Impact of reputation information sharing in an auction-based job allocation model for small and medium-sized enterprises

This research investigates the impact of reputation information sharing in an auction-based job allocation system using a multi-agent based simulation model based on three performance measures: economic efficiency, throughput index, and penalty index. Two forms of reputation information sharing systems, dyadic and public, were implemented and studied. Dyadic reputation systems deal with one-to-one information sharing, while public reputation systems deal with many-to-many information sharing. The paper proposes a hybrid auction mechanism, which is a combination of the sealed bid and reverse auction mechanisms. Analysis of the simulation results shows that reputation information sharing benefits the system tremendously by increasing the overall economic efficiency and throughput index, while decreasing the penalty index of the system. The results also show that as the significance of reputation in the market increases, the benefits realised in terms of economic efficiency and throughput index also increase.