Research on Professional Responsibility and Ethics in
Accounting
The Effectiveness of Instruction in Accounting Ethics Education: Another Look
David J. Burns James A. Tackett Fran Wolf
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THE EFFECTIVENESS OF
INSTRUCTION IN ACCOUNTING
ETHICS EDUCATION:
ANOTHER LOOK
David J. Burns, James A. Tackett and Fran Wolf
ABSTRACT
This study examines the effectiveness of instruction in accounting ethics
as measured by the impact of that instruction on the incidence of student
plagiarism in a college writing assignment.
This study avoids the potential problems inherent in measuring
Machiavellianism via a psychological questionnaire by using a “reverse
methodology,” whereby Machiavellianism is assessed directly from
behavior.
The results support past research suggesting that traditional collegiate
ethical education may not affect students’ ethical choices. The findings
also suggest that increasing penalties for ethical failures may be an effective means of deterring students and business professionals from engaging in inappropriate activities.
This study supports the use of a behavioral measure of Machivellianism
as a means of evaluating the effectiveness of alternative instructional
Research on Professional Responsibility and Ethics in Accounting, Volume 19, 149 180
Copyright r 2015 by Emerald Group Publishing Limited
All rights of reproduction in any form reserved
ISSN: 1574-0765/doi:10.1108/S1574-076520150000019015
149
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DAVID J. BURNS ET AL.
methods in ethics. This behavioral approach is superior to the traditional
questionnaire methodology because Machivellianism is judged based on
actual behavior rather than having students respond to hypothetical and
often stereotyped ethical cases, whereby the student can provide an artificial response that will be viewed favorably by the evaluator.
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The findings suggest that higher education needs to recognize the relevance of factors beyond mere ethical education when preparing students
for the ethical challenges they will face in the business world.
This paper employs a unique “reverse methodology” to measure
Machiavellianism. This reverse methodology has greater external validity in quasi-experimental ethical studies because the results can be extrapolated to real-world scenarios where there is a cost to behaving
ethically.
Keywords: Ethics education; Machiavellianism; ethical failures;
accounting education; academic dishonesty
Virtually all collegiate business programs require extensive ethical preparation in their curricula. Such widespread adoption of business ethics education has resulted primarily from the requirements of the Association to
Advance Collegiate Schools of Business (AACSB
The primary business
accrediting agency), which now mandates that business education include
an ethics component (Swanson & Frederick, 2005).
The drive to include ethics instruction in business education has also
risen from external sources. Some view the ultimate cause of many of the
recent business scandals to be weaknesses in the collegiate education of
those involved (e.g., Nonis & Swift, 2001; Smith, Davy, Rosenberg, &
Haight, 2002). In response, business practitioners and society are demanding increased and more effective instruction in business ethics (Evans &
Weiss, 2008; Luthar & Karri, 2005; Waples, Antes, Murphy, Connelly, &
Mumford, 2009). This drive also assumes that making students aware of
alternative ethical frameworks and providing training on how to analyze
ethical situations will translate into ethical behavior when these students
become business professionals. Within business, accounting appears to be
an area that deserves particular attention (Liu, Yao, & Hu, 2012). A number of recent high-profile accounting scandals has led to an increased desire
for accounting controls (e.g., Sarbanes-Oxley legislation) and for
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Effectiveness of Instruction in Accounting Ethics Education
151
accounting ethics education (Holder-Webb & Cohen, 2007; Yang & Wu,
2009; Young & Annisette, 2009).
The assumption that ethics education alone will positively affect the ethical behavior of students, however, is not necessarily valid. Students may be
trained to perform well on examinations regarding questions of ethical conduct or recognizing ethical issues (Gautschi & Jones, 1998), but extrapolating those results into real-world ethical dilemmas where the price for
ethical behavior must be paid in the form of decreased productivity or efficiency presents external validity issues (Williams & Dewett, 2005).
As Bloodgood, Turnley, and Mudrack (2010) hypothesized, providing
college training in ethics may not improve ethical behavior in students
whose personalities predispose them to act in their own self-interest. If this
hypothesis is correct, then to a large degree, the ethical preparation provided by many business schools may not be successful in altering the behavior of future executives. From this perspective, students who are
predisposed to behave ethically will do so, and students who are predisposed toward unethical conduct will do so regardless of the ethical theories
or analytic training that is presented to them in college. The counterargument to Bloodgood et al.’s hypothesis says that ethics courses cause students to think more carefully about the social consequences of unethical
behavior, thereby modifying their attitudes and increasing the likelihood
that they will avoid such behavior (French, 2006).
Currently, persuasive evidence indicating that taking college courses in
business ethics results in reduced unethical behavior when students migrate
into the business world appears to be absent (Williams & Dewett, 2005),
supporting Bloodgood et al.’s hypothesis. Indeed, several recent studies
report that business ethics instruction has little or no effect on the subsequent choices made by students (e.g., Jewe, 2008; Natale & Sora, 2010;
Peppas, 2003; Peppas & Diskin, 2001; Ritter, 2006). Seshadri, Broekemier,
and Nelson (1998) concluded that classes in business ethics have no impact
on the ethicality of students’ subsequent decision making. Consequently,
business students remain the most prolific cheaters on college campuses
(McCabe, Butterfield, & Trevino, 2006)
An examination of accounting ethics education research shows similar
results, although there is disagreement over whether ethical education ultimately produces accountants who will act more ethically (Tweedie, Dyball,
Hazelton, & Wright, 2013). Some evidence exists suggesting that ethics education may affect accounting students’ moral sensitivity (e.g., Dellaportas,
Leung, & Jackling, 2006), ethical standards (e.g., Keller, Smith, & Smith,
2007), and their cognitive moral capability (e.g., Jones, Massey, & Thorne,
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DAVID J. BURNS ET AL.
2003), but such effects may be short-lived (LaGrone, Welton, & Davis,
1996). Similarly, Liu et al. (2012) found that ethics instruction appears to
have at least a temporary effect on several ethics-related perceptions, such
as sensitivity and moral reasoning, but these effects appear to have limited
influence on the ethicality of choices actually made during one’s educational experience (e.g., academic dishonesty) or on subsequent decision
making in the workplace. Indeed, Thomas (2012) noted that the observational effects in past studies have been relatively weak. Loeb (1988) suggested that the goals of ethics education in accounting should be more
modest, focusing on issues such as helping students to recognize ethical
issues in accounting and to develop a sense of moral obligation instead of
directing behavior. Tweedie et al. (2013) noted that education is unlikely to
achieve even these more modest goals.
