1998
DOI: 10.1016/s0304-4076(98)00057-8
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Forecasting new product penetration with flexible substitution patterns

Abstract: We describe and apply choice models, including generalizations of logit called 'mixed logits,' that do not exhibit the restrictive 'independence from irrelevant alternatives' property and can approximate any substitution pattern. The models are estimated on data from a stated-preference survey that elicited customers' preferences among gas, electric, methanol, and CNG vehicles with various attributes.1999 Elsevier Science S.A. All rights reserved.JEL classification: C15; C35; L62; R41

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Cited by 598 publications
(397 citation statements)
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“…The first is the usual random-utility error term that augments the deterministic utility associated with each alternative. The other component pertains only to a subset of the alternatives, thereby imposing a particular correlation structure across the utility of different choice alternatives (Brownstone/Train 1999). A dummy variable, l j captures unobserved variance specific to the set of alternatives.…”
Section: Model Specificationmentioning
confidence: 99%
See 1 more Smart Citation
“…The first is the usual random-utility error term that augments the deterministic utility associated with each alternative. The other component pertains only to a subset of the alternatives, thereby imposing a particular correlation structure across the utility of different choice alternatives (Brownstone/Train 1999). A dummy variable, l j captures unobserved variance specific to the set of alternatives.…”
Section: Model Specificationmentioning
confidence: 99%
“…In specifying this correlation structure, the aim was to capture latent effects whose influence could otherwise violate the assumption of independence of irrelevant alternatives implied by the standard conditional logit model. Assuming the remaining error terms E ij in Equation (1) to be identically and independently distributed as Gumbel (or Type I extreme value), and conditioning on a particular value of w, the conditional choice probabilities of the error-component logit model are equal to (Brownstone/Train 1999):…”
Section: Model Specificationmentioning
confidence: 99%
“…However, there are factors influencing preferences that are unobservable or difficult to measure. In recent years, the use of mixed logit -ML (Brownstone and Train, 1999), has been increasing, allowing the incorporation of variations in unobservable preferences. These models imply an independently and identically distributed random term according to a Gumbel distribution -as well as the MNL -, but with an additional random component, which permits to work with greater flexibility.…”
Section: Estimation Of Discrete Choice Modelsmentioning
confidence: 99%
“…These models imply an independently and identically distributed random term according to a Gumbel distribution -as well as the MNL -, but with an additional random component, which permits to work with greater flexibility. Depending on the assumptions considered on the various random terms it is possible to model correlation and heteroscedasticity (Brownstone and Train, 1999). In order to characterize the heterogeneity of individuals more accurately, Bhat (1998) proposed an approach that allows the consideration of the existence of heterogeneity, both systematic and random.…”
Section: Estimation Of Discrete Choice Modelsmentioning
confidence: 99%
“…As noted in the econometric model section, unobserved characteristics of the choosers might affect the IIA assumption. One way to relax this assumption is to introduce individual random effects and estimate a mixed logit model (Brownstone and Train 1999). Using the same data set, Defever (2006) provides estimation implementing a mixed logit.…”
Section: Notesmentioning
confidence: 99%