A computational model of trust and reputation

Despite their many advantages, e-businesses lag behind brick and mortar businesses in several fundamental respects. This paper concerns one of these: relationships based on trust and reputation. Recent studies on simple reputation systems for e-Businesses such as eBay have pointed to the importance of such rating systems for deterring moral hazard and encouraging trusting interactions. However, despite numerous studies on trust and reputation systems, few have taken studies across disciplines to provide an integrated account of these concepts and their relationships. This paper first surveys existing literatures on trust, reputation and a related concept: reciprocity. Based on sociological and biological understandings of these concepts, a computational model is proposed. This model can be implemented in a real system to consistently calculate agents' trust and reputation scores.

1. Introduction

Trust and reputation underlies every face-to-face trade. A major weakness of electronic markets is the raised level of risk associated withwfpc the loss of the notions of trust and reputation. In an on-line setting, trading partners have limited information about each other's reliability or the product quality during the transaction. The analysis by Akerloff in 1970 on the Market for Lemons is also applicable to the electronic market. The main issue pointed out by Akerloff about such markets is the information asymmetry between the buyers and sellers. The buyers know about their own trading behavior and the quality of the products they are selling. On the other hand, the sellers can at best guess at what the buyers know from information gathered about them, such as their trustworthiness and reputation. Trading partners use each others' reputations to reduce this information asymmetry so as to facilitate trusting trading relationships.