Nonlinear Effects in Brand Choice Models: Comparing Heterogeneous Latent Class To Homogeneous Nonlinear Models

2007 ◽  
Vol 59 (2) ◽  
pp. 118-137 ◽  
Author(s):  
Marion Schindler ◽  
Bernhard Baumgartner ◽  
Harald Hruschka
2021 ◽  
pp. 109442812199190
Author(s):  
Mikko Rönkkö ◽  
Eero Aalto ◽  
Henni Tenhunen ◽  
Miguel I. Aguirre-Urreta

Transforming variables before analysis or applying a transformation as a part of a generalized linear model are common practices in organizational research. Several methodological articles addressing the topic, either directly or indirectly, have been published in the recent past. In this article, we point out a few misconceptions about transformations and propose a set of eight simple guidelines for addressing them. Our main argument is that transformations should not be chosen based on the nature or distribution of the individual variables but based on the functional form of the relationship between two or more variables that is expected from theory or discovered empirically. Building on a systematic review of six leading management journals, we point to several ways the specification and interpretation of nonlinear models can be improved.


2022 ◽  
Vol 136 ◽  
pp. 103552
Author(s):  
Georges Sfeir ◽  
Filipe Rodrigues ◽  
Maya Abou-Zeid

2011 ◽  
Vol 8 (1) ◽  
pp. 103 ◽  
Author(s):  
Sergio Colombo ◽  
Nick Hanley

The need to account for respondents’ preference heterogeneity in stated choice models has motivated researchers to apply random parameter logit and latent class models. In this paper we compare these three alternative ways of incorporating preference heterogeneity in stated choice models and evaluate how the choice of model affects welfare estimates in a given empirical application. Finally, we discuss what criteria to follow to decide which approach is most appropriate.


Author(s):  
Xianghong Ma ◽  
Alexander F. Vakakis

Abstract Transient nonlinear localization and beat phenomena are studied in a system of two rods coupled with a nonlinear backlash spring. The method of Karhunen-Loeve (K-L) decomposition is used to reduce the order of the dynamics, and to study nonlinear effects by considering energy transfers between leading K-L modes. The computed K-L modes are used to discretize the governing partial differential equations, thus creating accurate and computationally efficient low-dimensional nonlinear models of the system. Reconstruction of transient nonlinear responses using these low dimensional models reveals the accuracy of the order reduction. Poincare’ maps are utilized to study the nonlinear localization and beat phenomena caused by the clearance connecting the coupled rods.


1973 ◽  
Vol 10 (4) ◽  
pp. 421-427 ◽  
Author(s):  
Robert C. Blattberg ◽  
Subrata K. Sen

This paper investigates the small sample properties of minimum chi-square estimates of the parameters of stochastic brand choice models. It also describes and evaluates a statistical test which is appropriate for discriminating between two stochastic brand choice models when one is a constrained version of the other.


2020 ◽  
Vol 9 (2) ◽  
pp. 3-21
Author(s):  
Azzurra Annunziata ◽  
Lara Agnoli ◽  
Riccardo Vecchio ◽  
Steve Charters ◽  
Angela Mariani

This study aims to analyse the influence of alternative formats of health warnings on French and Italian Millennial consumers’ choices of beer and wine. Two Discrete Choice Experiments were built for wine and beer and two Latent Class choice models were applied in order to verify the existence of different consumer profiles. Results show that young consumers’ choices for wine and beer are influenced by framing, design and visibility of warnings. In both countries, the acceptance of warnings is higher for beer than for wine and in both cases consumers show higher utility for a logo on the front label: on the neck with a neutral message in the case of beer; on the front, without a message for wine. Latent Class choice models highlight the existence of different consumers’ groups with different levels of warning influencing their choices. In order to apply policies conducting to health benefits, our results suggest the need to focus on young individuals to communicate the risks of alcohol abuse through targeted messages and, more generally, to make them aware of the potential negative effects of excessive consumption of both wine and beer.


1987 ◽  
Vol 24 (2) ◽  
pp. 139-153 ◽  
Author(s):  
Rajiv Grover ◽  
V. Srinivasan

The authors define a market segment to be a group of consumers homogeneous in terms of the probabilities of choosing the different brands in a product class. Because the vector of choice probabilities is homogeneous within segments and heterogeneous across segments, each segment is characterized by its corresponding group of brands with “large” choice probabilities. The competitive market structure is determined as the possibly overlapping groups of brands corresponding to the different segments. The use of brand choice probabilities as the basis for segmentation leads to market structuring and market segmentation becoming reverse sides of the same analysis. Using panel data, the authors obtain the matrix of cross-classification of brands chosen on two purchase occasions and extract segments by using the maximum likelihood method for estimating latent class models. An application to the instant coffee market indicates that the proposed approach has substantial validity and suggests the presence of submarkets related to product attributes as well as to brand names.


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