A generalized framework for estimating customer lifetime value when customer lifetimes are not observed

Measuring customer lifetime value (CLV) in contexts where customer defections are not observed, i.e. noncontractual contexts, has been very challenging for firms. This paper proposes a flexible Markov Chain Monte Carlo (MCMC) based data augmentation framework for forecasting lifetimes and estimating customer lifetime value (CLV) in such contexts. The framework can be used to estimate many different types of CLV models—both existing and new. Models proposed so far for estimating CLV in noncontractual contexts have built-in stringent assumptions with respect to the underlying customer lifetime and purchase behavior. For example, two existing state-of-the-art models for lifetime value estimation in a noncontractual context are the Pareto/NBD and the BG/NBD models. Both of these models are based on fixed underlying assumptions about drivers of CLV that cannot be changed even in situations where the firm believes that these assumptions are violated. The proposed simulation framework—not being a model but an estimation framework—allows the user to use any of the commonly available statistical distributions for the drivers of CLV, and thus the multitude of models that can be estimated using the proposed framework (the Pareto/NBD and the BG/NBD models included) is limited only by the availability of statistical distributions. In addition, the proposed framework allows users to incorporate covariates and correlations across all the drivers of CLV in estimating lifetime values of customers.

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Revamping MBA programs for global competitiveness

World-wide, the MBA has become one of the most popular academic qualifications. In recent years, doubts have been raised regarding worth of the MBA degree, at least in its present form. This article examines the broad trends shaping business education and recommends how MBA curricula might be redesigned to make students globally aware, and be effective in the midst of global competition. Our focus here is on meeting future essential business needs that today's schools fail to sufficiently address. Although MBA education is at a crossroads, change will not be easy, as MBA education represents a sizeable global ‘industry.’ We conclude by listing issues which may be examined to make the change feasible.     

Corporate Social Responsibility and Psychosocial Risk Management in Europe

Corporate social responsibility (CSR) is a comprehensive concept that aims at the promotion of responsible business practices closely linked to the strategy of enterprises. Although there is no single accepted definition of CSR, it remains an inspiring, challenging and strategic development that is becoming an increasingly important priority for companies of all sizes and types, particularly in Europe. Promotion of well-being at work is an essential component of CSR; however, the link between CSR, working conditions and work organisation is still found to be unfamiliar to stakeholders. As CSR is strategic and is regarded by many companies and corporate leaders as an important development, it offers opportunities for psychosocial risk management, an area that is currently among the top priorities in working environment and well-being at work debates. However, the link between CSR and psychosocial risk management has not been addressed clearly before. This paper aims to explore the potential role of CSR in promoting well-being at work through the development of a framework for the management of psychosocial risks. As part of the research, key stakeholders [including the World Health Organization (WHO), the International Labour Organization (ILO), the European Agency for Safety and Health at Work (EU-OSHA), the European Commission (EC), employers’ associations, trade unions and other policy experts] across Europe participated in a survey, interviews and focus groups to assess and clarify the link between CSR and psychosocial risk management. On the basis of the findings, a CSR-inspired approach to the management of psychosocial issues at work is proposed. Such an approach can be a useful tool in contexts where, up until now, expertise and tradition in dealing with psychosocial issues have been lacking.     

A rationale for law of technological substitution

This paper links the popular S-shaped curves often used to represent the path of technological substitution with the evolutionary model of a self-organizing industrial system. In particular, the empirical Fisher-Pry law of technological substitution is given a conceptual rationale by treating technological innovations as structural fluctuations which affect an industry's growth path as defined by a set of non-linear differential equations. In so doing, the paper draws heavily on the articles by Allen and Batten.     

International Evidence on Institutional Trading Behavior and Price Impact

This study characterizes institutional trading in international stocks from 37 countries during 1997 to 1998 and 2001. We find that the underlying market condition is a major determinant of the price impact and, more importantly, of the asymmetry between price impacts of institutional buy and sell orders. In bullish markets, institutional purchases have a bigger price impact than sells; however, in the bearish markets, sells have a higher price impact. This differs from previous findings on price impact asymmetry. Our study further suggests that price impact varies depending on order characteristics, firm‐specific factors, and cross‐country differences.     

House Buying Behavior: An Empirical Study in Cross-Cultural Buyer Behavior

Some preliminary findings concerning experience, motivation, and search are presented from a cross-cultural study of buyer behavior in housing markets. Data were obtained from probability samples of 652 households in Connecticut and Northwest England. The results include comparative analyses of several dimensions of external search, five aspects of experience, reasons for moving, and husband-wife reasons for buying. Predictive models of search are developed with multivariate regression techniques. The findings indicate that the experience and motivational variables are not very powerful predictors of search. Significant cultural differences do occur in the level of many variables, but there are some interesting similarities in the underlying factor structure.     

