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Abstract:
We develop an analytical framework to investigate the competitive implications of personalized pricing technologies (PP). These technologies enable first-degree price discrimination: firms charge different prices to different consumers, based on their willingness to pay. We first show that, even though a monopolist makes a higher profit with PP, its optimal quality is the same with or without PP. Next, we show that in a duopoly setting, personalized pricing adds value only if it is associated with product differentiation. We then consider a model of vertical product differentiation, and show how personalized pricing on the Internet affects firms' choices of quality differentiation in a competitive scenario. There are two equilibria. We find that, when the PP firm has a high quality both firms raise their qualities, relative to the uniform pricing case. Conversely, when the PP firm has low quality, both firms lower their qualities. While it is optimal for the firm adopting PP to increase product differentiation, the non-PP firm seeks to reduce differentiation by moving in closer in the quality space. Our model also points out firms' optimal pricing strategies with PP, which may be non-monotonic in consumer valuations. Depending on the convexity of the marginal cost function, we outline the incentives of firms to deploy such technologies. Our model shows it is an optimal strategy for the low quality firm to adopt PP, if the other firm does not. Regardless of whether the low quality firm has PP, the high quality firm should adopt PP only if the cost function is not too convex. Next, if both firms acquire PP, then both firms earn lower profits than in the case where neither firm has PP. Essentially, they are trapped in a prisoner's dilemma. Finally, we show that, consumer surplus is highest when both firms adopt PP. Thus, despite the threat of first degree price discrimination, personalized pricing with competing firms can lead to an overall increase in consumer welfare.

Personalized Pricing, Product Differentiation, Price Competition, Electronic Commerce

Abstract:
We develop a model of vertical differentiation in the Internet search engine market. A key property of the model is that users who try out one engine may be dissatisfied with the results, and consult another engine in the same session. This residual demand allows lower quality engines to survive in equilibrium. We consider a two-period game between an incumbent and an entrant who enters in the second period. Since users prefer to try out a higher quality engine first, the demand for an engine is discontinuous in quality, depending on whether the engine is a leader or a follower. We take into account brand loyalty for the incumbent. The interaction of brand loyalty and a cost advantage for the entrant determines which engine is the leader in equilibrium.

Vertical differentiation, search engine, residual demand, brand loyalty

Abstract:
We investigate consumers' choice behavior for Internet search engines. Within this broad agenda, we focus on two interrelated issues. First, we will document whether consumers develop loyalty to a particular search engine. If loyalty does indeed develop, we seek to understand what is the importance of this loyalty in the search engine choice. We also explore how the level of interaction with the engine enhances or detracts from customer loyalty. Second, we seek to determine how search engine performance affects the user choice behavior. To accomplish our research objective, we first develop a conceptual model of search engine choice based on the literature in human-computer interaction and cognitive psychology. Next, we use a multinomial logit model to study 6,321 distinct search engine choices for six engines over a period of one year. Our findings show that user dissatisfaction with the results negatively affects the user choice both immediately as well as in the future. We also show that the impact of loyalty is small when users use engines primarily for search purposes but quite large when they use personalized features. Finally, we also test whether user choice is affected by the presence of banner advertisements on the Web. The results of this research provide insight into consumer behavior in the marketplace for Internet search engines and offer guidance to managers of these companies in developing sustainable competitive advantage through better product design.

Abstract:
In many industries, Internet referral services, hosted either by independent third-party infomediaries or by manufacturers, serve as digitally enabled lead-generators in electronic markets, directing consumer traffic to downstream retailers in a distribution network. This reshapes the extended enterprise from the traditional network of upstream manufacturers and downstream retailers, to include midstream third-party and manufacturer-owned referral servics in the supply chain. We model competition between retailers in a supply chain with such digitally- enabled institutions, and consider their impact on the optimal contracts between the manufacturer, referral intermediary and the retailers. Offline, retailers face a higher customer discovery cost. In return, they can engage in price discrimination based on consumer valuations. Online, they save on the discovery costs, but lose the ability to identify consumer valuations. This critical tradeoff drives firms' equilibrium strategies. We derive the optimal contracts for different entities in the supply chain and highlight how these contracts change with the entry of independent and manufacturer-owned referral services. The establishment of a referral service is a strategic decision by the manufacturer. It leads to a diversion of supply chain profit from a third-party infomediary to the manufacturer. Further, it enables the manufacturer to respond to an infomediary, by giving itself a greater flexibility in setting the unit wholesale fee to the profit maximizing level. Both third-party and manufacturer-sponsored referral services play a critical role in enabling retailers to discriminate across consumers different valuations. Retailers use online referral services to screen out low valuation consumers, and sell only to high valuation consumers in the online channel. Our model thus endogenously derives a correlation between consumer valuation and online purchase behavior. Finally, we show that under some circumstances, it is too costly for the manufacturer to eliminate the referral infomediary.

