Reputation in multi agent systems and the incentives to provide feedback

The emergence of the Internet leads to a vast increase in the number of interactions between parties that are completely alien to each other. In general, such transactions are likely to be subject to fraud and cheating. If such systems use computerized rational agents to negotiate and execute transactions, mechanisms that lead to favorable outcomes for all parties instead of giving rise to defective behavior are necessary to make the system work: trust and reputation mechanisms. This paper examines different incentive mechanisms helping these trust and reputation mechanisms in eliciting users to report own experiences honestly. --Trust,Reputation

Honor and Violence: An Account of Feuds, Duels, and Honor Killings

We present a theory of honor violence as a form of costly signaling. Two types of honor violence are identified: revenge and purification. Both types are amenable to a signaling analysis whereby the violent behavior is a signal that can be used by out-groups to draw inferences about the nature of the signaling group, thereby helping to solve perennial problems of social cooperation: deterrence and assurance. The analysis shows that apparently gratuitous acts of violence can be part of a system of norms that are Pareto superior to alternatives without such signals. For societies that lack mechanisms of governance to deter aggression or to enforce contracts, norms of honor can be a rational means of achieving these functions. The theory also suggests that cultures can become trapped in inefficient equilibria owing to path-dependent phenomena. In other words, costly signals of honor may continue to be sent even when they are no longer providing useful information

Knowledge management for self-organised resource allocation

Many open systems, such as networks, distributed computing and socio-technical systems address a common problem of how to define knowledge management processes to structure and guide decision-making, coordination and learning. While participation is an essential and desirable feature of such systems, the amount of information produced by its individual agents can often be overwhelming and intractable. The challenge, thus, is how to organise and process such information, so it is transformed into productive knowledge used for the resolution of collective action problems. To address this problem, we consider a study of classical Athenian democracy which investigates how the governance model of the city-state flourished. The work suggests that exceptional knowledge management, i.e. making information available for socially productive purposes, played a crucial role in sustaining its democracy for nearly 200 years, by creating processes for aggregation, alignment and codification of knowledge. We therefore examine the proposition that some properties of this historical experience can be generalised and applied to computational systems, so we establish a set of design principles intended to make knowledge management processes open, inclusive, transparent and effective in self-governed social technical systems. We operationalise three of these principles in the context of a collective action situation, namely self-organised common-pool resource allocation, exploring four governance problems: (a) how fairness can be perceived; (b) how resources can be distributed; (c) how policies should be enforced and (d) how tyranny can be opposed. By applying this operationalisation of the design principles for knowledge management processes as a complement to institutional approaches to governance, we demonstrate empirically how it can guide solutions that satisfice shared values, distribute power fairly, apply "common sense" in dealing with rule violations, and protect agents against abuse of power. We conclude by arguing that this approach to the design of open systems can provide the foundations for sustainable and democratic self-governance in socio-technical systems.Open Acces

Promoting transparency in the NGO sector: Examining the availability and reliability of self-reported data

Amid widespread calls for NGOs to become more accountable and transparent, this work examines the prevalence of discrepancies between what NGOs say and what they do. It does so using a unique dataset of 300 NGOs in Uganda with corresponding beneficiary assessments. Investigating NGO dishonesty with regards to financial transparency and community participation, the study finds a high incidence of misrepresentation among NGOs. Results from a Heckman probit model suggest that the determinants of misrepresentation differ according to the subject matter: the threat of being caught reduces the likelihood of dishonesty about financial transparency, while a desire to ‘save face’ to maintain a good reputation appears to be the main motivator of a misrepresentation of community consultation. The analysis provides tentative indications that NGOs with antagonistic relations with the government may be more likely to hide information and be dishonest. It also lends some support to the view that excessive and unrealistic donor demands may be an obstacle to openness and transparency. The findings of this work caution against an overly naïve and simplistic view of NGOs, and specifically, an overreliance on reported information when regulating, monitoring or surveying NGOs.