Interestingly, although Thomas (2012) observed that a college education
has a positive effect on students’ deliberative reasoning (when comparing
freshmen and senior accounting students), Josien and Broderick (2013)
observed that the rate of academic dishonesty increases as students progress through their education. Abdolmohammadi and Baker (2007)
observed that students’ moral reasoning is inversely related to their plagiarism activity. The relationship between ethical reasoning and academic dishonesty, therefore, does not seem to be clear. Bay and Greenberg (2001)
observed that knowing the right thing to do does not necessarily lead to
ethical choices. Similarly, Lampe and Engleman-Lampe (2012) suggested
that individuals often make choices not consistent with their beliefs and
attitudes of what may be the “right” course of action when they deal with
the subsequent dissonance through rationalization. To further complicate
matters, Ferguson, Collison, Power, and Stevenson (2011) suggested that
the way that accounting is taught may predispose accountants to act in
unethical fashions regardless of ethics education.
Determining whether a student is predisposed toward unethical behavior
is a difficult question. Josien and Broderick (2013) recognized that the largest limitation to research on academic dishonesty is the reliance on selfreported data. The limitations of self-report data are evident in three areas.
First, Burrus, McGoldrick, and Schuhmann (2007) noted that students
often do not have a clear picture of what cheating is. Without first giving
students a clear definition of academic dishonesty, students’ self-reports of
their cheating behavior may be inconsistent. Second, unethical individuals
with even modest intelligence would likely not willingly provide evidence of
their dishonesty, and would likely fabricate answers to questions or ethical
cases to conform to their professor’s expectations. Third, the use of survey
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Effectiveness of Instruction in Accounting Ethics Education
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instruments to measure personal predispositions raises similar concerns.
Bloodgood et al. (2010), for instance, used the Christie and Geis (1970)
Machiavellianism scale, a survey instrument to categorize students on
whether they exhibit Machiavellian attitudes. Here, savvy students may
recognize the variables that are being manipulated, and that these variables
contain features that are contrary to the educational expectations of college
student behavior. The anonymity of student responses to such questionnaires provides some assurance about the legitimacy of the data; yet, students recognize that their responses may alter the professor’s view of the
class as a whole, and thereby indirectly impact their grades. Accordingly,
the validity of measuring Machiavellianism via surveys in educational settings may be open to question.
Addressing the issue of how prior student attitudes impact the effectiveness of college ethics courses is challenging, and the problem needs to be
broken down into smaller issues. Ideally, student attitudes and behaviors
need to be measured under conditions where students are unaware that
they are being observed. The focus of this study is to accomplish this by
identifying students’ Machiavellian attitudes via actual behavior within the
educational environment and relate them to their beliefs that additional
ethics instruction and/or punishment will have the greatest effect on limiting unethical activity. The effects of additional ethical instruction in
accounting are also examined. This study employs a commercial plagiarism
search engine as a surrogate measure for Machiavellianism, and then compares plagiarism activity in an extensive writing assignment across three
variables: the presence or absence of enhanced ethical training; student evaluations of whether more ethical training would have prevented fraud in a
given ethics case; and student evaluations of whether harsher penalties
would have prevented fraud in the same ethics case. First, we review the
present state of research in student ethics. Second, we explore the
Machiavellian connection to ethics. Third, we develop and test hypotheses.
Finally, we draw conclusions.
THE PRESENT STATE OF RESEARCH IN
STUDENT ETHICS
The quantity of literature on academic dishonesty will overwhelm any first
time viewer of it with the prevalence and depth of cheating by students in
high school, college, and graduate school. Research shows that over 70
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DAVID J. BURNS ET AL.
percent of high school students have engaged in active cheating on their
assignments and at least 50 percent have plagiarized writing assignments
using the Internet (McCabe, 2005). Even worse, 77 percent of students in
the McCabe (2005) survey believe that Internet plagiarism is not a serious
issue, and the rate of cheating has been increasing over the past several decades (Galloway, 2012; Murdock, Miller, & Kohlhardt, 2004).
As would be expected, the situation in higher education is not much
better. The rate of reported cheating in college is in the 40 80 percent
range in most studies (e.g., Klein, Levenburg, McKendall, & Mothersell,
2007), with Brown, Weible, and Olmosk (2010) observing a high of 100 percent in an undergraduate management class. The rate of cheating in
higher education has also been increasing over the past several decades
(Chapman, Davis, Toy, & Wright, 2004; Jones, 2011; MacGregor &
Stuebs, 2012). Internet plagiarism is viewed as one of the most serious
cheating problems (Comas & Sureda, 2010). Although the use of the
Internet has created an explosion in student plagiarism (Granitz & Loewy,
2007; Quah, Stewart, & Lee, 2012), many students may not perceive
Internet plagiarism to be cheating (Gabriel, 2010). Lawson (2004), however, observed that students who have cheated on exams are more likely to
plagiarize, allowing him to conclude that plagiarism is viewed by students
to be similar to other forms of academic dishonesty. Abdolmohammadi
and Baker (2007) believed that plagiarism is particularly important to
accounting students since students’ degree of learning is lessened. They
further suggest that acts of plagiarism during one’s education may lead to
an increased tendency to engage in unethical activities once students find
themselves in the accounting profession.
The extensive ethical preparations of collegiate business programs do
not appear to lessen the plague of college cheating. Harris (1989), Smyth,
Davis, and Knoncke (2009), and Wood, Longenecker, and Moore (1988)
noted that business students appear to have lower ethical values than
non-business students. One prevailing theory on why cheating is more common among business students rests on the notion that business is a selfinterested endeavor and, accordingly, students with an interest in business
will have stronger egoism values (Williams & Dewett, 2005). Several studies
support this theory, observing differences between business students and
those pursuing degrees in other areas. McLean and Jones (1992), for
instance, observed that students pursuing business education are much
more Machiavellian than students pursuing other majors. Similarly,
Westerman, Bergman, Bergman, and Daly (2012) observed that business
students are similarly more narcissistic than students pursuing other
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Effectiveness of Instruction in Accounting Ethics Education
155
majors, specifically those pursuing psychology majors. Sautter, Brown,
Littvay, Sautter, and Bearnes (2008), however, observed no difference
between the narcissism of entering freshman business and nonbusiness
majors, suggesting that the differences observed in students’ narcissism
may be due to the academic environment faced by business school students.
Indeed, they observed supporting evidence the narcissism of business students appeared to increase during their college years. (It should be noted,
however, that they did not control for students changing majors.)
The overwhelming prevalence of college cheating in business schools is
inconsistent with the professed emphasis placed by these schools on ethics.
