Quantitative Marketing and Marketing Management

The paper addresses an issue that has been qualified as “challenging” in the literature, i.e., estimating the parameters of the well-known Pareto/NBD model. Previous researchers have circumvented th e apparent difficulty by bringing slight variations to the model. These changes turn out to be less innocuous than initially thought. The study proposes an alternative method to compute the parameters of the Pareto/NBD model with maximum likelihood. The method relies on the evaluation of a single one-dimensional integral. It is illustrated with two data sets that have been used in the literature. The procedure leads to the same parameter estimates as the previously published ones. It can be implemented in a spreadsheet.

The Analytic Hierarchy Process (AHP) is an often applied and well researched method in the area of multiattribute decision making. One of the main recurring tasks in AHP situations is the creation of pairwise comparison matrices, the examination of their consistencies, and the derivation of weights for the underlying objective functions.

The importance of controlling these consistencies and the consequences of subsequent adjustments of comparison matrices are sometimes unvalued issues in AHP applications. We conduct a simulation study to show that increasing inconsistencies caused by superimposed stochastic error-terms on consistent starting pairwise comparison AHP data result in decreasing correlations between the corresponding weights of the error-perturbed matrices and those of the consistent starting data and demonstrate that the weights derived from adjusted matrices do not show the improvements expected.

The paper shows how two dominant methodological approaches in quantitative marketing research of the last decades can be integrated. Combining the strengths of covariance structure analysis to control for measurement errors and the ability to predict choice behavior via the Multinomial Logit (MNL) model creates a powerful hybrid approach – the Integrated Choice and Latent variable (ICLV) model – for marketing research. We document the basic features of this approach and present an example which illustrates how the ICLV model can be used to explain travel mode choice. The hybrid modeling framework provides several advantages: (1) it gives a more realistic and comprehensive representation of the choice process taking place in the consumer’s “black box”; (2) it provides greater explanatory power; (3) it helps to remedy the biasing effect of neglecting important latent variables to explain choice behavior, thus allowing for a more accurate assessment of how marketing influences customers’ choice behavior.

The important key informant and common method problems in survey research are taken up in this article. The authors focus on the question how researchers can rely on multiinformant designs in order to limit the threats of key informant and common method bias on the validity and reliability of survey research. In particular, they show how researchers can effectively design studies that employ multiple informants and how multi-informant data can be aggregated in order to obtain more accurate results than can be obtained with single informant studies.

The author gives an overview of the state of research on aggregate market response modeling by means of multilayer perceptrons (MLPs), the most widespread type of artificial neural nets. As the author shows, MLPs are not limited to fixed parametric functional forms, but offer flexible approaches for modeling market response functions of marketing instruments.

In this paper, the authors propose a decision support for the strategic planning of the future powertrain and vehicle portfolio in the automotive industry. They use a hybrid market simulation approach for a simultaneous consideration of aggregated system and individual consumer behavior. This non-traditional simulation model allows for estimating the development of market shares of various powertrains in different vehicle size classes subject to the vehicle portfolio offered and to assumptions about consumer behavior and market environment.

In the present chapter, we briefly discuss how knowledge generation in marketing can be accomplished. In particular, we argue that generalizations offered by meta-analyses are very useful for managers in their decision making. To support this argument, we perform an empirical study on subjective estimations of price elasticities, advertising elasticities, and price promotion elasticities, showing that actual and future managers (i.e., master and PhD students) usually underestimate the effects of price changes, overestimate the impact of advertising, and heavily underestimate that of price promotions. We also demonstrate that subjective estimations improve after being confronted with the outcomes of meta-analyses.

Hierarchical models have become a workhorse tool in applied marketing research, particularly in the context of conjoint choice experiments. The industry has been pushing for ever more complex studies and 50+ random effects in a study are very common today. At the same time, respondent time and motivation is scarce as ever. Consequently, inference about high dimensional random effects critically depends on efficient pooling of information across respondents. In this paper we show how restrictions on the functional form of effects translate into more efficient pooling of information across respondents, compared to flexible functional forms achieved through categorical coding. We develop our argument contrasting the most restrictive functional form, i.e. linearity to categorical coding and then generalize to simple ordinal constraints. We close with suggestions on how to improve the pooling of information when definite functional form assumptions cannot be justified a priori, for example in studies that measure preferences over large sets of brands.