Three essays on investors' behavior in FinTech markets

This Doctoral Thesis is composed of three chapters on investors’ behavior in FinTech and digital financial markets. Specifically, chapter 1 looks at the investment behavior of backers in reward-based crowdfunding. Chapter 2 analyzes the behavior of backers in reward-based crowdfunding markets, which stigmatize by social sanctioning new and repeating entrepreneurs for their personal interest, so that they increase their status and influence capacity or decisiveness in the community. Finally, chapter 3 studies the strategic use of on-chain public transactions in the Ethereum blockchain in order to produce signals and make use of this information to make token use and investment decisions. This helps us better understand how the behavior of market participants, particularly users and investors, affects token prices.I acknowledge that this thesis has received financial support from the Spanish Ministry of Science, Innovation and Universities (Grant Ref. FPU18/01051), MEC PGC2018-097187-B-100 and WRDS-UC3M: Infrastructure for large scale data processing, FEDER UNC315-EE-3636, Comunidad de Madrid (EARLYFIN-CM, #S2015/HUM-3353), the Comunidad de Madrid-Spain under the Multiannual Agreement with UC3M in the line of Excellence of University Professors (EPUC3M12), as well as the V PRICIT (Regional Programme of Research and Technological Innovation).Programa de Doctorado en Empresa y Finanzas / Business and Finance por la Universidad Carlos III de Madrid. Mención InternacionalPresidente: Bartolomé Pascual Fuster.- Secretaria: Belén Adoración Nieto Domenech.- Vocales: Anand Mohan Goe

Towards a global participatory platform: Democratising open data, complexity science and collective intelligence

The FuturICT project seeks to use the power of big data, analytic models grounded in complexity science, and the collective intelligence they yield for societal benefit. Accordingly, this paper argues that these new tools should not remain the preserve of restricted government, scientific or corporate élites, but be opened up for societal engagement and critique. To democratise such assets as a public good, requires a sustainable ecosystem enabling different kinds of stakeholder in society, including but not limited to, citizens and advocacy groups, school and university students, policy analysts, scientists, software developers, journalists and politicians. Our working name for envisioning a sociotechnical infrastructure capable of engaging such a wide constituency is the Global Participatory Platform (GPP). We consider what it means to develop a GPP at the different levels of data, models and deliberation, motivating a framework for different stakeholders to find their ecological niches at different levels within the system, serving the functions of (i) sensing the environment in order to pool data, (ii) mining the resulting data for patterns in order to model the past/present/future, and (iii) sharing and contesting possible interpretations of what those models might mean, and in a policy context, possible decisions. A research objective is also to apply the concepts and tools of complexity science and social science to the project's own work. We therefore conceive the global participatory platform as a resilient, epistemic ecosystem, whose design will make it capable of self-organization and adaptation to a dynamic environment, and whose structure and contributions are themselves networks of stakeholders, challenges, issues, ideas and arguments whose structure and dynamics can be modelled and analysed. Graphical abstrac

Econometric Analysis of Pricing and Operational Strategies

This dissertation contains three essays. The first essay, entitled Pricing and Production Flexibility: An Empirical Analysis of the U.S. Automotive Industry, uses a detailed dataset of the U.S. auto industry to examine the relationship between production flexibility and responsive pricing. Our analysis shows that deploying production flexibility is associated with a reduction in observed discounts and with an increase in plant utilization. Our results allow quantifying some of the benefits of production flexibility. The second essay, entitled An Empirical Analysis of Reputation in Online Service Marketplaces, uses a detailed dataset from a leading online intermediary for software development services to empirically examine the role of reputation on choices and prices in service marketplaces. We find that buyers trade off reputation and price and are willing to accept higher bids posted by more reputable bidders. Sellers primarily use a superior reputation to increase their probability of being selected, as opposed to increasing their prices. Our analysis shows that the numerical reputation score has a smaller effect in situations where there exists a previous relationship between buyer and seller, when the seller has certified his or her skills, when the seller is local, or in situations that prompt higher interpersonal trust. The third essay, entitled The Effects of Product Line Breadth: Evidence from the Automotive Industry, studies the effects of product line breadth on market shares and costs, using data from the U.S. automotive industry. Our results show a positive association between product line breadth and market share and production costs. Beyond the effects on production costs, we study the effect of product line breadth on mismatch costs, which arise from demand uncertainty, and we find that product line breadth has a substantial impact on average discounts and inventories. Our results also show that platform strategies can reduce production costs and that a broader product line can provide a hedge against changes in demand conditions