Asia Pacific Management Review 18(4) (2013) 427-440
www.apmr.management.ncku.edu.tw
Empirical Factors of Cross-Cultural Students’ Aberrant Behavior in
E-Consumer Ethics
Long Chuan Lu*, Pin Lan Chen, Tsai Feng Liu
Department of Business Administration, National Chung Cheng University, Taiwan
Received 30 Jul 2010; Received in revised form 28 February 2012; Accepted 22 August, 2012
Abstract
This article explores student perceptions and attitudes towards aberrant Internet consumer
behaviours (ACB) and examines cross cultural differences in E-consumer ethics. Data
gathered from 365 students from more than five different cultures — Taiwan, China,
Indonesia, Malaysia, the U.S., and the U.K., and a group of other countries － were compared
in this investigation. The respondents from Southeast Asia displayed the highest E-ethics
while those from China exhibited the lowest. Most respondents spend 2 to 5 hours a day
browsing the internet. On average, the students from Taiwan displayed the highest E-ethics. A
high percentage of the respondents thought “Illegal and Questionable activities” are wrong;
while a lower percentage considered factors of “Human Internet Trade” and “Downloading
Material” are wrong. The result shows that Machiavellianism was significantly and negatively
related with to E-ethics, while consumer attitudes towards the Internet were not significantly
related to E-ethics.
Keywords: Aberrant consumer behaviors, consumer e-ethics, machiavellianism
1. Introduction2
More and more marketers are now using blogs or facebook to spread positive or negative
word-of-mouth on the internet, and consumers may not find out the secrets behind the
messages they receive. Su and Wang (2010) find adolescents choice and the influence
between the uncertainty avoidance and masculinity of cultural dimensions in Taiwan and
South Korea. They have been relative steadily and for that the powers to foretell the strategies
over family purchase decisions. Lu (2008) has shown that high sensation-seekers and high
Internet dependents are more likely to engage in online inter-personal deception than their
counterparts. Defining dysfunctional customer behaviors are adopted across a wide variety of
contexts. Fullerton et al. (1993) refer to aberrant consumer behaviors not only cheat
consumers, but also victimize them. From what has been said above, attitudes toward online
transactions serve as the bridge between individual’s cultural values, background
characteristics, education and the satisfaction of their needs.
Furthermore, most of the research on business ethics has focused on marketing related
activities (Ferrell and Gresham, 1985; Hunt and Vitell, 1986; Fraedrich et al., 1989). Murphy
and Laczniak (1981) reviewed the research on marketing ethics and concluded that most
studies examined ethics in relation to business and marketing situations, with just 5%
examining ethics in consumer situations. However, attitude has been evidently demonstrated
*
Corresponding author. E-mail: [email protected]
DOI:10.6126/APMR.2013.18.4.05
**
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to be the most important construct in social psychology (Ajzen, 1991). Consequently, it is
worth examining consumer ethics more closely.
The research provides an overview of the consumer ethics and internet-related aberrant
consumer behavior or misbehavior literature. We further measured equivalence in terms of
revising the questionnaire about Internet users’ ethics and built the framework and the method
of sampling. The researchers used a regression model and ANOVA in order to test the
hypotheses. Results denote that students in Taiwan have higher E-ethics on average than those
in the U.S. and U.K. Through the final implications of this study, we suggest that future
research deepen the investigation of the moderating effects of cross-cultural factors to better
predict the effects of the self-selection process on marketing persuasion strategies.
2. Literature review
2.1 Cross-culture and personal characteristics
The Hunt-Vitell (1986) model shows two main ethical assessments: a deontological
evaluation or a teleological evaluation. Vitell and Muncy (1992) identified attitude as an
important factor contributing to consumer ethical judgments. Vitell and Paolillo’s (2003)
original results were obtained from 569 heads of households in the U.S. Their results indicate
that consumers believe it more unethical to actively benefit from an illegal activity than to
passively benefit from it. However, their results might be different for Asian people where the
emphasis on social harmony and cooperation contrasts sharply with the Western focus on
individuality (Swinyard et al., 1990). Culture, for example, has been found to be a
fundamental determinant of ethical decision-making in Lu et al.’s study (1999). Another
factor that needs to be weighed in on is the difference between traditional and modern media,
because unlike the former the latter focuses on marketing campaigns that first create
awareness and then drive consumers through the process until they actually make an online
purchase (Goodwin, 1999).
Cyberspace exists separately from the physical world, and may have developed its own
ethical culture, with a unique a set of shared beliefs or standards that help individuals decide
(Freestone and Mitchell, 2004). The Internet cross-culture communication has created new
commerce, and affects consumers’ perceptions. The elements of culture are values, attitudes,
language and aesthetics (Fletcher, 2006). Every culture has its unique values and norms that
are developed over generations, and thus cultural factors impose a significant influence on
ethical issues. Defining the legality or ethics of Internet behaviors is thus highly challenging.
