Chain-store pricing and the structure of retail markets

This paper investigates competition between chain-stores and independents in the UK opticians' industry, using the relationship between the number of outlets present in a local market and the market size. Chain-stores are shown to have a significant effect on local market competition. In addition, the empirical approach is extended to allow inferences on the nature and extent of product differentiation. The results are broadly consistent with a model of vertical product differentiation in which chain-stores adopt national pricing strategies. The evidence suggests that the nature of competition between independent retailers depends on whether a chain-store is present.

A comparison of sales response predictions from demand models applied to store-level versus panel data

In order to generate sales promotion response predictions, marketing analysts estimate demand models using either disaggregated (consumer-level) or aggregated (store-level) scanner data. Comparison of predictions from these demand models is complicated by the fact that models may accommodate different forms of consumer heterogeneity depending on the level of data aggregation. This study shows via simulation that demand models with various heterogeneity specifications do not produce more accurate sales response predictions than a homogeneous demand model applied to store-level data, with one major exception: a random coefficients model designed to capture within-store heterogeneity using store-level data produced significantly more accurate sales response predictions (as well as better fit) compared to other model specifications. An empirical application to the paper towel product category adds additional insights. This article has supplementary material online.

Drawing association rules between purchases and in-store behavior:an extension of the market basket analysis

Shopping behavior is often exclusively studied through consumer purchases, since they are an easily measurable ouput. Still, the observation of in-store physical behavior (paths, moves and actions) is crucial, as is the quantification of its impact on purchases. Using an innovative PDA tool to precisely record and time stamp consumer’s moves and gestures, we extend the classical Market Basket Analysis (MBA) by integrating this new kind of information. We draw associations not only from purchases but also from in-store consumer moves and actions. We compare results of our new method with classical MBA results and show a significant improvement.

Exploring the link between In-store physical shopping behavior and purchases

Only little research investigates the relationship between consumer purchases and in-store physical shopping behavior, largely because of the difficulty involved with reconciling a precise observation of in-store behavior with a robust statistical analyses of the data. Using an innovative data collection method, this article determines that physical shopping behavior manifests itself along two main dimensions: shopping width (behavioral scope throughout the store) and shopping depth (specific store elements). Both dimensions have strong impacts on purchases: the former tends to influence the number of items bought, and the latter affects the price of purchased items, depending on the product category.

Drawing association rules between purchases and in-store behaviour:an extension of the market basket analysis

Shopping behavior is often exclusively studied through consumer purchases, since they are an easily measurable ouput. Still, the observation of in-store physical behavior (path, moves and actions) is crucial, as is the quantification of its impact on purchases. Using an innovative PDA tool to precisely record and time stamp consumers' moves and actions, we extend the classical Market Basket Analysis (MBA) by integrating this new information: associations between product categories are measured not only from purchases but also from consumer physical behavior. We compare results of our new method with classical MBA results and show a significant improvement.

Leadership propensity and sales performance among sales personnel and managers in a speciality retail store setting

We propose that specialty store managers, as well as outside sales personnel attached to the store, have selling responsibilities. In addition, we propose that sales personnel, as well as store managers, should have a propensity for leadership, which reflects an individual's enduring disposition to exhibit leadership within the context of his or her organizational roles. In two studies, we develop a new individual difference measure of propensity to lead and investigate its nomological validity within a specialty retail store environment. As predicted, leadership propensity was predictive of self-rated sales performance and a proclivity to identify prospects through cold calls to close sales, to reveal customer orientation, and to exhibit organizational citizenship behavior. We found that propensity to lead did not differ between salespeople and retail store managers, but we found that the respondent's role moderated the relationship between propensity to lead and supervisor performance ratings. Study limitations and managerial implications of this heretofore unidentified trait of salespeople are discussed.

Estimating the SCAN*PRO model of store sales: HB, FM or just OLS?

In this paper we investigate whether consideration of store-level heterogeneity in marketing mix effects improves the accuracy of the marketing mix elasticities, fit, and forecasting accuracy of the widely-applied SCAN*PRO model of store sales. Models with continuous and discrete representations of heterogeneity, estimated using hierarchical Bayes (HB) and finite mixture (FM) techniques, respectively, are empirically compared to the original model, which does not account for store-level heterogeneity in marketing mix effects, and is estimated using ordinary least squares (OLS). The empirical comparisons are conducted in two contexts: Dutch store-level scanner data for the shampoo product category, and an extensive simulation experiment. The simulation investigates how between- and within-segment variance in marketing mix effects, error variance, the number of weeks of data, and the number of stores impact the accuracy of marketing mix elasticities, model fit, and forecasting accuracy. Contrary to expectations, accommodating store-level heterogeneity does not improve the accuracy of marketing mix elasticities relative to the homogeneous SCAN*PRO model, suggesting that little may be lost by employing the original homogeneous SCAN*PRO model estimated using ordinary least squares. Improvements in fit and forecasting accuracy are also fairly modest. We pursue an explanation for this result since research in other contexts has shown clear advantages from assuming some type of heterogeneity in market response models. In an Afterthought section, we comment on the controversial nature of our result, distinguishing factors inherent to household-level data and associated models vs. general store-level data and associated models vs. the unique SCAN*PRO model specification.

Evaluation of a heating system using a heat pump and heat store

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Chain-store pricing and the structure of retail markets

This paper examines competition between chain-stores and independent retailers in the UK retail opticians' market. We demonstrate that the pricing policy adopted by chain-stores can determine the impact their entry has on independent retailers. Crucially, in this market the chain-store retailers set an identical national price across all local markets. Our results suggest that this pricing strategy lessens the detrimental effect competition from chain-stores has on independent retailers. © 2014 Springer Science+Business Media New York.

Making SENS:exploring the antecedents and impact of store environmental stewardship climate

Retailers increasingly recognize that environmental responsibility is a strategic imperative. However, little research has investigated or identified the factors that facilitate the successful implementation of environmentally responsible strategies across a network of customer-facing sales units (stores). We propose that a store manager’s ability to lead by example facilitates this process by fostering a supportive climate for store environmental stewardship (SENS-climate). By examining the influence of store managers’ actions on sales associates’ perceptions of the SENS-climate, as well as the subsequent impact on their performance—measured by margins, as well as sales of green and regular products—this study demonstrates that store managers can foster a SENS-climate by articulating their prioritization of environmental responsibility in their operational decisions. These positive effects are sustained by relational factors, such as the moderating effect of the store manager–sales associate dyadic tenure. In contrast, when store managers display high variability in their environmental orientation, it hinders the development of SENS-climate perceptions among sales associates. If sales associates perceive an enabling SENS-climate, they achieve higher margins and more green but fewer regular sales.