Trust, reputation identity in the electronic markets

Competitio Book Series, 2005

Trust, being the prerequisite of even the simplest exchanges, has a particular importance in electronic markets. The author uses a game theory model as a starting point to throw light upon on how occasional partners can bridge the mutual lack of information relating to each other’s strategy by applying a mixed strategy, and on how they can improve their pay-off by applying trigger or tit-for-tat strategies in the case of repeated games. As buyer-seller relationships are mostly incidental on the Internet, innovative trust-building solutions are needed to diminish risks. Such a mechanism is e.g. the institutionalization of buyers’ solidarity in reputation-building and -destroying actions. In principle, buyers can form an opinion on the utility of a piece of software or other knowledge-product if they possess it, but there is no sense buying it until they are convinced of its utility. Nevertheless, other buyers’ experiences published on the Internet put an end to this contradiction. The buyers’ solidarity works; certain buyers – recommending to buy, or dissuading from buying – help others make their decision. The intermediaries (from auctioneers to certifying institutions) make use of their own reputation to contribute to the elimination of the partners’ mutual mistrust. The study also deals with the special limits of developing trust in electronic transactions, with special regard to possible changes of partner’s’ identity. JEL-code: A13, D74, Z13

2002

Trust that suppliers and buyers will keep their word is a necessary ingredient to a well functioning marketplace. Nowhere is the issue trickier than for electronic markets, where transactions tend to be geographically diffuse and anonymous, putting them out of the reach of the legal safeguards and the long-term relationships that build trust in the brick-and-mortar world. Many online platforms have turned to automated reputation systems as a way of giving traders a heads-up on who they are dealing with. Here we describe a strategic framework for thinking about these systems. We also describe some lab data that provides an initial sense of effectiveness. We find that reputation has substantial positive effect, but not enough to be a close substitute for personal relationships; this is so even though our laboratory test abstracts away from many of the problems reputation systems must confront in the field. The evidence suggests directions for improving automated reputation system perf...

In online interactions in general, but especially in interactions between buyers and sellers on internet-auction platforms, the interacting parties must deal with trust and cooperation problems. Whether a rating system is able to foster trust and cooperation through reputation and without an external enforcer is an open question. We therefore explore through ecological analysis different buyer and seller strategies in terms of their success and their contribution to supporting or impeding trust and cooperation. In our agent-based model, the interaction between a buyer and a seller is defined by a one-shot trust game with a reputation mechanism. In every interaction, a buyer has complete information about a seller's past behavior. We find that cooperation evolves under two conditions even in the absence of an external sanctioning authority. On the one hand, some minimal fraction of buyers must make use of the sellers’ reputation in their buying strategies and, on the other hand, ...

This paper focuses on the interaction between network structure, the role of information, and the level of trust and trustworthiness in 3-node networks. We extend the investment game with one Sender and one Receiver to networked versions -one characterized by one Sender and two ) and one characterized by two Senders and one Receiver ([2s-1r]) -under two information conditions, full and partial. We develop a comparative model of trust for the networked exchange environments and generate two hypotheses:

Autonomous Agents and Multi-Agent Systems, 2013

In competitive electronic marketplaces where some selling agents may be dishonest and quality products offered by good sellers are limited, selecting the most profitable sellers as transaction partners is challenging, especially when buying agents lack of personal experience with sellers. Reputation systems help buyers select sellers by aggregating seller information reported by other buyers (called advisers). However, in such competitive marketplaces, buyers may also concern about the possibility of losing business opportunities with good sellers if they report truthful seller information. In this paper, we propose a trust-oriented mechanism built on game theoretic basis for buyers to: 1) determine optimal seller reporting strategy, by modeling the trustworthiness (competency and willingness) of advisers in reporting seller information; 2) discover sellers who maximize their profit by modeling the trustworthiness of sellers and considering the buyers' preferences on product quality. Experimental results confirm that competitive marketplaces operating with our mechanism lead to better profit for buyers and create incentives for seller honesty.

We provide theoretical and empirical analysis of a selling mechanism used by an Internet web-site that combines important features of auctions and gambling. This is the first analysis of such a selling mechanism, which provides insights into how the two kinds of behavior might be related in real life. The winner of the object is the bidder with the highest bid not submitted by any other bidder. In the equilibrium of our game theoretical model, each bid made with positive probability yields the same probability of winning. Bidders are more likely to submit higher bids, and the bid distribution does not depend on the value of the object or the highest bid allowed if one controls for the number of bidders. Most of these key theoretical predictions are confirmed by the data.

SSRN Electronic Journal, 2000

We analyze how different dimensions of a seller's reputation affect pricing power in electronic markets. We do so by using text mining techniques to identify and structure dimensions of importance from feedback posted on reputation systems, by aggregating and scoring these dimensions based on the sentiment they contain, and using them to estimate a series of econometric models associating reputation with price premiums. We find that different dimensions do indeed affect pricing power differentially, and that a negative reputation hurts more than a positive one helps on some dimensions but not on others. We provide the first evidence that sellers of identical products in electronic markets differentiate themselves based on a distinguishing dimension of strength, and that buyers vary in the relative importance they place on different fulfilment characteristics. We highlight the importance of textual reputation feedback further by demonstrating it substantially improves the performance of a classifier we have trained to predict future sales. This paper is the first study that integrates econometric, text mining and predictive modeling techniques toward a more complete analysis of the information captured by reputation systems, and it presents new evidence of the importance of their effective and judicious design.

2012

Reputation systems aim to reduce the risk of loss due to untrustworthy participants. This loss is aggravated by dishonest advisors trying to pollute the e-market environment for their selfinterest. A major task of a reputation system is to promote and encourage advisors who repeatedly respond with fair advice and to apply an opinion filtering or honesty checking mechanism to detect and resist dishonest advisors. This paper provides a dynamic approach to compute the aggregated shared reputation component by filtering out unfair advice and then generating the aggregated shared reputation value. The proposed approach is dynamic in nature as it is sensitive to the behaviour of advisors, value of the current transaction and encourages the cooperation among buyers as advisors. It provides incentive to honest advisors in lieu of repeated sharing of honest opinion by increasing the weight of their opinion and by making the increase in the reputation of honest advisors monotonically proportional to the value of a transaction.

2018

We discuss the results of an experimental public good game with group representatives in Germany and Japan, countries with varying levels of individualism. Representatives are permitted to communicate with their constituencies, but not with other representatives. We focus on accountability between representative and his constituency and on the risk taken in the interaction between representatives. German and Japanese subjects differ not only in their contribution behavior, but in their ability to reach agreement on strategy in pre-play communication. We find that between-country differences can be explained to a large extent by the framework for group behavior proposed by Yuki (2003).

Applied Economics, 2012

Feedback systems are claimed to be a crucial component of the success of electronic marketplaces like eBay or Amazon Marketplace. This article aims to examine the efficiency of various feedback systems on trust between anonymous traders, through a set of experiments based on the trust game. Our results indicate that trust is significantly improved by the introduction of a reputation feedback system. However such mechanisms are far from being perfect and are especially vulnerable to strategic ratings and reciprocation. Our findings indicate that some changes in rating rules may significantly improve the efficiency of feedback systems, by avoiding strategic rating or reciprocation, and hence stimulate trust and trustworthiness among traders. In particular, a system in which individuals are not informed of the other trader's decision before taking their own decision provides better results both in terms of trust and earnings. JEL classification: C92, C72, L14, L86. * CREM, CNRS, Université de Rennes 1, Marsouin and CIRANO (Montreal). [email protected] † CREM, CNRS, Université de Rennes 1, Marsouin. [email protected]