Franziska Völckner

How Important Are Brands? A Cross-Category, Cross-Country Study

This article focuses on the measurement of the overall importance of brands for consumer decision making—that is, brand relevance in category, or BRiC—across multiple categories and countries. Although brand equity measures for specific brands have attracted a large body of literature, the questions of how important brands are within an entire product category and the extent to which BRiC differs across categories and countries have been neglected. The authors introduce the concept of BRiC (a category-level measure, not a brand-level measure). They develop a conceptual framework to measure BRiC and the drivers of BRiC, test the framework empirically with a sample of more than 5700 consumers, and show how the construct varies across 20 product categories and five countries (France, Japan, Spain, the United Kingdom, and the United States). The results suggest a high validity of the proposed BRiC measure and show substantial differences between categories and countries. A replication study two-and-a-half years later confirms the psychometric properties of the suggested scale and shows remarkable stability of the findings. The findings have important implications for the management of brand investments.

Discovering unobserved heterogeneity in structural equation models to avert validity threats

A large proportion of information systems research is concerned with developing and testing models pertaining to complex cognition, behaviors, and outcomes of individuals, teams, organizations, and other social systems that are involved in the development, implementation, and utilization of information technology. Given the complexity of these social and behavioral phenomena, heterogeneity is likely to exist in the samples used in IS studies. While researchers now routinely address observed heterogeneity by introducing moderators, a priori groupings, and contextual factors in their research models, they have not examined how unobserved heterogeneity may affect their findings. We describe why unobserved heterogeneity threatens different types of validity and use simulations to demonstrate that unobserved heterogeneity biases parameter estimates, thereby leading to Type I and Type II errors. We also review different methods that can be used to uncover unobserved heterogeneity in structural equation models. While methods to uncover unobserved heterogeneity in covariance-based structural equation models (CB-SEM) are relatively advanced, the methods for partial least squares (PLS) path models are limited and have relied on an extension of mixture regression--finite mixture partial least squares (FIMIX-PLS) and distance measure-based methods--that have mismatches with some characteristics of PLS path modeling. We propose a new method--prediction-oriented segmentation (PLSPOS)--to overcome the limitations of FIMIX-PLS and other distance measure-based methods and conduct extensive simulations to evaluate the ability of PLS-POS and FIMIX-PLS to discover unobserved heterogeneity in both structural and measurement models. Our results show that both PLS-POS and FIMIX-PLS perform well in discovering unobserved heterogeneity in structural paths when the measures are reflective and that PLS-POS also performs well in discovering unobserved heterogeneity in formative measures. We propose an unobserved heterogeneity discovery (UHD) process that researchers can apply to (1) avert validity threats by uncovering unobserved heterogeneity and (2) elaborate on theory by turning unobserved heterogeneity into observed heterogeneity, thereby expanding theory through the integration of new moderator or contextual variables.

The Role of Parent Brand Quality for Service Brand Extension Success

Although substantial differences between product quality and service quality have spurred service research for the past 30 years, studies of brand extension success drivers in a services context measure the core driver of parent brand quality, using scales developed for fast moving consumer goods (FMCG). This study instead assesses parent brand quality with a context-specific measure, drawn from service quality research, and analyzes the relative effects of key brand extension success drivers for services. Partial least squares (PLS) modeling offers diagnostic information about the impact of three dimensions of perceived parent brand quality on the perceived service quality of an extension product, a key success metric for service brand extensions. In contrast with previous studies, the dominant success driver is parent brand quality rather than the perceived fit between the parent brand and the extension. Moreover, all three dimensions of parent brand quality constitute distinct drivers that should be considered when managers assess the chances of service brand extension success, with outcome quality having the strongest impact on service brand extension success. An importance performance analysis of the PLS estimates for 27 hypothetical service extensions demonstrates the diagnostic value of this approach and charts a ‘‘priority map’’ for managerial decisions.

The Double-Edged Sword of Foreign Brand Names for Companies from Emerging Countries

Foreign branding—or using brand names that evoke foreign associations through, for example, spelling a brand name in a foreign language—is a popular means in both developed and emerging countries of suggesting a specific country of origin (COO) in the hope that it will evoke certain product qualities. As a result, consumers increasingly encounter products with brand names that imply a COO that differs from the actual COO (where the product is manufactured). In four experiments, the authors find support for the hypothesis that incongruence between the actual COO and implied COO decreases purchase likelihood asymmetrically. Incongruence backfires in hedonic categories but has hardly any effect in utilitarian categories. Furthermore, incongruence decreases purchase likelihood more if the actual COO is an emerging rather than developed country. The authors address the psychological process underlying the asymmetric effect of incongruence by showing that consumers apply different information-processing strategies to hedonic versus utilitarian products. These results have important implications for (foreign) branding decisions.

Listen to Your Customers: Insights into Brand Image Using Online Consumer-Generated Product Reviews

ABSTRACT Online consumer-generated product reviews are a growing phenomenon and have led to the posting of colossal amounts of data by consumers on the Web. These data include consumers’ thoughts, opinions, and feelings about brands and offer firms the opportunity to “listen in” on consumers to get a better understanding of the topics discussed about their brands. Using the human associative memory model as the theoretical framework, the authors introduce an approach to convert online product reviews into meaningful information about brand images using a novel combination of text mining and network analysis methodologies. Following a network-based understanding of brand image, the authors use online product reviews to extract consumers’ brand associations and their interconnections as well as to depict and characterize the network of brand associations. In an empirical study, the authors test the approach and illustrate its managerial usefulness. The suggested approach allows managers to effectively monitor and detect strengths and weaknesses of brand image. Moreover, the proposed approach is one of the first attempts to measure brand image using consumer-generated content by applying text mining and network analysis.