The Aristotelian logic is simple: all cheaters behave unethically when they
cheat; many business students are cheaters; ergo, many business students
(students with extensive training in ethics) behave unethically. This logic is
consistent with Bloodgood et al. (2010), who found that taking a business
ethics course did not significantly alter student views on the ethicality of
academic dishonesty. Others provide evidence suggesting that a business
education itself may adversely affect students’ moral character (e.g., Frank,
Gilovich, & Regan, 1993; Schneider & Prasso, 2002). Interestingly, Tang
and Tang (2010) reported that students with ethical intentions may become
more ethical as the result of ethical instruction whereas students with
unethical intentions may become less ethical as the result of ethical instruction. Similarly, Bloodgood et al. (2010) observed that for students scoring
low on Machiavellianism, taking a business ethics course resulted in greater
acceptance of certain forms of college cheating.
Ethics education, therefore, does not appear to affect all individuals in
the same way. Indeed, for some, ethics education may lead to results contrary to those sought some students may act less ethically as a result of
ethics education. A possible reason for this surprising effect may be that
ethics education provides some students with a greater ability to rationalize
or justify their actions. Rationalizations allow individuals to alleviate their
moral anxiety by developing explanations (Zyglidopoulos, Fleming, &
Rothenberg, 2009) which make unethical activities appear acceptable.
MacGregor and Stuebs (2012) observed that students who are better at
rationalizing their choices are more likely to engage in academic dishonesty, including cheating. As a result of rationalizations, “corrupt individuals tend not to view themselves as corrupt” (Anand, Ashforth, & Joshi,
2004, p. 40). Moreover, Zyglidopoulos et al. (2009) suggested that the rationalizations given by individuals often are excessive, providing a basis for
more unethical actions in the future, or what Lowell (2012) referred to as a
downward ethics spiral. This indicates that academia may need to reflect
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carefully on this ethics anomaly and take a more realistic appraisal of what
college ethics courses accomplish.
Research suggests that student ethics may vary based on gender
(Crown & Spiller, 1998). Klein et al. (2007) observed that in about half of
the studies they examined, males cheat more than females, while no relationships were observed in the other half. Given the lack of agreement on
the existence of a gender effect, studies examining academic dishonesty
should control for gender.
On the other hand, students’ propensity to cheat appears to vary with
their GPA. Burrus et al. (2007) and Straw (2002), for instance, observed
that students with lower GPAs tend to be more likely to cheat. Straw attributes the difference in tendencies to differences in importance individuals
with lower GPAs have more to lose if they acquire a lower grade in a class.
An alternative explanation, however, may be that students with lower
GPAs may have earned the lower grades because they have less motivation,
use less effort or have lower abilities and rely on cheating to overcome
these shortcomings. Hence, studies examining student cheating activity
should also control for students’ GPA.
THE MACHIAVELLIAN CONNECTION
If higher education is to understand and reduce student dishonesty, it needs
to place greater focus on the causative factors of such behavior, rather than
simply espousing the opinion that more or better training in ethics is the
solution. One factor that has been studied in the literature is the personality
trait known as Machiavellianism.
Machiavellianism describes individuals with personalities that show a
low regard for conventional morality (Jones & Kavanagh, 1996).
Generally, individuals with strong Machiavellian characteristics (high
Machs) are manipulative in their dealings with others and focus on achieving their desired ends by any available means (Christie & Geis, 1970). A
“Machiavellian administrator is one who employs aggressive, manipulative,
exploiting, and devious moves in order to achieve personal and organizational objectives” (Calhoon, 1969, p. 211). This definition is, to some
degree, a misnomer. Niccolò Machiavelli’s most famous work, The Prince
(1513/2009), was written as a guide for 16th-century monarchs and rulers,
focusing on using deception, manipulation, and traditionally amoral
actions to achieve the greatest overall good for the citizens of the kingdom.
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Machiavelli’s unconventional ideas were arguably never intended to be
used for self-gain or personal enrichment, but rather as a rational means of
choosing the lesser of evils to achieve a greater good for society as a whole.
Nevertheless, the term, Machiavellianism, has since been applied to individuals who “do not take a moralistic view of themselves, others, or of interpersonal relations” (Geis, Christie, & Nelson, 1970, p. 76) and who
welcome the use of guile, deceit, and other similar means to accomplish
their objectives (Forgas, 1985; Winter, Stylianou, & Giacalone, 2004) without regard for the well-being of others (Tang & Tang, 2010).
High Mach individuals engage in unethical behavior not as an end in
itself, but rather as a means to achieving some particular economic benefit
or avoiding some type of punishment (Tang & Chen, 2008). Generally,
high Mach individuals are more accepting of unethical behavior, and have
a greater propensity for engaging in cheating activity (Granitz, 2003;
O’Fallon, & Butterfield, 2005; Wilson, Near, & Miller, 1996). Indeed,
within an academic setting, Quah et al. (2012) observed that high Mach
students hold more positive attitudes toward plagiarism than low Mach
students and Menon and Sharland (2011) observed a strong relationship
between Machiavellianism and attitudes toward academic dishonesty.
As discussed previously, using a questionnaire or survey to identify high
Mach individuals may lead to incorrect results. High Machs are, by their
nature, duplicitous and may decide to provide false information when the
circumstances show a potential advantage to using deception (Jones &
Paulhus, 2009). Similarly, using behavior is also superior to using students’
expressed rationale (or rationalization) for engaging in plagiarism after
they are caught (as used by Granitz & Loewy, 2007) since the expectation
is that high Machs would be unlikely to provide accurate responses if they
perceive such responses as possibly leading to negative consequences.
Another limitation on the validity of assessing Machiavellian personality
characteristics by means of a questionnaire concerns the lack of economic
consequences. Asking subjects a hypothetical question about whether they
would return a lost wallet filled with money, for instance, provides little
insight into what they would do if they actually found such a wallet.
Recent research raises additional concerns in attempting to predict
unethical behavior. Measures that assess Machiavellianism via a questionnaire or survey are no exception. Research suggests that individuals’ predictions of their behavior, including the ethicality of their actions, often differ
from the choices actually made (Epley & Dunning, 2000). Indeed, most
individuals believe that they are more ethical than their subsequent behavior suggests (Tenbrunsel, 1998; Tyson, 1992). Tenbrunsel, Diekmann,
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Wade-Benzoni, and Bazerman (2010) suggested that individuals possess a
different frame when they actually make decisions than when they are
predicting their behavior
due to “ethical fading” and other decision
biases, individuals often do not realize the ethical implications of decisions
when they actually make them, permitting the pursuit of less ethical behavior. Similarly, Bazerman and Tenbrunsel (2011) referred to “bounded
awareness,” where individuals do not perceive all of the pertinent information (e.g., information of an ethical nature) when making decisions.
Consequently, examining actual behavior is the preferable method of assessing the ethics of individuals’ choices.
Rather than identifying high Machs with a conventional psychological
questionnaire, an alternative would be to flag individuals as Machiavellian
when they engage in duplicitous behavior to achieve a desirable objective.
