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IMDS
105,9
Attitude toward ethical behavior
in computer use: a shifting model
1150
University of Tulsa, Management Information Systems Department, College of
Business Administration, Tulsa, Oklahoma, USA, and
Lori N.K. Leonard
Timothy Paul Cronan
University of Arkansas, Information Systems Department, Walton College of
Business, Fayetteville, Arkansas, USA
Abstract
Purpose – In this study the researchers attempt to identify factors that could influence an
individual’s attitude toward ethical behavior in the information systems (IS) environment and compare
them to the findings of an earlier study to determine any changes.
Design/methodology/approach – A sample of university students is used to assess environmental
influences (societal, belief system, personal, professional, legal, and business), moral obligation,
consequences of the action, and gender, in order to determine what influences an individual’s attitude
toward a behavior. Discriminant analysis is used to assess the factor influences.
Findings – The findings indicate that many factors influence attitude toward ethical decisions and
are dependent upon the type of ethical issue involved. Moreover, based on two time periods, the ethical
attitude influencers have shifted over time. The gender findings indicate that attitude influencers are
also dependent on the sex of the individual.
Originality/value – The findings show that attitude influencers have shifted over time (since an
earlier study), which means that organizations must periodically reassess their employees’ ethical
climate and adjust their ethics’ programs as attitude influencers change. The findings also show that
training programs need to focus on the different influencers for males and females.
Keywords Ethics, Attitudes, Behaviour, User studies, Information systems
Paper type Research paper
Industrial Management & Data
Systems
Vol. 105 No. 9, 2005
pp. 1150-1171
q Emerald Group Publishing Limited
0263-5577
DOI 10.1108/02635570510633239
Introduction
The misuse of and unethical behavior toward information systems (IS) have caused
significant losses to businesses and society. Organizations have invested in the
development and implementation of security measures, but computer misuse continues
to be a problem. Monetary loss through unethical and criminal use of computers is
estimated to be billions of dollars per year (Haugen and Selin, 1999; Hubbard and
Forcht, 1998; Marshall, 1999; McCollum, 2004; Parks, 2005; Power, 2000; Trembly,
1999).
Unacceptable, illegal, and/or unethical use of computers are concerns to
IS professionals because of the potential harm to society and to the integrity of the
IS profession. Therefore, research support has increased for studying the ethical
attitudes of personnel, deterrents to unethical behavior, the various types of unethical
behavior, and approaches to teaching ethics in the field of MIS (Aiken, 1988;
Bowie, 2005; Conner and Rumelt, 1991; Cougar, 1989; Foltz et al., 2005; Heide and
Hightower, 1988; Leonard et al., 2004; Oz, 1990; Paradice, 1990; Saari, 1987; Straub
and Nance, 1990; Steinke and Nickolette, 2003; Zalud, 1984).
Attitude has been found to significantly affect an individual’s intention to behave
ethically or unethically (Ajzen, 1989, 1991; Ajzen and Fishbein, 1969, 1980; Fishbein and
Ajzen, 1975; Leonard and Cronan, 2001). Therefore, understanding the dimensions of
attitude will lead to the further understanding of the influences on ethical behavior
intention. Society has changed significantly since Kreie and Cronan (1999) explored an
attitudinal model – even wider use of the internet, more identity theft, digital privacy,
etc. Given these changes, the dimensions of attitude are also expected to change.
Moreover, gender was not considered in Kreie and Cronan’s study; however, many
research studies have found a person’s gender to play a role in explaining ethical
behavioral attitude and intention (Banerjee et al., 1996; Gattiker and Kelley, 1999;
Deshpande, 1997; Leonard and Cronan, 2001; Leonard et al., 2004). Therefore, the
purpose of the present study is to identify the influences on an individual’s attitude
toward ethical behavior and to compare those influences to the findings of an earlier
study, as well as to determine the role of gender in attitude differences. Respondents
were presented with five IS dilemmas and an action and asked to indicate the probability
that they agreed with the action. Then, they are asked to indicate the degree to which
various factors influenced their attitude (toward ethical behavior) for each scenario.
Attitude toward ethical behavior model
Attitude toward ethical behavior is an individual’s degree of favorable or unfavorable
evaluation of a behavior. Bommer et al. (1987) proposed an ethical decision-making
model with several environmental factors that could explain general ethical behavior
(i.e. an individual’s attitude toward the behavior). The environmental influences are
societal, belief system, personal, professional, legal, and business. The societal
environment captures the social and cultural values that impact the individual (Ferrell
and Gresham, 1985). One’s belief system consists of religious values and beliefs
developed in an individual’s spiritual or religious environment. Personal values are an
individual’s personal goals, experiences, and moral level, and personal environment is
the influence of family, peers, and significant others (Ferrell and Gresham, 1985).
Professional environment consists of the codes of conduct and professional
expectations of an individual’s profession (Higgs-Kleyn and Kapelianis, 1999). Legal
environment captures the law, the legislation, and the government, which may
persuade individuals to refrain from some prohibited behavior. Business environment
consists of corporate goals and profit motive of the company in which the individual
works. A company’s stated policies may increase the probability of ethical behavior
(Trevino, 1986; Victor and Cullen, 1988).
In addition to an individual’s environmental influences, moral obligation and
potential (perceived) consequences of one’s behavior have been shown to influence an
individual’s attitude toward ethical behavior. Personal normative beliefs entails the
moral obligation an individual feels to perform or not to perform a behavior (Schwartz
and Tessler, 1972). Consequences capture an individual’s awareness that unethical
behavior may have a penalty that affects the decision maker and/or others. When
examining software piracy, Eining and Christensen (1991) reported that consequences
were a significant influence on an individual’s behavioral intention. Kreie and Cronan
(1998) also found that consequences influence ethical decision-making.
In 1999, Kreie and Cronan proposed an end-user computing model for an ethical
dilemma. Their model studied the influence of societal environment, belief system,
A shifting model
1151
IMDS
105,9
1152
Figure 1.
