Addressing Wealth Inequality Problem in Blockchain-Enabled Knowledge Community with Reputation-Based Incentive Mechanism

An increasing number of online knowledge communities have started incorporating the cut-edge FinTech, such as the tokenbased incentive mechanism running on blockchain, into their ecosystems. However, the improper design of incentive mechanisms may result in reward monopoly, which has been observed to harm the ecosystems of exiting communities. This study is aimed to ensure that the key factors involved in users’ reward distribution can truly reflect their contributions to the community so as to increase the equity of wealth distribution. It is one of the first to comprehensively balance a user’s historical and current contributions in reward distribution, which has not received sufficient attention from extant research. The simulation analysis demonstrates that the proposed solution of amending the existing incentive mechanism by incorporating a refined reputation indicator significantly increases the equity of rewards distribution and effectively enlarges the cost of achieving reward monopoly

Communication, Commitment, and Deception in Social Dilemmas: Experimental Evidence

Social norms of cooperation are studied under several forms of communication. In an experiment, strangers could make public statements before playing a prisoner’s dilemma. The interaction was repeated indefinitely, which generated multiple equilibria. Communication could be used as a tool to either signal intentions to coordinate on Pareto-superior outcomes, to deceive others, or to credibly commit to actions. Some forms of communication did not promote the incidence of efficient Nash play, and sometimes reduced it. Surprisingly, cooperation suffered when subjects could publicly commit to actions.coordination, cheap-talk, deception, indefinitely repeated game, social norms

Achieving reliability and fairness in online task computing environments

Mención Internacional en el título de doctorWe consider online task computing environments such as volunteer computing platforms running on BOINC (e.g., SETI@home) and crowdsourcing platforms such as Amazon Mechanical Turk. We model the computations as an Internet-based task computing system under the masterworker paradigm. A master entity sends tasks across the Internet, to worker entities willing to perform a computational task. Workers execute the tasks, and report back the results, completing the computational round. Unfortunately, workers are untrustworthy and might report an incorrect result. Thus, the first research question we answer in this work is how to design a reliable masterworker task computing system. We capture the workers’ behavior through two realistic models: (1) the “error probability model” which assumes the presence of altruistic workers willing to provide correct results and the presence of troll workers aiming at providing random incorrect results. Both types of workers suffer from an error probability altering their intended response. (2) The “rationality model” which assumes the presence of altruistic workers, always reporting a correct result, the presence of malicious workers always reporting an incorrect result, and the presence of rational workers following a strategy that will maximize their utility (benefit). The rational workers can choose among two strategies: either be honest and report a correct result, or cheat and report an incorrect result. Our two modeling assumptions on the workers’ behavior are supported by an experimental evaluation we have performed on Amazon Mechanical Turk. Given the error probability model, we evaluate two reliability techniques: (1) “voting” and (2) “auditing” in terms of task assignments required and time invested for computing correctly a set of tasks with high probability. Considering the rationality model, we take an evolutionary game theoretic approach and we design mechanisms that eventually achieve a reliable computational platform where the master receives the correct task result with probability one and with minimal auditing cost. The designed mechanisms provide incentives to the rational workers, reinforcing their strategy to a correct behavior, while they are complemented by four reputation schemes that cope with malice. Finally, we also design a mechanism that deals with unresponsive workers by keeping a reputation related to the workers’ response rate. The designed mechanism selects the most reliable and active workers in each computational round. Simulations, among other, depict the trade-off between the master’s cost and the time the system needs to reach a state where the master always receives the correct task result. The second research question we answer in this work concerns the fair and efficient distribution of workers among the masters over multiple computational rounds. Masters with similar tasks are competing for the same set of workers at each computational round. Workers must be assigned to the masters in a fair manner; when the master values a worker’s contribution the most. We consider that a master might have a strategic behavior, declaring a dishonest valuation on a worker in each round, in an attempt to increase its benefit. This strategic behavior from the side of the masters might lead to unfair and inefficient assignments of workers. Applying renown auction mechanisms to solve the problem at hand can be infeasible since monetary payments are required on the side of the masters. Hence, we present an alternative mechanism for fair and efficient distribution of the workers in the presence of strategic masters, without the use of monetary incentives. We show analytically that our designed mechanism guarantees fairness, is socially efficient, and is truthful. Simulations favourably compare our designed mechanism with two benchmark auction mechanisms.This work has been supported by IMDEA Networks Institute and the Spanish Ministry of Education grant FPU2013-03792.Programa Oficial de Doctorado en Ingeniería MatemáticaPresidente: Alberto Tarable.- Secretario: José Antonio Cuesta Ruiz.- Vocal: Juan Julián Merelo Guervó

Communication, Feedbacks and Repeated Moral Hazard with Short-lived Buyers

We show that experience good sellers facing myopic buyers can solve the inherent moral hazard problem by communicating their observation of quality before trade, provided that communication is part of their public track record. Such cheap-talk communication, if trusted, allows market prices to re ect the actual value created, thus providing an immediate reward for the seller's eort which complements the conventional, reputational incentives. Pre-trade communication achieves maximal eciency when truthful and the full eciency as the noise in the seller's observation vanishes. We fully characterize the conditions for communication to improve eciency and the extent to which it does so