Thus, students displaying a clear pattern of blatant academic dishonesty
could be classified as high Machs. Such an approach has its drawbacks
because adverse personal circumstances could entice a student to cheat on
an exam or writing assignment, when, in fact, such a digression would be
out of their normal character. Nevertheless, this approach to identifying
students with Machiavellian personalities does not suffer from the disinformational drawbacks of simply asking students whether they are deceptive
or manipulating individuals. The strength of a “dishonest students are
‘high Machs’” approach is the ability to collect or observe other additional
information that would, a priori, be associated with Machiavellian personalities. For example, Machiavellians’ engaging in cheating would undoubtedly consider the consequences of being caught, and would formulate an
excuse or argument to reduce the impact of any adverse penalty to their
dishonesty. Therefore, any student attitudes or actions that mitigate the
consequences of dishonesty could be viewed as additional evidence of a
Machiavellian personality.
HYPOTHESES
The overall conclusion of Bloodgood et al. (2010) focuses on the observation that individual personality characteristics play a larger role than ethics
instruction in determining student attitudes toward academic dishonesty.
Although research seems to support Bloodgood et al.’s (2010) hypothesis,
the study used a 20-item scale developed by Christie and Geis (1970) to
classify students according to their inclination for Machiavellian behavior.
As mentioned earlier, however, high Machs can be expected to engage in
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Effectiveness of Instruction in Accounting Ethics Education
159
duplicitous behavior to achieve a desirable objective, behavior that could
include replying to a questionnaire in a fashion to obtain possible desirable
outcomes instead of providing honest responses. The current study, therefore, avoids the use of a survey and instead assesses level of student plagiarism as measured by a similarity index (SI) and footnote disclosures as a
surrogate measure for Machiavellianism. These metrics are then compared
across two different student groups, one group being exposed to a lecture
on ethical theories and frameworks and the other group simply receiving a
factual presentation of ethics rules as developed by the American Institute
of Certified Public Accountants. Given that the research explored earlier
suggests that ethics education may not have a positive effect on subsequent
behavior, the following hypothesis is tested:
H1. Exposure to a discussion on ethics does not affect students’ subsequent incidence of academic dishonesty. Specifically, no relationship
exists between the level of student plagiarism in a college accounting
writing assignment and the type of training in ethical theories and frameworks students receive. Furthermore, the lack of a relationship remains
after controlling for the effects of gender and GPA.
As discussed above, classifying all cheating students as high Machs is
questionable. High Machs have a consistent and pervasive preference
toward manipulative opportunism, and some students may cheat only
when facing severe time constraints for studying or preparing assignments.
One would expect high Machs to more carefully consider the consequences
of being caught than students who cheated out of desperation, and, consequently, high Machs would have more formally developed and articulated
defensive strategies. Such strategies would be unobservable for research
purposes; yet, surrogates for defensive strategies and attitudes are
available.
In this study, one of the requirements for the writing assignment was for
students to point out whether the ethical failure in the examined case could
have been best prevented or mitigated with either additional ethical education and/or more severe punishment of offenders since they are two of the
most referenced mechanisms for lessening the incidence of cheating activity
by students. Punishment is often viewed to be a deterrent to undesirable
behavior, including cheating behavior. Several studies (e.g., Burns,
Manolis, & Ahuja, 2006; Chapman et al., 2004; Smith et al., 2002) observed
that students’ cheating tendencies drop dramatically if students view that
the perceived costs of cheating are high (a significant punishment with a
high risk of being caught and experiencing the punishment). This is
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DAVID J. BURNS ET AL.
consistent with deterrence theory, which was originally developed as a way
to reduce the occurrence of undesired behavior (Cheng, Li, Zhai, & Smyth,
2014). Deterrence theory assumes that disincentives can influence behavior,
where individuals make choices to avoid negative results, including punishment (Wenzel, 2004). Deterrence theory assumes that individuals are adequately rational to consider consequences when deciding courses of action
(Kennedy, 2010). Paternoster (2010) provided a summary of deterrence
research focusing on the deterrence of criminal activity. He notes that the
effect of deterrence on individuals’ choices does not seem to be as strong as
is commonly believed, but he suggests one reason for this lies in the temporal distance between an action and the associated punishment.
Deterrence researchers, however, are increasingly recognizing that the effectiveness of deterrents on influencing choices varies across a number of individual characteristics (Worrall, Els, Piquero, & TenEyck, 2014). Piquero,
Paternoster, Pogarsky, and Loughran (2011) termed the differences in the
ways that deterrents affect individuals “differential deterrability.”
Differences in Machivellianism logically should affect how individuals
respond to deterrents or the types of possible punishment. (Some deterrents
have the opposite effect on behavior, however, not deterring the questionable behavior, but facilitating it; Bazerman & Tenbrunsel, 2011. Hence, the
presence of deterrents themselves cannot guarantee positive changes in
behavior. Instead, the focus must be determining and implementing the
“right” deterrents.)
A priori, based on the characteristics of Machiavellianism, one would
expect high Machs to favor added ethical education rather than punishment. (This would be the opportunistic approach.) High Machs are likely
not to favor anything that could possibly be used against them (like punishment), which could impede them from reaching their goals. Ethics education, however, is relatively harmless and could be viewed as beneficial since
its assumed effectiveness could lead to an environment with less oversight,
facilitating questionable activities. (If instructors believe that ethical education can be effective in minimizing cheating, they may be less likely to provide oversight that has the goal of minimizing cheating activity.) Moreover,
as discussed earlier, ethics education appears to give students the tools
needed to rationalize academically dishonest behavior, so added ethics education could provide high Machs with additional insight into facilitate academic cheating.
On the other hand, one would expect low Machs (honest students) to
have a greater preference for punishing cheaters as a means for dissuading
unethical activity since their ethical behavior precludes punishment.
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Instead, cheaters would be more likely to be appropriately punished. Low
Machs, however, are less likely to favor increased ethics education. They
will likely see little reason for ethics education since it will likely be viewed
as having no effect on them (since their choices already tend to be more
ethical). Instead, the increased education would likely be viewed as merely
an additional activity to endure with little personal benefit.
Students who favor neither added ethics education nor increased punishment and students who favor both increased education and increased punishment would appear to lie between high Machs and low Machs
(moderate Machs) in terms of their relative Machiavellian tendencies.
Some moderate Machs (students who may be involved in cheating, but
not to the extent of high Machs) may favor neither education nor punishment they would prefer the lack of punishment so that it will not affect
any unethical behavior in which they may partake. They, however, do not
possess the desire to possibly facilitate cheating activities (which may be the
outcome of less oversight due to ethics education) or be as focused on their
cheating activities to seek out ways to rationalize their choices.