Attitude toward ethical
behavior of information
systems personnel
personal values, personal environment, professional environment, legal environment,
business environment, moral obligation, and awareness of consequences on an
individual’s decision as to the behavior, in each case, being acceptable (ethical) or
unacceptable (unethical). After assessing five cases using student subjects (from
computing classes at a Midwestern university in the United States), they found four of
the five cases to be considered unacceptable, with moral obligation being a significant
influence in all cases. Ultimately, the study showed that influencing factors differ by
case (i.e. situation).
Based on the Kreie and Cronan (1999) attitudinal model (Figure 1), the attitude
model in the present study indicates that an individual’s attitude toward ethical
behavior is influenced by several factors from the decision maker’s environment
(societal, belief system, personal, professional, legal and business), moral obligation
and the possible consequences of a behavior. These factors were originally identified
by Bommer et al. (1987)) in a model of ethical decision-making. However, the factors
were never empirically tested.
Ethical attitude has the propensity to change as society changes. Privacy is an issue
that is continually being discussed in the media. Computer security, or lack thereof,
and identity theft are also discussed on a regular basis. Therefore, most individuals
would have exposure to these issues over time, whereas in 1999 (when the Kreie and
Cronan study was published), students would have had considerably less exposure to
these important issues since they were not discussed much in the media or the
classroom.
Another issue more prevalent today is downloading music and movies from the
internet-piracy. Since many people downloaded music from Napster freely prior to
regulation and routinely copy movies and DVDs, those same people may have the
attitude that that behavior is acceptable practice and that the music/movies/DVDs
should be free regardless of the laws that govern it. Therefore, it is advantageous
to explore if attitude influencers may have changed over time. Consequently, there
is a need to reassess attitude influencers with a new sample from the same type of
population to see if the influencers proposed have changed over time.
There has been mixed research regarding gender as an indicator of ethical/unethical
behavioral intention. Yet, many researchers have found gender to influence ethical
behavior and attitude (Banerjee et al., 1996; Gattiker and Kelley, 1999; Deshpande,
1997; Kreie and Cronan, 1998; Leonard and Cronan, 2001; Leonard et al., 2004) with
women tending to judge questionable behavior as less ethical and indicating that they
would be less likely to engage in this behavior than men. Venkatesh et al. (2000) sought
to understand technology adoption and usage decisions by focusing on differences in
the decision-making process of men and women. They found:
.
attitude to influence behavioral intention for men more than women;
.
subjective norm to influence behavioral intention for women more than men; and
.
perceived behavioral control to influence behavioral intention for women more
than men.
Venkatesh and Morris (2000) also found behavioral intention to be influenced by
usefulness for men and ease of use for women, and subjective norm to influence
behavioral intention more strongly for women.
There is also evidence to suggest that men and women’s ethical decision-making
process is different. Loch and Conger (1996) found men to rely on their attitudes toward
an action when deciding to perform a computing act, whereas women rely on
prevailing social norms. Dawson (1997) also found women to reach ethical judgments
based on relationships rather than rights and rules. Therefore, it is important that
gender differences will also be included in this study.
Research model
A representation of the attitude toward ethical decision model for this study is:
ATT ¼ f ðSOC; BEL; PVAL; PE; PRF; LGL; BUS; MO; CONÞ
where
ATT
¼ Attitude toward ethical behavior – an individual’s degree of
favorable/unfavorable evaluation of the behavior in question.
SOC
¼ Societal environment – society’s values; an individual’s culture
(Bommer et al., 1987).
BEL
¼ Belief system – religious values and beliefs (Bommer et al., 1987).
A shifting model
1153
IMDS
105,9
1154
PVAL ¼ Personal values – an individual’s personal values, goals, and experiences
(Bommer et al., 1987).
PE
¼ Personal environment – the influence of family, peers and significant
others (Bommer et al., 1987; Ferrell and Gresham, 1985).
PRF
¼ Professional environment – codes of conduct and professional
expectations within an individual’s profession (Bommer et al., 1987;
Higgs-Kleyn and Kapelianis, 1999).
LGL
¼ Legal environment – law, legislation, and government (Bommer et al.,
1987).
BUS
¼ Business environment – corporate goals and profit motive (Bommer
et al., 1987; Trevino, 1986; Victor and Cullen, 1988).
MO
¼ Moral obligation – personal normative beliefs (Schwartz and Tessler,
1972).
CON
¼ Consequences – awareness that behavior may have consequences that
affect oneself and/or others (Bommer et al., 1987; Eining and Christensen,
1991; Rest, 1979).
Method
The ethical attitudinal model (1) hypothesizes that attitude is influenced by the
decision maker’s environmental factors, moral obligation, and possible consequences
of behaving one way or another. To measure the possible influential factors, a
survey instrument was used. The survey contains five computing cases (the same
cases used by Kreie and Cronan (1999) were used in order to justify a shifting
attitudes model) and captures the respondent’s attitude toward the behavior of the
person described in a case. The cases present situations involving ethical issues
such as individual privacy, data accuracy, and intellectual property – issues
described by Mason (1986). The cases used in the instrument are given in the
Appendix. Kreie and Cronan’s (1999) eight items on a five-point scale are used to
measure the influencers of attitude. Multiple discriminant analysis is used to
determine the effects of each factor on the acceptable/unacceptable ethical decision.
Stepwise discriminant analysis is used to determine the significant factors that
discriminate between the attitudes.
Sample
To be able to compare results of the present study with those of Kreie and Cronan,
questionnaire respondents were students[1] in computing classes at a Midwestern
university in the US (as were Kreie and Cronan’s respondents). Four hundred and
twenty-two (422)[2] survey responses were received. The sample consists of
48.3 percent female (51.7 percent male) respondents. The respondents’ ages
range from 18 to 54 years, with an average of 21.9 years. The average GPA is
2.8 (ranging from 1.0 to 4.0), the average work experience for these students is 1.1 years
(ranging from 0 to 6 years), and over half of the respondents (54.7 percent) are juniors
and seniors. The sample is comparable to that used by Kreie and Cronan (1999).
