Optimum design of electronic communities as economic entities

Electronic communities can be designed to organize consumers, to pool their purchasing power, and to guide their purchasing decisions. Such commercial electronic communities have the potential to facilitate the creation of novel marketplaces, and even radically change the buyer-seller interaction, as physical communities did throughout the history. Commercial electronic communities are groups of consumers that participate in the marketplace as a single unit. In addition to bargaining power gained from such bundling, such communities can expand markets by reducing market uncertainty, and they have the potential to drastically reduce consumers’ transaction costs, by facilitating group transactions and bulk purchasing. Communities are characterized by their size, their pricing strategy, and their membership characteristics. Analytical models and numeric analysis is utilized to compute the optimum size of a community for given market characteristics. Two major community pricing strategies are analyzed to improve the community design, and the conditions are derived where one dominates the other. Finally, market segmentation techniques are introduced to control the membership characteristics of the community to further improve the design. Levent V. Orman is a professor of Information Systems at Cornell University, Graduate School of Management. He received a Ph.D. degree from Northwestern University. He has taught courses and written articles on electronic commerce, database management, decision support systems, and expert systems. His recent articles appeared in Journal of Information Technology and Management, Journal of MIS, Acta Informatica, and IEEE Transactions on Knowledge and Data Engineering. He is the associate editor of the Journal of Database Management, and serves on the editorial board of the Journal of Information Technology and Management.     

Decision Support for Managing an Electronic Supply Chain

The growth of the Internet and electronic commerce opens new venues for companies to create flexible supply chains by offering high-speed communication and tight connectivity. To take full advantage of these new opportunities, companies need to be able to respond quickly to opportunities as they arise and make smart decisions taking into account the vast amount of data now available. We describe a decision support system which helps companies in making decisions about purchasing, manufacturing or promotions, while considering supplies and demands posted on the Internet, in addition to their own inventory, capacity and demand. The decision support system is currently being tested within an electronic marketplace we built for paper products, which went online in September 1999.     

Internet aggression in online communities: a contemporary deterrence perspective

Internet users' activities are critical to the development and success of Web 2.0 systems, such as online communities. Within the community's participation, knowledge sharing, and communications, users may conduct aggressive behaviors that would have a negative impact on that online community. This study investigates factors that affect Chinese users' aggression intention in online communities. Research findings show that online aggression can be inhibited by internal deterrents of face saving and moral beliefs, which may be enhanced through implementation of consequences from an effective community policy and peer pressure among community members. Differences in the effects of the deterrence measures exist between younger and older users. This paper contributes theoretically and empirically to Web 2.0 research and has practical implications for virtual community management.     

Design of Roles and Protocols for Electronic Negotiations

Support for negotiations in electronic markets is one of the primary issues in today's e-commerce research. Whereas most activities are focused on automation aspects, only few efforts address the design of electronic negotiations. However, for the efficiency of electronic negotiation processes and the success of resulting settlements, it is essential to achieve an a-priori agreement among the negotiating parties about issues such as the syntax and semantics of offer specifications, the sequence of actions, possible responses, or time constraints, because these factors might influence, for instance, the fairness of the electronic negotiation.This paper demonstrates how an explicit and specific design can capture the way electronic negotiations are organised. The organisation design meta-model presented is part of SILKROAD, a design and application framework for electronic negotiations. On the basis of this framework, organisations creating an electronic market or sellers intending to offer potential buyers the option to bargain, can generate, in a flexible and efficient way, customised electronic negotiation systems supporting the roles and protocols designed. Furthermore, the consequent application of this meta-model can lead to the discovery of common negotiation patterns, eventually resulting in a reference model for electronic negotiations.     

Energizing business transactions in virtual worlds: an empirical study of consumers’ purchasing behaviors

Virtual marketplaces for products and services have become major profit sources in virtual worlds (VWs). The large quantity and growth of virtual product transactions and their platform providers’ profits have made it critical to understand consumer purchasing behavior in VWs. However, as open-ended VWs such as Second Life have environments that differ from those of other online communities, the underlying mechanisms of consumers’ e-commerce behavior may not explain their VW behavior. Therefore, this study examines consumers’ VW behavior by considering three categories of factors influencing their purchasing behavior: the platform context (i.e., technical characteristics such as interactivity and vividness and social characteristics such as involvement), product context (i.e., product value), and virtual experience (i.e., flow and satisfaction). This study examines how these factors affect consumers when they purchase virtual products. Its results highlight the importance of flow experience in consumers’ VW behavior. Interactivity, vividness, and involvement are found to affect consumers’ virtual experience—flow, and involvement exhibits a significantly stronger influence on flow. Flow and involvement are found to affect product value, and flow exerts a stronger influence than involvement on product value. Flow and product value directly impact consumers’ willingness to purchase, whereas satisfaction with the virtual world experience, which is significantly affected by flow, is not associated with willingness to purchase. The results further indicate that product value is more influential on willingness to purchase than is flow. After describing the study’s contributions to both research and practice, I conclude the paper by presenting avenues for future research.     

