Lai and Kuo (2007)
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Source Details
Lai and Kuo (2007) | |
Title: | Preventing piracy use intention by rectifying self-positivity bias |
Author(s): | Lai, M., Kuo, C.C. |
Year: | 2007 |
Citation: | Lai, M., & Kuo, C. C. (2007). Preventing piracy use intention by rectifying self-positivity bias. Social Behavior and Personality: an international journal, 35(7), 961-974. |
Link(s): | Definitive |
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About the Data | |
Data Description: | 60 university students (41 female and 19 male) were randomly assigned to four between-subject designs that manipulated message framing (positive and negative) and information accessibility (high and low). |
Data Type: | Primary data |
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Cross Country Study?: | No |
Comparative Study?: | No |
Literature review?: | No |
Government or policy study?: | No |
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Abstract
Piracy has become a global challenge. In this study, the author proposed to discourage piracy intention by rectifying the self-positivity bias with message framing and information accessibility. Cartoon advertisements conveying either positively or negatively framed messages were produced. Respondents’ level of information accessibility of piracy behavior was manipulated. As predicted, using positively framed messages or increasing level of information accessibility can effectively reduce self-positivity bias. Moreover, in a low information accessibility scenario, positive rather than negative message framing is more effective in reducing self-positivity bias in using pirated products. Research implications, limitations, and suggestions for future research are also addressed.
Main Results of the Study
By framing anti-piracy messages as providing advantages to the user as opposed to emphasizing the potential negative impacts, marketers and lawmakers can appeal to users' self-positivity bias (the idea that positive things are more likely to happen to self and negative things are more likely to happen to others.)
Policy Implications as Stated By Author
Illegal downloading can be more effectively curbed by presenting advantages of legal downloading to users rather than emphasizing consequences.
Coverage of Study
Datasets
Sample size: | 60 |
Level of aggregation: | University students |
Period of material under study: | Not stated |