What have we learned about the welfare implications of information transpar- ency? We have found that information transparency affects producers and consumers differently. Although information transparency on the B2B ex- change is socially desirable, its private desirability is deeply divided between producers and consumers, and even among producers themselves. Our model shows a conflict between producers’ and consumers’ interests regarding information transparency of the B2B exchange. Producer surplus may rise because the interaction effect and allocation effect together tend to dominate the variation effect. Concerning the consumer side, there is no allocation effect present, but the interaction effect is operating against the variation effect.
Depending which effect dominates, consumers may benefit in some situations but may get hurt in other situations.
Certain types of companies (for example, high-cost suppliers of substitute products) will lack the incentives to join the B2B exchange as information transparency hurts more than helps them. In contrast to the widely held belief about its benefits (the so-called information transparency hypothesis), information transparency is indeed a double-edged sword. Our results suggest that the actual effects will be rather complicated — a transparent environment is not necessarily a good thing for all participants. This may partially explain the difficulty of most public B2B exchanges in signing up suppliers (Harris, 2001), and the recent observation that many firms switch from public exchanges to private exchanges (Hoffman et al., 2002), which tend to be less transparent than the public exchanges. For example, Wal-Mart, Cisco, Dell, and Hewlett- Packard have established private exchanges with their suppliers and business partners (Dai & Kauffman, 2002).
Our analysis shows that the welfare effects can be decomposed into two distinct effects — the variation effect on the revenue side and the allocation effect on the cost side. We found that dividing the welfare impact into these two separate effects is quite helpful to trace out the welfare impact. By introducing these new concepts, we point out the possibility that the transparency of cost information can be either beneficial or detrimental to consumers and producers. This highlights one of the differences of our model from the literature.
Thus this chapter provides a theoretical interpretation about the informational effects of B2B exchanges. On the other hand, one has to be careful when linking these results to real-world B2B exchanges. There are many reasons for firms to join a B2B exchange. The informational effects are just one, albeit an important one, of these many factors. Our model focuses on just one aspect of the informational effects induced by the B2B exchange — information trans- parency about costs. So the propositions and conclusions about welfare effects must be conditioned on this partial-equilibrium setting and the standard ceteris peribus assumptions under which they have been derived.
This paper can be extended in several directions. Informational effects can be multi-dimensional. We only modeled the horizontal information effects among competitors. We have not considered vertical information exchange between suppliers and manufacturers in a more general supply chain collaboration environment (Lee & Whang, 2000; Plice, Gurbaxani, & Zhu 2003). Many of these issues, especially information transparency in online supply chain col- laboration, deserve further research. Second, an extension of the current model might consider double-sided externalities in a neutral marketplace, where the buyer side and seller side influence each other. Third, it might be interesting to consider firms’ participation in multiple exchanges (Belleflamme, 1998). This is another fertile area for further research. We hope that the initial work presented in this chapter will motivate other researchers to build more sophis- ticated models and further examine the multiple dimensions of informational effects associated with electronic markets.
References
Agrawal, M., & Pak, M. (2002). Getting smart about supply chain manage- ment. The McKinsey Quarterly, 2, 22-26.
Bakos, J.Y. (1997). Reducing buyer search costs: Implications for electronic marketplaces. Management Science, 43(12), 1676-92.
Bakos, J.Y. (1998). The emerging role of electronic marketplaces on the Internet. Comm. of the ACM, 41(8), 35-42.
Basar, T., & Ho, Y.C. (1974). Informational properties of the Nash solutions of two stochastic nonzero-sum games. Journal of Economic Theory, 7, 370-387.
Belleflamme, P. (1998). Adoption of network technologies in oligopolies.
International Journal of Industrial Organization, 16, 415-444.
Clarke, R. (1983). Collusion and the incentives for information sharing. Bell Journal of Economics, 14, 383-94.
CRN Business Weekly. (2000, May 22). FTC, DOJ probe business-to- business marketplaces, Issue 895.
