Modeling the Privacy Decisions of Online Customers: The Role of Perceived Benefits and Risk

E-commerce is a rapidly developing and expanding phenomenon, and although it is successfully functioning in the current realities, having been taken out of the traditional market system, it appears to have several drawbacks to be addressed. One of these drawbacks lies in an obligatory revealing of an ever-increasing amount of personal data from the customers side, including highly sensitive information. The concerns raised from that personal data requirements tend to decrease the intention of individuals to disclose their information or even generally participate in the Ecommerce market. In that way, the current study has examined the ways customers make privacy decisions on disclosure online and how privacy concerns level and retailers’ additional incentives derived from the privacy calculus risk-benefits model may influence this behavior. The experimental survey was conducted via Yandex Toloka software by the means of which the final sample of 394 individuals 18+ aged, living in Saint-Petersburg or Moscow was obtained. Binary logistic regression and chi-square test were implemented for the analysis. As a result, it was found that, the general level of privacy concerns proved to be an important predictor of disclosure online, having a constant negative effect on it under all possible conditions. Among two privacy calculus aspects (benefits and risks) the independent effect of only privacy risk awareness was confirmed to significantly decrease the likelihood that a respondent will disclose information, while monetary rewards had shown no significant influence. The moderative effect of benefits and risks joint condition has been proven as well revealing an outbalancing impact. No moderative effect of privacy concerns on privacy calculus model has been found.