Privacy Management and Optimal Pricing in People-Centric Sensing

With the emerging sensing technologies such as mobile crowdsensing and Internet of Things (IoT), people-centric data can be efficiently collected and used for analytics and optimization purposes. This data is typically required to develop and render people-centric services. In this paper, we address the privacy implication, optimal pricing, and bundling of people-centric services. We first define the inverse correlation between the service quality and privacy level from data analytics perspectives. We then present the profit maximization models of selling standalone, complementary, and substitute services. Specifically, the closed-form solutions of the optimal privacy level and subscription fee are derived to maximize the gross profit of service providers. For interrelated people-centric services, we show that cooperation by service bundling of complementary services is profitable compared to the separate sales but detrimental for substitutes. We also show that the market value of a service bundle is correlated with the degree of contingency between the interrelated services. Finally, we incorporate the profit sharing models from game theory for dividing the bundling profit among the cooperative service providers.Comment: 16 page

The Role of the Mangement Sciences in Research on Personalization

We present a review of research studies that deal with personalization. We synthesize current knowledge about these areas, and identify issues that we envision will be of interest to researchers working in the management sciences. We take an interdisciplinary approach that spans the areas of economics, marketing, information technology, and operations. We present an overarching framework for personalization that allows us to identify key players in the personalization process, as well as, the 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 firm's value system. We review extant literature in the strategic behavior of firms, and discuss opportunities for analytical and empirical research in this regard. Next, we examine how a firm can learn a customer's preferences, which is one of the key components of the personalization process. We use a utility-based approach to formalize such preference functions, and to understand how these preference functions could be learnt based on a customer's interactions with a firm. We identify well-established techniques in management sciences that can be gainfully employed in future research on personalization.CRM, Persoanlization, Marketing, e-commerce,

The role of screening and cross-selling in bank-firm relationships

This paper presents a monopolistic competition model of a bank choosing the optimal level of the screening effort in the presence of cross-selling activities. We demonstrate that, in absence of informational synergies, the larger is the range of services that the bank produces, the lower is the optimal screening effort. The paper also analyses the impact of competition in the lending market on cross-selling activities and finds that, for sufficiently low levels of transportation costs, an increase in competition in the lending market increases the expected profitability of services, thus increasing banks’ incentives to engage in cross-selling activities.Policy games, policy effectiveness, controllability, Nash equilibrium existence, rational expectations

Product Bundling: Impacts of Product Heterogeneity and Risk Considerations

Bundling has been extensively studied in the literature and its benefits have been manifested through three perspectives of achieving better price discrimination, helping to save costs, and preserving the power for deterring a potential entrant. In this study, we examine two aspects of bundling which have not been studied before. We examine the impact of product heterogeneity on bundling decisions. We also address risk considerations in a bundling problem. Specifically, we consider a retailer who has the option of selling a bundle of two products (pure bundling policy), or selling the products separately (no-bundling policy). The retailer could also face a product selection problem for which we consider three scenarios of choosing two products with perfectly positively correlated, perfectly negatively correlated or independent reservation prices. We use a Mean-Variance approach to include retailer’s risk through her profit variability when maximizing the expected value of profit. We characterize the conditions under which a policy or scenario performs better than the others under the influence of product heterogeneity and/or retailer’s risk aversion. Among other findings, we show that optimal bundling price chosen by a risk-averse decision maker cannot be larger than the one chosen by a risk neutral decision maker

Evaluating Pricing Strategy Using e-Commerce Data: Evidence and Estimation Challenges

As Internet-based commerce becomes increasingly widespread, large data sets about the demand for and pricing of a wide variety of products become available. These present exciting new opportunities for empirical economic and business research, but also raise new statistical issues and challenges. In this article, we summarize research that aims to assess the optimality of price discrimination in the software industry using a large e-commerce panel data set gathered from Amazon.com. We describe the key parameters that relate to demand and cost that must be reliably estimated to accomplish this research successfully, and we outline our approach to estimating these parameters. This includes a method for ``reverse engineering'' actual demand levels from the sales ranks reported by Amazon, and approaches to estimating demand elasticity, variable costs and the optimality of pricing choices directly from publicly available e-commerce data. Our analysis raises many new challenges to the reliable statistical analysis of e-commerce data and we conclude with a brief summary of some salient ones.Comment: Published at http://dx.doi.org/10.1214/088342306000000187 in the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Does Service Bundling Reduce Churn?

We examine whether bundling in telecommunications services reduces churn using a series of large, independent cross sections of household decisions. To identify the effect of bundling, we construct a pseudo-panel dataset and utilize a linear, dynamic panel-data model, supplemented by nearest-neighbor matching. We find bundling does reduce churn for all three "triple-play" services. However, the effect is only "visible" during times of turbulent demand. We also find evidence that broadband was substituting for pay television in 2009. This analysis highlights that bundling helps with customer retention in service industries, and may play an important role in preserving contracting markets.Bundle, Service, Churn, Triple Play, Telecommunications, Cable, Broadband, Telephone, Screen

Me and you and everyone we know: an empirical analysis of local network effects in mobile communications.

This paper aims at investigating the importance that consumers assign to local network effects (i.e. the extent to which they take into account their contacts’ operators in determining their choices) and at identifying which individual characteristics affect consumers’ preferences in relation to local network effects. Based on a sample of 193 Italian students, we find that consumers are highly heterogeneous with respect to the evaluation of the importance of their friend/family’s operator when choosing their own provider, and that such heterogeneity is associated to specific characteristics related to individual innovativeness and patterns of mobile phone usage. In particular, consumers who are more interested in local network effects are typically sophisticated users, who use intensively voice services and who are early adopters. Interestingly, consumers who pay attention to local network effects end up spending relatively little in proportion to their intensity of use.