The interaction effects of information cascades, system recommendations and recommendations on software downloads

Purpose: When purchasing digital content (DC), consumers are typically influenced by various information sources on the website. Prior research has mostly focused on the individual effect of the information sources on the DC choice. To fill the gap in the previous studies, this research includes three main effects: information cascades, recommendations and word of mouth. In particular, the purpose of this paper is to focus on the interaction effect of information cascades and recommendations on the number of software downloads. Design/methodology/approach: The authors use the panel generalized least squares estimation to test the hypotheses by using a panel data set of 2,000 pieces of software at download.cnet.com over a month-long period. Product ranking and recommendation status are used as key independent variables to capture the effects of information cascades and recommendations, respectively. Findings: One of this study’s findings is that information cascades positively interact with recommendations to influence the number of software downloads. The authors also show that the impact of information cascades on the number of software downloads is greater than one of the recommendations from a distributor does. Originality/value: Information cascades and recommendations have been considered as the primary effects for online product choices. However, these two effects typically are not considered together in one research. As previous studies have mainly focused on each effect, respectively, the authors believe that this study may fill the gap by examining how these effects are interacted to one other to influence customers’ choices. The authors also show that the impact of information cascades on the number of software downloads is greater than one of the recommendations from a system does.