Despite the widespread adoption of recommender systems by online investment platforms, empirical research into their impact on online investors’ behaviors is scarce. Using data from a global e-commerce platform, the authors of this study adopt a regression discontinuity design and causally...

Advances in data collection and algorithms help advertisers to better target individual consumers by predicting each consumer's preferences. We first show that when consumers have uncertainties about their preferences, an ad targeted to a consumer carries an implicit message: the algorithm...

Early consumption of a product often benefits later consumers by revealing quality information. Inefficiency arises, however, because early consumers do not internalize the social value of their consumption. How could a platform that intermediates information between early and late consumers...

We conduct a field experiment on a movie-recommendation platform to identify if and how recommendations affect consumption. We use within-consumer randomization at the good level and elicit beliefs about unconsumed goods to disentangle exposure from informational effects. We find recommendations...

Electronic commerce firms adopt advanced technologies to provide personalization of marketing-mix with data for personalization co-created by consumers. This study explores customer's perception of value co-creation and how it impacts intention to co-create value. Customer perception of value...

In current days, the recommendation system is the most popular thing which is used in almost all websites and apps like Internshala, LinkedIn, Instagram, Facebook, Amazon, Netflix, and many more. All of them have used the recommendation system to create practical solutions for the users. A...

Purpose - In user-oriented websites, e.g. in news websites or in seller websites, it is important to take the user's preferences into account when deciding which items to place in higher-exposure locations. The traditional approach to solving this problem, based on maximizing the average user...