B.P.S. Murthi

The Role of the Management Sciences in Research on Personalization

We present a review of research studies that deal with personalization and synthesize current knowledge about these areas. We identify issues that we envision will be of interest to researchers working in the management sciences, taking an interdisciplinary approach that spans the areas of economics, marketing, information technology (IT), and operations research. We present a framework for personalization that allows us to identify key players in the personalization process as well as key stages of personalization. The framework enables us to examine the strategic role of personalization in the interactions between a firm and other key players in the firms value system. We conceptualize the personalization process as consisting of three stages: (1) learning about consumer preferences, (2) matching offerings to customers, and (3) evaluation of the learning and matching processes. This review focuses on the learning stage, with an emphasis on utility-based approaches to estimate preference functions using data on customer interactions with a firm.

Efficiency of mutual funds and portfolio performance measurement: A non-parametric approach

Abstract In finance, portfolio performance assessment is an important area of research. The two popular indices of performance are the Jensens alpha and the Sharpe index. However there are a number of shortcomings of the above measures that have been highlighted in the literature. We propose a new measure of performance that seeks to address the limitations of the earlier indices. The new index is calculated by employing a well known method in operations research called data envelopment analysis. We show the benefits of the proposed approach and assess the performance of mutual funds. We compare the results with traditional indices of performance. An interesting result we obtain is that the mutual funds are all approximately mean-variance efficient.

Consumers' Extent of Evaluation in Brand Choice

Brand choice models implicitly assume that consumers incorporate all relevant marketing information such as price, display, and feature for key brands on each purchase occasion. The authors examine whether consumers actively evaluate the brands on every occasion. They propose a multistate choice model with varying levels of evaluation and estimate the model with scanner data. In addition, the authors study the effect of household demographics, occasion-specific factors, as well as unmeasured household and purchase occasion factors on the extent of evaluation. The results indicate that consumers do not evaluate brands on all occasions. The authors discuss the implications of such limited evaluation. Copyright 1999 by University of Chicago Press.

Developing a measure of risk adjusted revenue (RAR) in credit cards market: Implications for customer relationship management

Current models of customer lifetime value (CLV) consider the discounted value of profits that a customer generates over an expected lifetime of relationship with the firm. This practice can be misleading in the financial services markets because it ignores the risk posed by the customer (such as delinquency and default). Specifically, in the credit card market, the correlation between revenue and risk is positive. Therefore, firms need to adjust a customer’s profits for the associated risk before developing a measure of customer lifetime value. We propose a new measure, risk adjusted revenue (RAR), that can incorporate multiple sources of risk and demonstrate the usefulness of the proposed measure in correctly assessing the value of a customer in the credit card market. The model can be extended to compute risk adjusted lifetime value (RALTV). We use the RAR metric to understand the effectiveness of different modes of acquisition, and of retention strategies such as affinity cards and reward cards. We find that both reward- and affinity-cardholders generate higher RAR than non-reward and non-affinity cardholders respectively. The ordering of different modes of acquisition with respect to RAR (in decreasing order) is as follows: Internet, direct mail, telesales, and direct selling.

Performance of the integrated random coefficients covariance probit model: Implications for brand choice

Abstract In probit brand choice models, researchers increasingly focus on random variation of key parameters of interest. An important source of such variation may be due to differing consumer response to marketing efforts across purchase occasions. Also, variables common across alternatives influence purchase behavior, but may not be measured. Failure to adequately control for both these factors may cause biased estimates. More importantly, the incorrect estimates may lead to erroneous managerial conclusions. While either problem can be directly addressed in a (non-independent) probit model, we focus on whether a joint specification of both factors is necessary. We highlight the potential for misleading managerial inferences by contrasting the model with both sources of variation against nested models, using empirical data on ketchup product category. Further, in a simulation study we establish the extent of bias in recovery of parameters due to different specifications of both factors.