Personal characteristics constructs includes various possible dimensions, including the
individual level of moral development, as suggested by Kohlberg (1981), and individual
personality. Machiavellianism, relativism, and idealism all denote characteristics or beliefs
that individuals hold regarding the world (Kenhove et al., 2001). Pinto and Kanekar (1990)
found a positive association between Machiavellianism and ethical sensitivity for male
students but a negative association between the two constructs for female students.
Freestone and Mitchell (2004) indicated that Generation Y consumers appear permissive
of software piracy, and many commented they feel such piracy does not directly harm sellers
because they cannot see the direct economic consequences of their actions. Eventually, some
activities were not perceived as unethical at all, and most of their types tended to be activities
involving the copying of intellectual property such as software, tapes or movies. They saw
themselves as victims of inflated software, music or movie prices, and blamed the industry for
keeping prices artificially high.
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2.2 Consumer internet-related aberrant behavior or misbehaviors
Music and movie downloading and software piracy are two common consumer
misbehaviors. Fullerton and Punj (1993) define aberrant consumer behavior (ACB) as
consumer behavior which infringes on regularly approved norms of behavior and which,
accordingly, is held as dishonorable by most traders and consumers. Freestone and Mitchell
(2004) pointed out that unethical consumer practices cut significantly into company profits,
and these misdemeanors include fraud, piracy, accessing pornography, cyber stalking, online
pharmacies, organ selling, and identity theft.
An important differentiation is also made in the literature between two common
misdemeanors: soft-lifting and counterfeiting. Soft-lifting refers to the unauthorized copying
of software for personal use, while counterfeiting involves the sale of unauthorized copies
(Husted, 2000). Logsdon, Thompson and Reid (1994) found that students frequently perceive
software piracy as involving low moral intensity. Glass and Wood (1996) found that software
piracy is frequently not perceived as an ethical problem, but rather as a result of individual
evaluations of distributive fairness, including comparing the ratio of outcomes to inputs.
Hackers are motived by various factors, some are simply trying to educate themselves
about systems, while others claim that they seek security holes simply for purposes of
notifying system administrators (Spafford, 1997). Hackers tend to be young males, aged
between 15 and 25 years. Most grow out of hacking and frequently go on to gain employment
in the legitimate end of information security (Embar-Seddon, 2002).
3. Research framework and hypotheses
Vitell (2003) pointed out that only personal characteristics and cultural environment
influence consumer ethics. In terms of personal characteristics, Machiavellian-oriented
persons possess a cool detachment that makes them less emotionally involved with others or
with saving face in potentially embarrassing situations. Consequently, the level of individual
ethics decreases as Machiavellianism increases (Vitell et al., 1991). Machiavellianism
therefore appears appropriate for an examination of consumer ethical ideologies.
The Internet differs from traditional information outlets in that barriers of time and
distance are minimized by marketers’ ability to create databases and consumers’ ability to
selectively obtain information (Cronin, 1994). Gallaway and Kinnear (2001) Survey results
and media reports both indicate significant consumer awareness of the ethical and legal issues
associated with downloading activities. This means that consumers are aware that deciding
whether to download music from the Internet involves a moral judgment. Thus, decisions to
engage in downloading may reflect an overall degree of ethical concern on the part of the
respondent (Levin et al., 2004).
The fact that the Internet enables more flexible information display (Bush et al., 2000)
also has an effect. Wu (2003), for instance, noted that consumers who shop online have higher
attitude scores that are directly related to online purchase decisions. Consumer demographic
characteristics are also significantly related to attitudes toward online shopping. For example,
consumers who inherently like computers and Internet usage tend to reflect high attitude
scores. Based on the literature review, the following hypotheses, which assume
Machiavellianism and attitudinal factors to be important personal characteristics that
influence consumer E-ethics, were postulated:
H1. Personal characteristics are influential to consumers’ E-ethics.
H1a. There is a negative relationship between consumers’ Machiavellianism and their E-thics.
H1b. There is a positive relationship between consumers’ attitude toward the Internet and
their E-ethics.
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Culture directly influences how an individual perceives ethical problems, alternatives, and
consequences (Hunt and Vitell, 1986). Culture research recognizes that individuals from
different backgrounds are exposed to different traditions, heritages, rituals, and religions, all
of which provide various learning environments and histories, and which in turn significantly
influence moral standards, beliefs, and behaviors in different cultures. That is, culture not
only influences learning, but also influences perceptions of right versus wrong, acceptable
versus unacceptable, and ethical versus unethical (Lu et al., 1999). Culture clearly influences
software piracy (Husted, 2000). Steidlmeier (1993) explains that intellectual property
protection is deeply rooted in Western cultural values of liberalism and individual rights.
