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Home List of Titles Ripped-off in cyberspace: financial transactions on the Internet and their psychological predictors
Please use this identifier to cite or link to this item: http://hdl.handle.net/1959.3/4280
- Ripped-off in cyberspace: financial transactions on the Internet and their psychological predictors
- Knowles, Ann; Moore, Susan M.; Barr, Trevor
- Past research on the uptake of e-commerce is mostly US based, atheoretical, and concerns Internet shopping, rather than encompassing the broader range of Internet financial transactions. 'Trust' has been implicated as an important predictor of consumer behaviour but its nature is unclear and data regarding its importance in comparison with other consumer, vendor, and website characteristics has been inconsistent. In the current study of 2000 randomly selected Australian Internet-users, a telephone survey was used to assess a range of potential predictors of trust in on-line transaction behaviour. Adapting the expectancy-valence model that has been applied in fear of crime research, the study explored the role of perceptions of likelihood and seriousness of negative outcomes in Internet financial transaction behaviour. Trust was conceptualised as the antithesis of perceived risk. Results indicated that trust was the strongest predictor of use of the Internet for financial transactions. In turn, the strongest predictor of trust was the perceived likelihood of negative outcomes, such as receiving bad service. Demographic variables such as education, age and gender had complex relationships with on-line transaction behaviours. The data were discussed in terms of barriers and enablers of trust in Internet use for financial transactions.
- Publication type
- Conference paper
- Research centre
- Swinburne University of Technology. School of Social and Behavioural Sciences
- 32nd Annual Meeting of the Society for Australasian Social Psychologists, Sydney, New South Wales, Australia, 24-27 April 2003.
- Publication year
- Australian Psychological Society
- Publisher URL