = 0.335).
5. The subjects identified six different faculties of study—business,
arts, science, engineering, education, and social work. Only students in
business were statistically different.
6. All P values reported are from two-sided Pearson chi-squared tests.
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