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Grocery retailers have access to detailed data on consumer purchases within their own chains. Previous research has used across-chain scanner panel data to develop optimal price cuts targeted to individual households but whether such a targeting strategy will work with only within-chain data is unknown. The purpose of this research is to address this specific question.

The authors use scanner panel data from multiple categories to create across-chain and within-chain purchase histories for the same consumers. They then estimate models of purchase decisions on the two datasets and compare their performance.

Within-chain data fares significantly worse on both fit and prediction criteria. Retailers' upside to customizing is minimal compared to those reported for manufacturers. Finally, customized prices based on the within-chain model significantly underperform the promise of across-chain data.

Store choice is not modelled. Research also needs to be replicated in other contexts. The authors conclude that limited purchase histories may not yield accurate enough estimates of marketing mix responsiveness, and that across-chain purchase histories are essential for effective targeted price cuts.

Loyalty card data may be useful for other purposes, like experimenting with segment-specific discounts, but its value in customizing prices at individual level is limited without adding other sources of information.

Previous research on price customization has been based almost exclusively on across-store data. However, retailers only have access to their own chain-specific data. This is the first study to comprehensively compare price customization based on within- and across-chain purchase data and show that the upside potential for price customization based on the former information set is quite limited.

The purpose of this paper is to describe the development of a scale (SITUZAP) to measure the situational factors that trigger channel switching, specifically within the television environment.

The domain construct is defined and 14 potential scale items were drawn from the literature and qualitative research. The scale was purified during the pilot phase and three scale items removed. The scale was re‐tested during the main study via an independent sample, confirming the two‐dimensional nature of the scale.

Reliability analysis indicates that the scale is internally consistent with co‐efficient alpha high across both pilot and main studies. Moreover, confirmatory factor analysis supports the two‐factor measurement model – “advertising triggers” and “RCD empowerment”. The test‐retest result (r=0.662) further provides evidence of stability within the scale. The scale has also been verified for content, criterion, discriminant, and nomological validity. All other indicators are within the acceptable range of statistics.

This is the first scale that measures the effect of situational factors on channel switching.

The automobile industry is a key contributor to the GDP in most developed countries. Whilst studies have mainly focused on new car markets, this research aims to investigate how consumers' socio-demographic profile impacts on the decision to buy used or new cars across different automobile segments.

The study focuses on a major car market in Europe, France. The data were obtained from the French Institute of Statistics (INSEE), consisting of a representative sample of 1,967 French households who bought a new or used car within a year of this study. The paper is based on random utility theory and applies multinomial logit modeling.

The findings suggest that economic, individual, household characteristics impact on car segment choice, as well as the decision of whether to buy a new or a used car.

This is one of the few studies investigating the demand for new and used cars in conjunction across car segments in a European context. It provides important insights into consumer choice in a mature market.

UK supermarkets need to be able to assess the current efficacy of the budget they allocate to promotional activities aimed at boosting sales. Therefore, the main objective of this article is to investigate consumer response to the four different promotional deals most commonly used in UK supermarkets: coupons, price discounts, samples and “buy‐one‐get‐one‐free”. Multi discriminant analysis was used on a study of 160 respondents to analyse whether there was an association between the four consumer promotional approaches and respondents’ reported buying behaviour. The findings indicate that only price discount promotions proved to be statistically significant on consumer’s reported buying behaviour. Purchase acceleration and product trial are found to be the two most influential variables related to a discount. For “buy‐one‐get‐one‐free”, while the result is not significant, the two variables, brand switching and purchase acceleration are statistically significant.

The main objective of this study is to identify the determinants of TV ads avoiding behavior between light and heavy avoiders in greater Cairo. To achieve the study objective, five hypotheses have been developed and tested by such statistical techniques as discriminant analysis, t‐tests, MannWhitney tests, and Chi Square tests. A questionnaire has been designed to collect data from a systematic random sample of adults in social clubs and shopping centers in greater Cairo. The number of usable questionnaires in data analysis was 364. The study findings show that all respondents except 3 were doing one or more of TV ads avoiding behavior. Cognitive avoiding represents the most frequently used avoiding behavior by light and heavy TV ads avoiders. The results also demonstrate that perceptions, attitudes toward advertising, and some motives were determinants of TV ads avoiding behavior. On the other hand, it was found that all demographic and socioeconomic characteristics, except types of channels, were not determinants of TV ads avoiding behavior between light and heavy TV ads avoiders. The study concludes with a number of academic and practical recommendations.

