BEYOND INSTITUTION-BASED TRUST: BUILDING EFFECTIVE ONLINE MARKETPLACES WITH SOCIAL MECHANISMS

Researchers have devoted considerable efforts to design effective online marketplaces, especially with respect to the institutional structures believed to establish buyer trust in the community of sellers. Comparatively speaking, the effectiveness of social mechanisms, although practically evidenced as important, has received much less attention in e-commerce research. In the current study we explore the contribution of social mechanisms–specifically IT-enabled instant messaging, the message box, online community and informal coalition programme–to effective online marketplaces. We propose that these mechanisms facilitate social relationships and trust building processes during transactions, in addition to the existing institutional structures. When consumerto- consumer (C2C) transactions are considered risky, the buyer-seller social relationship is more critical for buyers when forming their transaction intentions. The research model is largely supported by a pilot study of 104 buyers of TaoBao.com, China’s C2C leading marketplace. We discuss the findings, implications, and our preparations for a large-scale study

Towards the Design of a Robust Incentive Mechanism for E-Marketplaces with Limited Inventory (Doctoral Consortium)

ABSTRACT In e-marketplaces, reputation systems are prevalently applied to assist buyers to model seller trustworthiness based on ratings shared by other buyers. However, dishonest buyers may share untruthful ratings. Many incentive mechanisms have been proposed to elicit truthful ratings from buyers. These mechanisms have a common implicit assumption that sellers can provide a large number of products. In reality, e-markets with limited inventory exist in many scenarios. For example, dentist booking in US, as a marketplace, has been observed the phenomenon that the service demand is much larger than the service supply, and the second-hand markets where some used and workable goods (e.g., second-hand textbooks) are often in short supply due to lower prices. We call a marketplace in which the demand outweighs the supply a marketplace with limited inventory. In such marketplaces, buyers may lose profit if they provide truthful ratings due to competition from other buyers for the limited products provided by trustworthy sellers. In other words, providing truthful ratings is costly. The existing incentive mechanisms seldom consider such cost imposed on providing truthful ratings, which motivates us to design a new incentive mechanism for e-marketplaces with limited inventory. Moreover, a general assumption for incentive mechanisms is that every agent is rational and has the belief that others are also rational. However, in a realistic scenario, some agents may be irrational (bounded rationality or adversary), which may impede the efficiency of the mechanisms. In all, the aim of our research is to design an incentive mechanism for e-marketplaces with limited inventory that is robust against irrational agents

Dynamic Credibility Threshold Assignment in Trust and Reputation Mechanisms Using PID Controller

In online shopping buyers do not have enough information about sellers and cannot inspect the products before purchasing them. To help buyers find reliable sellers, online marketplaces deploy Trust and Reputation Management (TRM) systems. These systems aggregate buyers’ feedback about the sellers they have interacted with and about the products they have purchased, to inform users within the marketplace about the sellers and products before making purchases. Thus positive customer feedback has become a valuable asset for each seller in order to attract more business. This naturally creates incentives for cheating, in terms of introducing fake positive feedback. Therefore, an important responsibility of TRM systems is to aid buyers find genuine feedback (reviews) about different sellers. Recent TRM systems achieve this goal by selecting and assigning credible advisers to any new customer/buyer. These advisers are selected among the buyers who have had experience with a number of sellers and have provided feedback for their services and goods. As people differ in their tastes, the buyer feedback that would be most useful should come from advisers with similar tastes and values. In addition, the advisers should be honest, i.e. provide truthful reviews and ratings, and not malicious, i.e. not collude with sellers to favour them or with other buyers to badmouth some sellers. Defining the boundary between dishonest and honest advisers is very important. However, currently, there is no systematic approach for setting the honesty threshold which divides benevolent advisers from the malicious ones. The thesis addresses this problem and proposes a market-adaptive honesty threshold management mechanism. In this mechanism the TRM system forms a feedback system which monitors the current status of the e-marketplace. According to the status of the e-marketplace the feedback system improves the performance utilizing PID controller from the field of control systems. The responsibility of this controller is to set the the suitable value of honesty threshold. The results of experiments, using simulation and real-world dataset show that the market-adaptive honesty threshold allows to optimize the performance of the marketplace with respect to throughput and buyer satisfaction

