The nested logit model has been widely used to study nested choice. A typical example of such nested choice is store patronage and brand choice. An important limitation of the nested logit model is that it assumes that all alternatives at both levels of the nest are available in the choice set of the consumer. While there is a wide literature on the incorporation of restricted choice sets into ...

Richard Baskerville and Nancy Russo have shown how particular supervisor-student relationships can be seen as one of a number of metaphors, for example, a journey, a marriage, apprenticeship and servitude. In this paper we develop this idea further by suggesting problems associated with situations where students and supervisors might be proceeding on the basis of different metaphors, which we r...

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The simulation variance in the estimation of mixed logit parameters is found, in our application, to be lower with 100 Halton draws than with 1000 random draws. This finding confirms Bhat’s (1999a) results and implies significant reduction in run times for mixed logit estimation. Further investigation is needed to assure that the result is not quixotic or masking other issues.

The mixed logit model is considered to be the most promising state of the art discrete choice model currently available. Increasingly researchers and practitioners are estimating mixed logit models of various degrees of sophistication with mixtures of revealed preference and stated preference data. It is timely to review progress in model estimation since the learning curve is steep and the unw...

 Joint Optimization of Assortment Selection and Pricing under the Capacitated Multinomial Logit Choice Model with Product-Differentiated Price Sensitivities Ruxian Wang HP Laboratories HPL-2012-207 Multinomial Logit model; assortment optimization; multi-product price optimization Many firms face a problem to select an assortment of products and determine their prices to maximize the total prof...

In this research, we propose a novel approach for a multinomial logit model selection procedure: specifically, we apply association rules analysis to identifying potential interactions for multinomial logit modeling. Interaction effects are very common in reality, but conventional multinomial logit model selection methods typically ignore them. This is especially true for higher-order interacti...

The mixed logit model is considered to be the most promising state of the art discrete choice model currently available. Increasingly researchers and practitioners are estimating mixed logit models of various degrees of sophistication with mixtures of revealed preference and stated choice data. It is timely to review progress in model estimation since the learning curve is steep and the unwary ...

Several supervised learning algorithms are suited to classify instances into a multiclass value space. MultiNomial Logit (MNL) is recognized as a robust classifier and is commonly applied within the CRM (Customer Relationship Management) domain. Unfortunately, to date, it is unable to handle huge feature spaces typical of CRM applications. Hence, the analyst is forced to immerse himself into fe...