Similarly, other moderate Machs likely favor both ethics education and
punishment. Although the preferences are opposite of the other moderate
Machs mentioned above, the rationale is similar. For these students, the presence of punishment will likely be viewed as a constraint against “excessive”
cheating by high Machs (which would put moderate Machs at performance
disadvantage). The ethics education may lead to decreased oversight, as
mentioned above, likely making it easier for some unethical activity to
occur. Moreover, the ethics education may increase students’ abilities to
rationalize their unethical choices. Consequently, favoring both punishment
and ethics education will likely have appeal to some moderate Machs, while
others will likely favor neither punishment nor ethics education.
Consequently, Hypotheses 2 seems to be appropriate:
H2. Students who express that ethical failures can be best prevented
through additional ethical education are more likely to cheat than students who believe that ethical failures can best be prevented through
increased punishment. In other words, students who express that the
ethical failure in the examined case could have been best prevented or
mitigated with additional ethical education (hypothesized to be high
Machs) possess higher similarity indexes and include lower numbers of
references in their class project than students who express that the ethical failure could have been prevented with increased punishment
(hypothesized to be low Machs).
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METHODOLOGY
The above hypotheses are tested using a 2 × 2 × 2 full factorial, between
subjects design with 157 accounting seniors (93 males and 64 females) from
a Midwestern, AACSB accredited college of business. Separate sections of
the same upper division accounting class were used as cluster samples, with
each cluster serving as part of the experimental or control groups. In a true
experimental design, students would have been assigned randomly between
the experimental and control groups. This, however, was not practical since
students registered according to their own scheduling needs. Therefore, a
quasi-experimental design was employed. Any student who had previously
taken the course was removed from the study so each participant was viewing the lecture and presentation for the first time. Random assignment was
used to determine which student cluster received the enhanced ethics lecture
(treatment variable) and which received the stock lecture on the ethical
rules for accountants as determined by the American Institute of Certified
Public Accountants (control variable).
The enhanced ethics lecture presented persuasive arguments that students and business professionals benefit most when they act in a manner
that promotes ethical behavior in themselves and others. Two different litmus tests of ethical behavior were presented. First, the ideas of John Stuart
Mill’s Utilitarianism were examined. Second, Immanuel Kant’s Categorical
Imperative model (Universalization) was discussed and analyzed. Mill’s
and Kant’s models were presented as thought experiments in both business
and student ethics contexts, and they were stripped of jargon to make the
material readily understandable to persons without a philosophical background in ethics. Students were informed to use these alternative models of
ethical thought to navigate their way through ethical dilemmas. The convergence of both models on a particular course of action increases the likelihood that the action is not only ethical, but is also in accordance with
their own long-run best interest. Seventy-one of the students were exposed
to the enhanced ethics lecture and 86 students were presented with only a
factual presentation of the professional code.
The final levels in the design focused on categorizing student responses in
a term paper covering two classic ethical failures in the field of accounting.
Part of the assignment included the requirement that students identify
whether added ethical training or harsher punishment would have been
effective in preventing or mitigating the ethical failures that were depicted in
the cases. The cases were complex and described the factual circumstances
and details surrounding several ethically ambiguous scenarios where student
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163
judgment would be needed in identifying exactly where and why ethical
digressions occurred. Thus, the design of the study involves: (type of ethical
lecture given to the student) × (the student’s choice of whether additional
ethical education would have been effective in preventing or mitigating the
ethical failures depicted in the cases) × (student choice of whether harsher
punishment would have been effective in preventing or mitigating the ethical
failure depicted in the cases). Since relationships have been observed
between academic performance and ethical attitudes (e.g., Klein et al., 2007;
Lawson, 2004), student grade point average as reported by means of their
academic transcript served as a covariate. Furthermore, since ethical attitudes have been observed to vary by student gender (e.g., Lawson, 2004;
Smyth et al., 2009), student gender was treated as a control variable.
To ensure that they possessed a clear understanding of what is regarded as
plagiarism, students were given detailed instructions for preparing their term
paper. These instructions included the need for proper academic referencing
of sources used with specific examples of acceptable and unacceptable referencing procedures in the course syllabus. Students were also given a copy of
the University Code of Student Conduct, which provided a detailed description of their obligation to avoid academic misconduct and plagiarism. The
course syllabus contained a statement that any plagiarism or other academic
misconduct would result in a failing grade for the course.
The student papers were submitted electronically and then sent to a
commercial plagiarism detection service in a fashion similar to that used by
Abdolmohammadi and Baker (2007). The output from this service displayed a similarity index (SI) for each student. The SI metric represented
the proportion of the paper that was taken from Internet sources or from
published works from their proprietary database, including books, journal
articles, and manuscripts from other students. In addition to the SI metric,
the plagiarism detection service provided an HTML copy of the student’s
paper with highlighted sections and notes to show exactly from where the
suspected plagiarized material was taken. The student papers were examined in light of this information, and any flagged material or paraphrased
statements with proper references were noted and removed from the calculated SI. Thus, the instructor-adjusted SI represented quotations or paraphrasing from other sources that were not properly referenced by the
student.
In addition to the SI measurement, the number of verifiable academic
references was recorded for each student. The lack of academic references
is not, in itself, evidence of student plagiarism; however, one would expect,
a priori, an inverse relationship between the level of student plagiarism and
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DAVID J. BURNS ET AL.
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the number of academic references. Accordingly, students who were properly citing their sources would have more listed academic references than
students who were engaging in “cut and paste” plagiarism.
A pilot experiment was conducted in a prior semester to verify that the
cases and instructions were clear, and that students understood the assignment requirements. No problems were noted. The assignment was listed on
the course syllabus as a graded component with a weight equal to about 15
percent of their course grade.
Factors and Dependent Variables
The three factors evaluated in this study are the type of ethical lecture, students’ beliefs that ethical education will prevent or mitigate the incidence of
ethical lapses, and students’ beliefs that increased penalties for ethical violations will prevent or mitigate the incidence of ethical lapses as discussed
above. The dependent variables are the adjusted SI score from the assigned
term papers and the number of verifiable references cited by each student.
Student GPA was used as a covariate, and student gender was treated as a
categorical control variable. Multivariate analysis of covariance
(MANCOVA) was used to examine effects of the three factors on the joint
relationship between SI and the number of student references. (Since student gender is a categorical variable, it cannot be directly employed as a
covariate. Computationally, student gender was entered as a factor since
doing so is mathematically equivalent to including it as a covariate in the
form of a dummy variable.) In a secondary analysis, analysis of covariance
(ANCOVA) was used to separately evaluate SI and the number of student
citations. Both MANCOVA and ANCOVA are used for the sake of completeness; a significant MANCOVA result does not imply a significant
ANCOVA, and vice versa. Students were then classified into four groups
based on their beliefs that ethical education will lower the incidence of ethical lapses and on their beliefs that increased penalties for ethical violations
will lower the incidence of ethical lapses.
