204 research outputs found

    A Market Basket Analysis Conducted with a Multivariate Logit Model

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    The following research is guided by the hypothesis that products chosen on a shopping trip in a supermarket can indicate the preference interdependencies between different products or brands. The bundle chosen on the trip can be regarded as the result of a global utility function. More specifically: the existence of such a function implies a cross-category dependence of brand choice behavior. It is hypothesized that the global utility function related to a product bundle results from the marketing-mix of the underlying brands. Several approaches exist to describe the choice of specific categories from a set of many alternatives. The models are discussed in brief; the multivariate logit approach is used to estimate a model with a German data set.market basket analysis, multivariate logit model, brand choice behavior, marketing-mix

    Measuring changes in preferences and perception due to the entry of a new brand with choice data

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    Context effects can have a major influence on brand choice behavior after the introduction of a new product. Based on behavioral literature, several hypotheses about the effects of a new brand on perception, preferences and choice behavior can be derived, but studies with real choice data are still lacking. We employ an internal market structure analysis to measure context effects caused by a new product in scanner panel data, and to discriminate between alternative theoretical explanations. An empirical investigation reveals strong support for categorization effects and changes in perception, which affect customers in two out of five segments.context effects, categorization, brand choice models, new brand introduction

    Formative Measurement Models in Covariance Structure Analysis: Specification and Identification

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    Many researchers seem to be unsure about how to specify formative measurement models in software programs like LISREL or AMOS and to establish identification of the corresponding structural equation model. In order to make identification easier, a new, mainly graphically oriented approach is presented for a specific class of recursive models with formative indicators. Using this procedure it is shown that some models have erroneously been considered underidentified. Furthermore, it is shown that specifying formative indicators as exogenous variables rises serious conceptual and substantial issues in the case that the formative construct is truly endogenous (i. e. influenced by more remote causes). An empirical study on the effects and causes of brand competence illustrates this point.Formative Indicators; Latent Variables; Covariance Structure Analysis; Identification

    Context Effects as Customer Reaction on Delisting of Brands

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    The delisting of brands is frequently used by retailers to strengthen their negotiating position with the manufacturers and suppliers of their product assortment. However, retailers and manufacturers have to consider the risk of potential reactions when customers are faced with a reduced or modified assortment and thus, different choice. In this paper, two studies are presented which investigate customers` switching behavior if a (sub-)brand is unavailable and key determinants of the resulting behavior are discussed. Various conditions are tested by taking into account context theory. The results reveal that customer responses depend significantly on the context. A real-life quasi-experiment suggests that manufacturers may encounter substantially larger losses than retailers. Managerial implications for both parties can be derived and recommendations for further research are developed.Consumer decisions, delisting, context effects, switching behavior, retailing, logistic regression

    Is cross-category brand loyalty determined by risk aversion?

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    The need to understand and leverage consumer-brand bonds has become critical in a marketplace characterized by increasing unpredictability, diminishing product differentiation, and heightened competitive pressure. This is especially true for fast moving consumer goods (FMCG) manufacturers and retailers. Knowing why a customer stays loyal to a brand in multiple product categories is necessary for deriving suitable marketing strategies in the context of a brand extension, yet research on the motives, characteristics, life styles and attitudes of cross-category brand loyal customers has been investigated only in a limited number of studies. We will fill a gap in the literature on cross-category brand choice behavior by analyzing revealed preference data with respect to brand loyalty in several categories in which a brand competes. Provided with purchase and corresponding survey data we investigate the product portfolio of a leading nonfood FMCG brand. We segment consumers on the basis of their revealed brand preferences and, focusing on consumers’ risk aversion, identify cross-category brand loyal customers’ personality traits as determinants of their brand loyal purchase behavior.cross-category brand loyalty, risk aversion, share of category requirements, customer segmentation

    An empirical test of theories of price valuation using a semiparametric approach, reference prices, and accounting for heterogeneity

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    In this paper we estimate and empirically test different behavioral theories of consumer reference price formation. Two major theories are proposed to model the reference price reaction: assimilation contrast theory and prospect theory. We assume that different consumer segments will use different reference prices. The study builds on earlier research by Kalyanaram and Little (1994); however, in contrast to their work, we use parametric and semiparametric approaches to detect the structure of the underlying data sets. The different models are tested using a program module in GAUSS that was able to account for heterogeneity. The model types were calibrated by a simulation study. The calibrated modules were then used to analyze real market data.price valuation, semiparametric approach, reference prices, heterogeneity

    Estimation with the Nested Logit Model: Specifications and Software Particularities

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    Due to its ability to allow and account for similarities betweenpairs of alternatives, the nested logit model is increasingly used in practical applications. However the fact that there are two different specifications of the nested logit model has not received adequate attention. The utility maximization nested logit (UMNL) model and the non-normalized nested logit (NNNL) model have different properties, influencing the estimation results in a different manner. As the NNNL specification is not consistent with random utility theory (RUT), the UMNL form is preferred. This article introduces distinct specifications of the nested logit model and indicates particularities arising from model estimation. Additionally, it demonstrates the performance ofsimulation studies with the nested logit model. In simulation studies with the nested logit model using NNNL software (e. g. PROC MDC in SAS(c) ), it must be pointed out that the simulation of the utility function´s error terms needs to assume RUT-conformity. But as the NNNL specification is not consistent with RUT, the input parameters cannot be reproduced without imposing restrictions. The effects of using various software packages on the estimation results of a nested logit model are shown on the basis of a simulation study.nested logit model, utility maximization nested logit, non-normalized nested logit, simulation study

    "Investigating the Competitive Assumption of Multinomial Logit Models of Brand Choice by Nonparametric Modeling"

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    The Multinomial Logit (MNL) model is still the only viable option to study nonlinear responsiveness of utility to covariates nonparametrically. This research investigates whether MNL structure of inter-brand competition is a reasonable assumption, so that when the utility function is estimated nonparametrically, the IIA assumption does not bias the result. For this purpose, the authors compare the performance of two comparable nonpara-metric choice models that differ in one aspect: one assumes MNL com-petitive structure and the other infers the pattern of brands' competition nonparametrically from data.

    Estimation with the Nested Logit Model: Specifications and Software Particularities

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    The paper discusses the nested logit model for choices between a set of mutually exclusive alternatives (e.g. brand choice, strategy decisions, modes of transportation, etc.). Due to the ability of the nested logit model to allow and account for similarities between pairs of alternatives, the model has become very popular for the empirical analysis of choice decisions. However the fact that there are two different specifications of the nested logit model (with different outcomes) has not received adequate attention. The utility maximization nested logit (UMNL) model and the non-normalized nested logit (NNNL) model have different properties, influencing the estimation results in a different manner. This paper introduces distinct specifications of the nested logit model and indicates particularities arising from model estimation. The effects of using various software packages on the estimation results of a nested logit model are shown using simulated data sets for an artificial decision situation.nested logit model, utility maximization nested logit, nonnormalized nested logit, simulation study

    Brand equity

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    To explore how occurring critical incidents affect customer-brand relations, this study measures the impact on the basis of an online experiment. For this purpose, 1,122 usable responses are gathered considering the smartphone brands of Apple and Nokia as well as different scenarios. The respective reactions to these negative incidents are evaluated using the concept of customer-based brand equity. More precisely, a structure equation model is specified and differences in latent factor means are estimated taking into account perceived quality, various brand associations, loyalty and overall brand equity. The findings indicate that brand equity dimensions are not equally affected. Moreover, the results demonstrate that both brand equity and the business relationship before crisis moderate the effect of distinct critical incidents
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