Results
Table I presents a summary of the attitude toward the behavior and the factors theorized to
influence the individual’s attitude toward the situation. For each case, respondents
indicated the degree of influence each environmental factor had in assessing whether the
person’s behavior was acceptable or not (influence rated from “none” to “great”).
Respondents also indicated whether the actor in the case should have acted as described,
given certain consequences for such behavior. For cases A, B, D and E, respondents viewed
the behavior in question to be unacceptable (i.e. unethical). In case C, respondents thought
the behavior was acceptable (i.e. ethical). When compared to Kreie and Cronan (1999), our
study shows that the case perceptions (acceptable or unacceptable) have not changed.
Kreie and Cronan found cases A, B, D and E to be unacceptable and case C to be acceptable.
In case A, for instance, which describes a programmer who manipulates a bank’s
accounting system to hide his overdrawn account, the frequencies in Table I indicate
that 83.8 percent of the respondents view modifying the program as unacceptable.
Over 80 percent of the respondents said their personal values were very influential
(influence rated as “much” or “great”). Belief system, moral obligation and
consequences were also influential.
A general model is developed using multiple discriminant analysis. To increase the
power of the statistical tests, the 10 percent significance level ða ¼ 0:10Þ is used.
The attitude model tests the importance of each of the independent influences on the
measure of attitude toward the ethical behavior in question. Table II presents
the discriminant analysis results of the attitude model and classification values.
Models are developed for each of the five cases. Overall, moral obligation appears to
influence attitude in all five cases, and consequences is an influence in four of the five
cases and belief system in three of the five cases. As in the Kreie and Cronan (1999)
work, classification rates for the full model are listed as well as classification rates for
the reduced (significant) models. Moral obligation, consequences, belief system, and
personal values are found to be influences on attitude (toward ethical behavior) in case
A with a classification rate of 77.3 percent; moral obligation, consequences, belief
system, and business environment in case B with a classification rate of 76.4 percent;
moral obligation, personal environment, and consequences in case C with a
classification rate of 75.8 percent; moral obligation, consequences, and belief system in
case D with a classification rate of 68.2 percent; and moral obligation and personal
values in case E with a classification rate of 72.2 percent.
Table III provides a comparison of the current study findings to Kreie and Cronan’s
(1999) findings. Both studies found moral obligation to be a significant influence on
attitude. The current study found consequences to be an influence in four of the five
cases and belief system in three of the five cases. In the Kreie and Cronan study, legal
environment was important in four of the five cases, but it was not significant in any of
the cases in the current study.
Noting some differences in each ethical situation (case), we further the attitude
toward ethical behavior research by assessing attitude influencers for each case given
the respondent’s gender. Table IV presents a summary of the attitude toward the
behavior and the factors theorized to influence the individual’s (male or female) attitude
toward the situation for those who decided the behavior was unacceptable. Table V
presents the same information (male or female) for those who decided the behavior was
acceptable.
A shifting model
1155
Table I.
Factors and percent
weights used for ethical
decisions
Decision
N
Percent
Variable
Societal environment
None
Little
Moderate
Much
Great
Belief system
None
Little
Moderate
Much
Great
Personal values
None
Little
Moderate
Much
Great
Personal
environment
None
Little
Moderate
Much
Frequencies
1156
336
83.8
6.2
12.1
32.7
32.7
16.5
9.1
12.6
17.0
22.3
39.0
5.9
3.3
6.8
25.6
58.5
4.4
9.4
24.9
25.8
65
16.2
13.6
15.2
37.9
15.2
18.2
19.7
16.7
24.2
22.7
16.7
3.0
1.5
9.1
34.9
51.5
6.2
13.9
30.8
24.6
6.8
17.0
36.7
24.5
2.0
8.8
21.1
39.5
28.6
14.4
15.8
27.4
28.1
14.4
11.6
17.7
30.6
25.9
14.3
146
36.7
3.6
11.9
28.9
25.3
4.3
4.7
10.6
28.4
52.0
5.5
11.8
20.1
23.6
40.0
6.3
18.1
26.4
31.1
18.1
252
66.3
10.8
15.1
31.8
25.3
5.9
11.5
24.9
29.8
27.9
15.4
19.7
27.2
23.6
14.1
14.1
17.4
36.7
21.0
10.9
304
78.0
2.3
8.1
26.4
26.4
2.3
8.1
8.1
36.1
45.4
8.1
11.5
24.1
25.3
31.0
6.9
12.6
32.2
23.0
25.3
86
22.0
7.9
15.8
39.6
23.8
5.9
5.9
30.7
32.7
24.8
20.6
11.8
38.2
21.6
7.8
16.7
7.8
39.2
23.5
12.8
99
26.3
5.4
10.8
30.5
29.0
2.5
7.9
17.6
28.8
43.2
9.3
11.5
24.0
24.4
30.8
5.0
11.2
34.5
33.5
15.8
277
73.7
7.8
8.7
43.5
19.1
3.5
9.5
30.2
28.5
28.5
13.8
12.9
33.6
20.7
19.0
6.9
13.8
37.1
22.4
19.8
116
30.5
5.3
10.2
20.7
29.3
(continued)
3.4
5.2
9.0
29.6
52.8
8.2
9.0
16.9
28.1
37.8
4.1
7.9
18.0
39.0
31.1
265
69.5
Case A (programmer
Case C (company
Case D (used program
Case E (copied data made
manipulates accounting
Case B (software sent in
equipment used on
