Jin, D. Lee, K, “Impacts and Limitations of Intelligent Agents to Internet Commerce,” Lecture Notes in Computer Science, vol. 2105, pp. 33-48, July, 2001.pdf
Agent-based economy or agent-based electronic commerce is the term for describing one of possible next steps of electronic commerce. The systematic understanding of the agent-based economy is important for researchers to develop practical intelligent agent systems, and for current electronic commerce industries to cope with the challenges of the intelligent agents. With these purposes, we conduct a comprehensive review of ongoing and future impacts of intelligent agents to electronic commerce from business model perspective. We classify intelligent agents by their functions and roles in electronic commerce and analyze the business model change by intelligent agents, based on Timmers’s definition of business model. Changes in architecture of flows, responses of players, influences to revenue model and participant’s benefits, and funding source are discussed with real world business examples and related researches. We also discuss the limitations of intelligent agents in electronic commerce.
Moon, B. K., Lee, J. K., Lee, K. J., “A Next Generation Multimedia Call Center for Internet Commerce: IMC”, Journal of Organizational Computing and Electronic Commerce, vol. 10, no.4, pp.227-240, December, 2000.
Lee, K., Chang, Y., Choi, H., Kim, H., Park, Y., Park, B., “A Time-bound Framework for Negotiation and Decision Making of Virtual Manufacturing Enterprise,” Journal of Organizational Computing and Electronic Commerce, Vol. 14, no.1, 27-41, 2004. – SCI, ISSN:1054-1721. pdf
Virtual manufacturing has 2 characteristics as an agent-based electronic commerce environment: dynamic nature of resource status and variety of agents’ decision-making (i.e., scheduling) model. To reflect the characteristics, a relevant negotiation protocol should be designed and an appropriate decision-making model should be developed. In this article, from the perspective of a sales agent that is a middle man between customers and manufacturers in a virtual manufacturing environment, we provide a case study that suggests a time-bound framework for external negotiation between sales agents and customer agents, and internal cooperation between sales agents and manufacturing agents. We assume a job shop as the production model of a virtual manufacturing enterprise and formulate the optimal order selection problem with mixed integer programming, but its computation time is not acceptable for real-world problems. For this time-constrained decision making, we develop a genetic algorithm as an problem- solving method for the scheduling of the production model, which shows a reasonable computation time for real-world cases and good incremental problem-solving capability.
Sungwon Cho, Kyoung Jun Lee, Martha E. Crosby, David N. Chin, Evaluation of an online multidimensional auction system: A computer simulation investigation, Lecture Notes in Computer Science 3182:126-134, September, 2004. – SCIE ISSN:0302-9743.pdf
Through computer simulations, this paper evaluates the performance of an online multidimensional auction system with negotiation support and especially focuses on investigating the efficacy of two design features of online multidimensional auction system on its performance: sellers’ feedback and post-utility scoring method. The performance of the auction system is measured by joint gain and speed of convergence. The simulation results demonstrate that the use of sellers’ feedback and post-utility scoring method lead to better bargaining outcomes as measured by the buyer’s total utility and the number of auction rounds. The research results provide important theoretical implications about the role of information feedback in auction design.
Yong Sik Chang and Kyoung Jun Lee, A comparison shopping optimization model based on suppliers’ pricing contexts, Expert Systems with Applications, Volume 37, Issue 8, August 2010, Pages 5736-5744.pdf
Consumers in the online shopping environment have had difficulties in selecting an optimal supplier. This is caused by the fact that current comparison shopping services have limitations in considering supplier’s various pricing strategies. Current Comparison Shopping Model (CSM) including these limitations may enable online consumers to select a non-optimal supplier. To overcome these problems, we proposed a Comparison Shopping Optimization Model based on Suppliers’ Pricing Contexts (CSOM-SPC), which gives online consumers effective price-sorted suppliers. Through illustrative experimentation and paired t-test, we show that CSOM-SPC provides more realistic and effective comparison prices compared with current CSM.
Online shopping Comparison shopping Optimization model Pricing contexts