RESULTS
Table 1 provides summary statistics. Table 2 displays associations between
factors and variables. As expected, the two dependent variables are
strongly correlated (r = −.3385, p < .0005) indicating that as students
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Effectiveness of Instruction in Accounting Ethics Education
Table 1. Summary Statistics.
Parametric Statistics
Similarity index (SI)
Number of references
GPA
Mean
Standard Deviation
Minimum
Maximum
13.17
2.54
3.24
16.01
2.159
.471
0
0
2.21
87
11
4.00
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Frequencies
Action to Prevent Ethical Lapse
Increased ethical instruction
Increased penalties
Table 2.
Perceived to Be
Effective
Perceived Not to Be
Effective
83
84
74
73
Association Correlation Matrix of Factors and Variables.
Similarity Number of Ethical
Index (SI) References Instruction
Similarity index
(SI)
Number of
r = −.3385
references
p = .000
Ethical
r = −.2441
instruction
p = .002
Increase
r = −.3240
penalties
p = .000
Ethics lecture
r = .0375
p = .641
Gender
r = .2539
p = .001
GPA
r = −.2564
p = .001
Increase
Penalties
Ethics
Lecture
Gender
GPA
r = .227
p = .004
r = .2377
χ2 = .036
p = .003
p = .874
r = .0772 χ2 = 1.239
χ2 = .106
p = .336
p = .335
p = .751
r = .2937 χ2 = −.1255 χ2 = −.0977 χ2 = .095
p = .000
p = .117
p = .224
p = .760
r = .2139 r = −.0004
r = .1482 r = −.0270 r = −.0949
p = .007
p = .996
p = .064
p = .737
p = .237
Notes:
Pearson correlation and biserial correlations are reported when ratio measure(s) are examined.
Chi-squares are reported when both measures are nominal.
Significant (at the .05 level) relationships are indicated in bold.
Ethical Instruction = Students’ beliefs that ethical education will lower the incidence of ethical
lapses.
Increase Penalties = Student’s belief that increased penalties for ethical violations will lower the
incidence of ethical lapses.
Ethics Lecture = Exposure to enhanced ethics lecture.
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DAVID J. BURNS ET AL.
increasingly engage in plagiarism, they include fewer references. The relationships between the dependent variables and students’ GPA and gender
produce results consistent with past research. Students with higher GPAs
appear to plagiarize less as indicated by a lower SI score (r = −.2564,
p = .001) and a higher number of references (r = .2139, p = .007) than students with lower GPAs. Similarly, female students appear to plagiarize less
by having a lower SI score (t = 3.465, p = .001) and a higher number of
references (t = 3.514, p = .001) than male students. Finally, although the
summary statistics on students’ beliefs on providing ethical instruction or
increasing penalties for the unethical activity depicted in the cases are virtually identical, students’ responses were not observed to be statistically
associated (χ2 = −.036, p = .874).
MANCOVA results are reported in Table 3. The overall model is significant (at the .05 level). When the results for the individual variables are
examined, as expected, significant effects were noted for both GPA and
gender. A significant effect, however, was not observed for whether
students were exposed to the enhanced ethics lecture. This result supports
H1 exposure to the enhanced ethics lecture does not appear to affect students’ plagiarism activities after controlling for the effects of gender and
GPA. Significant effects were observed for the other two factors
students’ beliefs on whether ethical instruction and/or whether increased
penalties could have prevented or mitigated the ethical lapses depicted in
the case. None of the interactions between the factors and covariates was
significant.
For additional insight, individual ANCOVAs were conducted for the
two dependent variables independently. ANCOVA results are reported in
Table 4. The results for both ANCOVAs were consistent with the results
observed for the MANOVA.
To test the second hypothesis, the sample was split into four groups
based on their responses to whether they believe that the ethical failure in
the examined case could have been best prevented or mitigated with additional ethical education or with increased punishment. The groups and
summary statistics are displayed in Table 5. Group 3, the group believed to
consist of high Machs, displayed the highest mean SI and the lowest mean
number of references as expected. Similarly, Group 2, the group believed to
consist of low Machs, displayed the lowest SI and the highest number of
references, also as expected. The significances of the differences were tested.
The results of a MANOVA and individual ANCOVAs comparing the
groups while controlling for GPA and age and appropriate post hoc tests
are displayed in Table 6.
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Table 3.
Multivariate Analysis of Covariance (MANCOVA) Results.
Intercept
GPA
Provide ethical instruction
Increase penalties
Enhanced ethics lecture
Gender
Provide ethical instruction ×
Increase penalties
Provide ethical instruction ×
Enhanced ethics lecture
Provide ethical instruction ×
Gender
Increased penalties ×
Enhanced ethics lecture
Increase penalties ×
Gender
Enhanced ethics lecture ×
Gender
Provide ethical instruction ×
Increase penalties ×
Enhanced ethics lecture
Provide ethical instruction ×
Increase penalties ×
Gender
Provide ethical instruction ×
Enhanced ethics lecture ×
Gender
Increase penalties ×
Enhanced ethics lecture ×
Gender
Interaction term including all
Four factors
Wilks’ Lambda
F
Effect df
Error df
Significance
.896
.923
.920
.900
.996
.920
.986
8.101
5.834
6.005
9.354
.281
6.003
.964
2
2
2
2
2
2
2
139
139
139
139
139
139
139
.000
.004
.003
.001
.755
.003
.384
.991
.654
2
139
.522
.984
1.115
2
139
.331
.981
1.314
2
139
.272
.995
.376
2
139
.687
.995
.348
2
139
.707
.983
1.220
2
139
.298
.991
.605
2
139
.547
.996
.286
2
139
.752
.998
.167
2
139
.847
.994
.398
2
139
.673
Notes:
Significant (at the .05 level) relationships are indicated in bold.
Ethical instruction = Students’ belief that ethical education will lower the incidence of ethical
lapses.
Increase penalties = Student’s belief that increased penalties for ethical violations will lower the
incidence of ethical lapses.
Ethics lecture = Exposure to enhanced ethics lecture.
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DAVID J. BURNS ET AL.
Table 4.
Analysis of Covariance (ANCOVA) Results.