Data visualization aids have become popular tools to assist managerial decision making in marketing. For example, Geographical Information Systems (GIS) are often used to identify suitable retail locations, regional distributions for advertising campaigns, or targeting of direct marketing activities. GIS-based visualizations facilitate the assessment of store locations and help planners to select the most promising options. The selection of the best alternative requires a “visual optimization” which is typically supported by GIS–thematic maps. In an online experiment, we investigate the way how different GIS-based data representations influence marketing analysts’ decision making styles. Our results show that GIS-maps are a relevant part of the task environment and that the type of map visualization influences the activated decision processes. The invoked decision process is also shown to depend on the way symbol overload is handled by GIS-maps. We further find that analysts’ decision processes vary under time pressure and also relate to personal characteristics.

In this paper, the author emphasizes that sequences of discrete events and states researched in sociology and psychology are largely neglected in marketing research. Nonetheless, sequences are typical attributes of market behavior. Against this background, the author addresses the questions of which sequences could be of particular interest to marketing science and practice and how they could be researched empirically.

Knowledge about consumers’ preferences is of utmost importance for many marketing decisions, but transactional data are frequently unavailable. Therefore, marketing researchers have developed ground-breaking methods that build upon stated preference data to measure consumers’ preferences; these methods include self-explicated methods, ratingbased conjoint analysis, and choice-based conjoint analysis. This article describes DISE (Dynamic Intelligent Survey Engine), which aims to enhance research involving the measurement of consumer preferences. DISE is an extendable, web-based survey engine that supports the construction of technically sophisticated surveys and that limits the effort that researchers must invest to develop new preference methods. We discuss the overall architecture of DISE, discuss how to implement and include new data collection methods, and finally outline how these new methods can be employed in surveys, using an illustrative example. We conclude this article with an invitation to researchers to join in the development of DISE.

This study contributes to our understanding of different aspects of consumer behavior and its potential ties to economic crisis.

Compulsive buying has attracted the attention of several researchers in the consumer behavior domain dealing with both antecedents and consequences. However we know relatively little about whether and how compulsive buying is connected to the economic crisis. This event could magnify or change consumer tendencies and would allow us to tie attitudes to actual (or predicted) behavior. Our aim is to discover to develop a deeper understanding between the different dimensions of attitude toward money and financial trouble. Further we are interested whether compulsive buying would moderate this effect. We measure the dimensions of financial attitude on a scale developed by Yamauchi and Templer (1982) and use the Faber and Quinn scale (1992) for measuring compulsive buying.

Our research is based on a large scale empirical study that has been carried out in 2009 in Hungary. 1000 respondents, carrying one of housing, mortgage or personal loans, aged 18-59 created the sample. Hypothesis testing was done by structural equation modeling.

Eight distinct types of purchase behavior are distinguished in the model of the purchase cube proposed by the author, based on the purchase motives or reasons for buying underlying a purchase. One of the purchase types is repetitive purchase behavior, which is characteristic of functional purchases that are made deliberately rather than spontaneously and are relatively low in purchase involvement. This essay discusses the concept of repetitive purchase behavior and briefly reviews prior research that has investigated repetitive purchases from various perspectives.

In competitive markets, customer retention is in general more efficient than trying to attract new customers. Therefore, as a resulting outcome brand loyalty is regarded as a major strategic asset that has been investigated as an important source of equity. Most analyses, however, have been conducted in one specific product category only. The aspect of crosscategory related brand loyalty has been widely neglected so far. We concentrate on crosscategory relationships of national brands and on how customers’ brand choice decisions are related across several product categories. This knowledge is of relevance for retail managers and manufacturers who think of segment-specific promotion strategies that consider the customer segments’ loyalty patterns across categories. Our measure of brand loyalty is the Share of Category Requirements (SCR) to capture the relative share of category purchases that individual households give to each brand they buy, defined to be each brand’s market share among triers of the brand. We use the SCR measure as a behavioral and individualoriented measure. We use scanner panel and corresponding survey data. The scanner panel data contains households’ repeated FMCG purchase information of purchases in different kinds of store types within a limited geographic region. All the participating households were also asked to fill in a questionnaire on their values and attitudes. From an analysis of brand loyalty patterns different consumer segments result. An ex-post analysis based on general attitudes and other consumer characteristics reveals distinguishing factors between the consumer segments.

In this article we reanalyze the findings of an existing study on consumer-brand relationships conducted in Germany. Based on the data of more than nine hundred consumers and using advanced clustering methods, our study in principle supports the former findings indicating the existence of four generic types of consumer-brand relationships. These types are characterized as “best friendship,” “unemotional purpose-based relationship,” “loose contact,” and “happy partnership.” Furthermore, as the findings suggest, advanced methods of cluster analysis do not improve the solution provided by traditional clustering in each case.