The purpose of this study is to understand how young consumers engage in the multi-category context. To that end, engagement on the focal product (dating platforms) and the other product (matrimony platforms) were studied. The objective is to find an answer to the following research question: Why do consumers tend to engage more with the focal product, yet are likely to purchase its complement or substitute?

Semi-structured depth interviews and Straussian grounded theory method were used to collect, analyze and interpret the data.

Self-determination theory provides an answer to the research question. This study suggests: young consumers experience different levels of need fulfilment when they evaluate the focal product in the single-category and in the multi-category contexts; young consumers’ motivational orientation (controlled motivation, autonomous motivation and intrinsic motivation) results into high-level behavior and engagement (pleasure-seeking, platform abandonment, goal-oriented pleasure-seeking, goal-oriented problem-solving, anxious and outsourcing) with the focal product and the other product.

Value of the paper lies in developing a grounded theory framework for engagement in the multi-category context. This study can help practitioners in making important business decisions, especially in the dating and matrimony e-business categories.

Considers the past, present and future of marketing. Whimsically but not without seriousness, concludes that marketing faces something of a Y2K problem. Indeed, as the next millennium begins, concludes that, though the marketing concept may survive, the marketing function itself is dead. Nonetheless, cautions against the concomitant extermination of marketing scholars.

This paper aims to study the consequences of listing national brands in discounters. Is the discount channel a promising outlet for manufacturer brands? Is it an effective means to attract new buyers? Which combination of brand and discount destination at which price is best suited for this strategic move?

Based on a unique dataset (tracking grocery purchase behavior for a representative sample of German households) and employing both descriptive and multivariate statistical techniques, the authors examine the outcome for 134 national brands introduced in six discount chains in Germany between January 2003 and July 2004.

Both the manufacturer and discounter are able to grow their total performance in excess of the market following the introduction for the majority of the brands. Hence, potential cannibalization is more than offset by incremental revenues. It is found that, on average, close to 80 per cent of national brands' sales at a discounter is from new brand buyers. Discounters typically benefit less, as only 29 percent of brand sales are from new category buyers at their store.

Including manufacturer brands into a discount assortment will benefit both the manufacturers and the discounters. Examination of the substantial cross‐brand differences reveals that manufacturers and discounters attract more new customers with brands for which market penetration is still modest. Also, discounters gain more from adding branded offerings in underperforming categories, and benefit from brands that enjoy higher customer loyalty. Finally, national‐brand prices should be set carefully at discounters. It is advised to maintain their price premium even at a discounter.

Discounters are the fastest growing grocery format in Europe. Lately, many discounters add national brands to their private‐label dominated assortment, a move widely discussed in media with substantial implications for grocery channel management. This study provides a comprehensive evaluation of that trend.

The purpose of this paper is to incorporate explicitly consumer heterogeneity into market response models estimated with store‐level scanner‐data.

Latent structures in market response to a product category using aggregated scanner data registered by a supermarket are identified. Specifically, latent consumer segments with diverse preferences towards brands and different responses to marketing stimuli from data consisting of daily marketing actions (i.e. price, promotions, advertising, etc.) and sales of competing brands are identified.

The existence of different latent segments with diverse preferences and response patterns to marketing stimuli were detected. More specifically, the fit of the statistical analysis for the different model possibilities made it possible to identify four market segments. It was also found that the intrinsic brand attractiveness as a measure of consumer brand preference is different between segments. Finally, the price sensitivity is also different between segments.

The time cost necessary to obtain the parameter estimates is too high, which is usual in the models estimated with iterative EM algorithms.

This work deepens one's knowledge of the identification and selection of latent market structures, specifically latent segments with different purchase patterns and behaviours. The possibility of developing the analysis with aggregated data at the store level increases the potential utility for academics and marketing managers.

Although most applications use weekly data, this proposal models daily fluctuations in sales – as a result, making it possible to obtain consumer segments based on daily changes.

This chapter integrates research that highlights and demonstrates the importance of the marketing mix and customer attitudinal metrics in influencing the customer’s path to purchase. A key objective of this chapter is the provision of an integrative conceptual framework that links marketing actions to customer mindset metrics along the consumer’s path to purchase and the identification of the mechanisms by which customer mindset metrics contribute to consumer purchase journey. Specifically, it delineates two routes for the effects to manifest on sales: the “mindset route” where marketing actions influence customer mindset metrics, which in turn influence brand performance, or the “transactions route” where marketing actions influence market performance directly without influencing the intermediate mindset metrics. A second objective is to identify empirical patterns on incorporating marketing mix and mindset metrics along the path to purchase by reviewing key papers in this domain. Finally, the chapter concludes with the formulation of a rich, forward-looking research agenda on the customer mindset metrics – path to purchase link.