Analysis of an intermediary's strategies in electronic markets for decision technologies

Web-based technologies are changing the nature of commerce in both physical and information goods. Electronic intermediaries will play useful roles in such commerce, particularly in the use of decision technologies as services. We develop models to analyze an intermediary’s production and pricing strategies, taking into account marginal costs and network externalities, and assuming the intermediary wants to provide two levels of service. In the absence of marginal costs and network externalities, the intermediary should offer only one level of service at high quality. In the presence of marginal costs, the intermediary would offer both levels of service, resulting in market segmentation, depending on the relative efficiencies of producing these services. If the network effect is sufficiently large, the intermediary lowers the listing fee charged from the providers (boosting prices charged from the consumers), and all consumers are served. The intermediary’s technology strategy would drive him to reduce the quality of the low service in an effort to maximize profits from highvalue customers and in order to take advantage of the additional consumer surplus created by the network effect. This paper develops and analyzes mathematical models of intermediary or brokerage services used by consumers and suppliers in an electronic market. We use an economic model to analyze an electronic intermediary’s strategies with respect to quality of service pricing, taking into account marginal costs and network externalities. Our work is relevant to electronic intermediation in a number of areas, but is motivated by and grounded in the realm of Web-based electronic markets for computational services. 1. ELECTRONIC INTERMEDIARIES AND COMPUTATIONAL SERVICES Web-based technologies are having a profound impact on commerce. The Web’s ease of use and the reduction in transaction costs has led to significant growth in consumer-to-business commerce (e.g., purchase of books on Amazon.com), business-to-business commerce (e.g., integration across the supply chain with trading partners on GE’s trading partner network), intra-organizational work processes (e.g., reengineering of work and information flows in a hospital), and on the creation of virtual communities (for example, Tripod on Lycos). These technologies have the potential to change commerce in both physical goods and in information goods and services. Some current examples, in the latter category, are the delivery of music encoded in the MP3 format (www.mp3.com) and the distribution of software drivers (e.g., see www.hp.com) and components (see www.download.com). Analysis of an Intermediary’s Strategies 83 Software distribution over the Web is often done by transferring source or object code to the client platform (e.g., the desktop). An alternative is a “pay per use” model, in which a custom instance of the software is executed at the consumer’s request and the results are delivered to the consumer in an interactive session conducted over the network. This alternative is becoming attractive and feasible given the wide availability of a TCP/IP-based standards compliant platform and its integration with distributed object technologies such as CORBA, DCOM, and Java (for a detailed discussion of this point and associated technologies, see Bhargava and Krishnan 1998 ). Recently (see www.news.com), large vendors such as IBM and Oracle have announced application hosting services, permitting organizations to access applications and data, hosted on the vendors’ servers, via their Web browsers. Forrester Research estimates the applications hosting market to reach $6 billion dollars by the year 2001. These new Web-based application-hosting strategies are similar in concept to the service bureau model of the 1970s and 1980s, although updated to use current Web technologies. However, the Web can be used in a proactive manner to create a new service bureau model—one we refer to as a virtual service bureau (VSB)—that enables users to search, discover, and obtain executable access to a distributed set of applications and data maintained and managed by a distributed set of providers. Such service bureaus are essentially electronic intermediaries (or brokers) that facilitate transactions between consumers and providers of application hosting services. For example, they may help providers in advertising and help consumers in product discovery and selection. They may help consumers in setting up a decision technology for execution or help providers in creating a suitable Web-based interface for executing a technology. From the point of view of designing electronic intermediaries, it becomes prudent to ask a series of questions relating to the value of these services. Which of these services should an intermediary provide? What pricing strategies are optimal? What is the effect of various controllable and environmental variables on the intermediary’s profit and market share, and on the consumer surplus? If consumers and providers derive value from the intermediary’s services, these questions may be analyzed by developing mathematical models of economic activity. In this paper, we analyze the prices paid by the consumer and the provider to the intermediary for middleware services, and do not discuss the pricing arrangement for the decision technology itself. Factors considered in the analysis are the quality of service, the cost of producing it, and the profile of the consumers. The rest of this paper is organized as follows. We begin in section 2 with discussion of the pricing and quality decisions faced by an intermediary in a VSB for decision support software services. In section 3, we develop economic models of the intermediary’s pricing strategy problem and obtain interesting results in a variety of scenarios. We conclude with a discussion of insights gained from the model and our plans for future work in this area. 2. TECHNOLOGY STRATEGY OF AN INTERMEDIARY IN A VIRTUAL SERVICE BUREAU DecisionNet (Bhargava, Krishnan and Mueller 1997) and NEOS (Czyzyk, Owen and Right 1997) are two examples of emerging technologies for electronic intermediation between users and providers of decision technologies. According to Bailey and Bakos (1997), electronic intermediaries perform four roles: (1) aggregating content, (2) being a trusted agent, (3) facilitating the market, and (4) matching buyers and sellers. In the context of electronic commerce in decision technologies, Bhargava, Krishnan and Mueller (1998) discuss the various steps in the business cycle for both consumers and providers and argue that some form of intermediary support is required for such an electronic market to be successful. In this section, we use DecisionNet to illustrate service offerings that provide varied quality of services. 2.1 Electronic Intermediation in DecisionNet DecisionNet is a virtual service bureau. Providers of decision support applications can register meta-information about their application with a DecisionNet intermediary. The intermediary compiles and processes this meta-information to provide services to consumers. Depending on the type of meta-information supplied by the provider, the intermediary could provide services ranging from a simple keyword-based search for a decision support application to more complex searches that use knowledge about the semantics of interfaces in the VSB to compose (i.e., make the output of one application as an input to another) and execute applications. The intermediary could also bundle these services into packages, and several such packages could be designed from a given collection of services. We assume, for the sake of simplicity, that the intermediary wants to provide only Bhargava, Choudhary, Krishnan and Lee 84 two products: a lean broker package offering some low quality services and a fat broker package consisting of high quality services. For example, the lean broker provides services for matching buyers and sellers by maintaining a repository of metadata about decision technology resource providers. It offers resource providers a means to register their technologies, thereby entering resource metadata into the repository. By providing cataloging and search services on this metadata repository, it supports consumers in discovering various attributes of the product offerings and in selecting suitable resources for their tasks. The consumer is then directed to the resource provider for further transactions. The fat broker, in our example, provides additional services to facilitate logistical transactions, including product delivery (i.e., execution of decision technology) and settlement, between the consumer and provider. To do this, it captures additional metadata about the resource when the resource is registered by the provider. An individual technology, if sufficient for a consumer’s task, can be selected and scheduled for execution. Using the additional metadata, the broker manages the low-level operations associated with data formatting, file transfer, and remote execution. By keeping track of technology usage along various dimensions (time spent, number of pages, kilobytes transferred), it does price determination using various pricing schemes. The fat broker also supports interoperation between multiple technologies. That is, the broker assists consumers in selecting and sequencing the execution of multiple technologies via a language for creating a computational plan and data interchange between technologies. 2.2 Intermediary Characteristics and Network Effects In general, the intermediary needs to make decisions regarding the quality and price of services offered, and the lean-fat broker pair discussed above comprises just one point in this decision space. In analyzing this decision space, we consider four major characteristics of the intermediary. First, the quality of services offered (e.g., a service that offers composition of multiple resources is more useful than