Trust beyond reputation: A computational trust model based on stereotypes

Models of computational trust support users in taking decisions. They are commonly used to guide users' judgements in online auction sites; or to determine quality of contributions in Web 2.0 sites. However, most existing systems require historical information about the past behavior of the specific agent being judged. In contrast, in real life, to anticipate and to predict a stranger's actions in absence of the knowledge of such behavioral history, we often use our "instinct"- essentially stereotypes developed from our past interactions with other "similar" persons. In this paper, we propose StereoTrust, a computational trust model inspired by stereotypes as used in real-life. A stereotype contains certain features of agents and an expected outcome of the transaction. When facing a stranger, an agent derives its trust by aggregating stereotypes matching the stranger's profile. Since stereotypes are formed locally, recommendations stem from the trustor's own personal experiences and perspective. Historical behavioral information, when available, can be used to refine the analysis. According to our experiments using Epinions.com dataset, StereoTrust compares favorably with existing trust models that use different kinds of information and more complete historical information

A Woman’s Worth

This Article examines three traditionally “taboo trades”: (1) the sale of sex, (2) compensated egg donation, and (3) commercial surrogacy. The Article purposely invokes examples in which the compensated provision of goods or services (primarily or exclusively by women) is legal, but in which commodification is only partially achieved or is constrained in some way. I argue that incomplete commodification disadvantages female providers in these instances, by constraining their agency, earning power, or status. Moreover, anticommodification and coercion rhetoric is sometimes invoked in these settings by interest groups who, at best, have little interest in female empowerment and, at worst, have economic or political interests at odds with it

Risk Factors for Fraud in Elderly Americans

Americans over age 65 comprise approximately one eighth of our population, but about one third of scam victims. The risk of fraud in this population is of particular concern because it is increasing and the damage is greater; losses have been reported in billions of dollars, and elders typically cannot return to the work force to recoup their losses, which can amount to their life savings and even their independence. This project details the results of an unobtrusive research project consisting of a content analysis of more current literature to identify and examine risk factors of elder fraud

Digital Subjectivation and Financial Markets: Criticizing Social Studies of Finance with Lazzarato

The recently rising field of Critical Data Studies is still facing fundamental questions. Among these is the enigma of digital subjectivation. Who are the subjects of Big Data? A field where this question is particularly pressing is finance. Since the 1990s traders have been steadily integrated into computerized data assemblages, which calls for an ontology that eliminates the distinction between human sovereign subjects and non-human instrumental objects. The latter subjectivize traders in pre-conscious ways, because human consciousness runs too slow to follow the volatility of the market. In response to this conundrum Social Studies of Finance has drawn on Actor-Network Theory to interpret financial markets as technically constructed networks of human and non-human actors. I argue that in order to develop an explicitly critical data study it might be advantageous to refer to Maurizio Lazzarato’s theory of machinic subjugation instead. Although both accounts describe financial digital subjectivation similarly, Lazzarato has the advantage of coupling his description to a clear critique of and resistance to finance

Decisions under Uncertainty in Decentralized Online Markets: Empirical Studies of Peer-to-Peer Lending and Outsourcing

Recent developments in information technologies, especially Web 2.0 technologies, have radically transformed many markets through disintermediation and decentralization. Lower barriers of entry in these markets enable small firms and individuals to engage in transactions that were otherwise impossible. Yet, the issues of informational asymmetry that plague traditional markets still arise, only to be exacerbated by the "virtual" nature of these marketplaces. The three essays of my dissertation empirically examine how participants, many of whom are entrepreneurs, tackle the issue of asymmetric information to derive benefits from trade in two different contexts. In Essay 1, I investigate the role of online social networks in mitigating information asymmetry in an online peer-to-peer lending market, and find that the relational dimensions of these networks are especially effective for this purpose. In Essay 2, I exploit a natural experiment in the same marketplace to study the effect of shared geographical ties on investor decisions, and find that "home bias" is not only robust but also has an interesting interaction pattern with rational decision criteria. In Essay 3, I study how the emergence of new contract forms, enabled by new monitoring technologies, changes the effectiveness of traditional signals that affect a buyers' choice of sellers in online outsourcing. Using a matched-sample approach, I show that the effectiveness of online ratings and certifications differs under pay-for-time contracts versus pay-for-deliverable contracts. In all, the three essays of my dissertation present new empirical evidence of how agents leverage various network ties, signals and incentives to facilitate transactions in decentralized online markets, form transactional ties, and reap the benefits enabled by the transformative power of information technologies

