Being at the cutting edge of online shopping: Role of recommendations and discounts on privacy perceptions

Despite the explosion of selling online, customers continue to have privacy concerns about online purchases. To alleviate such concerns, shopping sites seek to employ interventions to encourage users to buy more online. Two common interventions used to promote online sales are: (1) recommendations that help customers choose the right product either based on historic purchase correlations or recommendations suggested by the retailer; and (2) discounts that increase the value of products. Building on privacy calculus, we theorize about how and why key, representative combinations of recommendations and discounts influence the effects of inhibitors and enablers on online purchase intention. Our research design incorporated recommendations coming from different sources for the recommendation (retailer and other customers' preferences) product relatedness (related products with historic purchases correlated to the focal product and unrelated products with no historic purchase correlation to the focal product) and two types of discounts (regular and bundle). Participants completed a browsing task in a controlled online shopping environment and completed a survey (n = 496). We found mixed results of moderating effects of recommendations and product relatedness on the effect of inhibitors and enablers on purchase intention. Although recommendations did not enhance the effects of inhibitors, they did enhance the effects of enablers on online purchase intention. We also found that product relatedness did not enhance the effect of privacy enablers on online purchase intentions. The results also showed that discounts enhance the effects of enablers, and that discounts can counteract the moderating effect of recommendations on the relationship between inhibitors and purchase intention under certain circumstances. We discuss theoretical and practical implications.