Customer equity, the asset value of customers, can be measured using different aggregate- and disaggregate-level approaches. The authors compare how customer equity is measured and maximized under various approaches. We find that, in the disaggregate-level approach, customer lifetime value is maximized by implementing customer-level strategies such as optimal resource allocation, purchase sequence analysis and balancing acquisition and retention spending. At the aggregate-level, improving the drivers of customer equity maximizes customer equity. A comparison of different aggregate approaches shows that, while an emphasis on retention is a common feature across approaches, conceptual differences in terms of accounting for existing customers and prospects, acquisition, and the projection period exist across the different approaches. The authors propose a hybrid approach, which addresses the issues and challenges in existing approaches and helps firms to measure and manage customer equity.

It is becoming increasingly apparent from the literature that marketers need to consider customer-level information when they generate a marketing strategy for the firm. In this article, the authors develop a customerfocused framework that uses a marketing strategy with an overall objective of maximized financial performance. This strategy is driven by seven customer-level marketing tactics and shows how actual customer data can be used to generate an actionable marketing strategy leading to optimal levels of profitability, customer equity, and shareholder value. In addition, the authors discuss a successful implementation of this strategy for several business-to-business and business-to-consumer firms and offer insights as to how to customize an implementation strategy for any firm, along with presenting potential challenges a firm may encounter during the implementation process. Several suggestions for future research are offered to explore and harness this newly available evidence.

This study focuses on the short-term sales response to price promotions in retail grocery stores and attempts to explain its variation using frequency of price promotions and the consecutive scheduling of price promotions. Retail managers' expectations and tenets from behavioral theories provide the basis for the hypotheses that the frequency of price promotions and consecutive scheduling of price promotions affect short-term response to price promotions. The hypotheses are tested on three frequently purchased product categories, using store-level data from retail chains in three major markets. The analysis is validated with additional data on the same product categories and markets. A variety of managerial implications are drawn from the results and suggestions for future research are offered.

This study tests and contrasts the ability of multidimensional scaling (MDS) and nonlinear mapping (NLM) in recovering complex data structures in attribute space, and aiding researchers and practitioners in making neighborhood interpretations. The relative merits of both MDS and NLM for product positioning are explored and discussed. A formal comparison of the performance of NLM versus MDS is presented using both simulated and actual data. The results of this study provid3e direction as to the conditions under which a nonlinear mapping algorithm is preferable over MDS.

This study attempts to build a decision model to evaluate job alternatives for doctorial students. The decision model is based on the Von Neumann-Morgenstern utility function. In this case of uncertainty, the utility function can order only preferences. In the case of certainty, the measurable value function can order both preferences as well as preference differences. The utility function is tested for the presence of the strength of preference concept using the theorem of "Substitution of Equal Exchange." A methodology has also been proposed to obtain responses to the utility function and then transforming that function to a measurable value function. The importance of the concept of ordering preference differences and incorporating risk measure is revealed by the superiority of the measurable value function over the utility function in terms of predictive validity.

To compete effectively in the global marketplace, marketing managers require insight into how a product gets adopted in different countries. For example, can international marketers identify specific cultural traits that may help them to forecast how quickly a new product will be adopted in a particular country or in a group of somehow related countries? Similarly, can they identify factors that suggest why the adoption process differs among countries? Although these diffusion-related questions address critical issues for international marketing managers, only a few studies have explored cross-national diffusion. To help fill this gap, V. Kumar, Jaishankar Ganesh, and Raj Echambadi present the results of a study that replicates and extends the findings of three previously published studies of cross-national diffusion. Their research aims to replicate four findings from the previous studies: the role of country-specific effects in explaining differences in diffusion parameters, the presence of a lead-lag effect, the use of cultural variables to explain systematically the diffusion patterns across countries, and the merit of country segmentation schemes based on diffusion parameters. They extend the previous research by integrating cross-sectional and time lag variables into a single framework, and they demonstrate how managers can apply this integrated framework for forecasting the diffusion of new products. They replicate the findings from the previous studies by using annual sales data for five product categories (VCRs, microwave ovens, cellular phones, home computers, and CD players) in the following countries: Austria, Belgium, Denmark, Finland, France, Germany, Italy, The Netherlands, Norway, Portugal, Spain, Sweden, Switzerland, and the UK. The product categories and time periods covered differ from the ones in the previous studies; some overlap exists among the countries in this study and the ones in the previous studies. The findings in this study suggest that country-specific characteristics (for example, cosmopolitanism, mobility, percentage of women in the labor force) are useful for identifying the differences in diffusion patterns across countries and innovations. This study also suggests that the lead-lag effect helps to explain differences in diffusion across countries. Factors that this study identifies as possibly influencing the clustering of countries with similar diffusion patterns include timing of entry, geographical proximity, and cultural or economic similarity.

Recent studies on cross-national diffusion have observed that when a new product innovation is introduced early in one country (the lead country) and with a time subsequent countries (the lag countries); the consumers are the lag countries learn about the product from the lead country adopters, resulting in a faster diffusion rate in lag countries. This study attempts to examine the relationship between lead and lag countries and to systematically capture the learning effect that takes place between the two social systems. In particular, this research examines the diffusion of retail point-of-sale scanners in countries that belong to the European Union, the Unites States, and Japan. It offers interesting insights for formulating efficient international marketing strategies.