Ranking algorithms are the information gatekeepers of the Internet era. We develop a stylized framework to study the effects of ranking algorithms on opinion dynamics. We consider rankings that depend on popularity and on personalization. We find that popularity driven rankings can enhance...

Consumers’ purchase decisions can be influenced by others’ opinions, i.e., word-of-mouth (WOM), and/or others’ actions, i.e., observational learning. While information technologies are creating increasing opportunities for firms to facilitate/manage these two types of social interaction,...

This paper develops an identification strategy to generate unbiased estimates of Internet usage spillovers using a unique data set of US households. I identify multiple potential sources of learning including those from the household's locality, from educational Internet subsidies, and from...

I study the implications of preference uncertainty in a consumer search environment with and without tracking. Consumers encounter information that is predictive about their type while searching. Depending on what con- sumers learn, they stop searching without a purchase and before sampling all...

This paper studies the role of observational learning in search markets where buyers do not take the list price as a take-it-or-leave-it offer. Using a unique data from the Beijing housing market, we estimate a structural model in which buyers infer a seller’s reservation value from the...

The use of coarse categories is prevalent in various situations and has been linked to biased economic outcomes, ranging from discrimination against minorities to empirical anomalies in financial markets. In this paper we study economic rationales for categorizing coarsely. We think of the way...

This paper articulates a network approach to knowledge processes and information systems in organizations. It proposes that cross-business-unit knowledge processes and the learning role of information systems are embedded within a network of relationships that link business units. Exploratory...

This paper provides an analysis of the impact of using machine learning to conduct profiling of individuals in the context of the EU General Data Protection Regulation.We look at what profiling means and at the right that data subjects have not to be subject to decisions based solely on...

Various forms of social learning and network effects are at work on crowdfunding platforms, giving rise to informational and payoff externalities. We use novel entrepreneur-backer data to study how these externalities shape funding dynamics, within and across projects. We find that backers...

The purpose of the paper is to show the importance of cognitive and affective process of computer and ICT usage, both in learning and in their daily work tasks. In the paper is used comparative method. It has been concluded that an individual has an active role and the use of ICT enables,...