Is cross-category brand loyalty determined by risk aversion?

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

Estimation with the Nested Logit Model: Specifications and Software Particularities

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

Estimation with the Nested Logit Model: Specifications and Software Particularities

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

Das Hybride Wahlmodell und seine Anwendung im Marketing

Traditional choice models assume that observable behavior results from an unspecified evaluation process of the observed individual. When it comes to the revelation of this process mere choice models rapidly meet their boundaries, as psychological factors (e.g., consumers’ perception or attitudes towards products) are not directly measurable variables and therefore cannot offhand be integrated within the model structure. The causal-analytic approach offers the possibility to specify not directly measurable factors as latent variables, and can thus reasonable supplement choice models. So far, methodological approaches investigating latent variables, and traditional choice models are perceived and applied independently of one another. In this paper the possibilities of an integration of latent variables into traditional choice models is pointed out, and an introduction into the modeling of hybrid choice models is provided. Furthermore, potential areas of application in marketing research are outlined.Hybrid choice model, latent variables, causal model, choice model

Four essays on modeling brand choice and brand loyalty

Die vorliegende Arbeit besteht aus vier Aufsätzen, die sich mit der Modellierung von Markenwahlverhalten und Markentreue beschäftigen. Der erste Aufsatz gibt eine Einführung in das Nested Logit Modell und weist auf die Existenz von zwei unterschiedlichen Spezifikationen hin. Das utility maximization nested logit (UMNL) und das non-normalized nested logit (NNNL) Modell besitzen unterschiedliche Eigenschaften, die die Schätzergebnisse beeinflussen. Mit einer Simulationsstudie werden die Konsequenzen der Verwendung verschiedener Softwarepakete demonstriert. Außerdem wird gezeigt, dass nur die UMNL Spezifikation bei Auferlegung einer Parameterrestriktion mit der Zufallsnutzentheorie konform ist. Der zweite Aufsatz untersucht anhand von realen Haushaltspaneldaten den Erfolg einer Familienmarkenstrategie. Die Signaling Theorie liefert einen Rahmen für die dem Markenwahlverhalten zugrunde liegenden psychologischen Prozesse zur Entstehung und Erklärung von produktkategorieübergreifender Markentreue. In einer empirischen Studie wird untersucht, inwieweit in einer Kategorie markentreue Kunden dieser Marke auch in anderen Produktkategorien treu sind. Es wird ein Markentreue-Hebel-Index entwickelt. Im dritten Aufsatz stehen die psychologischen Determinanten von kategorieübergreifenden Zusammenhängen im Markenwahlverhalten im Mittelpunkt. In einer empirischen Studie wird die Risikoaversion als entscheidender Bestimmungsfaktor von kategorieübergreifender Markentreue untersucht. Die konsumentenspezifische Risikoaversion wird dabei über Innovativeness und Status Quo Bias erfasst. Im vierten Aufsatz wird das Hybride Wahlmodell einem breiten Marketingpublikum vorgestellt. Klassische Wahlmodelle gehen davon aus, dass das beobachtbare Verhalten das Resultat eines nicht spezifizierten Evaluationsprozesses des Individuums ist. Der kausalanalytische Ansatz hingegen erlaubt die Spezifikation nicht direkt messbarer Faktoren als latente Variablen und kann somit Wahlmodelle sinnvoll ergänzen.This thesis is composed of four essays that pick up topics in brand choice and brand loyalty modeling. The first essay gives an introduction to the nested logit model and points attention to the existence of two different specifications. The utility maximization nested logit (UMNL) model and the non-normalized nested logit (NNNL) model have different properties which impact the estimation results. In a simulation study, the consequences of the usage of different software packages for model estimation on the estimation results is demonstrated. It is also shown that only the UMNL specification with an imposed parameter restriction is consistent with the underlying random utility theory. The second essay investigates the success of an umbrella branding strategy using household panel data. Signaling theory provides a framework for the underlying psychological processes in consumers'' brand choice behavior and can contribute in the formation and explanation of loyalty to the brand in multiple categories. An empirical study determines whether there is a tendency for loyal consumers from one product category to be loyal to the same brand in other product categories as well. Therefore, a cross-category brand loyalty leverage index is developed. In the third essay, consumer-specific psychological determinants of cross-category relations between brand loyal choice decisions are discussed. In an empirical study, the concept of risk aversion is considered as the key determinant of cross-category brand loyalty. Consumers'' risk aversion is derived from their innovativeness and status quo bias. In the fourth essay, the hybrid choice model is introduced to the broad marketing audience. Traditional choice models assume that observable behavior results from an unspecified evaluation process of the observed individual. The causal-analytic approach offers the possibility to specify not directly measurable factors as latent variables, and can thus reasonably supplement choice models

Does umbrella branding really work?

Numerous studies on the drivers of brand extension success [Aaker and Keller, 1990, Broniarczyk and Alba, 1994, Hem et al., 2003, Völckner and Sattler, 2006] found evidence that parent-brand characteristics and the fit between parent brand and transfer product are the main and most influential factors driving brand extension success. However, the ability of a brand to transfer its brand loyal customers from the parent to the extension category has been widely neglected. Brand loyalty can be regarded as a consequence of the underlying assumption of customers transferring their quality perceptions, their brand knowledge, and their experience with the brand from one category to the other [Erdem and Swait, 1998]. We find empirical evidence that consumers who are loyal to the brand in the leading (parent) product category show a higher probability to be loyal to that same brand in another (extension) category compared to those consumers who are not loyal in the leading category. Moreover, as the overall success of the extension includes positive retroactive effects of the extension product on the parent product or brand [Erdem, 1998], the arising question is whether there are differences between extension product categories regarding their attachment to the parent category and their ability to stimulate brand loyal purchases in the parent category, i.e., speaking of ’leader’ and ’follower’ categories in terms of brand loyal purchase behavior. This might even hold true for the relationship of any two categories the brand competes

Is cross-category brand loyalty determined byrisk aversion?

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

Estimation with the Nested Logit Model

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

Das Hybride Wahlmodell und seine Anwendung im Marketing

Traditional choice models assume that observable behavior results from an unspecified evaluation process of the observed individual. When it comes to the revelation of this process mere choice models rapidly meet their boundaries, as psychological factors (e.g., consumers’ perception or attitudes towards products) are not directly measurable variables and therefore cannot offhand be integrated within the model structure. The causal-analytic approach offers the possibility to specify not directly measurable factors as latent variables, and can thus reasonably supplement choice models. So far, methodological approaches investigating latent variables, and traditional choice models are perceived and applied independently of one another. In this paper the possibilities of an integration of latent variables into traditional choice models is pointed out, and an introduction into the modeling of hybrid choice models is provided. Furthermore, potential areas of application in marketing research are outlined