Customer-Based Valuation

Customer lifetime value (CLV) has emerged as an important metric to manage and grow customers. Marketing scholars have written many books and articles on this topic. However, most of this research has focused on tactical marketing decisions. While this is important, it is not enough to gain attention of senior managers who are concerned about firm level metrics such as stock price. To have greater impact marketing needs to go beyond brand-level profits to show the impact of marketing actions on firm profitability. In this paper we focus on customer lifetime value and its link to firm value. We discuss research that provides customer-based valuation of firms and suggest directions for future research.     

Organizational energy: an empirical study in Indian R&D laboratories

Analyzing the way organizations function and the processes that operate within these organizations is an important managerial responsibility. We have adopted a people–oriented approach called organizational energy to develop a simple process for diagnosing the level of satisfaction of scientists working in R&D laboratories. Psychic energy as reflected in different work activities in an organization is manifested in energy generating and energy draining activities that can be reduced to an energy count. The present study assesses the use of mental energy by scientific personnel working in three national laboratories in India with the objective of increasing the energy count for improving organizational effectiveness. We hope that the results can be used as the basis for initiating action to improve the motivation and utilization of scientists in India, to support the overall goal of self–reliance in science and technology.     

Issues in the estimation and application of latent structure models of choice

Our paper provides a brief review and summary of issues and advances in the use of latent structure and other finite mixture models in the analysis of choice data. Focus is directed to three primary areas: (1) estimation and computational issues, (2) specification and interpretation issues, and (3) future research issues. We comment on what latent structure models have promised, what has been, to date, delivered, and what we should look forward to in the future.     

Oil and stock market activity when prices go up and down: the case of the oil and gas industry

We examine the asymmetric effects of daily oil price changes on equity returns, market betas, oil betas, return variances, and trading volumes for the US oil and gas industry. The responses of stock returns associated with negative changes in oil prices are higher than that associated with positive changes in oil prices. Stock risk measured by market beta is influenced more due to oil price decreases than due to oil price increases. On the other hand, oil risk exposures (oil betas) and return variances are more influenced by oil price increases than oil price decreases. The results of our study indicate that oil and gas firm returns, market betas, oil betas, return variances respond asymmetrically to oil price changes. We also find that relative changes in oil prices along with firm-specific factors such as firm size, ROA, leverage, market-to-book ratio (MBR) are important in determining the effects of oil price changes on oil and gas firms’ returns, risks, and trading volumes.     

Leveraging Information Across Categories

Companies are collecting increasing amounts of information about their customers. This effort is based on the assumption that more information is better and that this information can be leveraged to predict customers' behavior in a variety of situations and product categories. For example, information about a customer's purchase behavior in one category can be helpful in predicting his potential behavior in a related category, which in turn could help a firm in its cross-selling efforts. In this paper, we present a model to better understand and predict a consumer's purchases and preferences when we may have limited or no information about him in one or more product categories. Conceptually this involves leveraging information from purchases of other consumers in multiple categories as well as partial information (e.g., purchase in one of the categories) of the target consumer. Our approach builds on the pioneering work of (Rossi et al. (1996)) who demonstrate the value of purchase information in the context of a single product category. We present results from an extensive simulation as well as an application on scanner panel data. Our simulation shows many interesting and somewhat surprising results. Specifically, we find that compared to a single-category analysis, a cross-category analysis does not lead to any significant improvement in data likelihood in most cases. Therefore, the single-category analysis of (Rossi et al. (1996)) is even more powerful than previously thought. However, we also find that a cross-category analysis does improve parameter recovery in many situations as compared to a single-category analysis. It is in these conditions that retailers can use cross-category information to better implement micro marketing programs. We demonstrate the transfer of information across categories in an application of two grocery products—Breakfast Foods and Table Syrup. In spite of a reasonable correlation (0.21) in the price parameter across these two categories, our simulation guidelines predict very little benefit of cross-category analysis over single-category analysis. Our empirical results confirm this prediction.     

Investigating the recall inhibition effect: A test of practical considerations

Alba and Chattopadhyay (1985, 1986) have demonstrated that having consumers think about a familiar brand can interfere with the retrieval of competitive brand names, including those that might otherwise be considered for purchase. However, their research is silent about two issues of pragmatic importance. First, is it possible to inhibit retrieval of the consumer's preferred brand? Second, can an unfamiliar brand evoke recall inhibition? Our findings indicate that recall inhibition does not extend to the preferred brand. Our findings further suggest that recall inhibition can be induced by cueing consumers with an unfamiliar brand name, but that such inhibition is less pervasive than evoked by a highly familiar brand name.     

DYNAMIC OUTPUT RESPONSE REVISITED: THE INDIAN CASH CROPS

Diverse instruments have been used to encourage developing agriculture. In the process, billions of dollars have been spent on providing incentives to peasants. Given scarce resources, an important concern has been the issue of what policy instruments to emphasize. In this regard, useful policy information can be gleaned from the role of expected profits (revenue and input prices), assets (irrigation and infrastructure), and relevant risks, in evoking peasant response. Using panel data for the period 1967/1968 to 1999/2000 pertaining to seven major Indian cash crops cultivated across 14 major states, we find strong evidence of a differential producer response in the post‐liberalization phase, although the important variables per se are much the same. Our results suggest that the preferred policy ought to emphasize availability of irrigation, affordable fertilizer, and rural infrastructure, rather than incessant increases in output prices.     

Employee service abandonment in offshore operations: A case study of a US multinational in India

Indian Business Process Outsourcing (BPO) exports industry has witnessed an exponential growth over the last few years. This has been accompanied by a shortage of talented skilled workers to serve the BPO sector. Attracting and retaining talented employees has become the chief challenge of HR departments in the BPO industry. This study examines the demographic antecedents of job abandonment among call centre employees in India using a large firm level data. The theoretical and practical implications of the findings are discussed.