Trust and reputation systems represent a significant trend in decision support for Internet mediated service provision. The basic idea is to let parties rate each other, for example after the completion of a transaction, and use the aggregated ratings about a given party to derive a trust or reputation score, which can assist other parties in deciding whether or not to transact with that party in the future. A natural side effect is that it also provides an incentive for good behaviour, and therefore tends to have a positive effect on market quality. Reputation systems can be called collaborative sanctioning systems to reflect their collaborative nature, and are related to collaborative filtering systems. Reputation systems are already being used in successful commercial online applications. There is also a rapidly growing literature around trust and reputation systems, but unfortunately this activity is not very coherent. The purpose of this article is to give an overview of existing and proposed systems that can be used to derive measures of trust and reputation for Internet transactions, to analyse the current trends and developments in this area, and to propose a research agenda for trust and reputation systems.

Our trust conceptualizations have benefited from discussions with Ellen Berscheid and Larry Cummings of the University of Minnesota. The authors also thank three anonymous reviewers from the Organizational Behavior division of the 1996 meeting of the Academy of Management for their comments on an earlier version of this paper. THE MEANINGS OF TRUST What does the word ‘trust ’ mean? Scholars continue to express concern regarding their collective lack of consensus about trust’s meaning. Conceptual confusion on trust makes comparing one trust study to another problematic. To facilitate cumulative trust research, the authors propose two kinds of trust typologies: (a) a classification system for types of trust, and (b) definitions of six related trust types that form a model. Some of the model’s implications for management are also outlined. 2 THE MEANINGS OF TRUST “...trust is a term with many meanings. ” (Williamson, 1993: 453) “Trust is itself a term for a clustering of perceptions. ” (White, 1992: 174) Scholars and practitioners widely acknowledge trust's importance. Trust makes cooperative endeavors happen (e.g., Arrow, 1974; Deutsch, 1973; Gambetta, 1988). Trust is a key to positive interpersonal relationships in

Automation is often problematic because people fail to rely upon it appropriately. Because people respond to technology socially, trust influences reliance on automation. In particular, trust guides reliance when complexity and unanticipated situations make a complete understanding of the automation impractical. This review considers trust from the organizational, sociological, interpersonal, psychological, and neurological perspectives. It considers how the context, automation characteristics, and cognitive processes affect the appropriateness of trust. The context in which the automation is used influences automation performance and provides a goal-oriented perspective to assess automation characteristics along a dimension of attributional abstraction. These characteristics can influence trust through analytic, analogical, and affective processes. The challenges of extrapolating the concept of trust in people to trust in automation are discussed. A conceptual model integrates research regarding trust in automation and describes the dynamics of trust, the role of context, and the influence of display characteristics. Actual or potential applications of this research include improved designs of systems that require people to manage imperfect automation.

The term trust management suggests that trust can be managed, for example by creating trust, by assessing trustworthiness, or by determining optimal decisions based on specific levels of trust. The problem to date is that trust management in online environments is a diverse and ill defined discipline. In fact, the term trust management is being used with very different meanings in different contexts. This paper examines various approaches related to online activities where trust is relevant and where there is potential for trust management.

This is a careful and insightful case study of how the Toyota Production System manages the paradox of efficiency and flexibility, which arises periodically in connection with model changeovers. The authors detail the functioning of four organizational mechanisms—metaroutines, partitioning, switching, and ambidexterity. However, of particular interest is the contextual reinforcing role of training and trust in administrative structures, procedures, and rules.

To describe the concept of transitive trust in a simplified way, assume that agent A trusts agent B, and that agent B trusts agent C, then by transitivity, agent A trusts agent C. Trust transitivity manifests itself in various forms during real life human interaction, but can be challenging to concisely model in a formal way. In this paper we describe principles for expressing and analysing transitive trust networks, and define requirements for their validity. This framework can be used for modelling transitive trust in computerised interactions, and can be combined with algebras and algorithms for computing propagation of both trust and distrust. This is illustrated by an example where transitive trust is mathematically analysed with belief calculus.

In this paper we investigate the relationship between supplier trust in the buyer and transaction costs and information sharing in a sample of 344 supplier-automaker exchange relationships in the U.S., Japan, and Korea. Our findings indicate that perceived trustworthiness reduces transaction costs and is correlated with greater information sharing in supplier-buyer relationships. Moreover, the findings suggest that the value created for transactors, in terms of lower transaction costs, may be substantial. In particular, we found that the least trusted automaker spent significantly more of its face-to-face interaction time with suppliers on contracting and haggling when compared to the most trusted automaker. This translated into procurement (transaction) costs that were five times higher for the least trusted automaker. Finally, we argue that trust is unique as a governance mechanism because it not only minimizes transaction costs, but also has a mutually causal relationship with information sharing which also creates value in the exchange relationship. Other governance mechanisms (e.g., contracts, financial hostages) are necessary costs incurred to prevent opportunistic behavior but do not create value beyond transaction cost minimization. Our findings provide empirical evidence that

To identify the effect of social capital on financial development, we exploit the well-known differences in social capital (Banfield (1958), Putnam (1993)) across different parts of Italy. In areas of the country with high levels of social capital, households invest less in cash and more in stock, are more likely to use checks, have higher access to institutional credit, and make less use of informal credit. The effect of social capital is stronger where legal enforcement is weaker and among less-educated people. These results are not driven by omitted environmental variables, since we show that the behavior of movers is still affected by the level of social capital present in the province where they were born.

ABSTRACT: In hybrid situations where artificial agents and human agents interact, the artificial agents must be able to reason about the trustworthiness and deceptive actions of their human counterpart. Thus a theory of trust and deception is needed that will support interactions between agents in virtual societies. There are several theories on trust (fewer on deception!), but none that deals specifically with virtual communities. Building on these earlier theories, the role of trust and deception in virtual communities is analyzed, with examples to illustrate the objectives a theory of trust should fulfill. KEY WORDS AND PHRASES: Deception, multiagent systems, trust, virtual society. The inhumanity of the computer is in the fact that once programmed and put to work, it behaves in a perfectly honest way. —Isaac Asimov Trust and Deception in Artificial Agents and Societies Electronic commerce can only succeed if the general public trusts the virtual environment. Trust, therefore, is an important issue [20, 25, 29, 44]. As is well

Within the practitioner literature, trust has often been noted as a key component for the success of knowledge management practices; however, trust is a very complex construct that has many different facets and definitions. This paper reviews the trust literature to create an understanding of the different types and bases of trust. These types and bases of trust are then applied to the knowledge management processes (knowledge generation, knowledge codification, knowledge transfer, and knowledge application) to create better understanding of the possible relationships between trust and the knowledge management processes, and which processes require which type of trust for knowledge management success. Implications for practitioners and research are then discussed.