Higgins, Fell and Wilson (2006)

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1. Relationship between protection (subject matter/term/scope) and supply/economic development/growth/welfare 2. Relationship between creative process and protection - what motivates creators (e.g. attribution; control; remuneration; time allocation)? 3. Harmony of interest assumption between authors and publishers (creators and producers/investors) 4. Effects of protection on industry structure (e.g. oligopolies; competition; economics of superstars; business models; technology adoption) 5. Understanding consumption/use (e.g. determinants of unlawful behaviour; user-generated content; social media)

A. Nature and Scope of exclusive rights (hyperlinking/browsing; reproduction right) B. Exceptions (distinguish innovation and public policy purposes; open-ended/closed list; commercial/non-commercial distinction) C. Mass digitisation/orphan works (non-use; extended collective licensing) D. Licensing and Business models (collecting societies; meta data; exchanges/hubs; windowing; crossborder availability) E. Fair remuneration (levies; copyright contracts) F. Enforcement (quantifying infringement; criminal sanctions; intermediary liability; graduated response; litigation and court data; commercial/non-commercial distinction; education and awareness)

Source Details

Higgins, Fell and Wilson (2006)
Title: Digital Piracy: Assessing the Contributions of an Integrated Self-Control Theory and Social Learning Theory Using Structural Equation Modeling
Author(s): Higgins, G. E., Fell, B. D., Wilson, A. L.
Year: 2006
Citation: Higgins, G. E., Fell, B. D. and Wilson, A. L. 2006. Digital Piracy: Assessing the Contributions of an Integrated Self-Control Theory and Social Learning Theory Using Structural Equation Modeling. Criminal Justice Studies: A Critical Journal of Crime, Law and Society, 19, 3-22.
Link(s): Definitive , Open Access
Key Related Studies:
Discipline:
Linked by: Higgins (2007), Higgins, Wolfe and Ricketts (2009)
About the Data
Data Description: The researchers gave a self-report questionnaire to college students at an eastern university in the USA, in the fall 2004 semester. 392 completed questionnaires an the sample was on average 21.37 years old (±2.27) and sophmores in college. The sample was 61% females and 39% males.
Data Type: Primary data
Secondary Data Sources:
Data Collection Methods:
Data Analysis Methods:
Industry(ies):
Country(ies):
Cross Country Study?: No
Comparative Study?: Yes
Literature review?: No
Government or policy study?: No
Time Period(s) of Collection:
  • Fall 2004
Funder(s):

Abstract

Results indicated that low self-control and social learning theory could integrate in different ways to explain digital piracy. Specifically, the study developed a three-factor model that indicated that low self-control, combined with social learning, could lead to digital piracy. This supports Hirschi and Gottfredson’s (1993) assertion that self-control is impacted by constraints. The constraint in this case is the need for individuals to learn how to perform digital piracy. The authors suggest that universities seeking to reduce digital piracy should consider developing policies and programs based on social learning theory. Participants were 392 college students who completed a self-report questionnaire measuring aspects of social control, association with digital pirating peers, attitudes toward software piracy, and intentions to commit digital piracy. The analysis involved the use of structural equation modeling to test how four models of low self-control and social learning combined to produce the commission of digital piracy. Future research should use different measures of digital piracy and should consider the theoretical links that low self-control has with other theories in terms of their contribution to explaining digital piracy. Future research should also consider using a longitudinal design.

Main Results of the Study

  • The purpose of the present study was to shed light on an emerging form of white-collar crime like digital piracy by applying crime theories. The study examined the links between self-control theory and social learning theory and digital piracy.

4 models are used in the paper:

  1. The first model produces confirmatory factor analysis to assess the construct validity;
  2. Second structural model is examined to find out if the link between low self-control and digital piracy is mediated by social learning theory;
  3. Third model finds low self-control and social learning theory have independent direct links with digital piracy;
  4. Fourth model finds that low self-control has an indirect effect on digital piracy, but low self-control maintains a direct effect on digital piracy.
  • That is, low self-control and social learning theory have independent direct links with digital piracy (Model Three). Further, low self-control has an indirect effect on digital piracy, but low self-control maintains a direct effect on digital piracy (Model Four).
  • The study provides evidence that low self-control, social learning theory, and digital piracy have a link. Specifically, the results suggest that the link between low self-control and digital piracy is partially mediated by social learning theory.


Policy Implications as Stated By Author

University administrators should develop policy that may aid in the reduction of digital piracy. The focus of these programs should come from social learning theory. These policies should emphasize developing proper friendships with nondigital pirating peers.



Coverage of Study

Coverage of Fundamental Issues
Issue Included within Study
Relationship between protection (subject matter/term/scope) and supply/economic development/growth/welfare
Relationship between creative process and protection - what motivates creators (e.g. attribution; control; remuneration; time allocation)?
Harmony of interest assumption between authors and publishers (creators and producers/investors)
Effects of protection on industry structure (e.g. oligopolies; competition; economics of superstars; business models; technology adoption)
Understanding consumption/use (e.g. determinants of unlawful behaviour; user-generated content; social media)
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Coverage of Evidence Based Policies
Issue Included within Study
Nature and Scope of exclusive rights (hyperlinking/browsing; reproduction right)
Exceptions (distinguish innovation and public policy purposes; open-ended/closed list; commercial/non-commercial distinction)
Mass digitisation/orphan works (non-use; extended collective licensing)
Licensing and Business models (collecting societies; meta data; exchanges/hubs; windowing; crossborder availability)
Fair remuneration (levies; copyright contracts)
Enforcement (quantifying infringement; criminal sanctions; intermediary liability; graduated response; litigation and court data; commercial/non-commercial distinction; education and awareness)
Green-tick.png

Datasets

Sample size: 392
Level of aggregation: University students
Period of material under study: 2004