Studying Perceived Risk has been a well researched topic in IS. Together with my coauthors, we conducted a meta-analysis to see how different research methods and groups have analyzed perceived risk on intention to purchase.
| Authors | Alexander Pelaez | Hofstra University, Hempstead, NY, USA |
| Chi-Wen Chen | California State University Dominguez Hills, Carson, CA, USA; | |
| Yan Xian Chen | Five Element Analytics, Merrick, NY , USA |
ABSTRACTThis article conducts a meta-analysis to determine the effect of perceived risk on intention to purchase in e-commerce settings. The literature generally favors the negative relationship between the two variables; however, some studies have found this relationship to be not significant or even positive. Thirty-five studies were examined, representing 39 overall samples across multiple contexts with a total sample size of 13779 and overall weighted effect size (Pearson’s r) for all studies of −0.362 (95% CI: −.432, −.286), a significant medium effect, with a stronger effect in B2C than B2B contexts. Major IS journals rarely report non-significant results and reflect publication bias, posing a problem for a comprehensive meta-analysis. Due to the reluctance to report or accept, studies showing non-significant results represent a significant challenge for IS research. Our aim is to encourage more meta-analysis in IS literature and utilize this methodology to analyze previously held theories.Citation: Pelaez, A., Chen, C. W., & Chen, Y. X. (2017). Effects of Perceived Risk on Intention to Purchase: A Meta-Analysis. Journal of Computer Information Systems, 1-12.