without paying required accessible during contract
system)
error was kept)
personal time)
fee)
work)
Acceptable Unacceptable Acceptable Unacceptable Acceptable Unacceptable Acceptable Unacceptable Acceptable Unacceptable
IMDS
105,9
Great
Professional
environment
None
Little
Moderate
Much
Great
Legal environment
None
Little
Moderate
Much
Great
Business
environment
None
Little
Moderate
Much
Great
Frequencies
35.5
5.0
9.7
11.5
25.3
48.5
7.9
9.1
21.2
23.2
38.5
6.5
12.9
18.8
27.9
34.0
24.6
6.1
12.1
22.7
27.3
31.8
6.1
13.6
21.2
28.8
30.3
7.7
7.7
27.7
35.4
21.5
6.8
12.9
31.3
28.6
20.4
8.2
16.3
34.0
27.2
14.3
6.2
17.2
28.3
28.3
20.0
15.0
8.3
13.4
28.0
28.0
22.4
6.7
14.6
22.4
31.1
25.2
5.9
11.4
23.6
29.1
29.9
30.4
9.2
12.4
30.1
25.8
22.6
14.1
19.3
24.8
25.2
16.7
4.9
8.5
26.8
32.7
27.1
17.1
8.1
8.1
17.2
26.4
40.2
9.2
17.2
16.1
32.2
25.3
4.6
8.1
21.8
25.3
40.2
36.8
6.9
10.8
25.5
38.2
18.6
10.8
10.8
33.3
28.4
16.7
2.0
7.9
28.7
35.6
25.7
12.9
5.4
6.8
24.7
29.8
33.3
5.7
7.5
22.2
31.9
32.6
4.3
5.0
20.4
29.4
40.9
24.4
34.6
4.5
7.1
15.0
29.2
44.2
6.7
9.4
17.2
26.2
40.5
7.1
9.7
18.7
27.0
37.5
(continued)
20.9
3.5
10.3
18.1
42.2
25.9
3.5
12.9
29.3
34.5
19.8
5.2
12.1
23.3
25.9
33.6
Case A (programmer
Case C (company
Case D (used program
Case E (copied data made
manipulates accounting
Case B (software sent in
equipment used on
without paying required accessible during contract
system)
error was kept)
personal time)
fee)
work)
Acceptable Unacceptable Acceptable Unacceptable Acceptable Unacceptable Acceptable Unacceptable Acceptable Unacceptable
A shifting model
1157
Table I.
Table I.
5.8
13.8
27.6
23.0
30.0
–
4.6
5.8
25.3
64.4
45.5
25.3
19.2
7.8
2.3
4.2
3.9
13.6
19.8
58.4
9.9
16.8
18.8
15.8
38.6
21.0
24.0
35.0
17.0
3.0
1.8
3.6
13.6
22.2
58.8
4.3
11.5
29.0
31.5
23.7
4.2
7.5
24.2
15.0
49.2
15.0
24.2
35.8
14.2
10.8
2.3
1.9
9.7
16.9
69.3
1.9
6.0
21.1
25.9
45.1
Notes: A dash ( –) represents a zero weight; variables whose frequencies are in italics were determined to be significant variables based on stepwise
discriminant analysis; athe actual wording regarding awareness of consequences varied based on the scenario
The following two items were scored on a 5-point scale with two anchors
Moral obligation
No obligation
24.6
3.8
36.7
6.2
No obligation
30.8
10.0
33.3
12.8
No obligation
21.5
15.0
21.8
32.7
No obligation
13.9
32.8
6.1
24.1
Strong obligation
9.2
38.1
2.0
24.1
Awareness of
consequences a
Should have
10.8
3.0
17.0
5.1
Should have
9.2
3.0
12.9
4.7
Should have
20.0
5.6
14.3
11.8
Should have
29.2
13.3
20.4
19.2
Should not have
30.8
74.9
35.4
59.2
Frequencies
1158
Case A (programmer
Case C (company
Case D (used program
Case E (copied data made
manipulates accounting
Case B (software sent in
equipment used on
without paying required accessible during contract
system)
error was kept)
personal time)
fee)
work)
Acceptable Unacceptable Acceptable Unacceptable Acceptable Unacceptable Acceptable Unacceptable Acceptable Unacceptable
IMDS
105,9
Predicted
Case A a
Moral obligation
Awareness of
consequences
Belief systems
Personal values
Case B a
Moral obligation
Awareness of
consequences
Belief system
Business environment
Case C a
Moral obligation
Personal environment
Awareness of
consequences
Case D a
Moral obligation
Awareness of
consequences
Belief system
Case E a
Moral obligation
Personal values
Unacceptable Acceptable Total
Unacceptable
260
76
336
Acceptable
Total
15
275
50
126
65
401
Unacceptable
192
60
252
Acceptable
Total
34
226
112
172
146
398
65
72
21
232
86
304
Total
137
253
390
Unacceptable
193
84
277
Acceptable
Total
33
226
66
150
Unacceptable
Acceptable
Total
184
25
209
81
91
172
Unacceptable
Acceptable
Model classification rate
Reduced
(significant)
Full
(percent)
(percent)
A shifting model
1159
77.3
78.1
76.4
77.0
75.8
77.4
99
376
68.2
69.3
265
116
381
72.2
74.7
Note: aFactors listed were significant variables in the reduced model
It is noted that females viewed the behavior in question to be more unacceptable
(i.e. unethical) than did males (Table IV), and that males view the behavior in question
to be more acceptable (i.e. ethical) than females (Table V). For example, in case
A (which describes a programmer who manipulates a bank’s accounting system to
hide his overdrawn account), the frequencies in Tables IV and V indicate that of the
334 responses classified as unacceptable, 50.3 percent are females and 49.7 percent are
males, and of the 65 responses classified as acceptable, 29.2 percent are females and
70.8 percent are males. Table VI summarizes the acceptable/unacceptable decisions by
case for both males and females.
Two general models are developed (males and females) using discriminant
analysis. To increase the power of the statistical tests, the 10 percent significance
level ða ¼ 0:10Þ is used. Table VII presents the discriminant analysis results of the
attitude model and classification values for females and males for each of the five
cases. For the females, generally moral obligation appears to influence attitude in
all five cases, and many other environmental factors influence attitude depending
on the case in question. Moral obligation, consequences, and societal environment
are found to be influences on attitude (toward ethical behavior) in case A with a
Table II.
