A new choice model is derived, rooted in the framework of Random Regret Minimization (RRM). The proposed model postulates that when choosing, people anticipate and aim to minimize regret. Whereas previous regret-based discrete choice-models assume that regret is experienced with respect to only the best of foregone alternatives, the proposed model assumes that regret is potentially experienced ...

In applications such as recommendation systems and revenue management, it is important to predict preferences on items that have not been seen by a user or predict outcomes of comparisons among those that have never been compared. A popular discrete choice model of multinomial logit model captures the structure of the hidden preferences with a low-rank matrix. In order to predict the preference...

We study the assortment optimization problem under the Sequential Multinomial Logit (SML), a discrete choice model that generalizes the multinomial logit (MNL). Under the SML model, products are partitioned into two levels, to capture differences in attractiveness, brand awareness and, or visibility of the products in the market. When a consumer is presented with an assortment of products, she ...

The goal of this study is to introduce a statistical method regarding the analysis of specific latent data for regression analysis of the discrete data and to build a relation between a probit regression model (related to the discrete response) and normal linear regression model (related to the latent data of continuous response). This method provides precise inferences on binary and multinomia...

Discrete choice models as demand forecasting techniques have been used for transportation applications for more than thirty years. The multinomial and nested logit models are probably the most widely applied in this context. Alternative speciic constants (ASCs), although playing an important role in these models, have received very little attention in theoretical studies. In this paper, we try ...

MNP is a publicly available R package that fits the Bayesian multinomial probit model via Markov chain Monte Carlo. The multinomial probit model is often used to analyze the discrete choices made by individuals recorded in survey data. Examples where the multinomial probit model may be useful include the analysis of product choice by consumers in market research and the analysis of candidate or...

This paper uses individual loan data for a national lender to estimate loan price elasticities across loan products and racial groups. The data contain detail on closing dates and prices, enabling control for market volatility and construction of pseudo-prices for foregone products. The empirical model is a mixed multinomial and conditional logit which is rooted in a structural utility framewor...

Parking policy is an important component of contemporary travel demand management policies. The effectiveness of many parking policy measures depends on influencing parking type choice, so that understanding the factors affecting these choices is of considerable practical importance. Yet, academic interest in this issue has been, at best, intermittent. This paper reports the results of an analy...

Swiss metropolitan areas are comprised of a system of communities with considerable fiscal autonomy. This study investigates how the income tax differentials across communities in an urban area affect the households` location decisions. Data from the urban agglomeration of Basel for the year 1997 is used. This unique data set contains tax information from all households that moved either within...