Dai, Q., & Kauffman, R.J. (2002). Business models for Internet-based procurement systems and B2B electronic markets: An explanatory as- sessment. Intl. Journal of Electronic Commerce.
Disabatino, J. (2002, June 28). DOT report on Orbitz inconclusive. Computer World.
Federal Trade Commission. (2000). Competition policy in the world of B2B electronic marketplaces.
Fudenberg, D., & Tirole, J. (1991). Game theory. Cambridge, MA: MIT Press.
Gal-Or, E. (1986). Information transmission - Cournot and Bertrand equilib- ria. Review of Economic Studies, 53, 85-92.
Grossman, S. (1981). An introduction to the theory of rational expectations under asymmetric information. Review of Economic Studies, 48(4), 541-559.
Grover, V., Ramanlal, P., & Segars, A. (1999). Information exchange in electronic markets: Implications for market structures. Intl. J. of Elec- tronic Commerce, 3(4), 89-102.
Hansen, M., Mathews, B., Mosconi, P., & Sankaran, V. (2001). A buyer’s guide to B-to-B markets. The McKinsey Quarterly, 2, 33-36.
Harris, N. (2001, March 16). Private exchanges may allow B-to-B commerce to thrive after all. Wall Street Journal.
Hoffman, W., Keedy, J., & Roberts, K. (2002). The unexpected return of B2B. The McKinsey Quarterly, 3.
Jordan, J., & Radner, R. (1982). Rational expectations in microeconomic models: An overview. Journal of Economic Theory, 26, 201-223.
Kauffman, R., & Walden, E. (2001). Economics and electronic commerce:
Survey and directions for research. Intl. Journal of Electronic Com- merce, 5(4), 5-116.
Koch, C. (2002, December 1). Covisint’s last chance. CIO, 16(5).
Lee, H.L., & Whang, S. (2000). Information sharing in a supply chain. Intl. J.
Manufacturing Technology and Management, 1(1), 79-93.
Li, L. (1985). Cournot oligopoly with information sharing. Rand Journal of Economics, 16(4), 521-36.
Malueg, D., & Tsutsui, S. (1998). Distributional assumptions in the theory of oligopoly information exchange. Intl Journal of Industrial Organiza- tion, 16, 785-97.
Meehan, M. (2001, April 3). Collaborative commerce still needs some time.
Computerworld.
Mullaney, T. (2003, May 12). The e-biz surprise. Business Week, special report.
Novshek, W., & Sonnenschein, H. (1982). Fulfilled expectations Cournot duopoly with information acquisition and release. Bell Journal of Eco- nomics, 13, 214-218.
Plice, R., Gurbaxani, V., & Zhu, K. (2003). The economic impact of B2B exchanges on supplier-manufacturer relationships: The interaction of industry structure and exchange design. Working paper, University of California, Irvine.
Shapiro, C. (1986). Exchange of cost information in oligopoly. Review of Economic Studies, 53(3), 433-46.
Sinha, I. (2000, March-April). Cost transparency: The Net’s real threat to prices and brands. Harvard Business Review, 3-8.
Tirole, J. (1988). The theory of industrial organization. Cambridge, MA:
MIT Press.
Vives, X. (1984). Duopoly information equilibrium: Cournot and Bertrand.
Journal of Economic Theory, 34, 71-94.
Vives, X. (1990). Trade association disclosure rules, incentives to share information, and welfare. Rand Journal of Economics, 21(3), 409-430.
Zhu, K. (1999). Strategic investment in information technologies: A real- options and game-theoretic approach. Doctoral dissertation. Stanford University, Stanford, CA.
Zhu, K. (2002). Information transparency in electronic marketplaces: Why data transparency may hinder the adoption of B2B exchanges. Electronic Markets, Special Issue on B2B E-Commerce, 12(2), 92-99.
Zhu, K. (2004). Information transparency of business-to-business electronic markets: A game-theoretic analysis. Management Science, 50(5), 670- 685.
Zhu, K., & Weyant, J. (2003). Strategic decisions of new technology adoption under asymmetric information. Decision Sciences, 34(4), 643-675.