A Dynamic Model for Digital Advertising: The Effects of Creative Format, Message Content, and Targeting on Engagement

The authors study the joint effects of creative format, message content, and targeting on the performance of digital ads over time. Specifically, they present a dynamic model to measure the effects of various sizes of static (GIF) and animated (Flash) display ad formats and consider whether different ad contents, related to the brand or a price offer, are more or less effective for different ad formats and targeted or retargeted customer segments. To this end, the authors obtain six months of data on daily impressions, clicks, targeting, and ad creative content from a major U.S. retailer, and they develop a dynamic zero-inflated count model. Given the sparse, nonlinear, and non-Gaussian nature of the data, the study designs a particle filter/Markov chain Monte Carlo scheme for estimation. Results show that carry-over rates for dynamic formats are greater than those for static formats; however, static formats can still be effective for price ads and retargeting. Most notably, results also show that retargeted ads are effective only if they offer price incentives. The study then considers the import of these results for the retailers media schedules.

Robustness of the negative binomial distribution to model purchase incidence: A simulation study

Negative Binomial Distribution (NBD) has been widely employed in marketing to model purchase incidence. In this paper, we undertake a simulation study to examine the sensitivity of NBD when the number of purchases in a given period is Poisson or Erlang 2 but the underlying heterogeneity is different from gamma. In particular, we allow the heterogeneity to follow three other flexible and well-known distributions: inverse Gaussian, lognormal and Weibull. All these distributions have shapes that are similar to the gamma. Moreover, we evaluate the performance of three alternative models namely, the Condensed Negative Binomial (CNBD), the Generalized Negative Binomial (GNBD) and the Generalized Poisson (GPD). Our simulation results indicate that NBD is robust to the violation of gamma heterogeneity when the interpurchase time is exponential and the coefficient of variation of the heterogeneity distribution is either low or moderate. CNBD exhibits similar robustness when the interpurchase time is Erlang 2. Howe...

Invited Editorial—A Descriptive Analysis of Publications in Marketing Science Over Its History

Using the University of Texas at Dallas database on publications in the top 24 business journals, we examine the evolution of Marketing Science as reflected by participation of faculty from top ranked business schools on one hand, and diversity on the other hand, as evidenced by contributions from different countries and from faculty of a wider set of schools. We show that faculty from top-ranked business schools have always published in Marketing Science , and continue to do so. We also show that the variety of schools with authors who publish in Marketing Science has increased, and that much of this expansion has occurred outside of North America. This international expansion appears to be driven by collaborations between authors in North America and those in other areas. One of the factors that may be fueling the increase in the variety of schools with authors publishing in Marketing Science is an increased tendency for collaboration by three or more authors. In general, Marketing Science has remained an outlet for authors from top schools, and has also become a place where authors from a much broader array of schools, especially those outside the United States, can publish.Data, as supplemental material, are available at http://dx.doi.org/10.1287/mksc.2015.0957 .

DOES RACE MATTER WITHIN A MULTICULTURAL CONTEXT? ALTERNATE MODES OF THEORIZING AND THEORY TESTING.

Within a set of multicultural organizations, we conduct a firm level six-year, longitudinal analysis on the direct impact that racial diversity in human resources has on financial performance. Consistent with Blaus (1977) theory of heterogeneity predictions, we test for a curvilinear relationship between diversity and performance. We find that the model with nonlinear effects of racial diversity on performance fits the data better than the linear effects model. We find that organizations with low to moderate levels of racial diversity were negatively impacted by diversity consistent with social identity theory while firms with higher levels of diversity realized positive performance gains as suggested by information and decision-making theoretical tenets. Further, we tested the moderating effects of industry type, munificent environments, stable environments, and diversity management efforts on this relationship. This nonlinear, U-shaped, relationship was stronger in service-oriented relative to manufact...

Robustness of the negative binomial distribution : a simulation study: Robustness of the negative binomial distribution

Negative Binomial Distribution (NBD) has been widely employed in marketing to model purchase incidence. In this paper, we undertake a simulation study to examine the sensitivity of NBD when the number of purchases in a given period is Poisson or Erlang 2 but the underlying heterogeneity is different from gamma. In particular, we allow the heterogeneity to follow three other flexible and well-known distributions: inverse Gaussian, lognormal and Weibull. All these distributions have shapes that are similar to the gamma. Moreover, we evaluate the performance of three alternative models namely, the Condensed Negative Binomial (CNBD), the Generalized Negative Binomial (GNBD) and the Generalized Poisson (GPD). Our simulation results indicate that NBD is robust to the violation of gamma heterogeneity when the interpurchase time is exponential and the coefficient of variation of the heterogeneity distribution is either low or moderate. CNBD exhibits similar robustness when the interpurchase time is Erlang 2. Howe...