Robert P. Leone

Psychological Implications of Customer Participation in Co-Production

Customer participation in the production of goods and services appears to be growing. The marketing literature has largely focused on the economic implications of this trend and has not addressed customers’ potential psychological responses to participation. The authors draw on the social psychological literature on the self-serving bias and conduct two studies to examine the effects of participation on customer satisfaction. Study 1 shows that consistent with the self-serving bias, given an identical outcome, customer satisfaction with a firm differs depending on whether a customer participates in production. Study 2 shows that providing customers a choice in whether to participate mitigates the self-serving bias when the outcome is worse than expected. The authors present theoretical and practical implications and provide directions for further research.

Linking Brand Equity to Customer Equity

Customer equity and brand equity are two of the most important topics to academic researchers and practitioners. As part of the 2005 Thought Leaders Conference held at the University of Connecticut, the authors were asked to review what was known and not known about the relationship between brand equity and customer equity. During their discussions, it became clear that whereas two distinct research streams have emerged and there are distinct differences, the concepts are also highly related. It also became clear that whereas the focus of both brand equity and customer equity research has been on the end consumer, there is a need for research to understand the intermediary’s perspective (e.g., the value of the brand to the retailer and the value of a customer to a retailer) and the consumer’s perspective (e.g., the value of the brand versus the value of the retailer). This article represents general conclusions from the authors’ discussion and suggests a modeling approach that could be used to investigate linkages between brand equity and customer equity as well as a modeling approach to determine the value of the manufacturer to a retailer.

A Dynamic Model of Purchase Timing with Application to Direct Marketing

Abstract Predicting changes in individual customer behavior is an important element for success in any direct marketing activity. In this article we develop a hierarchical Bayes model of customer interpurchase times based on the generalized gamma distribution. The model allows for both cross-sectional and temporal heterogeneity, with the latter introduced through the component mixture model dependent on lagged covariates. The model is applied to personal investment data to predict when and if a specific customer will likely increase time between purchases. This prediction can be used managerially as a signal for the firm to use some type of intervention to keep that customer.

Market Structure Analysis: Hierarchical Clustering of Products Based on Substitution-in-Use

In this paper, product usage data, employing a substitution-in-use criterion, are analyzed and shown to yield managerially useful product-market structures for financial services. These structures ...

Coupon face value: Its impact on coupon redemptions, brand sales, and brand profitability☆☆☆

Abstract Although much research has examined the impact of coupons on redemption rates, incremental sales, and market share, only a few studies have addressed the impact of coupons on brand profitability. One possible reason is lack of readily available profitability data. In the absence of such data, researchers have used managerial judgments (Neslin and Shoemaker, 1983) and experiments (Chapman, 1986) to investigate the profitability of coupons. We propose an integrative framework for evaluating the impact of coupon face value on brand profitability and implement it by using readily available scanner data. The research reveals that when a manufacturer optimizes the market-level profitability from a coupon program, profit for individual chains in the market could be suboptimal.

Variability of brand price elasticities across retail stores: Ethnic, income, and brand determinants

Abstract Retail pricing decisions are often made with respect to the price sensitivity of shoppers in a retail store or market area. This paper explores how certain brand and consumer characteristics relate to the variability of brand price elasticities across stores belonging to the same chain. The authors measure the price sensitivity of 14 liquor brands sold in 35 store locations. Since the stores operate in a monopoly environment, the analysis is free from the confounds caused by competitive pricing or promotional activity that often hamper retail pricing studies. Also, the monopoly situation provides data that represent a census of brand sales in the categories studied. Results of a two-stage econometric analysis show that brand price elasticity is higher for brands that are promoted more frequently and for brands that have higher market shares. The magnitude of brand price elasticity is also found to be directly related to the household income in a market area and inversely related to the proportion of residents in a market area who are African-American.

Aggregate and disaggregate sector forecasting using consumer confidence measures

Abstract The usefulness of the combination of Katonas “ability and willingness to buy” framework and Bayesian vector autoregression for business forecasting was examined. Models were estimated with and without a measure of consumer confidence and with either a vector autoregression model with lag structure determined by a stepwise (VAR) or a Bayesian (BVAR) approach. Additionally, Katonas framework was tested at different levels of aggregation of consumer expenditures. Unlike in past research, monthly data were used in the operationalization of the framework. It was found that the BVAR, along with the consumer confidence measure, performed the best across three forecasting horizons and three performance measures. Any degradation of model performance at lower levels of aggregation across expenditure categories was only modest. The findings suggest that the use of BVAR, with consumer confidence index as a predictor should be considered in business forecasting.

Retail promotional advertising: Do the number of deal items and size of deal discounts affect store performance?

Abstract Retailers use advertised price promotions to attract customers and stimulate store traffic and sales. While several studies have investigated the efficacy of individual-brand promotions, little empirical research has investigated the ways in which store-level promotion strategies influence retail performance. This article reports on a natural experiment involving a change in a grocery stores promotion strategy from featuring many items at small discounts, to a few items at deep discounts. Results of a time series intervention analysis indicate that such a change in strategy led to an increase in chain-level sales dollars but did not affect customer traffic.

Forecasting the effect of an environmental change on market performance: An intervention time-series approach

Abstract Forecasting the effects of changes in advertising or pricing strategies on a companys sales or market share is an important task faced by marketing managers. This paper applies a time series approach, intervention analysis, to several marketing policy applications illustrating the flexibility and value of the method for testing hypotheses and providing forecasts. Empirical evidence is presented for two different marketing situations, one that involves a change in advertising and another that involves offering price specials.

Economic Trends and Being Trendy: The Influence of Consumer Confidence on Retail Fashion Sales

Consumers who make early purchases of fashion apparel often pay a premium for being the first to wear the new styles. These consumers are often characterized as being relatively less price sensitive and more affluent than those who make their purchases later in the selling season. In this study we show that the sales of fashion apparel early in the season are substantially influenced by the confidence consumers have about the future state of the economy. Monthly sales data from five divisions of a Fortune 500 retailer are pooled together in a hierarchical Bayes model to produce estimates of the influence of consumer confidence and purchasing ability. These variables are shown to have a differential pre-season and in-season effect on sales, with confidence being a stronger predictor of pre-season sales and ability a stronger predictor of in-season sales. This result indicates that, when developing marketing plans, retailers need to be aware of the fact that fashion-forward consumers who purchase apparel ea...