Numerous developing countries do not accept the legitimacy of claims by businesses to have
monopolized intellectual property. Swinyard et al. (1990) found that Singaporean students
were more influenced by the consequences of their actions in relation to their selves, families,
and communities than U.S. students by the illegality of copying software. Whiteman, et al.
(1998) also found that U.S. students had less permissive attitudes towards the ethics of
computer use than students from Hong Kong and Singapore.
Furthermore, Franke and Nadler (2008) forecast regarding the effects of the four superior
cultural dimensions on entire ethical attitudes across countries. Fletcher (2006) further states
that when targeting a specific culture on the Internet, the situation should be direct and should
seek commitment from the consumer. Based on the above review of the relevant literature on
the influence of culture, we propose the following hypothesis:
H2. Cultural differences influence consumer E-ethics.
4. Methodology
The questionnaire included questions on MACH IV, consumer attitudes towards the
Internet, and Internet-related aberrant behaviors. Questions dealing with MACH IV scale
were developed by Christie and Geis (1970). Consumer attitudes towards Internet questions
were derived from the attitudinal statements from the questionnaire of Vitell and Muncy
(1992). Questions dealing with Internet-related aberrant behaviors were adopted from
Freestone and Mitchell (2004). Principal Factor analysis was used to classify the consumers’
Internet related aberrant behaviors. The final part of the questionnaire comprised of
demographic questions. The questionnaire of this study was administered via the Internet.
Respondents were emailed a link to the website and asked to refer others in the target
population to the site to complete the questionnaire. For improving the reliability and validity
of the research, we used multiple-forward translation. The questionnaire scales were based on
the English version and were translated into Chinese and then back into English.
For testing the effects of cultural differences on E-ethics and provide a stark contrast
across each of the items. Taiwan and Southeast Asia were selected as the sample because of
their similar religious backgrounds, Buddhism, and their Confucian-oriented educational and
social systems. Undergraduate students were selected as the sample population because they
have grown up with computers and the Internet. Additionally, their relative homogeneity
reduced the potential for random errors versus a sample taken from the general public.
The questionnaire comprised four parts: multi-items dealing with Internet-related aberrant
behaviors, multi-item scales for Machiavellianism, multi-item scales related to consumer
attitudes towards the Internet, and questions regarding demographic status. Original items
were utilized as much as possible, with modifications as deemed necessary. To reveal
perception levels for each situation, all of the items were measured using a five-point Likerttype scale ranging from 1 (strongly disagree) to 5 (strongly agree). Internet-related aberrant
behaviors were measured using 23 items taken from Freestone and Mitchell (2004), the aim
being to measure consumer E-ethics. The scales comprised five dimensions: illegal activities
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(α=0.88), questionable activities (α=0.72), hacking related activities (α=0.71), human Internet
trade (α=0.71), and downloading materials (α=0.78). Higher scores denoted high individual
ethics towards the Internet. Machiavellianism was measured using the Mach IV scale
designed by Christie and Geis (1970). The Cronbach α of this scale was 0.79. Kenhove,
Vermeir, and Verniers (2001) also used the Mach IV scale to measure Machiavellianism, and
the cronbach α was 0.71. A high score on this measure indicated high Machiavellianism.
Items measuring consumer attitude towards the Internet were adopted and modified from the
scale of Vitell and Muncy (1992). Numerous researchers have adopted this scale (Al-Khatib
et al., 1997). In sum, a high score denoted a positive individual attitude towards the Internet.
5. Data analysis
The final sample comprised 365 questionnaires, representing an effective response rate of
99%. Respondents were almost equally balanced in terms of gender. Most respondents were
aged between 20 and 29 years. Respondent education level was primarily undergraduate and
graduate (57.5% undergraduate; 39.5% graduate). Most respondents (56.2%) indicated that
they spend 2 to 5 hours a day using the Internet. Regarding nationality, respondents were
mostly from Taiwan (74%), with the next largest group coming from Indonesia (14%) (see
Table 1).
Table 1. Characteristics of the sample
Gender
Male
Female
Frequency
Percent
182
183
49.9
50.1
Age
10-19
45
12.3
20-29
262
71.8
30-39
45
12.3
40-49
11
3.0
Above 50
2
0.5
Time of Browsing the Internet ( hours )
1
25
6.9
2
43
11.8
3
62
17.0
4
42
11.5
5
59
16.2
6
30
8.2
7
5
1.4
8
33
9.0
10
34
9.3
12
17
4.7
13
1
0.3
15
3
0.8
16
3
0.8
17
1
0.3
18
1
0.3
20
1
0.3
Education
Undergraduat
Graduate
Doctor
Other
Nationality
Taiwan
China
U.S.A
U.K
Indonesia
Malaysia
Myanmar
Macanese
Hong Kong
Korea
Brazil
India
Thailand
France
Vietnam
Singapore
431
Frequency
Percent
210
144
9
2
57.5
39.5
2.5
0.5
270
10
3
1
18
51
1
2
2
1
1
1
1
1
1
1
74.0
2.7
0.8
0.3
4.9
14.0
0.3
0.5
0.5
0.3
0.3
0.3
0.3
0.3
0.3
0.3
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We try to test measurement equivalent of consumer E-ethics attitudes of across cultures.