Classification rates for
factors used
IMDS
105,9
Current study
Case A
1160
Case B
Case C
Case D
Table III.
Comparison of studies for
attitude influence
Case E
Model classification
rate (percent
correctly classified)
Kreie and Cronan
(1999)
Moral obligation
Consequences
Belief system
Personal values
Moral obligation
Consequences
Belief system
Business environment
77.3
Moral obligation
Personal environment
Consequences
Moral obligation
Conseqeunces
Belief system
75.8
68.2
Moral obligation
Legal environment
66.9
Moral obligation
Personal values
72.2
Moral obligation
Consequences
Legal environment
74.8
76.4
Moral obligation
Consequences
Belief system
Legal environment
Moral obligation
Consequences
Personal values
Societal environment
Legal environment
Moral obligation
Model classification
rate (percent
correctly classified)
77.6
73.1
75.3
classification rate of 77.5 percent; moral obligation, belief system, and professional
environment in case B with a classification rate of 80.2 percent; moral obligation
and personal environment in case C with a classification rate of 78.9 percent;
moral obligation, belief system, personal values, personal environment, and legal
environment in case D with a classification rate of 76.4 percent; and moral
obligation, societal environment, and business environment in case E with a
classification rate of 76.7 percent.
Overall for the males, moral obligation appears to influence attitude in all five cases,
and consequences and personal values are influences in four of the five cases. Moral
obligation, consequences, belief system, and legal environment are found to be
influences on attitude (toward ethical behavior) in case A with a classification rate of
79.3 percent; moral obligation, consequences, personal values, societal environment,
and belief system in case B with a classification rate of 75.7 percent; moral obligation,
personal values, business environment, and consequences in case C with a
classification rate of 74.8 percent; moral obligation, consequences, personal values,
professional environment, and societal environment in case D with a classification rate
of 70.6 percent; and moral obligation and personal values in case E with a classification
rate of 69.7 percent.
Comparing the findings for females and males, moral obligation is a significant
influence on attitude for both. However, males also use personal values and their
awareness of consequences when assessing a behavior. Females have different
variables influencing attitude depending on the situation in question. There is no
consistency in the case assessments by females other than the influence of moral
obligation.
Decision
N
Percent
Variable
Societal environment
None
Little
Moderate
Much
Great
Belief system
None
Little
Moderate
Much
Great
Personal values
None
Little
Moderate
Much
Great
Personal environment
None
Little
Moderate
Much
Great
Professional environment
None
Little
Moderate
Much
Frequencies
166
49.7
7.1
13.0
32.5
31.4
16.0
11.2
13.6
18.9
26.6
29.6
6.6
4.2
8.3
28.6
52.4
4.1
11.2
26.6
29.0
29.0
7.1
10.7
14.9
22.6
168
50.3
5.3
11.2
32.9
34.1
16.5
7.0
11.7
15.2
18.1
48.0
5.3
2.3
5.3
22.2
64.9
4.7
7.6
22.8
22.8
42.1
2.9
8.8
8.1
27.5
Case A
(programmer
manipulates
accounting system)
Females
Males
5.3
7.5
21.8
25.6
3.0
9.1
28.8
22.0
37.1
3.8
5.3
10.5
25.6
54.9
3.0
10.5
23.3
20.3
42.9
5.3
16.5
23.2
33.8
21.1
133
52.8
6.6
15.7
25.6
33.1
4.1
14.9
28.9
28.9
23.1
5.0
4.1
10.7
31.4
48.8
8.3
13.2
16.5
27.3
34.7
7.4
19.8
29.8
28.1
14.9
119
47.2
Case B (software
sent in error was
kept)
Females
Males
2.1
8.5
17.0
19.2
4.3
4.3
19.2
23.4
48.9
–
10.6
6.4
31.9
51.1
6.4
17.0
23.4
19.2
34.0
4.2
14.9
34.0
19.2
27.7
47
55.3
7.5
7.5
27.5
32.5
–
12.5
35.0
30.0
22.5
5.1
5.1
10.3
41.0
38.5
10.0
5.0
25.0
32.5
27.5
10.0
10.0
30.0
27.5
22.5
38
44.7
Case C (company
equipment used on
personal time)
Females
Males
2.7
4.8
16.4
25.3
2.1
10.3
31.5
26.7
29.5
2.7
6.1
15.8
25.3
50.0
5.5
11.6
24.7
24.7
33.6
3.5
10.3
31.7
35.9
18.6
146
52.9
6.0
5.3
24.8
33.8
9.0
11.3
29.3
31.6
18.8
2.3
9.9
19.7
32.6
35.6
13.5
11.3
23.3
24.1
27.8
6.8
12.0
37.6
30.8
12.8
130
47.1
Case D (used
program without
paying required fee)
Females
Males
137
51.7
5.8
7.9
21.6
41.0
23.7
12.2
8.6
17.3
33.1
28.8
5.0
5.8
10.1
32.4
46.8
7.3
11.6
23.9
28.3
29.0
6.5
7.2
16.6
33.8
(continued)
128
48.3
2.3
7.8
14.1
36.7
39.1
3.9
9.4
16.4
22.7
47.7
1.6
4.7
7.8
26.6
59.4
3.1
8.6
17.2
30.5
40.6
2.3
7.0
13.3
24.2
Case E (copied data
made accessible
during contract
work)
Females
Males
A shifting model
1161
Table IV.
Factors and percent
weights used for
unacceptable decisions
Table IV.