Internet Referral Services, Electronic Markets, Price Dispersion, Franchise Fees, Discovery Costs, Electronic Intermediary, Digital Supply Chain

Abstract:
Piracy has been a major problem for perpetually licensed software. Usage-based licensing architecture such as pay-per-use or software-as-a-service can offer technology-based protection against piracy. We provide an analytical framework to examine the economic implications of pay-per-use versus perpetual licensing in a market with potential piracy, network effect, and heterogeneous consumers in terms of marginal usage benefit and acquisition costs for pirated software. We show that the potential piracy rate, the user inconvenience cost of pay-per-use licensing, consumer heterogeneity, and the network strength are important factors determining a vendor's optimal choice of licensing architecture. While perpetual licensing tends to be optimal when consumers have homogeneous valuations, pay-per-use is more profitable than perpetual licensing or mixed licensing in markets with heterogeneous consumers and low user inconvenience costs. If the inconvenience cost is low enough, pay-per-use will be more profitable than perpetual licensing even if the market has no potential piracy. The presence of network effect also favors pay-per-use over perpetual licensing; if the network effect is strong, pay-per-use will always dominate perpetual licensing regardless of the inconvenience cost or the potential piracy. With more heterogeneous consumers, higher potential piracy, lower inconvenience costs, and stronger network effects, pay-per-use licensing yields not only higher vendor profits but also a higher social surplus than perpetual licensing. Important managerial implications are also discussed.

software pricing, piracy, network effect, licensing innovation, pay-per-use, usage based pricing, software licensing, perpetual licensing

Abstract:
Information security is growing to be an IT priority for many firms, but several critical dimensions of enterprise security like type of loss or strategic effects of countermeasures have received little attention in the economics-based literature. We develop a model of a contagious threat that can attack multiple divisions of a firm's enterprise network and cause both availability and confidentiality losses. Firms commonly deploy countermeasures to mitigate the harmful effects of threats. Such deployment is complicated by the CIO's lack of information on the information systems of the divisions and due to the differing goals of division managers. In this setting, we model the business process and interconnectivity requirements of the enterprise and demonstrate how to optimally design the security architecture, which consists of protection, recovery and cryptographic measures. We evaluate commonly suggested mechanisms like subsidies and liability and find that they are inadequate as well as informationally demanding. To remedy these problems which directly impact practitioners, we derive mechanisms that have no ex-post informational requirements and are easily implementable for both availability and confidentiality losses. Some of our results are counterintuitive, notably that countermeasure can be overdeployed by division managers and that having a single platform for all divisions can decrease unexpected confidentiality losses.

Information Security, Availability Losses, Confidentiality Losses, Enterprise Security Architecture

Abstract:
To improve operational efficiencies while providing state of the art healthcare services, hospitals rely on IT enabled physician referral systems (IT-PRS). This study examines learning curves in an IT-PRS setting to determine whether agents achieve performance improvements from cumulative experience at different rates and how information technologies transform the learning dynamics in this setting. We present a hierarchical Bayes model that accounts for different agent skills (domain and system), and estimate learning rates for three types of referral requests: emergency (EM), non-emergency (NE), and non-emergency out of network (NO). Further, the model accounts for complementarities among the three referral request types and the impact of system upgrade on learning rates. We estimate this model using data from more than 80,000 referral requests to a large IT-PRS. We find that (1) The IT-PRS exhibits a learning rate of 4.5% for EM referrals, 7.2% for NE referrals, and 12.3% for NO referrals. This is slower than the learning rate of manufacturing (on average 20%) and more comparable to other service settings (on average 8%). (2) Domain and system experts are found to exhibit significantly different learning behaviors. (3) Significant and varying complementarities among the three referral request types are also observed. (4) The performance of domain experts is affected more adversely in comparison to system experts immediately after system upgrade. (5) Finally, the learning rate change subsequent to system upgrade is also higher for system experts in comparison to domain experts. Overall, system upgrades are found to have a long term positive impact on the performance of all agents. The learning curve estimation of this study contributes to the development of theoretically grounded understanding of learning behaviors of domain and system experts in an IT enabled critical healthcare service setting.

Business Value of IT, Economics of IS, Econometrics, Physician Referral System, Learning Curves, IT Enabled Call Centers.

Abstract:
In this paper we investigate how well banks manage their reserves. The optimal policy takes into account expected foregone interest on excess reserves and penalty costs for going below required reserves. Using a unique panel data-set on daily clearing house settlements of a cross-section of Mexican banks we estimate the deposit uncertainty banks face, and in turn their optimal reserve behavior. The most important variables for forecasting the deposit uncertainty are the interbank fund-transfers of the day, certain calendar dates, and the interest differential between the money market rate and the discount rate - a measure reflecting the bank's opportunity cost of money holdings. For most banks the model's prediction accord relatively well with the observed reserve behavior of banks. The model produces reserves costs that are significantly smaller relative to the case when reserves are set via simple rule of thumb. Furthermore, alternative motives for holding reserves (such as liquidity and reputation effects) do not seem to be the explanation for why certain banks hold relatively large reserves.

Institutional subscribers to the NBER working paper series, and residents of developing countries may download this paper without additional charge at www.nber.org.

Abstract:
The Internet search engine market has seen a proliferation of entrants over the last few years. While Yahoo! was the early market leader, there has been entry by both lower quality engines and higher quality ones (such as Google). Prior work on quality differentiation requires that low quality products have low prices, in order to survive in a market with high quality products. However, the price charged to users of search engines is typically zero. Therefore, consumers do not face a trade-off between quality and price. Why do lower quality products survive in such a market? We develop a vertical differentiation model which explains this phenomenon. The quality of the results provided by a search engine is inherently stochastic, and there is no charge to using an engine. Therefore, users who try out one engine may consult a lower quality engine in the same session. This "residual demand" allows lower quality products to survive in equilibrium. We then extend our model to incorporate horizontal differentiation as well and show that residual demand leads to higher quality and less differentiation in this market. Engines want to attract competitors' customers and therefore have a strong incentive to be "similar" to each other.

Search Engine, Residual Demand, Quality, E-Commerce, Product Differentiation, Economic Analysis, Vertical differentiation, Brand loyalty