The goal of many product positioning strategies is to create similarity perceptions with other products in the market. Product managers often seek to reach this goal by communicating the same information as competitors (e.g., highlighting the same product feature as an existing competitor product), which however, can also generate negative side effects (e.g., “me too” perceptions). This article introduces an alternative tactic aimed at overcoming such weaknesses, namely the communication of similar types of positioning bases as a means for creating similarity perceptions. To empirically test the value of this alternative, the study here uses an open sort task employing real products and advertisements. The study demonstrates that consumers classify products in terms of similarity based on their underlying positioning bases as anchored in advertisements. The study also shows that consumers do not use concrete positioning bases more often as a basis for classification than abstract positioning bases. These findings hold in three product categories which differ along several important characteristics, and point to the importance of selection of the type positioning basis. The study discusses implications and limitations of the study as well as avenues for future research.

This study reports the findings of two experiments involving location-aware mobile marketing messages (LA-MMM). It is intended to test whether real behavioral effects can be elicited through LA-MMM received at the point of sale. In the first experiment, participants received a LA-MMM while passing the store to which the message was related; in the second experiment, they received a LA-MMM while shopping in the store itself. The messages were of different types, containing a discount coupon, drawing attention to special offers or advertising specific brands of milk and chocolate.

The findings suggest that LA-MMM have only a limited influence on consumers’ approach behavior towards stores, store choice and buying behavior. LA-MMM are thus not nearly as influential on consumers as it has often been suggested. LA-MMM are by no means an effective way to increase sales of a particular brand in the short term and should only be used in conjunction with other marketing tools and promotions.

Consumers of repeat-purchase goods have a higher probability of choosing products that they have purchased in the past. This form of persistence or state dependence has emerged in scanner panel data for many product categories. Considering the existence of state dependence by firms is important for the better understanding of consumer purchase behavior and pricing. If state dependence is a function of loyalty, then firms may want to engage in strategic pricing to control the evolution of preferences. However, manufacturers and retailers have limited access to scanner panel data. In addition, scanner panel data are often not suitable for use in pricing decisions because they provide price information only for those items that a consumer has purchased in a particular store and on a certain day. In this paper, we will show how firms can use readily available store-level scanner data in combination with tracking data, which firms routinely collect, to estimate the impact of state dependence on consumer purchase behavior and determine the resulting effect on the pricing decisions of firms. We model demand using a flexible, random coefficient logit model for aggregated data that takes into account the heterogeneity of brand perceptions and customer responses to pricing and promotions. This model also accounts for the possibility that competing brands exhibit flexible substitution patterns. The results indicate that consumers may change their purchase behavior if they have recently purchased a particular brand. We then use the demand side estimates on the supply side to show how retailer pricing and profitability are affected if a retailer does or does not anticipate state dependence in predicting consumer purchase behavior.

In premium durable markets post-purchase contacts between customers and dealers are typically sparse, making each after sales contact a valuable opportunity to build-up and ensure customer satisfaction and loyalty. Customer loyalization becomes increasingly difficult due to extended service intervals and increasing price competition in basic technical support. The identification of cross-culturally mattering drivers of customer service satisfaction in after sales business is therefore an issue of increasing importance.

Based on a sophisticated customer survey differences of service quality perception and underlying triggers are analyzed. The study contrasts individualistic with collectivistic cultural contexts and empirically substantiates nonlinearity of satisfaction triggers in the case of premium durables. We show that individualistic and collectivistic backgrounds may reveal significant differences regarding important triggers of service satisfaction (e.g. explanation of work done), whereas brand sympathy over-proportionally triggers service satisfaction across cultures. The knowledge of internationally counting after sales service satisfaction triggers and nonlinearity of effects allows for optimizing global process standards, focusing the training of service personnel on aspects that really count, as well as planning of effective marketing activities.

Typically, in a specific category, a product or service can be defined not only by the brand it bears but also by multiple other attributes (e.g., pack size, price level, product formulation): a total of ten attributes for our example, detergents. While many papers have been devoted to brand loyalty, very few have been devoted to loyalty to other attributes: Is a household loyal to a certain pack size? To a certain price level? To a certain product formulation? These questions have important managerial implications in terms of the design and management of a brand’s product line. In this paper, we propose a systematic comparison of brand loyalty against loyalty to other attributes. We show that the two common measures of behavioural loyalty, share of category requirements and repeat rate, have problematic validity, due to the confounding influence of market share and purchase rate. In contrast, we argue that the Polarization index avoids these confounds and is therefore a better measure of loyalty. On the example of detergents, we show how to use Polarization to compare behavioural loyalty across attributes (e.g., are households more loyal to brands or to price levels?) and across different levels of one attribute (e.g., are consumers more loyal to high price levels than to low price levels?).