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Similarity Index
Intercept
GPA
Provide ethical instruction
Increase penalties
Enhanced ethics lecture
Gender
Provide ethical instruction ×
Increase penalties
Provide ethical instruction ×
Enhanced ethics lecture
Provide ethical instruction ×
Gender
Increased penalties ×
Enhanced ethics lecture
Increase penalties ×
Gender
Enhanced ethics lecture ×
Gender
Provide ethical instruction ×
Increase penalties ×
Enhanced ethics lecture ×
Provide ethical instruction ×
Increase penalties ×
Gender
Provide ethical instruction ×
Enhanced ethics lecture ×
Gender
Increase penalties ×
Enhanced ethics lecture ×
Gender
Interaction term including all
Four factors
F
df
16.230
6.707
7.014
11.930
.261
4.991
.256
1
1
1
1
1
1
1
.968
Number of References
Significance
F
df
Significance
.000
.011
.009
.001
.610
.027
.614
.122
6.920
7.010
5.884
.215
8.922
1.855
1
1
1
1
1
1
1
.728
.009
.009
.017
.643
.003
.175
1
.327
.181
1
.671
.198
1
.657
1.801
1
.182
.277
1
.600
2.573
1
.111
.514
1
.475
.139
1
.709
.670
1
.414
.093
1
.760
1.429
1
.234
1.420
1
.235
.636
1
.393
1
.532
.113
1
.738
.382
1
.537
.093
1
.761
.191
1
.662
.001
1
.981
.774
1
.381
,427
Notes:
Significant (at the .05 level) relationships are indicated in bold.
Ethical instruction = Students’ belief that ethical education will lower the incidence of ethical
lapses.
Increase penalties = Student’s belief that increased penalties for ethical violations will lower the
incidence of ethical lapses.
Ethics lecture = Exposure to enhanced ethics lecture.
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Effectiveness of Instruction in Accounting Ethics Education
Table 5. Student’s Belief That Ethical Education or Increased Penalties
for Ethical Violations Will Lower the Incidence of Ethical Lapses.
Frequencies
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Student’s Belief That Increased
Penalties for Ethical Violations Will
Lower the Incidence of Ethical
Lapses
Students’ belief that ethical
education will lower the
incidence of ethical lapses
No
Yes
No
Group 1 37
Group 3 38
Yes
Group 2 37
Group 4 45
Summary Statistics
Similarity Index
Group 1
Group 2
Group 3
Group 4
Mean Number of References
Mean
Std. deviation
Mean
Std. deviation
13.78
4.30
22.53
12.04
16.773
4.551
21.989
10.57
2.41
3.70
1.82
2.29
2.153
2.209
1.814
2.074
The overall MANCOVA is significant (at the .05 level) indicating significant differences across the four groups. For further insight, the results from
individual ANCOVAs (where SI and number of references were viewed
separately) are provided. The results from both ANCOVAs were consistent
with the results observed for the MANOVA.
Post hoc test was conducted for each ANCOVA. Since disagreement
exists over the appropriateness of using Tukey tests when ANCOVAs are
used (as opposed to ANOVAs), Šidák tests were utilized. The results of
post hoc Šidák tests are also displayed in Table 6.
For SI, a significant (at the .05 level) difference was observed for only
one group comparison. The significant difference was observed between
Group 2 and Group 3, supporting H2. Specifically, a significant difference
was observed between the SIs for the groups viewed to represent high
Mach and low Mach individuals
high Mach students possess significantly higher SIs than low Mach individuals, signifying higher rates of plagiarism. For number of references, significant (at the .05 level) differences
were observed for two group comparisons. First, a significant difference
was again observed between Group 2 and Group 3, supporting the H2.
Specifically, a significant difference was observed between the number of
references cited for the groups believed to represent high Mach and low
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DAVID J. BURNS ET AL.
Table 6.
Analysis of Covariance Results.
MANCOVA
Wilks’ Lambda
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Intercept
GPA
Group
Gender
Gender × Group
.897
.937
.830
.910
.965
F
Effect df
Error df
Significance
2
2
6
2
6
147
147
294
147
294
.000
.009
.000
.001
.515
8.436
4.911
4.774
7.276
.874
ANCOVAS
Similarity Index
Intercept
GPA
Group
Gender
Gender × Group
Number of References
F
df
Significance
F
df
Significance
16.322
6.623
6.796
7.185
.530
1
1
3
1
3
.000
.011
.000
.008
.662
.005
5.039
4.844
10.073
1.123
1
1
3
1
3
.945
.026
.003
.002
.342
Group 1
Group 2
Šidák pairwise comparisons Similarity index
Group 1
Group 2
−8.246
.088
Group 3
7.119
15.365
.215
.000
Group 4
−.601
7.644
.999
.113
Šidák pairwise comparisons Number of references
Group 1
Group 2
1.021
.162
Group 3
−.651
−1.673
.673
.003
Group 4
−.300
−1.322
.986
.022
Notes:
Significant (at the .05 level) relationships are indicated in bold.
Group 3
−7.720
.127
.351
.972
Group 4
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Mach individuals high Mach students cited significantly fewer references
than low Mach individuals. A significant difference was also observed
between Group 2 (low Machs) and Group 4 (students who prescribed both
more ethical education and increased penalties). This suggests that low
Machs may be particularly committed to referencing materials or “doing
the right thing.” In other words, they may be more focused on avoiding
having their actions interpreted as being unethical.
Support, therefore, is observed for H2.
DISCUSSION AND CONCLUSION
Today’s business students are tomorrow’s business leaders. Consequently,
students’ views of ethical behavior will logically influence their choices
when they enter the business world. Lawson (2004) observed a strong relationship between students’ ethical choices in academia and in the business
world suggesting “students who cheat on exams or who plagiarize papers
were more likely to be accepting of the need for unethical behavior in the
workforce than those who do not engage in academic dishonesty” (p. 195).
Brown and Choong (2005) and Nonis and Swift (2001) observed similar
relationships. Hence, academic cheating is often used as an indicator for
future ethical behavior on the job (Smyth et al., 2009). Consequently, the
academic dishonesty of collegiate business students should be an important
concern for businesses (Klein et al., 2007).
The paradox between the mandated ethical preparation of collegiate
business students and the noted high levels of academic misconduct by
those same students is troubling. The results of this study support past
research suggesting that ethical education may not positively affect students’ ethical choices (Bloodgood et al., 2010). Many believe that the solution to ethical failures in business is increased ethical education. Ethics
research, however, does not seem to support this solution, although it needs
to be recognized that the current study examined only the effect of a single
ethics-enhanced lecture. Higher education needs to recognize that factors
beyond mere ethical education and training may determine whether students and business professionals will behave ethically.
The results are consistent with Tenbrunsel et al. (2010), who raise the
possibility that ethics education may increase individuals’ perceptions of
their own ethicality but may not have a positive effect on actual decision
making. They suggest that individuals “unwittingly engage in behaviors
that they would condemn upon further reflection or awareness” (p. 155).
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Hence, it appears that it is preferable to examine students’ actual cheating
behavior and the context in which is occurs than their ethical perceptions.
