Wednesday 1 February 2012

A new look at software piracy: Soft lifting primes an inauthentic sense of self, prompting further unethical behavior

an article by Wen-Bin Chiou (National Sun Yat-Sen University, Institute of Education, Taiwan), Peng-Hui Wan (Carnegie Mellon University, Pittsburgh, USA) and Chin-Sheng Wan (Southern Taiwan University, Taiwan) published in International Journal of Human-Computer Studies Volume 70 Issue 2 (February 2012)

Abstract

Soft lifting refers to the process whereby a legally licensed software program is installed or copied in violation of its licensing agreement. Previous research on this pervasive kind of unethical computer use has mainly focused on the determinants of this unethical act, which are rooted in personal, economic, technological, cultural, socio-political, or legal domains. However, little is known about the symbolic power that soft lifting has on the sense of self. Based on recent advances in behavioural priming, we hypothesised that soft lifting can influence the signals one sends to oneself; more specifically, soft lifting may prime individuals to experience an inauthentic sense of self, which, in turn, prompts further unethical behaviour.

In Study 1, we showed that participants, primed with the memory of a recent soft lifting experience, cheated more than participants recalling a recent experience of purchasing authentic software or than control participants. Moreover, feelings of inauthenticity mediated the priming effect of soft lifting on dishonest behaviour.

In Study 2, participants primed with soft lifting showed a greater willingness to purchase a wide range of counterfeit products over authentic products.

Besides those antecedents or correlates of soft lifting already identified in the literature, educators should pay more attention to the negative impact of soft lifting on the self-images of users, which may go beyond computer-related behaviours. Priming may provide a new direction for HCI researchers to examine the impact of computer-use-related factors on users’ perceptions, motivations, and behaviours.


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