Lutz Hildebrandt

Consumer retail satisfaction in rural areas: A reanalysis of survey data

Abstract Due to the decline of the number of small neighborhood stores, especially in rural areas, it is hypothesized that the quality of retail supply in these areas is attenuated. A causal modelling approach is applied to secondary data measuring retail supply in rural and urban areas. An explicit test of validity proposes a four-dimensional measurement model of retail satisfaction. Competing hypotheses are tested in a complex causal model to reveal the causes of retail satisfaction, measured by four dimensions. The analysis identifies accessibility and diversity of retailers as important dimensions of retail satisfaction, which are affected by situational variables of the household. The location of the household is shown to be a strong factor for (dis)satisfaction.

Store image and the prediction of performance in retailing

Abstract The success factor approach has come under scrutiny in recent years. It postulates that success and failure of a strategic business unit can be traced back to a limited number of key factors. For the domain of retail planning, however, only a few published studies have investigated the strategic factors that determine the performance of retail business units. Until now, success factor studies have not explicitly taken into account individual customer data. Customer evaluations or behavior have been represented in models only by using management judgments or other indirect measures. In this study of success factors in food retailing, the analysis of customer-oriented measures of the key factors of retail performance is proposed. A measurement model of retail store image that captures the customer perception of strategic variables like quality and price level is tested and used to predict a marketing outcome measure as an indicator for business success.

Multiple-Category Decision-Making: Review and Synthesis

In many purchase environments, consumers use information from a number of product categories prior to making a decision. These purchase situations create dependencies in choice outcomes across categories. As such, these decision problems cannot be easily modeled using the single-category, single-choice paradigm commonly used by researchers in marketing. We outline a conceptual framework for categorization, and then discuss three types of cross-category dependence: cross-category consideration cross-category learning, and product bundling. We argue that the key to modeling choice dependence across categories is knowledge of the goals driving consumer behavior.

Methodische Probleme bei der Erfolgsfaktorenforschung — Messfehler, formative versus reflektive Indikatoren und die Wahl des Strukturgleichungs-Modells

ZusammenfassungDieser Beitrag ist ein methodisches Plädoyer zur Verwendung adäquater Methoden in der empirischen Erfolgsfaktorenforschung. Wir zeigen die methodischen Probleme bei der Anwendung der LISREL-Methodologie auf empirische Erfolgsfaktorenstudien auf. Die Trennung in latente Konstrukte und reflektive Indikatoren, um zwischen einem Mess- und Strukturmodell unterscheiden zu können, und die Eliminierung von intern nicht konsistenten Indikatoren ist falsch, wenn es sich wie bei Erfolgsfaktorenstudien häufig um formative Indikatoren handelt, aus denen sich die Konstrukte ergeben. Durch die Wahl der falschen Messstruktur werden wichtige Facetten des Konstrukts vernachlässigt, und man erhält inhaltlich andere Ergebnisse. Bleibt man in der Strukturgleichungs-Methodologie, so empfiehlt sich die Anwendung von PLS, da dort die Indikatoren sowohl formativ als auch reflektiv spezifiziert werden können und geringere Anforderungen an die Daten gestellt werden. Mit Hilfe eines Beispiels wird demonstriert, dass sich insbesondere durch die Eliminierung von Indikatoren und weniger durch die Schätzmethode stark unterschiedliche Ergebnisse ergeben. Hier wird allerdings argumentiert, dass man im Falle ausschließlich formativer Indikatoren zu Regressionsanalysen zurückkehren sollte, weil man Multikollinearität durch Indexbildung behandeln und zusätzlich Nichtlinearitäten und unbeobachtete Heterogenität berücksichtigen kann.SummaryWe demonstrate methodological problems with the application of the so called “Cronbach’s α — LISREL”-paradigm. Working with unobserved latent constructs operationalized through indicators allows for differentiating into a measurement and structural model. However, while the elimination of internally inconsistent indicators is correct for reflective indicators, this proves to be incorrect for the mostly formative indicators in success factor studies. This neglects important facets of the problem which lead to results that vary according to the included indicator set. In this context, the analysis of structural equation models with LISREL is not appropriate because it can handle only reflective indicators while PLS allows for formative indicators. However, in the latter case it is often better to apply ordinary least squares regression to the battery of indicators because multicollinearity has to be dealt with in both, PLS and OLS, while regression models can handle nonlinear relationships as well as unobserved heterogeneity.

