We develop an extension of the familiar linear mixed logit model to allow for the direct estimation of parametric non-linear functions defined over structural parameters. Classic applications include the estimation of coefficients of utility functions to characterize risk attitudes and discounting functions to characterize impatience. There are several unexpected benefits of this extension, apa...

This paper deals with the correspondence between macro and micro spatial interaction and choice models, in both a static and a dynamic context. After a review of recent literature, special attention is devoted to the interpretation of aggregate spatial interaction models (both the conventional gravity or entropy models and the more general theory of movement devëloped by Alonso) in the framewor...

The emergence of Intelligent Transportation Systems and the associated technologies has increased the need for complex models and algorithms. Namely, real-time information systems, directly influencing transportation demand, must be supported by detailed behavioral models capturing travel and driving decisions. Discrete choice models methodology provide an appropriate framework to capture such ...

Modeling travel behavior is a key aspect of demand analysis, where aggregate demand is the accumulation of individuals’ decisions. In this chapter, we focus on “short-term” travel decisions. The most important short-term travel decisions include choice of destination for a non-work trip, choice of travel mode, choice of departure time and choice of route. It is important to note that short-term...

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 ...

While there is general agreement that consumer taste heterogeneity is crucially important in marketing, there is no consensus on a preferred approach to modeling heterogeneity. In this paper, we assess the performance of five alternative choice models, using ten empirical data sets. We include the popular latent class (LC) model, and the mixed logit (MIXL) model where utility weights are assume...

This paper describes the development of railway station choice models suitable for defining probabilistic station catchments for use in the aggregate demand models typically used to forecast demand for new rail stations. Revealed preference passenger survey data obtained from the Welsh and Scottish Governments was used for model calibration. Techniques were developed to identify trip origins an...

In this paper discrete choice models, Logit and Probit are examined in order to predict the economic recession or expansion periods in USA. Additionally we propose an adaptive neuro-fuzzy inference system with triangular membership function. We examine the in-sample period 1947-2005 and we test the models in the out-of sample period 2006-2009. The forecasting results indicate that the Adaptive ...

In contrast to the classical discrete choice experiment, the respondent in a rank-order discrete choice experiment, is asked to rank a number of alternatives instead of the preferred one. In this paper, we study the information matrix of a rank order nested multinomial logit model (RO.NMNL) and introduce local D-optimality criterion, then we obtain Locally D-optimal design for RO.NMNL models in...

This paper describes the development of two models which determine the financial solidity of Dutch non-life insurers: an ordered logit model and a neural network model. Since bankruptcies of Dutch insurance companies are very rare, the annual assessment texts made by the supervisor are used to classify the companies into one of the three possible groups: strong, moderate, or weak. Both models u...