Softlifting is an individual act of copying software
without the legal right to do so, and is distinct from two other
forms of software piracy: commercial piracy (for distribution
and sale) and corporate piracy (institutional lack of appropriate
means to control software distribution within an organization)
[Hornik, 1994]. That the concept of software piracy has been distinguished
into three classes of behaviors reflects both the growing concern
and understanding of the nature of these activities. The earliest
attempts to control software piracy were aimed at minimizing the
vendors' losses from both commercial and corporate piracy, which
began with the introduction of microcomputers in the 1980s. The
formation of the US Software Publishers Association (SPA) in 1988,
and, subsequently, the international Business Software Alliance,
resulted in a highly visible spate of successful lawsuits against
US and international firms engaging in either commercial or corporate
piracy (BSA, 1994). The software industry's focus on commercial
and corporate piracy reflects a reasonable effort to protect themselves
from tens of billions of lost sales dollars worldwide, since these
types of pirates are both easier to detect and easier entities
from which to recover lost revenues.
Our work focuses on individual level of piracy, whereby
individuals copy software for personal use. Softlifting research
draws upon not only the piracy literature, but also on the broader
domains of social psychology (theories of planned behavior and
of cognitive dissonance), ethics, and information systems. This
empirical work complements broader works on ethical theory and
concepts advanced most recently by Walsham (1996), who relates
classical ethical theory to the practice of IS; Conger et al.
(1995), who emphasizes the need to understand users so that policies,
rewards and punishments can be developed; Laudon (1995), who contributes
a typology of ethical theories within which the IS community can
reason about ethical issues; and, most broadly, Mason (1995),
who calls upon the IS community to help shape the direction of
society.
This study builds directly on the growing literature
attempting to identify demographic characteristics that can predict
the likelihood of softlifting. Most recently, Simpson et al. (1994)
hypothesize a two-stage model in which five factors (stimulus,
socio-cultural, legal, personal, and situational) affect one's
ethical decision process - and that the decision process alone
accounts for one's softlifting behaviors. They conclude that gender,
religion, personal gain and situational factors affect the decision
to softlift, and that ethical perceptions of softlifting have
no bearing upon the practice. Logsdon et al. (1994) report prevalence
of softlifting among university students with little support for
their hypothesis that softlifting is related to level of moral
judgment, suggesting that this issue has low moral intensity.
These recent results are largely consistent with earlier works
in the field: Im and Van Epps (1992), who found soft-lifting prevalent
in accredited business schools; Solomon and O'Brien (1990), and
later, O'Brien et al. (1991), who found that softlifting is both
wide-spread and deemed acceptable among university students; and
Taylor and Shim (1993), who report that while business executives
softlift less than academicians, both view softlifting as mildly
unethical.
Our main dependent variable is the Intention
to softlift (see Fig. 1), and we hypothesize that Intention
is a function of two main constructs: Background and Attitudes.
Background factors are assumed stable over time for an
individual and directly influence the Intention to softlift.
We also hypothesize that Background influences Attitudes,
a construct that varies over time. Attitudes about
softlifting separately influence the Intention to softlift.
(This influence will either amplify or diminish the Background
influence, depending on the individual's stage of resolving any
cognitive dissonance.) Each of the constructs is comprised of
several factors. While the full model is the subject of an ongoing
study, this paper focuses exclusively upon "Path 1,"
the influence of Background upon Intention to softlift.
We investigate these hypotheses defining Path 1: (1) perceptions of higher rates of softlifting among peers yields greater softlifting Intention; (2) a strong ethical profile is associated with weaker Intention to softlift; (3) increased levels of computer use at home yield higher levels of softlifting; (4) increasing levels of purchased software yields lower levels of softlifting; (5) increased knowledge of the piracy statutes are associated with lower levels of softlifting; and (6) gender has no effect on Intention to softlift. We include gender in our set of independent variables because its role in the existing literature is not well understood. A complete discussion of these hypotheses is available from the authors.
Three hundred seventy-three students from several
MBA, Executive MBA, and undergraduate business and engineering
classes were given a questionnaire covering demographics, access
to computers, knowledge of copyright law, attitudes about copying
software, as well as their willingness to do so under several
scenarios. The questionnaire includes twenty items from Paulhus
(1990) Balanced Inventory of Desirable Responding (BIDR) which
has been shown to detect and measure impression management bias.
A total of ninety-seven responses were discarded: 85 for incompleteness
and 12 for impression management bias, leaving 276 usable responses
(74% usable response rate). We re-used the BIDR items in the study
to develop a set of ethics factors within our Background
construct, because these items have strong face validity as indicators
of an individual's practical ethical profile. To our knowledge,
this is the first study to use these items for broader purposes.
The dependent variable, Intention to softlift,
is investigated using three sets of scenarios concerning respondents'
intent to copy software for friends' entertainment, school, and
work purposes. If respondents agree to softlift for any item within
the entertainment scenario, they are classified as demonstrating
Intention to softlift. Respondents who answer "no"
for all of the entertainment scenarios are classified as demonstrating
no Intention to softlift. The same scheme is used to determine
softlifting Intentions for school and work scenarios.
