Previous studies have attempted to address online uncertainties from the relationship marketing perspective. The purpose of this paper is to argue that the integration of media richness theory (MRT) and cognitive fit theory (CFT) can contribute a new perspective in addressing consumers’ transaction-specific uncertainties in online retailing.
On the basis of MRT and CFT, a research model was developed by correlating online channel media richness (OCMR), online–offline information integration (OOII), information privacy concern, perceived deception and online loyalty. The model was empirically examined based on survey data collected from 258 multi-channel consumers in China.
An analysis of structural equation model showed that OCMR is negatively associated with information privacy concern and perceived deception but is not significant to online loyalty. Information privacy concern has a negative influence on online loyalty, but the effect of perceived deception is not significant. Moreover, information privacy concern is positively related to perceived deception. The OOII strengthens the influence of OCMR but not the moderating effect of integrated promotion, product and price information on the relationship between OCMR and online loyalty.
This study contributes to the extant literature on online retailing by examining the effect of OCMR on online transaction uncertainties. Information integrity in the form of OOII was proposed to complement OCMR. Results have shown that OCMR is significant in reducing online uncertainties, and OOII strengthens this effect, thereby enhancing online loyalty.
This work was supported by the National Key R&D Program of China (2018YFB1601401), the National Natural Science Foundation of China (NSFC: 71622009, 71571169, 71571177, 71731010) and the Fundamental Research Funds for the Central Universities (WK2040160028).
Li, Y., Liu, H., Lee, M. and Huang, Q. (2019), "Information privacy concern and deception in online retailing: The moderating effect of online–offline information integration", Internet Research, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/INTR-02-2018-0066Download as .RIS
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