Essays in Financial Economics

In my dissertation, I dive into three specific areas in financial economics. Chapter 1 of my Ph.D. dissertation studies how the boom in off-exchange trading at the market close affects the close price discovery. In recent years, investment banks like Goldman Sachs have started a guaranteed close business where investors looking to buy or sell shares of a certain stock can get a guarantee from the bank to execute their orders at the close price set on the primary exchange. Using the TAQ data and a quasi-experimental shock from NYSE fee cut, we find that when the fraction of trades through guaranteed close increases, the informativeness of close price increases. We develop a model where investors choose which venue to trade in. A bank conducting guaranteed close business competes with the exchange on transaction fees, and gains profit from trading strategically utilizing the order flow information. The bank\u27s trading activity concentrates the price-relevant information into the exchange. Consequently, the guaranteed close improves price discovery at the market close. Chapter 2 of my Ph.D. dissertation studies the long-term effects of experiencing high levels of job demands on the aging and mortality of CEOs. The estimation exploits variation in industry crises and takeover protection. First, we apply neural-network based ML techniques to assess visible signs of aging in pictures of CEOs. We estimate that exposure to a distress shock during the Great Recession increases CEOs\u27 apparent age by one year over the next decade. Second, using hand-collected data on the dates of birth and death for 1,605 CEOs of large, publicly-listed U.S. firms, we estimate the resulting changes in mortality. The hazard estimates indicate that CEOs\u27 lifespandecreases by 1.5 years in response to an industry-wide downturn, and increases by two years when insulated from market discipline via anti-takeover laws. Our findings imply significant health costs of managerial stress, also relative to known health risks. Chapter 3 of my Ph.D. dissertation provides an economically interpretable and easy-to-calculate approximation to optimal portfolio choice over the life cycle. The standard literature that solves the numerical optimal portfolio policy requires complicated backward induction, making it hard to apply for providing financial advice. Real-world financial advisors, on the other hand, tend to neglect the risky nature of human capital and offer advice that is not truly optimal. We bridge the gap by first using a reduced-form regression to predict discount rates of future incomes over an agent\u27s life. Our prediction method achieves an R-squared of more than 90% over a wide range of simulations. Furthermore, by plugging the discount rates we predict into Merton (1969) formula, we obtain an approximate solution that has an average difference within 2% when compared to optimal solution solved through backward induction

Determinantes de la intención de uso de las aplicaciones de banca para móviles: una extensión del modelo TAM clásico

This study has been conducted with financial support received from Excellence Research Project P12-SEJ-1980 of the Andalusia Regional Government and Project ECO2012- 39576 of Spanish Ministry of Economy and Competitiveness.For financial institutions mobile banking has represented a breakthrough in terms of remote banking services. However, many customers remain uncertain due to its security. This study develops a technology acceptance model that integrates the innovation diffusion theory, perceived risk and trust in the classic TAM model in order to shed light on what factors determine user acceptance of mobile banking applications. The participants had to examine a mobile application of the largest European bank. In the proposed model, an approach to external influences was included, theoretically and originally stated by Davis et al. (1989). The proposed model was empirically tested using data collected from an online survey applying structural equation modeling (SEM). The results obtained in this study demonstrate how attitude determine mainly the intended use of mobile apps, discarding usefulness and risk as factors that directly improve its use. Finally, the study shows the main management implications and identifies certain strategies to reinforce this new business in the context of new technological advances.Para las entidades financieras la banca para móviles ha representado una innovación en términos de servicios de banca remota. Sin embargo, muchos clientes siguen considerando incierta su seguridad. Este estudio desarrolla un modelo de aceptación tecnológica que integra, en el modelo TAM clásico, la teoría de la difusión de la innovación, el riesgo percibido y la confianza, a fin de clarificar qué factores determinan la aceptación de las aplicaciones de banca para móviles por parte del usuario. Los participantes tuvieron que examinar una aplicación para móviles perteneciente al mayor banco europeo. En el modelo propuesto, se incluyó una aproximación hacia las influencias externas, que fue establecida de manera teórica y original por parte de Davis et al. (1989). El modelo propuesto se testó empíricamente utilizando la información recolectada mediante una encuesta online, aplicando el modelo de ecuaciones estructurales (SEM). Los resultados obtenidos en el estudio demuestran el modo en que la actitud determina principalmente el uso previsto de las aplicaciones para móvil, descartando la utilidad y el riesgo como factores que mejoran directamente su uso. Por último, el estudio muestra las principales implicaciones para la gestión, e identifica ciertas estrategias de refuerzo de este nuevo negocio en el contexto de los nuevos avances tecnológicos.Excellence Research Project P12-SEJ-1980 of the Andalusia Regional GovernmentProject ECO2012- 39576 of Spanish Ministry of Economy and Competitivenes