First, it is necessary to confirm these factors are expanded to include an intercept term for the
observed variables. The second, we try to use Factor analysis based on the principal
components method was applied to classify Internet-related aberrant consumer behaviors,
which served as the independent variable in this study and was used to test consumer E-ethics.
As shown in Tabe 2, this study identified four factors explaining aberrant consumer Internetrelated behaviors. The Cronbach α of this scale was 0.944. The dimensions of illegal activities,
questionable activities, for human Internet trade, and downloading specific type of material
had Cronbach aplhas of 0.9416, 0.9053, 0.8247, and 0.9524, respectively. The reliabilities
were all excellent. The Cronbach α of MACH IV scale was 0.62 in this study. The scale was
used to measure respondent Machiavellianism, with a high score indicating high
Machiavellianism. Kenhove, Vermeir, and Verniers (2001) argued that the level of ethics of
an individual decreased with increasing Machiavellianism. The scale of consumer attitude
towards the Internet with Cronbach α of 0.73 contained three items in this study.
Table 2. A rotated factor structure for Internet related aberrant behaviors (Alpha = 0.944)
Statements
1. Gaining unauthorized
access to systems with
intention to participate
in terrorist activity.
2. Using stolen credit
cards to order goods
over the Internet.
3. Setting up medical
websites for
commercial gain via
exploitation of gullible
people.
4. Gaining unauthorized
access with intention
to plant viruses aimed
at causing damage to
the system.
5. Impersonating someone
else by using their
credit card to purchase
goods, e.g., family
members.
6. Selling counterfeit
goods over the
Internet.
7. Using credit card
numbers that you
haven’t stolen but have
“discovered” yourself,
Illegal
activities
Questionable
activities
α= 0.9416 α= 0.9053
0.846
Human
Internet
trade
α= 0.8247
Downloading
material
% Agree
it is
wrong
α= 0.9524
57.6
0.836
56.5
0.835
54.6
0.821
55.4
0.764
57
0.721
0.449
0.706
53.8
51.3
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e.g., from websites.
8. Hacking into phone
lines to make calls for
which you won’t be
billed.
9. Accessing and
downloading child
pornography.
10. Arranging to “meet”
people for paid
company with the
likelihood that it will
lead to sex.
11. Selling counterfeit
goods over the
Internet.
12. Sending malicious
emails.
13. Accessing sites with
bad taste subject
matter, e.g.,
rotten.com.
14. Online gambling, e.g.
casinos.
15. Using the Internet as a
meeting point for
questionable subject,
e.g., religious cults,
anti-social groups.
16. Buying potential
offensive products
over the Internet, e.g.,
Nazi memorabilia.
17. Gaining unauthorized
access to systems to
“crack” them and find
system flaws for fund/
as a hobby.
18. Gaining unauthorized
access to computer
systems (hacking) in
the knowledge that it
is illegal.
19. Adopting children
using payment via the
Internet.
20. Purchased eggs via the
Internet for the “DIY”
IVF treatment.
21. Purchasing organs for
0.704
0.314
53.9
0.606
52
0.580
0.544
50.9
0.553
0.439
45.5
0.551
0.498
52.6
0.807
38.8
0.754
0.331
37.9
0.706
0.303
35.5
0.515
0.609
0.405
0.595
0.342
43.7
0.512
0.536
0.305
47.3
0.832
23.6
0.829
31.8
0.768
37.6
433
48.9
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transplant over the
Internet.
22. Downloading movie
files from the Internet
for free.
23. Downloading music
files from the Internet
for free, e.g., Napster
sites or similar.
0.955
6.8
0.953
6
The purpose of the statistical analyses conducted was to empirically test the two
hypotheses. It was first necessary to explore regression analysis by using four dimensions
(Illegal activities, Questionable activities, Human Internet trade, and Downloading material)
and the whole array of Internet aberrant activities as the dependent variables and
Machiavellianism and attitude toward Internet as the independent variables. Further, ANOVA
analysis was carried out using culture as the independent variable and using these five
dimensions as the dependent variables to measure cultural differences. The results of the
regression analysis for the five models of this study are shown in Table 3. The five models
presented here were all significant. The first model used all items of the Internet Aberrant
Behaviors’ Scale as the dependent variable. This model reflected 4.2% explanation power,
7.851 for its F-value, and was significant (p=0.002). Independent variables’ betas in this
model were -0.257 (MACH) and 0.099 (Attitude), and they were significant (p=0.002 and
0.020). H1a and H1b were supported in this model.