Early Movers Advantage? Evidence from Short Selling during After‐Hours on Earnings Announcement Days

We examine short sellers’ after‐hours trading (AHT) following quarterly earnings announcements released outside of the normal trading hours. Our innovation is to use the actual short trades immediately after the announcements. We find that on these earnings announcement days, there is significant shorting activity in AHT relative to shorting activity both during AHT on nonannouncements days and during regular trading sessions around announcements. Short sellers who trade after‐hours on announcement days earn an excess return of 0.82% and 1.40% during before‐market‐open (BMO) and after‐market‐close (AMC)sessions, respectively. The magnitude of these returns increases to 1.48 (3.92%) for BMO (AMC) earnings announcements with negative surprise. We find that the reactive short selling during AHT has information in predicting future returns. Short sellers’ trades have no predictive power if they wait for the market to open to trade during regular hours. In addition, we find that the weighted price contribution during AHT increases with an increase in after‐hours short selling. Overall, our results suggest that short sellers in AHT are informed. Our findings remain robust using alternative holding periods and after controlling for macroeconomic news announcements during BMO sessions.     

An Approach for Determining Optimal Product Sampling for the Diffusion of a New Product

Free samples are an effective means for introducing and promoting a new product. However, product sampling is also expensive. As a result, careful consideration must be given to the question of how many samples should be distributed. To encourage product adoption in any target market, a company needs to determine the “right” amount of sampling. In other words, a firm needs to determine the optimal number of samples that must be available for trial by the innovators, early adopters, and other key consumers who influence the adoption rate of the new product. With too few samples, the product might not reach enough of these key consumers to generate the word-of-mouth recommendations necessary for market success. On the other hand, offering too many free samples is a waste of a company's resources. Dipak Jain, Vijay Mahajan, and Eitan Muller propose a framework for determining the optimal levels of product sampling. In addition to identifying the upper bounds for the sampling levels of both durable and nondurable products, their model identifies the optimal size of product sampling based on such parameters as the coefficients of innovation and imitation, market potential, discount rate, and gross margin. Several observations are made regarding the relationships between the optimal sampling level and the various parameters used in the model. For example, a high sampling level is not appropriate for a product with a high coefficient of innovation. On the other hand, if a product has a high coefficient of imitation, the sampling level should be high because a significant number of trials are necessary for word of mouth to be effective. High sampling levels are also indicated by a high discount rate or gross margin. For durable goods, the optimal level of neutral sampling (i.e., sampling that does not specifically target innovators and early adopters) rarely exceeds 5%, and the maximum level is 7%. The optimal target sampling level is always higher than the corresponding neutral case, but, in most cases, only marginally so. For the parameter ranges chosen in this article, the maximum level for target sampling is approximately 9%. However, it is important to note that the theoretical upper bounds are no more than benchmarks for the maximum possible level of sampling. In practical situations, the optimal level may be considerably lower than these upper bounds. In such cases, the actual values will depend on the values for the various parameters used in the model.     

A partial least squares approach to digital finance adoption

In present times, the adoption and adaption of technology have become empirical. This paper helps in determining the factors of perceived risk and perceived benefits in order to understand the willingness or hesitance of people to adopt digital finance. An attempt is made to study the influence of perceived risk and benefit as the determinants of digital finance adoption. The data were collected from individuals of Northern India through a structured questionnaire. The study collected data from 411 respondents through a structured questionnaire. Partial Least Square Structural Equation Modelling has been adopted to analyze the data through SmartPLSv2. For better understanding, perceived risk constituted three constructs-Security risk, financial risk and performance risk, and perceived benefit included seamless transaction, economic benefit and convenience. The research concluded that both perceived risk and benefits influence the adoption of digital finance. Perceived benefit has more impact on digital finance adoption than perceived risk. The findings of the paper are beneficial for digital finance service providers and marketers to enhance the awareness and advantages of digital finance according to the needs of consumers. The present study adds value to the existing literature on the relationship between perceived risk, perceived benefit and adoption of digital finance.

     

Inflation and Default Dynamics

Changes in inflation, particularly if they are sharp, can have important consequences for nominal contracts, especially debt instruments such as fixed-rate bonds. This paper examines the intricate dynamics of inflation and defaults. The experience of the United States during the past four decades is subjected to empirical analysis to examine how the nature of the relationship changed as we shifted from a high inflation to a low inflation regime. The paper is organized as a three-part study. We initially examine the U.S. default experience, as summarized in Moody's speculative grade default rate, along with industry differences. The paper then scrutinizes U.S. inflation dynamics as seen in different summary measures of the general price level and delves into pricing power issues. The study proceeds to examine co-movements in the inflation and default series from a theoretical and empirical standpoint and the results confirm the intuitive postulate: higher the inflation rate, the more pricing power companies have; greater pricing power leads to, better earnings and repayment abilities for firms and a lower incidence of defaults.