53.2
6.4
19.2
19.2
25.5
29.8
2.1
8.5
14.9
25.5
48.9
6.3
14.6
27.1
27.1
25.0
–
–
4.2
27.1
68.8
19.0
6.6
19.8
26.5
30.6
16.5
6.6
15.7
31.4
30.6
15.7
5.8
13.2
29.8
29.8
21.5
5.0
5.9
16.0
21.9
51.3
–
10.3
7.7
23.1
59.0
5.1
12.8
28.2
17.9
35.9
15.0
7.5
20.0
27.5
30.0
12.5
15.0
12.5
40.0
20.0
25.0
Case C (company
equipment used on
personal time)
Females
Males
2.7
4.1
6.8
20.3
66.2
4.7
11.5
28.4
30.4
25.0
4.1
4.1
21.9
28.1
41.8
2.1
8.2
21.2
30.8
37.7
50.7
0.8
3.1
21.4
24.4
50.4
3.8
11.5
29.8
32.8
22.1
6.8
9.8
27.8
31.6
24.1
9.8
6.8
23.3
33.1
27.1
30.1
Case D (used
program without
paying required fee)
Females
Males
2.3
0.8
6.2
10.9
79.8
3.1
5.4
16.3
31.0
44.2
6.3
9.4
15.6
27.3
41.4
3.1
9.4
16.4
21.1
50.0
53.1
2.2
2.9
13.0
22.5
59.4
0.7
6.6
25.6
21.2
46.0
7.9
10.1
21.6
26.6
33.8
10.1
9.4
18.0
30.9
31.7
36.0
Case E (copied data
made accessible
during contract
work)
Females
Males
Notes: A dash ( –) represents a zero weight; variables whose frequencies are in italics were determined to be significant variables based on stepwise
discriminant analysis; athe actual wording regarding awareness of consequences varied based on the scenario
Great
52.3
44.6
39.9
Legal environment
None
5.9
10.1
6.8
Little
7.6
10.7
9.8
Moderate
17.5
25.0
18.8
Much
24.6
21.4
31.6
Great
44.4
32.7
33.1
Business environment
None
7.0
5.9
9.8
Little
9.9
16.0
11.3
Moderate
17.0
20.7
24.8
Much
28.1
27.2
25.6
Great
38.0
30.2
28.6
The following two items were scored on a 5-point scale with two anchors
Moral obligation
No obligation
4.7
2.3
6.6
No obligation
9.9
10.1
12.5
No obligation
13.4
16.1
35.3
No obligation
32.6
33.3
19.1
Strong obligation
39.5
36.9
26.5
a
Awareness of consequences
Should have
3.5
2.4
5.2
Should have
4.1
1.8
3.7
Should have
2.3
8.4
8.1
Should have
9.4
17.4
16.9
Should not have
80.7
69.5
66.2
Case B (software
sent in error was
kept)
Females
Males
1162
Frequencies
Case A
(programmer
manipulates
accounting system)
Females
Males
IMDS
105,9
Decision
N
Percent
Variable
Societal environment
None
Little
Moderate
Much
Great
Belief system
None
Little
Moderate
Much
Great
Personal values
None
Little
Moderate
Much
Great
Personal environment
None
Little
Moderate
Much
Great
Professional environment
None
Little
Moderate
Frequencies
46
70.8
19.6
17.4
37.0
15.2
10.9
21.7
19.6
26.1
21.7
10.9
4.4
2.2
10.9
34.8
47.8
8.9
17.8
26.7
26.7
20.0
8.7
13.0
23.9
19
29.2
–
10.0
40.0
15.0
35.0
15.0
10.0
20.0
25.0
30.0
–
–
5.0
35.0
60.0
–
5.0
40.0
20.0
35.0
–
10.0
20.0
Case A
(programmer
manipulates
accounting system)
Females
Males
3.7
7.4
27.8
3.7
14.8
31.5
31.5
18.5
–
3.7
24.1
39.9
33.3
9.3
24.1
22.2
25.9
18.5
3.7
20.4
35.2
25.9
14.8
54
37.2
7.8
23.3
28.9
8.7
18.5
40.2
19.6
13.0
3.3
12.0
19.6
39.1
26.1
17.6
11.0
30.8
29.7
11.0
16.3
16.3
27.2
26.1
14.1
91
62.8
Case B (software
sent in error was
kept)
Females
Males
4.3
4.3
28.1
9.4
16.6
30.2
25.9
18.0
5.0
10.1
25.9
27.3
31.7
11.5
25.9
22.3
23.7
16.6
13.0
20.9
36.7
20.7
8.6
138
45.5
5.4
12.1
25.9
12.1
13.3
33.3
24.9
16.4
6.7
12.7
24.2
31.5
24.9
18.8
14.6
31.5
23.0
12.1
15.2
14.6
37.0
20.6
12.7
165
54.5
Case C (company
equipment used on
personal time)
Females
Males
–
11.8
23.5
11.8
11.8
44.1
26.5
5.9
2.9
2.9
29.4
29.4
35.3
29.4
2.9
38.2
20.6
8.8
20.6
14.7
29.4
20.6
14.7
32
33.3
3.0
6.1
31.8
6.1
18.2
36.4
22.7
16.7
7.6
7.6
31.8
33.3
19.7
16.4
16.4
38.8
20.9
7.5
14.9
4.5
44.8
23.9
11.9
64
66.7
Case D (used
program without
paying required fee)
Females
Males
64
55.2
4.7
17.2
35.9
20.3
21.9
17.2
15.6
29.7
21.9
15.6
3.1
9.4
37.5
26.6
23.4
7.9
12.7
42.9
15.9
20.6
3.1
15.6
21.9
(continued)
52
44.8
9.6
9.6
38.5
25.0
17.3
9.6
9.6
38.5
19.2
23.1
3.9
9.6
21.2
30.8
34.6
7.7
3.9
44.2
23.1
21.2
3.9
3.9
13.5
Case E (copied data
made accessible
during contract
work)
Females
Males
A shifting model
1163
Table V.
Factors and percent
weights used for
acceptable decisions
Table V.
