Trial-offer markets, where customers can sample a product before deciding whether to buy it, are ubiquitous in the online experience. Their static and dynamic properties are often studied by assuming that consumers follow a multinomial logit model and try exactly one product. In this paper, we study how to generalize existing results to a more realistic setting where consumers can try multiple ...

In this article, the authors explore the social bases of cultural consumption by examining the association between newspaper readership and social status. They report a strong and systematic association between status and newspaper readership which is consistent with the expected link between status in the classical Weberian sense, on the one hand, and cultural level and lifestyle, on the other...

In this paper we consider how to model basketball's points per possession data, and we show that the flexibility provided by a multinomial logistic regression is required for modeling this type of data. We show how to apply this model to ranking college basketball teams, and a method for estimating team win probabilities with this model is provided. We show how to use these win probabilities to...

The increasing attention towards the environmental impact of IT (information technology) demands reorientation from IT departments. Research has outlined that the importance of Green IT is related to IT business alignment and environmental initiatives while uncertainty potentially derives from missing standards, measurements, or missing internal support for Green IT. We assume that importance a...

This document discusses the Information Theoretically Efficient Model (ITEM), a computerized system to generate an information theoretically efficient multinomial logistic regression from a general dataset. More specifically, this model is designed to succeed even where the logit transform of the dependent variable is not necessarily linear in the independent variables. This research shows that...

In this paper we discuss auxiliary variable approaches to Bayesian binary and multinomial regression. These approaches are ideally suited to automated Markov chain Monte Carlo simulation. In the first part we describe a simple technique using joint updating that improves the performance of the conventional probit regression algorithm. In the second part we discuss auxiliary variable methods for...