Table 3. Regression analysis
R -Square
F
Beta
Model 1 (Dependent: Internet aberrant behaviors)
0.042
7.851
Variables
(Constant)
4.400
MACH
-0.257
Attitude
0.099
Model 2 (Dependent: Illegal activities)
0.043
8.113
Variables
(Constant)
4.621
MACH
-0.224
Attitude
0.141
R -Square
F
Model 3 (Dependent: Questionable activities)
0.027
10.188
Variables
(Constant)
MACH
Attitude
Beta
t
Sig.
0.002*
17.126
-3.179
2.334
0.000***
0.002*
0.020*
0.000***
16.690
-2.565
3.080
0.000***
0.011*
0.002*
t
Sig.
0.002*
4.849
-0.332
0.091
434
16.850
-3.192
1.767
0.000***
0.002*
0.078
L.-C. Lu et al. / Asia Pacific Management Review 18(4) (2013) 427-440
Model 4 (Dependent: Human Internet trade)
0.012
4.358
Variables
(Constant)
MACH
Attitude
Model 5 (Dependent: Downloading materials)
0.011
3.963
Variables
(Constant)
MACH
Attitude
0.038*
4.240
-0.259
-0.043
12.375
-2.088
-0.824
0.000*
0.038*
0.411
0.047*
2.871
-0.246
0.070
8.411
-1.991
1.346
0.000***
0.047*
0.179
Significance: * - less than 0.05; **- less than 0.01; ***- less than 0.001.
The second model’s dependent variable comprised the dimensions of illegal activities.
This model had 4.3% explanation power, 8.113 for its F-value, and was also significant
(p=0.000). Independent variables’ betas in this model were -0.224 (MACH) and 0.141
(Attitude), and they were also significant (p=0.011 and 0.002). H1a and H1b were also
supported in this model. The dimensions of questionable activities constituted the dependent
variable in the third model which had 2.7% explanation power, 10.188 for its F-value, and
was significant (p=0.002). Independent variables’ betas in this model were -0.332 (MACH)
and 0.091 (Attitude), and only the MACH variable was significant (p=0.002). H1a and H1b
were supported in this model but the relationship between consumers’ attitude toward Internet
and their E-ethics was not significant.
The fourth model used the dimensions of human Internet trade as the dependent variable.
This model had 1.2% explanation power, 4.358 for its F-value, and was also significant
(p=0.038). Independent variables’ betas in this model were -0.259 (MACH) and -0.043
(Attitude), and only the MACH variable was significant (p=0.038). The attitude variable was
not significant (p=0.411) and had the opposite relationship compared to the H1b. It indicated
that consumers who have a positive attitude toward the Internet have low E-ethics, and a high
percentage agreeing to human Internet trade. Hence, only H1a was supported in this model.
The final model used the dimensions of downloading material as the dependent variable. This
model had 1.1% explanation power, 3.963 for its F-value, and was also significant (p=0.047).
The betas of the independent variables in this model were -0.246 (MACH) and 0.070
(Attitude), and only the MACH variable was significant (p=0.047). H1a and H1b were
supported, but the relationship between consumer attitude towards the Internet and E-ethics
was not significant in this model.
Table 4 show ANOVA analysis was used to test hypothesis 2, namely “Cultural
difference influences consumer E-ethics”. More than five different cultures were compared in
this analysis: Taiwan, China, the U.S. and the U.K., Indonesia and Malaysia, and a group of
other countries. Myanmar, Macao, Hong Kong, Korea, Vietnam, Singapore, etc., were
included in the group of other countries, and most of the countries in this group were located
in Southeast Asia. Overall, the group of other countries had the highest mean score (4.13) for
Internet aberrant behaviors, while China had the lowest (3.63) from all the countries,
indicating that respondents in other countries had higher E-ethics while those in China had
lower E-ethics. Regarding illegal and questionable activities, respondents from other countries
also had the highest (4.53 and 4.11), while those from China had the lowest (4.12 and 3.43).
Respondents from Indonesia and Malaysia had the highest (3.71) and China had the lowest
(3.07) E-ethics in relation to human Internet trade. Respondents generally had high mean
scores exceeding 3 in these four sections, indicating high E-ethics. The opposite situation
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applied for downloading material, with respondents in other countries having the highest (2.5)
E-ethics and those from the U.S. and the U.K. having the lowest (1.5). Furthermore, in the
five sections, Taiwanese respondents also displayed high E-ethics except in human related
activities. Generally, respondents elsewhere exhibited high E-ethics while those in China
displayed low E-ethics. Most other countries are from Southeast Asia, whose societies are
more traditional and conservative, while Chinese consumers failed to develop a collective,
ethics-oriented mind-set because of their communistic society. Additionally, downloading
material via the Internet is popular in developed countries, that is, the U.S and the U.K., and
respondents from these countries scored low in terms of this dimension of E-ethics. Cultural
differences significantly influence consumer E-ethics only in the dimension of illegal
activities (p=0.029). Generally, ANOVA did not support H2.