31.7
31.7
13.7
17.3
22.3
26.6
20.1
8.6
15.1
28.8
22.3
25.2
45.0
27.1
20.0
5.7
2.1
2.1
3.6
7.9
20.0
66.4
25.6
14.4
9.8
14.1
33.7
29.4
13.0
7.6
15.2
30.4
26.1
20.7
37.0
29.4
25.0
6.5
2.2
22.8
13.0
14.1
20.7
29.4
6.0
4.2
18.0
19.8
52.1
45.5
24.0
18.6
9.6
2.4
9.6
10.2
30.7
28.9
20.5
14.5
20.5
27.1
24.1
13.9
33.1
23.5
Case C (company
equipment used on
personal time)
Females
Males
6.3
9.4
6.3
15.6
62.5
15.6
34.4
25.0
25.0
–
8.8
14.7
29.4
26.5
20.6
14.7
11.8
32.4
17.7
23.5
38.2
26.5
11.8
20.6
23.5
16.2
27.9
23.9
19.4
38.8
13.4
4.5
6.0
9.0
23.9
44.8
16.4
9.0
10.5
32.8
34.3
13.4
34.9
24.2
Case D (used
program without
paying required fee)
Females
Males
–
9.1
14.6
14.6
61.8
14.6
30.9
27.3
10.9
16.4
3.9
11.5
15.4
28.9
40.4
3.9
9.6
25.0
36.5
25.0
42.3
36.5
7.7
6.2
32.3
15.4
38.5
15.4
18.5
43.1
16.9
6.2
6.3
12.5
29.7
23.4
28.1
3.1
15.6
32.8
32.8
15.6
42.2
17.2
Case E (copied data
made accessible
during contract
work)
Females
Males
Notes: A dash ( –) represents a zero weight; variables whose frequencies are in italics were determined to be significant variables based on stepwise
discriminant analysis; athe actual wording regarding awareness of consequences varied based on the scenario
Much
30.0
26.1
31.5
Great
40.0
28.3
29.6
Legal environment
None
–
8.7
5.6
Little
20.0
10.9
20.4
Moderate
15.0
23.9
33.3
Much
20.0
32.6
24.1
Great
45.0
23.9
16.7
Business environment
None
–
11.1
5.6
Little
15.0
4.4
9.3
Moderate
20.0
31.1
33.3
Much
40.0
33.3
31.5
Great
25.0
20.0
20.4
The following two items were scored on a 5-point scale with two anchors
Moral obligation
No obligation
21.1
26.1
35.2
No obligation
21.1
34.8
40.7
No obligation
26.3
19.6
16.7
No obligation
15.8
13.0
5.6
Strong obligation
15.8
6.5
1.9
Awareness of consequences a
Should have
10.5
10.9
7.4
Should have
10.5
8.7
11.1
Should have
21.1
19.6
14.8
Should have
15.8
34.8
20.4
Should not have
42.1
26.1
46.3
Case B (software
sent in error was
kept)
Females
Males
1164
Frequencies
Case A
(programmer
manipulates
accounting system)
Females
Males
IMDS
105,9
166
49.7
168
50.3
334
46
70.8
19
29.2
65
145
54
37.2
91
62.8
252
133
52.8
119
47.2
303
138
45.5
165
54.5
85
47
55.3
38
44.7
96
32
33.3
64
66.7
276
146
52.9
130
47.1
265
128
48.3
52
44.8
116
137
51.7
64
55.2
Case A
Case B
Case C
Case D
Case E
Acceptable Unacceptable Acceptable Unacceptable Acceptable Unacceptable Acceptable Unacceptable Acceptable Unacceptable
Note: Indicates the percent acceptable for each case, or unacceptable for each case.
a
Males
N
Percenta
Females
N
Percenta
Total
N
Frequencies
A shifting model
1165
Table VI.
Summary for
acceptable/unacceptable
decisions by male and
female
IMDS
105,9
Female
1166
Table VII.
Comparison of gender
findings
Model classification
rate (percent
correctly classified) Male
Case A Moral obligation
Consequences
Societal environment
77.5
Case B Moral obligation
Belief system
Professional environment
80.2
Case C Moral obligation
Personal environment
78.9
Case D Moral obligation
Belief system
Personal values
Personal environment
Legal environment
Case E Moral obligation
Societal environment
Business environment
76.4
76.7
Moral obligation
Consequences
Belief system
Legal environment
Moral obligation
Belief system
Consequences
Personal values
Societal environment
Moral obligation
Consequences
Personal values
Business environment
Moral obligation
Personal values
Consequences
Professional environment
Societal environment
Moral obligation
Personal values
Model classification
rate (percent
correctly classified)
79.3
75.7
74.8
70.6
69.7
Discussion and conclusions
The purpose of this research was to determine whether environmental factors, moral
obligation, and awareness of consequences influence an individual’s attitude toward
ethical behavior and to compare those findings to Kreie and Cronan’s (1999) work to see
if the attitude influencers have changed, and to test if gender differences exist as well.
The proposed model suggests that an individual’s attitude toward ethical behavior is
influenced by society, by the professional, legal, and business environments, and by
one’s belief system, personal values, personal environment, moral obligation and
awareness of consequences. The influences of these environmental factors varied, and
have changed from the Kreie and Cronan study, based on the ethical issues involved.
Many of the proposed model’s influences do exist and attitude has many
dimensions. However, only moral obligation and consequences influence attitude,
consistently, when testing individual cases, as compared to the Kreie and Cronan study
where moral obligation and legal environment were of highest importance. Perceptions
of the cases, as being acceptable or unacceptable, have not changed but the variables of
influence have shifted. Referring to Table III, it is interesting that legal environment is
no longer an influence, especially since more laws are in effect than there was in 1999.
Respondents seem more concerned about consequences, if any, and not the laws that
do exist. Also, looking at individual cases, none of the exact same influences exist as
were stated by Kreie and Cronan; all five cases resulted in different variables of
influence than found in the previous study. Clearly, the attitude influencers have
changed over time and do depend on the situation being assessed. Attitude could
change continually as new influences are introduced, or society changes. Therefore,
attitude influencers will need to be reassessed as changes over time occur in society.