A Comparison of Current PLS Path Modeling Software: Features, Ease-of-Use, and Performance

After years of stagnancy, PLS path modeling has recently attracted renewed interest from applied researchers in marketing. At the same time, the availability of software alternatives to Lohmoller’s LVPLS package has considerably increased (PLS-Graph, PLS-GUI, SPAD-PLS, SmartPLS). To help the user to make an informed decision, the existing programs are reviewed with regard to requirements, methodological options, and ease-of-use; their strengths and weaknesses are identified. Furthermore, estimation results for different simulated data sets, each focusing on a specific issue (sign changes and bootstrapping, missing data, and multi-collinearity), are compared.

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.

Gruppenvergleiche bei hypothetischen Konstrukten — Die Prüfung der Übereinstimmung von Messmodellen mit der Strukturgleichungsmethodik

ZusammenfassungBei einem Vergleich von Gruppen anhand hypothetischer Konstrukte muss gewährleistet sein, dass die Messmodelle in den Gruppen gleich sind. Andernfalls besteht die Gefahr, dass falsche Rückschlüsse über die Unterschiede auf der latenten Ebene gezogen werden. Dieser Beitrag bietet einen state-of-the-Art zur Überprüfung der Messinvarianz mit der Mehrgruppenanalyse konfirmatorischer Faktormodelle. Ein Schwerpunkt liegt dabei auf der Ermittlung nichtinvarianter Indikatoren, wobei unterschiedliche Ansätze zur Identifikation latenter skalen sowie die wesentlichen Teststrategien verglichen werden. Die empirische studie zur Invarianz eines Messmodells der psychologischen Markenstärke („Brand Potential Index“) zeigt, dass bei einem Vergleich loyaler und nichtloyaler Konsumenten die Indikatoren Kaufabsicht und Weiterempfehlungsbereitschaft nichtinvariant sind. Aufgrund der Messinvarianz der übrigen Indikatoren sind aber sowohl Vergleiche auf der latenten Ebene als auch direkte Mittelwertvergleiche für die invarianten Indikatoren zulässig.SummaryComparing groups (e.g., customer segments) with respect to hypothetical constructs requires that the measurement models are equivalent across groups. Otherwise, conclusions drawn from the observed indicators regarding differences at the latent level (mean differences, differences in the structural relations) might be severly distorted. However, with the exception of intercultural studies, at present researchers in business administration do not pay enough attention to this issue. This article provides a state of the art on how to apply multi-group confirmatory factor analysis to assess measurement invariance. The required steps in the simultaneous analysis of the indicator means and variances/covariances are described, placing special emphasis on how to determine noninvariant indicators (“partial measurement invariance”). Here, different approaches to the identification of latent scales as well as the main test strategies are discussed. The procedure is demonstrated considering the construct brand strength (“Brand Potential Index”, BPI®) introduced by GfK Market Research as an example. The empirical study shows that the indicators buying intention and intention to recommend the brand are noninvariant across loyal and non-loyal consumers. Since the remaining seven BPI® indicators are invariant, comparisons at the latent variable level as well as for the invariant indicators are meaningful. Observed group differences in buying intention overestimate the underlying group differences in perceived brand attractiveness. Possible statistical as well as substantial explanations for these findings are discussed.

Probleme der Validierung mit Strukturgleichungsmodellen

Dieser Beitrag setzt sich mit der Leistungsfahigkeit von Strukturgleichungsmodellen bei der Validitatsprufung von Messmodellen fur hypothetische Konstrukte auseinander und geht auf ausgewahlte Problembereiche bei der gangigen Anwendung dieser Methodik fur die Skalenkonstruktion ein. Insbesondere werden mit der Kontrolle verschiedener Arten von Methodeneffekten Alternativen zur Elimination von Indikatoren ausschlieslich auf Basis statistischer Kriterien (z. B. interne Konsistenz) aufgezeigt.

Unobservable effects in structural models of business performance

Critiques of the concept of key success factors have raised objections both conceptually and methodologically. From the latter perspective, common research practice is criticized for neglecting the influence of firm-specific, unobservable variables (e.g., management skills). To control for these effects a structural equation approach (LISREL) to the analysis of panel data is proposed. In an empirical study based on the PIMS annual data base the influence of unobservables on the direct and indirect effects of product quality on profitability is examined. It is shown, how a step by step extension of a basic simultaneous equation model sheds some light on the role unobservable variables play. Even after controlling for persistent unobservable effects product quality and market share remain significant determinants of profitability.

Modeling Joint Purchases with a Multivariate MNL Approach

Our research examines the hypothesis that products chosen on a shopping trip to a supermarket indicate the preference interdependencies of consumers between different products or brands. The bundle chosen on the trip can be regarded as an indicator of a global utility function. This function implies a cross-category dependence of brand choice behavior. We hypothesize that the global utility function related to a product bundle is the result of the marketing-mix of the underlying brands. The structure of the chosen products allows us to uncover the impact of certain marketing-mix variables and product bundle buying behavior.