Software Agents for Automated Transaction Negotiations: Implementation and Evaluation

Software agents have the potential to serve as effective surrogates of humans in conducting business transactions in an electronic commerce environment. The reported proceeding research aims to evaluate the performance of software agents in automated transaction negotiations. As part of this research, agents are being built using IBM aglets, and their performance evaluation within various experimental settings is currently underway

Demystifying Wireless Technologies: Navigating Through The Wireless Technology Maze

A significant part of the growth in consumer-to-business electronic commerce is likely to originate from the increasing numbers of mobile computing devices and smart telephone devices. Most of the data from mobile computers will be carried over by emerging wireless networks. Many wireless technologies and standards are now available. As a result, it is becoming increasingly difficult for non-domain experts like managers, to sort through the maze of wireless technologies and standards to make business decisions involving these technologies. This article surveys existing and emerging wireless technologies and uses the Open System Interconnect (OSI) framework to organize the wireless landscape. The survey provides a quick reference to the entire spectrum of wireless technologies in use today

Negotiation Behaviors in Agent-Based Negotiation Support Systems

Prior research on negotiation support systems (NSS) has paid limited attention to the information content in the observed bid sequences of negotiators as well as on the cognitive limitations of individual negotiators and their impacts on negotiation performance. In this paper, we assess the performance of human subjects in the context of agent-based NSS, and the accuracy of an exponential functional form in representing observed human bid sequences. We then predict the reservation values of negotiators based on their observed bids. Finally, we study the impact of negotiation support systems in helping users realize superior negotiation outcomes. Results indicate that an exponential function is a good model for observed bids

Negotiation Behaviors in Agent-Based Negotiation Support Systems

Prior research on negotiation support systems (NSS) has paid limited attention to the information content in the observed bid sequences of negotiators as well as on the cognitive limitations of individual negotiators and their impacts on negotiation performance. In this paper, we assess the performance of human subjects in the context of agent-based NSS, and the accuracy of an exponential functional form in representing observed human bid sequences. We then predict the reservation values of negotiators based on their observed bids. Finally, we study the impact of negotiation support systems in helping users realize superior negotiation outcomes. Results indicate that an exponential function is a good model for observed bids

Can Recommender Systems Reduce Healthcare Costs? The Role of Time Pressure and Cost Transparency in Prescription Choice

This paper presents and synthesizes results from three studies (two controlled experiments and one interview) on using recommender systems to reduce healthcare costs at prescription time, while taking time pressure into account. All of our subjects were real practicing physicians, nurse practitioners, or physician assistants. Across these studies, a total of 160 medical practitioners used a system that provides recommendations for medications along with associated cost information. The main finding was a general tendency among practitioners to reduce healthcare costs by prescribing lower cost medications when cost information is provided by a recommender system. The time pressure faced daily by prescribers, however, appears to impact the use of recommendations by nurse practitioners and physician assistants more than it does physicians. These results have significant implications for cost reduction in healthcare and for the design of effective real-time healthcare recommender systems