Fleming, Parravano and Zizzo (2016)

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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

Fleming, Parravano and Zizzo (2016)
Title: To Pay or Not to Pay? Determinants of Unlawful Product Acquisition
Author(s): Fleming, P., Parravano, M., Zizzo, D. J.
Year: 2016
Citation: Fleming, P., Parravano, M., & Zizzo, D. J. (2016). To Pay or Not to Pay? Determinants of Unlawful Product Acquisition. CREATe Working Paper No 1 (January 2016).
Link(s): Definitive , Open Access
Key Related Studies:
Discipline:
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About the Data
Data Description: A total of 223 students from the University of East Anglia (UEA), in Norwich, U.K., took part in the experiment. Subjects were recruited using the online system ORSEE (Greiner, 2004). Sessions took place at the Centre for Behavioural and Social Sciences (CBESS) UEA on-campus lab facilities.
Data Type: Primary data
Secondary Data Sources:
Data Collection Methods:
Data Analysis Methods:
Industry(ies):
Country(ies):
Cross Country Study?: No
Comparative Study?: No
Literature review?: No
Government or policy study?: No
Time Period(s) of Collection:
  • 2004
Funder(s):
  • CREATe

Abstract

We present a laboratory experiment that systematically investigates the determinants of acquisition behavior with a negative externality on a rights holder. We consider social and moral determinants of unlawful behavior as well as standard penalty and punishment risk trade-offs. We find that, while punishment risk and penalty size reduce unlawful behavior, they are not the only determinants that do. Moral determinants matter: there being a victim, and the victim deserving to be the rights holder, makes a difference. Social norms also matter: controlling for other variables, one point more of social appropriateness increase unlawful behavior by around 30-40%.

Main Results of the Study

This study examines the determinants of unlawful product acquisition. In particular, this paper explores the factors influencing the negative externality acquisition behavior (NEAB) and test the following hypotheses in a lab experiment.Hypotheses:* H1 (risk trade-off): Unlawful product acquisition decreases when the punishment probability increases.* H2 (penalty trade-off): Unlawful product acquisition is lower in the tasks with high penalty (£18) than in those in which the amount of the penalty is lower (£6).The following hypotheses follow respectively from our discussion of victimless crimes, high or low marginal damage, wealth and perceived deservingness of the rights holder:* H3 (victimless behavior): The presence of a rights holder reduces risk taking that damages him or her relative to an equivalent neutrally framed risk taking task.* H4 (low vs high marginal damage): Unlawful product acquisition is higher in the treatments in which the number of consumers per rights holder is higher (10) and the rights holder’s profit is lower (10%) than in those in which the number of consumers is lower (2) and the rights holder’s profit is higher (50%).* H5 (wealth): Unlawful product acquisition is higher in the tasks where the rights holder has a high endowment (£22) than in the tasks in which the rights holder has a low endowment (£4).* H6 (deservingness): Unlawful product acquisition is lower in the treatments where the rights holder has exerted effort than in the treatments in which the rights holder has exerted no effort.The moral scenario analysis is more exploratory and we do not formulate explicit hypotheses, though it would be reasonable to assume that Kantians should be more law/rule abiding, that one such rule would be not to harm others, and as a result they would be less likely to engage in NEAB.In relation to the social determinants of NEAB, there is a clear prediction:* H7 (social norms): NEAB is predicted by observers’ opinion about the social appropriateness of unlawful product acquisition in a particular task/treatment.Results:* H1 is supported. NEAB becomes less frequent when the punishment probability increases.* H2 is supported. NEAB is lower when the penalty is higher.* H3 is supported. Framing the task in terms of having a victim that is affected by NEAB reduces risky choices relative to purely risky choice tasks.* There is almost no evidence for H4, i.e. a low or high marginal return to the rights holder do not seem to matter.* H5 is not supported. The probability of consumers engaging in unlawful product acquisition is not higher in the tasks where the rights holder has high wealth (£22) than in the tasks in which the rights holder has low wealth (£4).* H6 is supported. The probability of the consumer engaging in unlawful product acquisition is lower in the conditions where the rights holder has exerted effort than in the treatments in which the rights holder has exerted no effort. Consumers care about deservingness to some degree.* H7 is strongly supported. Unlawful product acquisition is predicted by social norms, as measured by the Observers’ opinion about the social appropriateness of unlawful product acquisition in a particular task/treatment.* Utilitarian-minded subjects may engage less in NEAB.

Policy Implications as Stated By Author

The authors suggest that the largest behavioral effect comes from social norms. They estimated that, controlling for a range of variables as well as individual level clustering, one point more of social appropriateness increases unlawful product acquisition in our experiment by around 30-40%. This implies the potential usefulness of policy measures that try to shift the perceptions of such social norms.


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)
Green-tick.png
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)
Green-tick.png
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: 223
Level of aggregation: University students
Period of material under study: 2004