Table 4. Results of ANOVA
Dependent
Variables
Internet
Aberrant
Behavior
Illegal
Activities
Questionable
Activities
Human
Internet
Trade
Downloading
Material
Between Groups
Within Groups
Total
Between Groups
Within Groups
Total
Between Groups
Within Groups
Total
Between Groups
Within Groups
Total
Between Groups
Within Groups
Total
Sum of
Squares
3.653
166.808
170.460
5.877
194.170
200.046
4.422
273.600
278.022
4.920
382.231
387.151
4.722
377.687
382.409
df
4
359
363
4
360
364
4
360
364
4
360
364
4
359
363
Mean
Square
0.913
0.465
F
Sig.
1.965
0.099
1.469
0.539
2.724
0.029*
1.106
0.760
1.455
0.216
1.230
1.062
1.158
0.329
1.180
1.052
1.122
0.346
Significance: * - less than 0.05; **- less than 0.01; ***- less than 0.001.
6. Conclusion and discussion
This study examined student ethics in relation to the Internet (E-ethics). Most respondents
were under-graduate and graduate students aged 20 to 29 years old. Subjects spend an average
of 2 to 5 hours daily browsing the Internet. Taiwan, Malaysia, and Indonesia accounted for
most of the study subjects. This study divided aberrant Internet behaviors into four categories:
illegal, questionable, human online trading, and downloading materials. Over 50% of
respondents agreed that illegal activities are wrong, but few agreed that human online trading
and downloading material are wrong. Human Internet trade relates to the basic human need to
maintain health and have children, which is why few respondents viewed such behavior as
wrong. Downloading material is very prevalent in modern life. Regardless of the country of
origin, no respondents saw these activities as wrong.
Regarding the research question, a significant relationship between personal
characteristics and E-ethics was identified. Consumer Machiavellianism was negatively
related with E-ethics in all five multi-regression models, demonstrating that increased
Machiavellianism is associated with lower ethics. Identical results were found by Kenhove,
Vermeir, and Verniers (2001). Nevertheless, consumer attitude towards the Internet was not
significantly and positively related with E-ethics except in models 1 (Internet aberrant
436
L.-C. Lu et al. / Asia Pacific Management Review 18(4) (2013) 427-440
behaviors) and 2 (Illegal activities). Additionally, consumer attitude exhibited an opposite
relationship in model 4 (Human Internet trade). Regarding consumer attitude towards the
Internet, Tsai and Lin (2004) pointed out that male adolescents perceived the Internet more as
a “toy”, while female adolescents perceived it more as a “technology” “tool” or “tour”. The
study also indicated that females viewed the Internet more pragmatically, whereas males
believed they could obtain more enjoyment from the Internet. Additionally, males expressed
significantly more positive attitudes than females regarding two aspects of the Internet:
usefulness and perceived control. Despite this, females were still the main decision makers
regarding adopting children or purchasing eggs for “DIY” IVF treatment via the Internet. H1b
was not significant and had an opposite relationship in this study. This may result from the
difference between the attitudes of male and female adolescents towards the Internet.
H2 was examined via ANOVA analysis, revealing that cultural differences towards Eethics were not significant except in the dimension of illegal activities. Study respondents
primarily came from Asian countries, including Taiwan, Malaysia, Indonesia, and China. The
traditions and customs of these countries are nearly the same. Ku (2002) indicated that the
similar culture background shared by Taiwan and Southeast Asia may be a reason for the
similar level of E-ethics among the respondents from these countries. Additionally, the
ANOVA description demonstrated that some countries primarily from Southeast Asia had
higher E-ethics than others, except in the dimension of human Internet trade. Generally, China
has lower E-ethics than other countries, except in the dimension of downloading materials.
This difference may result because Southeast Asia has a low level of economic development
and China is a communistic society.
Few studies considered consumer E-ethics and combined the three scales (Internet
aberrant behavior, Machiavellianism, and Attitude toward Internet) to test their relationship
with E-ethics. A limitation of this study, however, is the unbalanced distribution in the
number of respondents in this study Taiwan had 270 respondents while Malaysia and
Indonesia has 68. Nonetheless, the study results suggest students in Taiwan have higher Eethics on average than those in the U.S. and U.K. The consumer education and Internet
restraints therefore should be strengthened to reduce aberrant Internet activities. Fukukawa
(2002) identified social influence as an effective marketing tool of the important components
that influence questionable consumption behaviors. A limitation of the study is the effective
responses are scarce from each country. Future research should target younger and older
respondents, particularly since Internet culture can be considered global, transcending
national and cultural boundaries (Johnston and Johal, 1999). Another limitation is we use four
ethics items in the cross-cultural analysis. Additionally, comparisons of consumers’ E-ethical
beliefs with more widely varied personality variables can enhance the limited knowledge of
this area.
