Trust and Reputation Building in E-Commerce

Transactions on online markets require a great deal of trust among anonymous trading partners. To mitigate some of the risks involved in anonymous transactions, several online market sites have implemented reputation management mechanisms that differ in structure and probably functionality. In a series of experiments, this study examines the impact of two simple reputation management mechanisms on the evolution of trust and trustworthiness in a repeated trust game among strangers. Les transactions par Internet exigent une confiance considérable entre les intervenants anonymes. Pour minimiser les risques associés à des opérations anonymes, les responsables de plusieurs marchés en ligne ont mis en place des mécanismes de gestion de réputation différant en structure et fonctionnalité. Dans une série d'expériences, cette étude évalue l'impact de deux mécanismes relativement simples sur la confiance et la coopération dans un jeu de confiance répété entre étrangers.Trust, Reputation, Experimental Economics, E-commerce, Mondialisation, commerce international, temps de travail, intégration économique

Building communities for the exchange of learning objects: theoretical foundations and requirements

In order to reduce overall costs of developing high-quality digital courses (including both the content, and the learning and teaching activities), the exchange of learning objects has been recognized as a promising solution. This article makes an inventory of the issues involved in the exchange of learning objects within a community. It explores some basic theories, models and specifications and provides a theoretical framework containing the functional and non-functional requirements to establish an exchange system in the educational field. Three levels of requirements are discussed. First, the non-functional requirements that deal with the technical conditions to make learning objects interoperable. Second, some basic use cases (activities) are identified that must be facilitated to enable the technical exchange of learning objects, e.g. searching and adapting the objects. Third, some basic use cases are identified that are required to establish the exchange of learning objects in a community, e.g. policy management, information and training. The implications of this framework are then discussed, including recommendations concerning the identification of reward systems, role changes and evaluation instruments

Trust beyond reputation: A computational trust model based on stereotypes

Models of computational trust support users in taking decisions. They are commonly used to guide users' judgements in online auction sites; or to determine quality of contributions in Web 2.0 sites. However, most existing systems require historical information about the past behavior of the specific agent being judged. In contrast, in real life, to anticipate and to predict a stranger's actions in absence of the knowledge of such behavioral history, we often use our "instinct"- essentially stereotypes developed from our past interactions with other "similar" persons. In this paper, we propose StereoTrust, a computational trust model inspired by stereotypes as used in real-life. A stereotype contains certain features of agents and an expected outcome of the transaction. When facing a stranger, an agent derives its trust by aggregating stereotypes matching the stranger's profile. Since stereotypes are formed locally, recommendations stem from the trustor's own personal experiences and perspective. Historical behavioral information, when available, can be used to refine the analysis. According to our experiments using Epinions.com dataset, StereoTrust compares favorably with existing trust models that use different kinds of information and more complete historical information