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Activity Number: 416 - A Tour of Statistical Innovations in Marketing Research
Type: Contributed
Date/Time: Tuesday, August 1, 2017 : 2:00 PM to 3:50 PM
Sponsor: Section on Statistics in Marketing
Abstract #322530
Title: MaxDiff Adjusted to Items Non-Availability and Network Effects
Author(s): Stan Lipovetsky* and Michael W. Conklin
Companies: GfK North America and GfK North America
Keywords: MaxDiff ; Markov chain ; Chapman-Kolmogorov equations ; network effects
Abstract:

MaxDiff, or Maximum Difference, aka Best-Worst Scaling, is a discrete choice method widely used for finding utilities and choice probabilities among multiple alternatives. Data for such modeling is given by respondents who are presented with several items and chooses the best and worst alternatives. Estimation of utilities is usually performed in a multinomial-logit (MNL) modeling technique which produces utilities and choice probabilities of the compared items. This paper describes how to obtain the robust probability estimation adjusted to possible absence of items in actual purchasing. For this aim we apply Markov chain modeling in form of Chapman-Kolmogorov system of differential equations and its steady-state solution which can be reduced to eigenproblem by a stochastic matrix and solved analytically. The obtained closed-form solution suggests a robust modification of choice probabilities with accounted cases of items non-availability. Adjustment to choice probability with network effects is also considered. Numerical example by marketing research data is used and the results are discussed. This approach is useful for theoretical descriptions and practical applications.


Authors who are presenting talks have a * after their name.

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