The primary methodological strength of this study rests on using actual
incidences of unethical conduct (plagiarism) to establish Machiavellianism
rather than using a student questionnaire, which respondents can manipulate. The questionnaire approach has stronger internal validity in terms of
accurately measuring the precise features of Machiavellian personality
types; however, it lacks the external validity of extrapolating those results
into real-world ethical dilemmas. Indeed, research suggests that a disconnect exists between one’s ethical attitudes and one’s behavior, a disconnect
that can be aggravated by the use of rationalizations. By reversing the normal diagnostic paradigm (by measuring actual behavior based on deviant
behavior (plagiarism) in an academic setting instead of utilizing a questionnaire to establish students’ Machiavellianism), the study provides external
validity to Bloodgood et al.’s finding that Machiavellianism is positively
associated with the view that college cheating is acceptable.
As a part of this reversed experiment, high Mach individuals were not
merely identified as individuals who engaged in plagiarism. A priori, based
on the characteristics of Machiavellianism, one would expect high Machs
to favor added ethical education rather than punishment (this would be the
opportunistic approach), and one would expect low Machs (honest students) to have a greater preference for punishing cheaters. Students who
favor neither added ethical education nor increased punishment and students who favor both would appear to lie between high Machs and low
Machs.
The results support the above methodology. Students who expressed the
belief that increased punishment (low Machs) would be able to prevent or
mitigate the ethical failures depicted in the cases were less likely to have
been involved in plagiarism and provided more references on the written
assignment, whereas students who expressed that added education (high
Machs) would be able to prevent or mitigate the ethical failures in the cases
were more likely to have been involved in plagiarism and provided fewer
references. Besides providing insight into Machiavellianism, these results
provide clues into how institutions of higher education and businesses may
be able to best attempt to prevent or mitigate ethical failures. The results
suggest that students who are most likely to be involved in ethical failures
(high Machs) do not favor the use of increased penalties as a way to prevent to mitigate ethical failures. They may view the increased penalties to
be a significant hindrance to continued ethical failures. Hence, although
ethics education may not be effective in positively affecting behavior, the
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173
study suggests that increasing specific penalties for ethical failures may be
effective.
This conclusion is consistent with past research on deterrents to academic dishonesty. Deterrence theory suggests that the incidence of cheating
activity will depend in part on the perceived costs of engaging in the activity (McCabe & Trevino, 1997; Tibbetts, 1999). Part of the problem with
ethical failures, therefore, may be the lack of sufficient deterrents (penalties). Indeed, several studies (e.g., Chapman et al., 2004; Smith et al., 2002)
have observed that students’ cheating tendencies drop dramatically if students view that the perceived costs of cheating are high (a high risk of being
caught). Research on the effectiveness of honor codes on the incidence of
cheating behavior supports this conclusion. McCabe Trevino and
Butterfield (2001) observed that the existence of an honor code in and of
itself is insufficient to have a significant effect on students’ cheating behavior
it must be enforced to be effective. In other words, effective deterrents (penalties) may be needed.
In conclusion, although the study does not suggest that ethics instruction is not worthwhile, it does support the research that suggests that ethics
education may not positively affect the ethics of many students. What
should be the focus of ethics research then? The results suggest that a more
fruitful approach for future research may be to focus more attention on the
relative effectiveness of various forms of deterrents to ethical failures. Since
high Machs are logically those who are most likely to engage in cheating
activity, deterrents to unethical activity may be able to affect the choices of
these individuals. Research, therefore, indicates that developing appropriate penalties may be successful to prevent or mitigate ethical failures.
The study is significant for several reasons. First, the results provide
classroom instructors with insight into the causes of Internet plagiarism;
that is, Internet plagiarism may originate in the nature of the students
involved instead of a lack of ethical instruction. The study also supports
previous studies which similarly suggest that the effects of ethical instruction may not affect students’ ethical behavior.
Second, through the means used to assess students’ Machiavellianism,
the study was able to bring the role of deterrence (penalties) into the discussion as a possible substitute to ethics education as a way to prevent or mitigate ethical failures. The results suggest that classroom instructors may be
able to effectively reduce academic dishonesty by increasing deterrents to
academic dishonesty instead of expanding ethical instruction.
Third, past research suggests that unethical behavior in an academic setting appears to lead to unethical behavior in business. Consequently, the
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study suggests that unethical behavior in business may arise at least in part
from the qualities of individual business persons
some individuals may
have more Machiavellian tendencies than others. If true, this suggests that
a focus on hiring may be an area where significant change can be enacted.
It further suggests that the extent of potential hirees’ ethical education may
not be the best evidence to examine to predict their likely future choices.
Instead, the findings suggest that potentially more fruitful examination will
focus on evidence of the relative Machiavellianism of potential hires as
identified through their past ethical failures.
Lastly, the study employed a “reverse methodology,” where students’
Machiavellianism was assessed directly from behavior instead of via a scale
or via measuring attitudes. By assessing actual behavior, external validity
can be enhanced and several measurement shortcomings can be overcome.
Limitations
The study possesses a number of limitations which may limit the generalizability of the results. First, the study included students attending advanced
accounting classes at a single university. The generalizability of the results
to students attending other academic institutions or those pursuing other
majors has not been assessed. Second, the study classified students as high
Machs based on only one form of academic dishonesty. The generalizability of the findings to other forms of academic dishonesty has not been
unequivocally established. Third, although past research examining the
effects of ethics education tended to observe only short-term effects, this
study only examines the short-term effects of the ethics lecture. Fourth, students in the experimental group were only exposed to only a single
enhanced ethics lecture. The results may be different if ethics were integrated throughout the course or throughout the accounting curriculum.
Finally, although past research suggests a strong relationship between
ethics within an academic environment and ethics in the workplace, the
generalizability of the findings of this study to ethics in the workplace has
not been examined.
In addition to expanding the study to include different groups of students studying accounting at different types of universities and at different
stages of their education, further research can provide additional insights
into unethical academic behavior. Longitudinal studies examining the longterm effects of ethics instruction, for instance, would be insightful.
Furthermore, extending the study to address different types of academic
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dishonesty besides Internet plagiarism would provide further knowledge of
academic dishonesty.
Additional insight can be gathered by further examining the measurement of Machiavellianism. For instance, how does the Machiavellianism as
measured in this study relates to Machiavellianism as measured by a survey? Such examination may provide additional insight into the disconnect
observed to often exist between ethical attitudes and individuals’ actual
behavior. Specifically, what factors may affect the size of this disconnect?
For instance, are high Mach individuals more accepting of unethical activities (possess lower ethical attitudes)? Burns, Smith, and Lanasa (1993) provided evidence that they are not, suggesting that Machivellianism and
ethical attitudes may not differ. If true, does this mean that there is a more
profound disconnect between ethical attitudes and behavior for high Mach
individuals (are high Mach individuals more likely to experience ethical
fading, bounded awareness)? Does this suggest that high Mach individuals
are more likely to employ rationalizations?
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