Moral Courage in Organizations

{Excerpt} Moral courage is the strength to use ethical principles to do what one believes is right even though the result may not be to everyone’s liking or could occasion personal loss. In organizations, some of the hardest decisions have ethical stakes: it is everyday moral courage that sets an organization and its members apart. Courage is the ability to confront danger, fear, intimidation, pain, or uncertainty. Physical courage is fortitude in the face of death (and its threat), hardship, or physical pain. Moral courage, the form the attribute nowadays refers to, is put simply the ability to act rightly in the face of discouragement or opposition,possibly and knowingly running the risk of adverse personal consequences. Springing from ethics—notably integrity, responsibility, compassion, and forgiveness—it is thequality of mind or spirit that enables a person to withstand danger, difficulty, or fear; persevere; and venture. Comprehensively—as said by Christopher Rate et al., it is awillful, intentional act, executed after mindful deliberation, involving objective substantial risk to the bearer, and primarily motivated to bring about a noble good or worthy enddespite, perhaps, the presence of the emotion of fear

The Art of Crafting Formal-Informal Linkages: On the Enduring Appeal of Belo Horizonte’s Hippie Fair

Peter Mörtenböck and Helge Mooshammer explore the accelerating hybridization of formal and informal economic practices underway at one of Latin America’s largest open-air markets, Belo Horizonte’s “Hippie Fair,” officially called the Feira de Arte, Artesanato e Produtores de Variedades da Avenida Afonso Pena. Belying its uniform and ordered appearance, the fair’s multi-actor structure highlights the proliferation of formal-informal linkages that affect not only street vendors, manufacturers, and administrative bodies, but also large segments of the city’s population. The authors argue that two decades of globalization, in conjunction with the recent economic crisis and emerging forms of self-organized economies, have substantially altered the relationship between the informal and formal sectors, both conceptually and practically. They show the importance and ambivalence of the ongoing spatial transformation of informal markets in generating new economic climates that, in some cases, create alternative socioeconomic places, and in others, an expansion of capitalist markets

Promoting Honesty in Electronic Marketplaces: Combining Trust Modeling and Incentive Mechanism Design

This thesis work is in the area of modeling trust in multi-agent systems, systems of software agents designed to act on behalf of users (buyers and sellers), in applications such as e-commerce. The focus is on developing an approach for buyers to model the trustworthiness of sellers in order to make effective decisions about which sellers to select for business. One challenge is the problem of unfair ratings, which arises when modeling the trust of sellers relies on ratings provided by other buyers (called advisors). Existing approaches for coping with this problem fail in scenarios where the majority of advisors are dishonest, buyers do not have much personal experience with sellers, advisors try to flood the trust modeling system with unfair ratings, and sellers vary their behavior widely. We propose a novel personalized approach for effectively modeling trustworthiness of advisors, allowing a buyer to 1) model the private reputation of an advisor based on their ratings for commonly rated sellers 2) model the public reputation of the advisor based on all ratings for the sellers ever rated by that agent 3) flexibly weight the private and public reputation into one combined measure of the trustworthiness of the advisor. Our approach tracks ratings provided according to their time windows and limits the ratings accepted, in order to cope with advisors flooding the system and to deal with changes in agents' behavior. Experimental evidence demonstrates that our model outperforms other models in detecting dishonest advisors and is able to assist buyers to gain the largest profit when doing business with sellers. Equipped with this richer method for modeling trustworthiness of advisors, we then embed this reasoning into a novel trust-based incentive mechanism to encourage agents to be honest. In this mechanism, buyers select the most trustworthy advisors as their neighbors from which they can ask advice about sellers, forming a social network. In contrast with other researchers, we also have sellers model the reputation of buyers. Sellers will offer better rewards to satisfy buyers that are well respected in the social network, in order to build their own reputation. We provide precise formulae used by sellers when reasoning about immediate and future profit to determine their bidding behavior and the rewards to buyers, and emphasize the importance for buyers to adopt a strategy to limit the number of sellers that are considered for each good to be purchased. We theoretically prove that our mechanism promotes honesty from buyers in reporting seller ratings, and honesty from sellers in delivering products as promised. We also provide a series of experimental results in a simulated dynamic environment where agents may be arriving and departing. This provides a stronger defense of the mechanism as one that is robust to important conditions in the marketplace. Our experiments clearly show the gains in profit enjoyed by both honest sellers and honest buyers when our mechanism is introduced and our proposed strategies are followed. In general, our research will serve to promote honesty amongst buyers and sellers in e-marketplaces. Our particular proposal of allowing sellers to model buyers opens a new direction in trust modeling research. The novel direction of designing an incentive mechanism based on trust modeling and using this mechanism to further help trust modeling by diminishing the problem of unfair ratings will hope to bridge researchers in the areas of trust modeling and mechanism design