References
Ajzen, I. (1991) The theory of planned behaviour. Organizational Behavior and Human
Decision Processes, 50, 179-211.
Al-Khatib, Vitell, Scott J., Rawwas, Mohammed Y.A. (1997) Consumer ethics: A crosscultural investigation. European Journal of Marketing, 31(11/12), 750-767.
Bush, V.D., Venable, B.T., Bush, A.J. (2000) Ethics and marketing on the internet:
practitioners’ perceptions of societal, industry and company concerns’. Journal of
Business Ethics, 23(3), 237-248.
Chen, J.S., Wang, Sijun. (2010) A cross-cultural study of east Asian adolescents’ influence in
family purchase decisions. Journal of Global Business and Technology, 6(1), 52-67.
Christie, R., Geis, F.L. (1970) Studies in machiavellianism. Academic Press, New York, NY.
437
L.-C. Lu et al. / Asia Pacific Management Review 18(4) (2013) 427-440
Cronin, Mary J. (1994) Doing business on the Internet: How the electronic highway is
transforming american companies. Van Nostrand Reinhold, New York, NY.
Embar-Seddon, Ayn (2002) Cyberterrorism. The American Behavioral Scientist, 45(6), 10331045.
Ferrell, O.C., Gresham Larry G. (1985) A contingency framework for understanding ethical
decision making in marketing. Journal of Marketing, 49(3), 87-97.
Fletcher, R. (2006) The impact of culture on website content, design, and structure. Journal of
Communication Management, 10(3), 259-273.
Fraedrich, John, Ferrell, O.C., Pride, William M. (1989) An empirical examination of three
machiavellian concepts. Journal of Business Ethics, 8(9), 687-695.
Franke, George R., Nadler, S. Scott. (2008) Culture, economic development, and national
ethical attitudes. Journal of Business Research, 61(3), 254-264.
Freestone O., Mitchell V. (2004) Generation Y attitudes towards e-ethics and internet-related
misbehaviours. Journal of Business Ethics, 54(2), 121-128.
Fukukawa, Kyoko (2002) Developing a framework for ethically questionable behavior in
consumption. Journal of Business Ethics, 41(1/2), 99-120.
Fullerton, Ronald A., Punj, G. (1993) Choosing to misbehave: A structural model of aberrant
consumer behavior. Advances in Consumer Research, 20(1), 570-574.
Gallaway, T., Kinnear, D. (2001) Unchained melody: A price discrimination-based policy
proposal for addressing the MP3 revolution. Journal of Economic Issues, 35(2), 279-288.
Glass, Richard S., Wood, Wallace A. (1996) Situational determinants of software piracy: An
equity theory perspective. Journal of Business Ethics, 15(11), 1189-1199.
Goodwin, T. (1999) Measuring the effectiveness of online marketing. Journal of the Market
Research Society, 41(4), 403-407.
Hunt, Shelby D., Scott M.V. (1986) A general theory of marketing ethics. Journal of
Macromarketing, 6, 5-15.
Husted, B.W. (2000) The impact of national culture on software piracy. Journal of Business
Ethics, 26(3), 197- 211.
Johnston, K., Johal, P. (1999) The Internet as a “Virtual Cultural Region”: Are extant cultural
classification schemes appropriate? Internet Research: Electronic Networking
Applications and Policy, 9(3), 178-186.
Kenhove, Patrick Van, Vermeir, Iris, Verniers, Steven (2001) An empirical investigation of
the relationships between ethical beliefs, ethical ideology, political preference and need
for closure. Journal of Business Ethics, 32(4), 347-362.
Kohlberg, Lawrence (1981) The Philosophy of Moral Development – Moral Stages and the
Idea of Justice. Harper and Row, San Francisco, CA.
Ku, Samuel C.Y. (2002) The political economy of regime transformation: Taiwan and
Southeast Asia. World Affairs, 165(2), 59-79.
Levin, Aron M., Dato-on, Mary Conway, Rhee, Kenneth (2004) Money for nothing and hits
for free: The ethics of downloading music from peer-to-peer web sites. Journal of
Marketing Theory and Practice, 12(1), 48-61.
Logsdon, J.M., Thompson, J.K., Reid, R.A. (1994) Software piracy: Is it related to level of
moral judgment. Journal of Business Ethics, 13(11), 849-857.