Separating Negative and Positive Effects of Price with Choice-Based Conjoint Analyses

Franziska Völckner is Assistant Professor at the Institute of Marketing, Retailing and Management Science, University of Hamburg, Von-Melle-Park 5, D-20146 Hamburg, Germany, Phone: +49-40-42838-3695, Fax: +49-40-42838-3650, E-Mail: voelckne@econ.unihamburg.de Henrik Sattler (corresponding author) is Professor of Marketing and Managing Director of the Institute of Marketing, Retailing and Management Science, University of Hamburg, Von-Melle-Park 5, D-20146 Hamburg, Germany, Phone: +49-40-42838-6401, Fax: +49-40-42838-3650, E-Mail: uni-hamburg@henriksattler.de Separating Negative and Positive Effects of Price with Choice-Based Conjoint Analyses

Markentransfererfolgsanalysen bei kurzlebigen Konsumgütern unter Berücksichtigung von Konsumentenheterogenität

ZusammenfassungDer Beitrag analysiert erstmals, inwiefern Signifikanz und relative Wirkungsstärke der Erfolgsfaktoren von Markentransfers zwischen verschiedenen Konsumentensegmenten variieren. Untersucht werden nahezu sämtliche Erfolgsfaktoren, die sich in vorangegangenen empirischen Studien mindestens einmal als signifikant erwiesen haben. Die empirische Basis umfasst 66 real in den Markt eingeführte Transferprodukte aus einer Vielzahl von Produktkategorien kurzlebiger Konsumgüter. Es zeigt sich, dass die Schlussfolgerungen der bisherigen Forschung hinsichtlich Signifikanz und relativer Wirkungsstärke der Erfolgsfaktoren durch die Vernachlässigung von Konsumentenheterogenität mit erheblichen Verzerrungen behaftet sind.SummaryThis paper is intended to investigate the empirical generalizability of prior findings concerning factors affecting consumer evaluations of brand extensions. We investigate the significance and relative importance of such brand extension success factors and test to which extent our findings can be generalized across consumer segments. Our study includes all major factors which have been proven by past research to be of significant relevance under a certain set of circumstances (i.e. factors that turned out to be significant at the p < 0.10 level in at least one empirical study). In total we analyze 66 existent fast moving consumer goods brand extensions stemming from leading German parent brands within a large variety of extension categories. Using an a priori segmentation as well as a latent class approach we found major differences between consumer segments. Our results show that prior research findings are considerably biased as a result of ignoring consumer heterogeneity.

Does Chain Labeling Make Private Labels More Successful

Some retailers use their chain names to identify their private labels. We find that chain labeling increases the likelihood that consumers correctly recognize a private label as belonging to a specific retailer, and that on average, chain labeling improves consumers’ attitudes toward private labels. We also identify two boundary conditions for this effect: chain labeling helps for standard, but not for economy private labels, and it improves consumers’ attitudes toward private labels in categories with low brand relevance. These results have important implications for managers on whether and when to use chain labeling for their private labels.

Präferenzmessung bei unsicheren Produkteigenschaften: Risikoberücksichtigung bei Ergebnissen aus Conjoint-Analysen

ZusammenfassungKaufentscheidungen sind häufig dadurch gekennzeichnet, dass Konsumenten im Vorfeld nicht sicher sein können, was für eine Qualität sie bekommen. Diese Unsicherheit wird bislang in Conjoint-Analysen als populärster Methode zur Messung von Konsumentenpräferenzen nicht berücksichtigt. Hierdurch kann es zu erheblichen Verzerrungen bei der Ermittlung von Gesamtnutzenwerten für alternative Angebote und somit bei der Prognose von Wahlanteilen und der Schätzung von Response-funktionen kommen. Der Beitrag stellt ein Verfahren vor, mit dem die Ergebnisse von Conjoint-Analysen um Unsicherheitsaspekte korrigiert werden können und verdeutlicht in einer empirischen Studie das Ausmaß des vermuteten „Unsicherheits-Bias“ herkömmlicher Ansätze.SummaryConjoint measurement is one of the most popular methods for measuring consumers’ preference structures. In many purchase decisions consumers do not know the exact value of a product attribute, but may only be aware of it as a random variable with a certain probability distribution. Unless the effects of uncertain attribute values on the perceived value of a product are considered, utility values computed from conjoint analysis might be biased and lead to an over- or underestimation of the choice shares of the investigated alternatives. However, conjoint measurement does not consider this kind of uncertainty so far. The objective of this paper is twofold. First, we develop a procedure for modifying the results of conjoint-analyses to consider the effects of uncertain attribute values. Second, we present an empirical application of this procedure and quantify the size of the potential bias when uncertainty is ignored.

Attitude-Based Versus Choice-Behavior-Based Success of Brand Extensions

This study compares the effects of brand extension success drivers across attitude-based and choice-behavior-based measures of extension success within the FMCg sector. Previous research considers different success measures in separate studies, focusing mainly on attitude-based measures. We suggest and empirically test different effects of commonly applied success drivers on one attitude-based and three choice-behavior-based extension success measures. Our findings imply that fit and parent brand strength may not be dominant success drivers in the context of choice-behavior-based success measures. Instead, marketing support for the extension product drives choice-behavior-based brand extension success.