Reputation Systems: A framework for attacks and frauds classification

Reputation and recommending systems have been widely used in e-commerce, as well as online collaborative networks, P2P networks and many other contexts, in order to provide trust to the participants involved in the online interaction. Based on a reputation score, the e-commerce user feels a sense of security, leading the person to trust or not when buying or selling. However, these systems may give the user a false sense of security due to their gaps. This article discusses the limitations of the current reputation systems in terms of models to determine the reputation score of the users. We intend to contribute to the knowledge in this field by providing a systematic overview of the main types of attack and fraud found in those systems, proposing a novel framework of classification based on a matrix of attributes. We believe such a framework could help analyse new types of attacks and fraud. Our work was based on a systematic literature review methodology.info:eu-repo/semantics/publishedVersio

Trust-Promoting Seals in Green Information Systems: The Case of Smart Meters and Privacy

Green Information Systems (IS) often require to obtain data in order to assess environmental outcomes and improve sustainable behaviours. As a result, privacy concerns can act as a barrier to the utilization of Green IS. We explore the case of smart meters, which track users’ personal energy usage data and provide real-time information, thus allowing users to reduce energy consumption. In this research-in-progress paper, we report on the development of a research model and experimental design to test the impact of trust seals, which can help to build trust and alleviate privacy concerns. For this reason, we refer to green energy and privacy seals that assess and certify the energy efficiency and privacy practices of companies. We further explore opt-out mechanisms, which give consumers the possibility to opt out of smart meter data collection that can also lead to a reduction of consumers’ privacy concerns with smart meters

Trust Transfer in the Sharing Economy - A Survey-Based Approach

The sharing economy is experiencing explosive growth around the globe in which trust plays a crucial role and builds the foundation of the services. With the rise of the sharing economy and the increasing numbers of cross-contextual users, this research aims at the lack of trust transference possibilities across the Peer-to-Peer applications and has the goal to find out whether and how trust can be transferred between the platforms, so that new users do not have to create their reputation from scratch every time they join a new platform. First, this research provides an in-depth literature review of trust transfer theories. Secondly, a conceptual research model for the role of the imported trust in the context of the sharing economy is outlined and analysed by proposing and evaluating a questionnaire using structural equation modeling. Throughout the study, a three-dimensional scale of trust, i.e. ability, benevolence and integrity, is validated in the context of the sharing economy. The experimental study shows that both the overall and subdimensional trust in the provider is directly affected by the overall trust in the platform, the perceived reputation as well as the perceived social presence. The study also provides empirical evidence for the existence of trust transferability. The findings show that in addition to the immanent ratings, imported ratings also significantly affect the perceived reputation of the provider positively. Finally, this paper discusses further details of the trust transfer processes and broadens implications for future research. The sharing economy is experiencing explosive growth around the globe in which trust plays a crucial role and builds the foundation of the services. With the rise of the sharing economy and the increasing numbers of cross-contextual users, this research aims at the lack of trust transference possibilities across the Peer-to-Peer applications and has the goal to find out whether and how trust can be transferred between the platforms, so that new users do not have to create their reputation from scratch every time they join a new platform. First, this research provides an in-depth literature review of trust transfer theories. Secondly, a conceptual research model for the role of the imported trust in the context of the sharing economy is outlined and analysed by proposing and evaluating a questionnaire using structural equation modeling. Throughout the study, a three-dimensional scale of trust, i.e. ability, benevolence and integrity, is validated in the context of the sharing economy. The experimental study shows that both the overall and subdimensional trust in the provider is directly affected by the overall trust in the platform, the perceived reputation as well as the perceived social presence. The study also provides empirical evidence for the existence of trust transferability. The findings show that in addition to the immanent ratings, imported ratings also significantly affect the perceived reputation of the provider positively. Finally, this paper discusses further details of the trust transfer processes and broadens implications for future research.  Keywords: Sharing Economy, Trust, Trust Transfer, Reputation, Peer-to-pee