Shopbots, agents that automatically search the Internet for goods and/or services on behalf of consumers, herald a future in which autonomous agents become an essential component of nearly every facet of electronic commerce [Chavez and Maes1996, Kephart et al. 1998, Tsvetovatyy et al. 1997]. In response to a consumer's expressed interest in a specified good or service, a typical shopbot can query several dozen web sites, and then collate and sort the available information for the user -- all within seconds. For example, www.shopper.com claims to compare 1,000,000 prices on 100,000 computer-oriented products! In addition, www.acses.com compares the prices and expected delivery times of books offered for sale on-line, while www.jango.com and webmarket.junglee.com offer everything from apparel to gourmet groceries. Shopbots can out-perform and out-inform even the most patient, determined consumers, for whom it would take hours to obtain far less coverage of available goods and services.
Shopbots deliver on one of the great promises of electronic commerce and the Internet: a radical reduction in the cost of obtaining and distributing information. It is generally recognized that freer flow of information will profoundly affect market efficiency, as economic friction will be reduced significantly [Lewis1997, DeLong and Froomkin1998]. Transportation costs, menu costs -- the costs to firms of evaluating, updating, and advertising prices -- and shopping costs -- the costs to consumers of seeking out optimal price and quality -- will all decrease, as a consequence of the digital nature of information as well as the presence of autonomous agents that find, process, collate, and disseminate that information at little cost. What are the implications of the widespread use of shopbots and related types of autonomous agents in electronic marketplaces, and how might species of computational agents evolve?
DeLong and Froomkin DeLong98 qualitatively investigate the ongoing emergence of shopbots; in particular, they note that short of violating anti-trust laws, firms will be hard pressed to prevent their competitors from sponsoring shopbots, in which case those who do not do so will experience decreased sales. In this paper, we utilize quantitative techniques to address the aforementioned questions. We propose, analyze, and simulate a simple economic model designed to capture the present role of shopbots as agents of economic change, particularly with regard to consumer preferences, as they decrease the cost of obtaining information in markets known to exhibit price dispersion. Looking ahead several years into the future, we project that shopbots will evolve into economic entities (i.e., utility maximizers) in their own right, interacting with billions of other self-interested software agents. Moreover, we predict the emergence of pricebots -- economically-motivated agents that set prices so as to maximize the profits of firms, just as shopbots seek prices that minimize costs for consumers. Accordingly, we study adaptive price-setting algorithms which pricebots might utilize to combat the growing community of shopbots, in a full-fledged agent-based economy.
This paper is organized as follows. The next section, Section 2, presents our model, which is analyzed in Section 3 from a game-theoretic point of view. Section 4 describes various adaptive price-setting algorithms and the results of their simulation under the prescribed model. A possible evolution of shopbots and pricebots is discussed Section 5. Concluding remarks and ideas for future work appear in Section 6.