Factor analysis is employed to identify the orthogonal components of the twenty BIDR items in conjunction with three questions relating to the peer environment. This analysis indicates seven (7) significant dimensions (eigenvalues greater than 1). The corresponding factor scores are used as the independent variables Peer Views and Ethical Factor 1 through Ethical Factor 6 within a regression framework. As previously discussed, we employ several additional independent variables: computer Use-at-home, measured in sessions per week; Purchase level (lowest level in the intercept, with Purchase level2 through 6 in the model); Knowledge of laws (number of correct responses out of 10 questions); and Gender (dummy variable with 0=female; 1=male).
Our results support the proposed model in that the
Background construct is shown to be a significant predictor
of Intention to softlift. There is variation, however,
among the predictors for the three different softlifting scenarios.
Table 1 presents our regression findings with significant variables
shown in bold. We hypothesized that softlifting would be more
prevalent among people who frequently use a computer at home,
a hypothesis that is partly supported by our model when the intended
software is for school purposes (but not for entertainment or
work). Perhaps computer use at home is irrelevant with respect
to softlifting work-related software due to the specialized nature
of the software, or a perception that work-related software should
be purchased by one's employer. The meaning of our findings with
respect to entertainment is not clear.
The hypothesis that people who purchase greater amounts
of software are less likely to softlift is supported by the estimates
shown for Purchase level 6: an indication that there is
a significant difference between the lowest and highest purchase
levels. This result suggests that not only do people who purchase
a considerable amount of software tend to follow rules, but that
they also expect their friends to do so. This interpretation also
suggests that they internalize a deontological ethical perspective
that suggests individuals are guided by a set of unvarying principles
(Walsham, 1996).
Peer Views is a significant
predictor of softlifting in all three scenarios, and is consistent
with other works (Peace and Galletta, 1996). In addition, at least
one Ethical Factor is significant in each scenario, with
four of the six significant for work purposes. While we did not
expect this variation, the result is broadly consistent with consequential
ethical theories (Walsham, 1996) that individuals consider the
context of behaviors in judging their ethicality.
These Ethical Factors have not yet been investigated
to understand fully how they relate to constructs from social
psychological or ethical theories. Our results indicate that respondents'
Intention to softlift is influenced by ethical considerations,
a conclusion that differs from previous research. Since variables
chosen to represent ethics constructs differ across studies, it
is possible that the works are identifying different sub-factors
included within a broad ethics construct. Our results suggest
the opportunity to explore more fully ways of operationalizing
the ethics construct.
Softlifting is as complex a phenomenon as it is prevalent, and individuals are continually faced with the opportunity to copy software without the authority to do so. Demonstrating the Intention to softlift under a variety of scenarios has been shown to be a function of several variables in one's Background. This result supports the existence of Path 1 on our proposed model, and work is underway to investigate the two remaining paths. To the extent that we can uncover the correlates to softlifting, the IS profession will be positioned to offer guidance on methods and policies to minimize the occurrence. Further work is required to understand more fully the dynamics leading to softlifting.
The authors would like to thank Professors Robert
D. Rogers and Gautam Vora for their insightful assistance with
the data analysis. Any remaining errors are the full responsibility
of the authors. Appreciation to the UNM Anderson Schools of Management
Research Allocations Committee for funding in support of this
work.
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Peer Views | 0.068388 | 3.182* | 0.079734 | 4.172* | 0.057448 | 2.102* | |
Ethical factor1 | 0.066586 | 3.150* | 0.065237 | 3.471* | 0.123989 | 4.614* | |
Ethical factor2 | 0.011797 | 0.567 | 0.018746 | 1.012 | 0.024987 | 0.944 | |
Ethical factor3 | 0.028897 | 1.281 | 0.019439 | 0.969 | 0.070105 | 2.444* | |
Ethical factor4 | 0.044438 | 2.049* | 0.027044 | 1.402 | 0.065824 | 2.388* | |
Ethical factor5 | 0.02267 | 1.082 | 0.017202 | 0.923 | 0.07703 | 2.891* | |
Ethical factor6 | -0.006924 | -0.333 | -0.004069 | -0.22 | 0.026704 | 1.009 | |
Use-at-home | 0.005111 | 1.562 | 0.006181 | 2.124* | 0.001474 | 0.354 | |
Purchase level2 | -0.001688 | -0.033 | 0.054664 | 1.194 | 0.011318 | 0.173 | |
Purchase level3 | -0.045487 | -0.665 | -0.065853 | -1.082 | -0.061815 | -0.711 | |
Purchase level4 | -0.002043 | -0.021 | -0.025935 | -0.3 | -0.010117 | -0.082 | |
Purchase level5 | 0.012422 | 0.12 | 0.051157 | 0.561 | 0.021442 | 0.164 | |
Purchase level6
(highest) | -0.237792 | -2.47* | -0.218574 | -2.554* | -0.31482 | -2.573* | |
Knowledge of laws | -0.014322 | -1.503 | -0.011488 | -1.356 | -0.018839 | -1.555 | |
Gender | 0.064466 | 1.427 | 0.007866 | 0.196 | 0.062098 | 1.081 | |
2.834 | 0.0004 | 3.895 | 0.0001 | 4.589 | 0.0001 | ||
0.1405 | 0.1835 | 0.2093 | |||||
0.0909 | 0.1364 | 0.1637 |
*Significant at the .01 level