An experimental analysis of multi-attribute auctions
Decision Support Systems
Artificial Intelligence: A Modern Approach
Artificial Intelligence: A Modern Approach
Agent learning in supplier selection models
Decision Support Systems - Special issue: Decision theory and game theory in agent design
Expert Systems with Applications: An International Journal
Solving multiple scenarios in a combinatorial auction
Computers and Operations Research
Reinforcement learning: a survey
Journal of Artificial Intelligence Research
A strategy for evaluating a fuzzy case-based construction procurement selection system
Advances in Engineering Software
Market-Based Task Allocation Mechanisms for Limited-Capacity Suppliers
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Bid evaluation behavior in online procurement auctions involving technical and business experts
Electronic Commerce Research and Applications
Hi-index | 12.05 |
Behavioral uncertainty of a supplier is a major challenge to a buyer operating in e-procurement setting. Modeling suppliers' behavior from past transactions, estimation of possible future performance and integrating this knowledge with the winner determination process can bring a new dimension to procurement process automation. We propose a states-space model to capture the uncertainty involved in long-term supplier behavior. The states represent the performance level of a supplier. This behavioral aspect is then integrated with the winner determination process of a multi-attribute reverse auction for efficient supplier selection using parallel MDP. We also propose an implementation framework to collect the feedback on supplier, generate an aggregate performance score and integrate it with the winner determination process. The performance aggregation and winner determination with help of Markov decision process effectively uses the past performance information. In addition, it updates performance information in regular invervals and allevates the problem of maintaining a long history. We compare the MDP-based selection with that of performance score-based selection through a simulation experiment. It is observed that our scheme gives better buyer utility, selects best suppliers and fetches better quality product. The benefits realized through these attributes to the buyer increases the efficiency of the MDP-based selection process.