Online publishers and advertisers have recently shown increasing interest in using targeted advertising online. Such targeting allows them to present users with advertisements that are a better match, based on their past browsing and search behavior and other available information (e.g., hobbies registered on a web site). This technique, known as behavioral targeting, has been hailed as the new “Holy Grail” in online advertising because of its potential effectiveness. In this paper, we study the economic implications when an online publisher engages in behavioral targeting. The publisher auctions off an advertising slot and is paid on a cost-per-click basis. Using a horizontal differentiation model to capture the fit between a user and an advertisement being displayed, we identify the factors that affect the publisher’s revenue, the advertisers’ payoffs, and social welfare. We show that revenue for the online publisher in some circumstances can double when behavioral targeting is used. However, increased revenue for the publisher is not guaranteed: in some cases, the prices of advertising and hence the publisher’s revenue can be lower, depending on the degree of competition and the advertisers’ valuations. We identify two effects associated with behavioral targeting: a competitive effect and a propensity effect. The relative strength of the two effects determines whether the publisher’s revenue is positively or negatively affected. We also demonstrate that, although social welfare is increased and small advertisers are better off under behavioral targeting, the dominant advertiser might be worse off and reluctant to switch from traditional advertising.
The existence and persistence of price dispersion for identical products in online markets have been welldocumented in the literature. Possible explanations of this price dispersion, derived mainly using hedonic price models, have seen only modest success. In this paper, we propose a competitive model based on online retailers' differentiation mainly in service provided and recognition enjoyed to explain price dispersion. Our exploratory empirical analyses, using cross-sectional data, demonstrate that the competitive model provides a better explanation of the association between prices and online retailers' service and recognition levels. In addition, our competitive model is able to explain observations that are seemingly inconsistent with the hedonic model such as the negative association between service and price. This paper contributes to the literature on price dispersion by offering a differentiation model that provides a good fit with data and by proposing a theory that explains previous counterintuitive observations of prices. Our model also helps an e-tailer to choose a desirable position in the competitive market.
To cut costs, companies have chosen to deliver a variety of service offerings online. However, the digital systems providing such services (e-service) have always been complemented with or supported by humanbased service (h-service). Whereas h-service has total costs that increase with the demand for services, e-service mainly requires a fixed investment upfront, which can be amortized over the totality of customers served. Considering the different nature of the costs of h-service and e-service and the heterogeneity of customer preferences for services, we derive the optimal mix of h-service and e-service for a service-providing company vis-à-vis its competitor. Our theoretical analysis finds the subgame-perfect Nash equilibria that determines the optimal positions in a duopoly setting. We further study the competitive dynamics of the system to examine how firms stay on the equilibrium paths. Using simulation, we investigate the effects of starting positions, small adjustments in h-service and/or e-service, and monotonic expansions of e-service on the final positioning and profits of the firms. Our results demonstrate that when firms follow a local best-reply strategy, they may end up in a position of low profitability, and when only monotonic expansions of e-service are allowed, both firms may end up overinvesting in e-service.
The capabilities of network technologies have facilitated the growth of electronic commerce. Major issues--notably, security and product quality uncertainty--still pose serious challenges to the further adoption of electronic commerce. Traditional market transactions have a long history and well-understood protections for buyers and sellers. In the electronic markets, formal and informal mechanisms such as trusted third parties (TTP) have emerged trying to ensure safe transactions . In this paper, we investigate under what conditions people will stick to the traditional market and face-to-face transactions, and under what conditions electronic transactions will be the convention of the future. Of particular interest is the role of TTPs in facilitating online transactions. Using evolutionary game theory, we present an analytical model of buyer and seller choices and examine which patterns of transactions can be sustained. We further study how the traders' adaptive behavior may influence the outcome of the market evolution. Through this analysis, we demonstrate that the market will show divergence: for commodity products, electronic transactions through TTPs will get established as the convention for market transactions when traders use historical information about other traders' past strategies. For "look and feel" products, the market evolution depends on the initial distribution of the transaction strategies in the population.
Traditional development of large-scale information systems is based on centralized information processing and decision making. With increasing competition, shorter product life-cycle, and growing uncertainties in the marketplace, centralized systems are inadequate in processing information that grows at an explosive rate and are unable to make quick responses to real-world situations. Introducing a decentralized information system in an organization is a challenging task. It is often intertwined with other organizational processes. The goal of this research is to outline a new approach in developing a supply chain information system with a decentralized decision making process. Particularly, we study the incentive structure in the decentralized organization and design a market-based coordination system that is incentive aligned, i.e., it gives the participants the incentives to act in a manner that is beneficial to the overall system. We also prove that the system monotonically improves the overall organizational performance and is goal congruent.
Prior research has generated considerable knowledge on information systems design from software engineering and user-acceptance perspectives. As organizational processes are increasingly embedded within information systems, one of the key considerations of many business processes--organizational incentives--should become an important dimension of any information systems design and evaluation, which we categorize as the third dimension: incentive alignment.Incentive issues have become important in many IS areas,including distributed decision support systems (DSS), knowledge management, and e-business supply chain coordination. In this paper we outline why incentives are important in each of these areas and specify requirements for designing incentive-aligned information systems. We identify and define important unresolved problems along the incentive-alignment dimension of information systems and present a research agenda to address them.