The influence of gender was also assessed. The findings indicate that attitude has
many dimensions for males and females, and the attitude influencers not only depend on
the behavior in question but on the gender of the individual. Females generally viewed
the behaviors in question as more unacceptable (i.e. unethical) than males, and males
viewed the behaviors in question as more acceptable (i.e. ethical) than females. Female
attitudes toward ethical behavior depended on moral obligation in all cases examined.
However, depending on the situation, various influencers were present which indicates
that females assess the situation and do not rely on the same factors for all cases. Male
attitudes toward ethical behavior depended primarily on moral obligation, awareness of
consequences, and personal values. Therefore, males have a given set of parameters
when assessing a situation, where as females adjust their parameters based on the
situation. For example in case C (company equipment that was used on personal time),
moral obligation and personal environment were influencers for females, and moral
obligation, consequences, personal values, and business environment were influencers
for males. In this situation it appears that women are influenced by their peers, and men
are influenced by their own personal goals, corporate goals, and the possible
consequences of their actions. This clearly shows how one’s attitude can be different
based on gender, given that the influencers are so drastically different.
Since the ethical attitude of an individual in any given situation is dependent on
many factors, both internal (personal values, belief system) and external (societal
environment, legal environment, etc.), an assessment of individual situations would be
useful in comparing the impact of different issues (cases). Additional information
technology issues should, therefore, be considered when assessing attitude toward
ethical behavior. Further research is needed to identify influences on attitude toward
ethical behavior. Also, attitude influencers have shifted over time, which means that
organizations must continually assess their employees’ ethics’ climate and adjust their
ethics’ programs as attitude influencers change.
Given the gender findings, training programs need to focus on the different influencers
for males and females. Also, emphasis should be placed on establishing the importance of
the influencers that might create more ethical behavior for males or females. Future
research should seek to further the gender findings by studying a professional setting.
Notes
1. Many research studies have used students as subjects. Students have been assumed to be
suitable surrogates for business managers and decision makers. Results should be generally
applicable to actual business managers, which is especially the case when researchers are
interested in the ethical decision-making process. Student samples can be used without a
major threat to generalizability (“Methods in Business Ethics”, Journal of Business Ethics,
9(6), June 1990, p. 463).
2. N varies for some analyses because of incomplete responses.
References
Aiken, R.M. (1988), “Reflections on teaching computer ethics”, paper presented at the Fourteenth
SIGCSE Technical Symposium on Computer Science Education, pp. 8-11.
A shifting model
1167
IMDS
105,9
1168
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Appendix. Scenarios
Case A
A programmer at a bank realized that he had accidentally overdrawn his checking account.
He made a small adjustment in the bank’s accounting system so that his account would not have
an additional service charge assessed. As soon as he made a deposit that made his balance
positive again, he corrected the bank’s accounting system.
Case B
With approval from his boss, a person ordered an accounting program from a mail-order
software company. When the employee received his order, he found that the store had
accidentally sent him a very expensive word processing program as well as the accounting
package that he had ordered. He looked at the invoice, and it indicated only that the accounting
package had been sent. The employee decided to keep the word processing package.
Case C
A computer programmer enjoyed building small computer applications to give his friends. He
would frequently go to his office on Saturday when no one was working and use his employer’s
computer to develop computer applications. He did not hide the fact that he was going into the
building; he had to sign a register at a security desk each time he entered.
Case D
A computing service provider offered the use of a program at a premium charge to subscribing
businesses. The program was to be used only through the service company’s computer.
An employee at one of the subscribing businesses obtained a copy of the program accidentally,
when the service company inadvertently revealed it to him in discussions through the system
(terminal to terminal) concerning a possible program bug. All copies of the program outside of
the computer system were marked as trade secret, proprietary to the service, but the copy the
customer obtained from the computer was not. The employee used the copy of the program after
he obtained it, without paying the usage fee to the service.
Case E
A marketing company’s employee was doing piece work production data runs on company
computers after hours under contract for a state government. Her moonlighting activity was
performed with the knowledge and approval of her manager. The data were questionnaire
answers of 14,000 public school children. The questionnaire contained highly specific questions
on domestic life of the children and their parents. The government’s purpose was to develop
statistics for behavioral profiles, for use in public assistance programs. The data included the
respondents’ names, addresses, and so forth.
The employee’s contract contained no divulgement restrictions, except a provision that
statistical compilations and analyzes were the property of the government. The manager
discovered the exact nature of the information in the tapes and its value in business services his
company supplied. He requested that the data be copied for subsequent use in the business.
The employee decided the request did not violate the terms of the contract, and she complied.
(Lori N. K. Leonard is an Associate Professor of Management Information Systems at the
University of Tulsa. Leonard received her PhD from the University of Arkansas and is an active
member of the Decision Sciences Institute. Her research interests include electronic commerce,
electronic data interchange, ethics in computing, and online auctions. Her publications have
appeared in Journal of Computer Information Systems, Information & Management, Journal of
the Association for Information Systems, Journal of Organizational Computing and Electronic
Commerce, Journal of End User Computing, as well as in other journals, and Proceedings of
various Conferences.
Timothy Paul Cronan is Professor of Information Systems and M.D. Matthews Chair in
Information Systems in the Walton College of Business, University of Arkansas, Fayetteville.
Cronan received his DBA from Louisiana Tech University and is an active member of the
Decision Sciences Institute and The Association for Computing Machinery. He has served as
Regional Vice President and on the Board of Directors of the Decision Sciences Institute and as
President of the Southwest Region of the Institute. In addition, he has served as Associate Editor
for MIS Quarterly. His research interests include ethics in computing, local area networks,
downsizing, expert systems, performance analysis and effectiveness, and end-user computing.
His publications have appeared in Decision Sciences, MIS Quarterly, OMEGA The International
Journal of Management Science, The Journal of Management Information Systems,
Communications of the ACM, Journal of End User Computing, Database, Journal of Research
on Computing in Education, Journal of Financial Research, as well as in other journals, and
Proceedings of various Conferences.)
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