Online Reputation Systems and Cumulative Advantage

The study of online reputation systems and their importance for promoting trust and cooperation and, therefore, the smooth functioning of online markets has received considerable attention over the last few years. In the first part of our talk we will try to give a brief overview of the existing theoretical and empirical work in this field, summarize the main findings from this research and identify open questions where results are either controversial or do not yet exist. The second part of our talk will focus on one of these issues that deserve further research, namely the relation between online reputation systems and processes of "cumulative advantage." Cumulative advantage is the mechanism where a favorable relative position of having a good reputation becomes a resource for further relative gains. The process leads to increased status inequality and a heavily skewed distribution of number of feedbacks, i.e. the ties in the reputation network. We present empirical evidence for direct and indirect reputation effects on the micro level of an auction reputation system and discuss the distributional consequences for the market level.

Trust and Reputation in Internet Auctions

Exchange between anonymous actors in Internet auctions corresponds to a one-shot prisoner's dilemma-like situation. Therefore, in any given auction the risk is high that seller and buyer will cheat and, as a consequence, that the market will collapse. However, mutual cooperation can be attained by the simple and very efficient institution of a public rating system. By this system, sellers have incentives to invest in reputation in order to enhance future chances of business. Using data from about 200 auctions of mobile phones we empirically explore the effects of the reputation system. In general, the analysis of nonobtrusive data from auctions may help to gain a deeper understanding of basic social processes of exchange, reputation, trust, and cooperation, and of the impact of institutions on the efficiency of markets. In this study we report empirical estimates of effects of reputation on characteristics of transactions such as the probability of a successful deal, the mode of payment, and the selling price (highest bid). In particular, we try to answer the question whether sellers receive a "premium" for reputation. Our results show that buyers are willing to pay higher prices for reputation in order to diminish the risk of exploitation. On the other hand, sellers protect themselves from cheating buyers by the choice of an appropriate payment mode. Therefore, despite the risk of mutual opportunistic behavior, simple institutional settings lead to cooperation, relatively rare events of fraud, and efficient markets.

The FORA Framework - A Fuzzy Grassroots Ontology for Online Reputation Management

Online reputation management deals with monitoring and influencing the online record of a person, an organization or a product. The Social Web offers increasingly simple ways to publish and disseminate personal or opinionated information, which can rapidly have a disastrous influence on the online reputation of some of the entities. This dissertation can be split into three parts: In the first part, possible fuzzy clustering applications for the Social Semantic Web are investigated. The second part explores promising Social Semantic Web elements for organizational applications,while in the third part the former two parts are brought together and a fuzzy online reputation analysis framework is introduced and evaluated. Theentire PhD thesis is based on literature reviews as well as on argumentative-deductive analyses.The possible applications of Social Semantic Web elements within organizations have been researched using a scenario and an additional case study together with two ancillary case studies—based on qualitative interviews. For the conception and implementation of the online reputation analysis application, a conceptual framework was developed. Employing test installations and prototyping, the essential parts of the framework have been implemented.By following a design sciences research approach, this PhD has created two artifacts: a frameworkand a prototype as proof of concept. Bothartifactshinge on twocoreelements: a (cluster analysis-based) translation of tags used in the Social Web to a computer-understandable fuzzy grassroots ontology for the Semantic Web, and a (Topic Maps-based) knowledge representation system, which facilitates a natural interaction with the fuzzy grassroots ontology. This is beneficial to the identification of unknown but essential Web data that could not be realized through conventional online reputation analysis. Theinherent structure of natural language supports humans not only in communication but also in the perception of the world. Fuzziness is a promising tool for transforming those human perceptions intocomputer artifacts. Through fuzzy grassroots ontologies, the Social Semantic Web becomes more naturally and thus can streamline online reputation management.

Reputation Formation and the Evolution of Cooperation in Anonymous Online Markets

Theoretical propositions stressing the importance of trust, reciprocity, and reputation for cooperation in social exchange relations are deeply rooted in classical sociological thought. Today’s online markets provide a unique opportunity to test these theories using unobtrusive data. Our study investigates the mechanisms promoting cooperation in an online-auction market where most transactions can be conceived as one-time-only exchanges. We first give a systematic account of the theoretical arguments explaining the process of cooperative transactions. Then, using a large dataset comprising 14,627 mobile phone auctions and 339,517 DVD auctions, we test key hypotheses about the effects of traders’ reputations on auction outcomes and traders’ motives for leaving feedback. Our statistical analyses show that sellers with better reputations have higher sales and obtain higher prices. Furthermore, we observe a high rate of participation in the feedback system, which is largely consistent with strong reciprocity—a predisposition to unconditionally reward (or punish) one’s interaction partner’s cooperation (or defection)—and altruism—a predisposition to increase one’s own utility by elevating an interaction partner’s utility. Our study demonstrates how strong reciprocity and altruism can mitigate the free-rider problem in the feedback system to create reputational incentives for mutually beneficial online trade.

Structural and Institutional Determinants of Influence Reputation: A Comparison of Collaborative and Adversarial Policy Networks in Decision Making and Implementation

The central assumption in the literature on collaborative networks and policy networks is that political outcomes are affected by a variety of state and nonstate actors. Some of these actors are more powerful than others and can therefore have a considerable effect on decision making. In this article, we seek to provide a structural and institutional explanation for these power differentials in policy networks and support the explanation with empirical evidence. We use a dyadic measure of influence reputation as a proxy for power, and posit that influence reputation over the political outcome is related to vertical integration into the political system by means of formal decision-making authority, and to horizontal integration by means of being well embedded into the policy network. Hence, we argue that actors are perceived as influential because of two complementary factors: (a) their institutional roles and (b) their structural positions in the policy network. Based on temporal and cross-sectional exponential random graph models, we compare five cases about climate, telecommunications, flood prevention, and toxic chemicals politics in Switzerland and Germany. The five networks cover national and local networks at different stages of the policy cycle. The results confirm that institutional and structural drivers seem to have a crucial impact on how an actor is perceived in decision making and implementation and, therefore, their ability to significantly shape outputs and service delivery.