Start Date
12-13-2015
Description
Costly product returns have become a significant problem for most online retailers. In this study, we investigate the conflicting relationship between online product page viewing and product returns. Based on expectation disconfirmation theory, we explain two counteracting effects of product page viewing on product returns, and propose that more product page viewing leads to higher likelihood of product returns. Moreover, we examine the role of three IT systems, namely product recommendation systems, product visualization systems and consumer review systems, in attenuating the effect of product page viewing on product returns. By using a unique clickstream dataset, we employ a fixed effect logit model to test the research hypotheses. Our study has the potential to contribute to the extant literature by unveiling how consumers’ pre-purchase behaviors influence their return behaviors. Practitioners can also benefit from this research in deciding how to economically invest in IT systems to reduce product return rates.
Recommended Citation
Ding, Yi; Xu, Haifeng; and Tan, Bernard, "A Conflicting Relationship Between Online Product Page Viewing And Product Returns" (2015). ICIS 2015 Proceedings. 21.
https://aisel.aisnet.org/icis2015/proceedings/eBizeGov/21
A Conflicting Relationship Between Online Product Page Viewing And Product Returns
Costly product returns have become a significant problem for most online retailers. In this study, we investigate the conflicting relationship between online product page viewing and product returns. Based on expectation disconfirmation theory, we explain two counteracting effects of product page viewing on product returns, and propose that more product page viewing leads to higher likelihood of product returns. Moreover, we examine the role of three IT systems, namely product recommendation systems, product visualization systems and consumer review systems, in attenuating the effect of product page viewing on product returns. By using a unique clickstream dataset, we employ a fixed effect logit model to test the research hypotheses. Our study has the potential to contribute to the extant literature by unveiling how consumers’ pre-purchase behaviors influence their return behaviors. Practitioners can also benefit from this research in deciding how to economically invest in IT systems to reduce product return rates.