Prospects and problems in modeling group decisions

This paper summarizes some of the major issues related to group decision modeling. We briefly review the existing work on group choice models in marketing and consumer research. We draw some generalizations about which models work well when and use those generalizations to provide guidelines for future research.     

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.     

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.     

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.     

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.     

Customer query handling in sales interactions

Using a novel approach with video-recordings of sales interactions, this study focuses on a dynamic analysis of salesperson effectiveness in handling customer queries. We conceptualize salesperson behaviors, namely, resolving, relating, and emoting, as separate elements of customer query handling and empirically identify the distinct verbal and nonverbal cues that salespeople use to display these behaviors during sales interactions. We draw from compensation effects in social cognition theory to propose that customers’ perceptions of a salesperson’s effectiveness are prone to trade-offs between competence (resolving behaviors) and warmth (relating and emoting behaviors). Results, robust to endogeneity corrections, support the proposed tradeoffs such that the effectiveness of salesperson’s resolving behavior is significantly curtailed, even neutralized, by the salesperson’s relating and emoting behaviors. We situate these counterintuitive results within the extant theory and research on sales interactions, and outline implications for practice.     

Supplier evaluation in the context of circular economy: A forward step for resilient business and environment concern

Resource depletion is a concern for the global economy; many think that available resources on the planet will not be able to cater to an ever-growing population. Thus, economies are trying to become circular, leaving behind the linear tradition linear approach. In the circular economy (CE), physical resources and energy are made to loop back into the supply chain (SC) for a more extended period. Proper selection of suppliers is an essential criterion towards proper execution of the CE principle in SC. In this research, we have constructed a framework for evaluating the supplier concerning the CE implementation. Further, this research identifies the criterion and sub-criterion, which are pertinent for evaluating the supplier in CE context. Fuzzy-based ‘Criteria Importance Through Inter-Criteria Correlation (CRITIC)’ method is justifiably applied to determine the aggregated weights of the criteria. Finally, ‘Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS)’ method is used to determine the suppliers' ranking in the Indian automobile industry. Six criteria and 24 sub-criteria are obtained as per recent literature and then inputs from experts. ‘Environment’ criterion came out as the most favourable criterion with a subjective weight of 0.230. The current research is one of the first such attempts to provide criteria for supplier selection in a CE environment. The developed framework would help organisations in implementing CE-based supplier selection. The identified criteria and sub-criteria would provide organisations with means to evaluate suppliers and help suppliers develop an effective and efficient CE based on the SC.