Designing Agent-Based Electronic Employment Markets

Two modes of matching people with jobs prevail at present: 1) hierarchical planning and 2) distributed markets. Each has strengths and limitations, but few systems have been designed to take advantage of strengths corresponding to both. With evolving information technology, however, the job-matching process could be accomplished far more equitably and efficiently using web-based markets within the firm, and intelligent agents offer excellent potential to help both potential employees and employers find one another in a distributed, electronic marketplace. But realizing this potential goes well beyond simply changing the rules of internal job matching or making agent technology available to job searchers. Rather, the corresponding markets and technologies must be designed, together, to mutually accomplish the desired results (e.g., efficient and effective matching) and conform to necessary properties (e.g., market clearing). Through the research described in this paper, we draw from Game Theory results to assess the feasibility of using two-sided matching algorithms to address this market-design problem. We also draw from current agent research to address the information technology dimension of the problem by implementing a proof-of-concept multi-agent system to enact, automate and support the corresponding market solution. This paper integrates the key economic and technological elements required to design robust electronic employment markets. And the corresponding research provides new knowledge and insight into co-development of the requisite economic markets and agent technologies.     

The role of intermediaries in electronic marketplaces: developing a contingency model

Abstract. Early research in electronic markets seemed to suggest that e‐ commerce transactions would result in decreased costs for buyers and sellers alike, and would therefore ultimately lead to the elimination of intermediaries from electronic value chains. However, a careful analysis of the structure and functions of electronic marketplaces reveals a different picture. Intermediaries provide many value‐adding functions that cannot be easily substituted or ‘internalized’ through direct supplier–buyer dealings, and hence mediating parties may continue to play a significant role in the e‐commerce world. In this paper we provide an analysis of the potential roles of intermediaries in electronic markets and we articulate a number of hypotheses for the future of intermediation in such markets. Three main scenarios are discussed: the disintermediation scenario, in which market dynamics will favour direct buyer–seller transactions; the reintermediation scenario, in which traditional intermediaries will be forced to differentiate themselves and re‐emerge in the electronic marketplace; and the cybermediation scenario, in which wholly new markets for intermediaries will be created. The analysis suggests that the likelihood of each scenario dominating a given market is primarily dependent on the exact functions that intermediaries play in each case. A detailed discussion of such functions is presented in the paper, together with an analysis of likely outcomes in the form of a contingency model for intermediation in electronic markets.     

Electronic Survey Methodology: A Case Study in Reaching Hard-to-Involve Internet Users

Using the Internet to conduct quantitative research presents challenges not found in conventional research. Paper-based survey quality criteria cannot be completely adapted to electronic formats. Electronic surveys have distinctive technological, demographic, and response characteristics that affect their design, use, and implementation. Survey design, participant privacy and confidentiality, sampling and subject solicitation, distribution methods and response rates, and survey piloting are critical methodological components that must be addressed.

In this article, quality criteria for electronic survey design and use based on an investigation of recent electronic survey literature are presented. The application of these criteria to reach a hard-to-involve online population-nonpublic participants of online communities (also known as "lurkers")-and survey them on their community participation, a topic not salient to the purpose of their online communities is demonstrated in a case study. The results show that a hard-to-reach audience can be reached using the quality criteria that are most important for reaching these types of audiences. The results suggest how the use of some criteria may conflict and what researchers may experience when conducting electronic surveys in an online culture in which people are not tolerant of intrusions into online lives.     

The Advantages of Designing Adaptive Business Agents Using Reputation Modeling Compared to the Approach of Recursive Modeling

Adaptive business agents operate in electronic marketplaces, learning from past experiences to make effective decisions on behalf of their users. How best to design these agents is an open question. In this article, we present an approach for the design of adaptive business agents that uses a combination of reinforcement learning and reputation modeling. In particular, we take into account the fact that multiple selling agents may offer the same good with different qualities, and that selling agents may alter the quality of their goods. We also consider the possibility of dishonest agents in the marketplace. Our buying agents exploit the reputation of selling agents to avoid interaction with the disreputable ones, and therefore to reduce the risk of purchasing low value goods. We then experimentally compare the performance of our agents with those designed using a recursive modeling approach. We are able to show that agents designed according to our algorithms achieve better performance in terms of satisfaction and computational time and as such are well suited for the design of electronic marketplaces.