Marketing theory suggests market orientation as an effective strategy for achieving and maintaining competitive advantage (Kohli/Jaworski 1990; Narver/Slater 1990). Reviewing the literature, Jaworski et al. (2000) criticize most conceptualizations of the construct to be too narrow and to neglect a proactive understanding of shaping customers and/or the market. Against this background, we discuss two approaches to being market oriented: the first can be described as a ‘market driven’ and the second as a ‘market shaping’ approach. We develop new measures for the latter construct and empirically test its antecedents and consequences. Moreover, we examine moderator variables affecting the market shaping orientation-performance linkage, using a sample of 181 firms.

The present study contributes to our understanding of brand image formation in sport sponsorship. The authors propose that event image, event-sponsor fit and sponsorship exposure mediate the effect of interest in the sponsored event on sponsor image in two ways. First, high interest in the sponsored event increases perceived event image which in turn benefits sponsor image. Second, high event interest increases spectatorship of the event, and hence exposure to the sponsors of the event. High sponsorship exposure positively impacts on perceived event-sponsor fit and further on sponsor image. Empirical tests at two large televised sport events confirm the proposed hypotheses. Sponsorship managers and event organizers need to be cautious, however, that high levels of exposure can be a nuisance for spectators and might have a direct negative impact on perceived sponsor image.

In this “thought piece”, as a marketing academic, the author reflects on what truly matters in terms of research into marketing in this century. Based upon a careful scan of the “goings on” in the world, he first offers a configuration that may aid in research idea or specific topic generation and then culls out broad areas that are worthy of academic enquiry by marketers of this new millennium.

We show that market response uncertainty can be judiciously harnessed in determining the optimal advertising budget and spending pattern to improve the expected profitability of a firm. Using stochastic optimal control, we derive the optimal feedback advertising policy to accomplish this objective, and establish that the optimal advertising policy increases profitability at a rate directly proportional to the error variance.

Multiple sponsorships, which refer to sponsees that are sponsored by two or more brands, are gaining managerial relevance. Surprisingly, prior research has focused on single sponsorships, i.e., sponsees with only one sponsoring brand. This study is first to analyze image transfer effects within multiple sponsorships. Specifically, this research investigates image transfer effects (1) from the sponsee (e.g., FIFA World Cup) to the sponsoring brands and (2) between the sponsoring brands as well as the influence of the fit between the participating entities and brand familiarity on these transfer effects. The findings indicate that a familiar sponsoring brand primarily benefits from the sponsee, whereas an unfamiliar sponsoring brand mainly benefits from a connection with a familiar sponsoring brand.

Money-back guarantees (MBGs) and low-price guarantees (LPGs) are frequently implemented in retailing practice to positively influence consumer behavior. In this literature review 28 MBG and 30 LPG studies are systemized and discussed. While both a behavioral and an economic research stream exist, the focus of this review is on the effects of MBGs and LPGs on consumer behavior. Furthermore, this literature review provides some avenues for future MBG and LPG research and offers implications for retailing practice.

The heritage aspect is a crucial part of a luxury brand as it has to appear both perfectly modern to the society of the day and at the same time laden with history. Heritage adds the association of depth, authenticity and credibility to the brand’s perceived value and can result in an intensified brand loyalty and the willingness to accept higher prices. Incorporating relevant theoretical and empirical findings, the aim of the present study is to examine the antecedents and outcomes of luxury value and brand heritage as perceived by consumers and effects resulting on brand strength. Based on a structural modeling approach, results reveal the most important effects of the perceived luxury and heritage of a brand on consumer perceived value in terms of the customer’s economic, functional, affective, and social evaluation of a brand and its related effects on the affective, cognitive and intentional brand strength.

The goal of this study was to investigate how students at the Center for Business Studies at the University of Vienna and the Vienna University of Economics and Business differ with respect to their personality traits and their expectations of their respective universities. To this aim, 816 students at the University of Vienna and the Vienna University of Economics and Business were surveyed using face-to-face interviews. Results indicate that students at the two institutions differ in a variety of ways. Students at the University of Vienna evaluate broad course offerings, support services by lecturers, and a good climate between students as being more important than do students at Vienna University of Economics and Business. Respondents in the two samples also differ with respect to their self-assessed verbal and quantitative skills. The implications of these results are discussed and findings are compared with those of an earlier study investigating students at the two universities.