Lu, Long-Chuan, Rose, Gregory M., Blodgett, Jeffrey G. (1999) The effects of cultural
dimensions on ethical decision making in marketing: An exploratory study. Journal of
Business Ethics, 18(1), 91-106.
Lu, H.Y. (2008) Sensation-seeking, Internet dependency, and online interpersonal deception.
Cyberpsychology and Behavior, 11(2), 227-231.
Murphy, P.E., G.R. Laczniak (1981) Marketing ethics: A review with implications for
managers, educators and researchers. Review of Marketing, 251-266.
438
L.-C. Lu et al. / Asia Pacific Management Review 18(4) (2013) 427-440
Pinto, A.K. Kanekar, S. (1990) Social perception as a function of Machiavellianism. Journal
of Social Psychology, 130, 755-762.
Spafford, E.H. (1997) Are hacker break-ins ethical? Computers, Ethics, and Society, 77-88.
Steidlmeier, Paul (1993) The moral legitimacy of intellectual property claims: American
business and developing country perspectives. Journal of Business Ethics, 12, 157-165.
Swinyard, W.R., Rinne, H., Kau, A.K. (1990) The morality of software piracy: A crosscultural analysis. Journal of Business Ethics, 9(8), 655-664.
Tsai, C.C., Lin, C.C. (2004) Taiwanese adolescents’ perceptions and attitudes regarding the
internet: Exploring gender differences. Adolescence, 39(156), 725-734.
Vitell Scott J. (2003) Consumer ethics research: Review, synthesis and suggestions for the
future. Journal of Business Ethics, 43(1/2), 33-47.
Vitell Scott J., Lumpkin, James R., Rawwas Mohammed, Y.A. (1991) Consumer ethics: An
investigation of the ethical beliefs of the ethical beliefs of elderly consumers. Journal of
Business Ethics, 10(5), 365-376.
Vitell Scott J., Muncy, James (1992) Consumer ethics: An empirical investigation of factors
influencing ethical judgments of the final consumer. Journal of Business Ethics, 11(8),
585-598.
Vitell Scott J., Paolillo Joseph, G.P. (2003) Consumer ethics: The role of religiosity. Journal
of Business Ethics, 46(2), 151-162.
Whitman, M.E., Townsend, A.M., Hendrickson, A.R., Rensvold, R.B. (1998) Computer
aversion and computer-use ethics in U.S. and Asian cultures. Journal of Computer
Information Systems, 38 (4), 19-24.
Wu, Shwu-Ing (2003) The relationship between consumer characteristics and attitude toward
online shopping. Marketing Intelligence and Planning, 21(1), 37-44.
439
L.-C. Lu et al. / Asia Pacific Management Review 18(4) (2013) 427-440
Appendix A
Descriptions of attitude toward Internet scale (Alpha = 0.737)
Strongly
Statements
disagree
(%)
Mean
1
2
1. I don’t like shopping over the Internet.
3.17
4.2
13.6
2. Most advertisements on the Internet are
not trustworthy.
3. E-commerce is extremely not safe.
3
19.2
4
20.1
Strongly
agree
(%)
5
6.5
2.70
5.6
25.2
17.7
13.5
1.7
2.89
5.2
17.8
21.5
16.8
2.3
Descriptions of MACH IV scale (Alpha = 0.62)
Statements
Mean
3.20
1. People who want to get ahead in the world
lead clean, moral lives.
2. There is no excuse for lying to someone else. 3.02
3. Honesty is the best policy in all cases.
2.69
4. One should take action only when sure it is
2.67
morally right.
5. Most people are brave.
3.22
6. Most people are basically good and kind.
2.44
7. The biggest difference between criminals and 2.41
others is that the criminals are stupid
enough to get caught.
8. It is wise to flatter important people.
2.66
9. It is hard to get ahead without cutting
2.77
corners.
10. Never tell anyone the real reason you did
2.95
something unless it is useful to do so.
11. Anyone who completely trusts others is
3.27
asking for trouble.
12. All in all, it is better to be humble and
1.86
honest than to be important and dishonest.
13. It is possible to be good in all respects.
2.38
440
Strongly
agree
(%)
5
6.6
Strongly
disagree
(%)
1
4.0
2
13.3
3
19.2
4
20.5
5.8
10.7
7.2
15.9
20.3
26.9
16.3
13.1
13.3
22.7
17.1
12.8
3.1
2.4
3.7
1.9
7.7
14.9
12.1
31.8
23.8
24.1
15.0
13.6
21.5
7.2
7.3
4.2
2.1
4.2
6.5
6.3
22.4
21.2
22.9
21.3
10.0
11.0
1.9
4.0
4.9
16.4
24.1
13.8
4.5
1.7
13.1
19.8
24.3
4.9
24.5
28.0
8.0
2.6
0.7
10.8
29.9
12.9
8.6
1.6