Trustnet: a Trust and Reputation Management System in Distributed Environments

With emerging Internet-scale open content and resource sharing, social networks, and complex cyber-physical systems, trust issues become prominent. Despite their rigorous foundations, conventional network security theories and mechanisms are inadequate at addressing such loosely-defined security issues in decentralized open environments.In this dissertation, we propose a trust and reputation management system architecture and protocols (TrustNet), aimed to define and promote trust as a first-class system parameter on par with communication, computation, and storage performance metrics. To achieve such a breakthrough, we need a fundamentally new design paradigm to seamlessly integrate trust into system design. Our TrustNet initiative represents a bold effort to approach this ultimate goal. TrustNet is built on the top of underlying P2P and mobile ad hoc network layer and provides trust services to higher level applications and middleware. Following the TrustNet architecture, we design, implement, and analyze trust rating, trust aggregation, and trust management strategies. Especially, we propose three trust dissemination protocols and algorithms to meet the urgent needs and explicitly define and formulate end-to-end trust. We formulate trust management problems and propose the H-Trust, VectorTrust, and cTrust scheme to handle trust establishment and aggregation issues. We model trust relations as a trust graph in distributed environment to enhance accuracy and efficiency of trust establishment among peers. Leveraging the distributed Bellman-Ford algorithm, stochastic Markov chain process and H-Index algorithm for fast and lightweight aggregation of trust scores, our scheme are decentralized and self-configurable trust aggregation schemes.To evaluate TrustNet management strategies, we simulated our proposed protocols in both unstructured P2P network and mobile ad hoc network to analyze and simulate trust relationships. We use software generated data as well as real world data sets. Particularly, the student contact patterns on the NUS campus is used as our trust communication model. The simulation results demonstrate the features of trust relationship dissemination in real environments and the efficiency, accuracy, scalability and robustness of the TrustNet system.Computer Science Departmen

Communication, commitment, and deception in social dilemmas: experimental evidence

Social norms of cooperation are studied under several forms of communication. In an experiment, strangers could make public statements before playing a prisoner’s dilemma. The interaction was repeated indefinitely, which generated multiple equilibria. Communication could be used as a tool to either signal intentions to coordinate on Pareto-superior outcomes, to deceive others, or to credibly commit to actions. Some forms of communication did not promote the incidence of efficient Nash play, and sometimes reduced it. Surprisingly, cooperation suffered when subjects could publicly commit to actions.

What's in a name and when does it matter? The hot and cold market impacts on underpricing of certification, reputation and conflicts of interest in venture capital backed Korean IPOs

This article analyses the impact of the participation of venture capital (VC) firms on underpricing in 372 businesses brought to IPO during the period 1999-2001 in KOSDAQ. Korea's second-tier stock market, KOSDAQ, has grown dramatically since 1999 and about half of the firms listed in KOSDAQ during this period were VC-backed, thus providing a good testing ground for empirical analysis. We measure VC participation in terms of pre IPO share-ownership by VC firms and attempt to differentiate IPO impacts between VCs grouped in terms of their reputation (measured by their dominance of the VC market, and by their affiliation in terms of ownership by banks and security companies). In estimating impacts we control for a wide range of variables which may affect the extent of underpricing. These include uncertainty inducing factors such as the age, size, profitability, leverage, and technical riskiness (measured by sector and R&D intensity) of the firm brought to IPO. We also control for market conditions using proxies for hot and cold market effects based on the numbers of contemporaneous IPOs, underpricing trends and market price movements. Finally in addition to allowing for the impact of underwriting quality we control for share overhang and price revision effects. We find that, controlling for other relevant factors, pre-IPO ownership by VCs has an insignificantly negative impact on underpricing in both hot and cold markets. However in cold markets reputational effects within the VC group do matter. In those conditions the top 3 VCs and those owned by or affiliated with banks are significantly associated with lower underpricing. The same is true for the quality of underwriting. However in hot market conditions none of these effects are present.Initial Public Offering; Underpricing; Venture Capital; Certification; Conflict of Interest, Informational Advantage

Fraudulent Corporate Signals: Conduct as Securities Fraud

Paying a dividend, repurchasing shares, underpricing an initial public offering, pledging collateral, and borrowing using short-term, instead of long-term debt, are all forms of corporate communications. They are “corporate signals” that tell investors certain things about a company’s operations and current financial position, and about the managers’ confidence in its future performance. This Article provides the first comprehensive analysis of the relationship between corporate signals and securities fraud. The incentive to communicate using corporate signals has increased in recent years, a phenomenon that, I argue, is due to the growing complexity of public corporations, and, importantly, to a number of changes in federal securities laws aimed at better deterring fraud and making companies more transparent. The Article makes three major contributions. First, it identifies this deep connection between the use of corporate signals (both truthful and deceptive) and recent changes in securities laws. Second, it identifies significant social costs associated with corporate signaling, which commentators and policymakers have over-looked: signals can encourage stock bubbles, create costly “signaling races,” and lead to the loss of information about companies and industries. Third, it provides a normative account of how a lawmaker could design antifraud provisions under the securities laws in order to reduce total fraud, instead of simply rechanneling deceptive practices from the realm of written and oral statements to that of deceptive corporate signals