Adaptive Build-up and Breakdown of Trust: An Agent Based Computational Approach

This article employs Agent-Based Computational Economics (ACE) to investigate whether, and under what conditions, trust is viable in markets. The emergence and breakdown of trust is modeled in a context of multiple buyers and suppliers. Agents develop trust in a partner as a function of observed loyalty. They select partners on the basis of their trust in the partner and potential profit, with adaptive weights. On the basis of realized profits, they adapt the weight they attach to trust relative to profitability, and their own trustworthiness, modeled as a threshold of defection. Trust and loyalty turn out to be viable under fairly general conditions.     

Consumer trust in B2C e-Commerce and the importance of social presence: experiments in e-Products and e-Services

Reducing social uncertainty—understanding, predicting, and controlling the behavior of other people—is a central motivating force of human behavior. When rules and customs are not sufficient, people rely on trust and familiarity as primary mechanisms to reduce social uncertainty. The relative paucity of regulations and customs on the Internet makes consumer familiarity and trust especially important in the case of e-Commerce. Yet the lack of an interpersonal exchange and the one-time nature of the typical business transaction on the Internet make this kind of consumer trust unique, because trust relates to other people and is nourished through interactions with them.This study validates a four-dimensional scale of trust in the context of e-Products and revalidates it in the context of e-Services. The study then shows the influence of social presence on these dimensions of this trust, especially benevolence, and its ultimate contribution to online purchase intentions.     

Trust and health in Eastern Europe: Conceptions of a new society

Little attention has been paid to why trends and levels of mortality and morbidity differ in Eastern Europe and few studies have addressed people's own perceptions of their new political system – perceptions which per se may be important for social development. The aim of the present study was to analyse the extent to which trust and economic circumstances affect self‐rated health in Poland, Estonia and Russia and how much health differences between the countries can be explained by these factors. A better economy and higher trust were related to better individual health, while economic factors seemed most important for inter‐country differences. It is probable that both institutional factors and individual perceptions contribute to people's well‐being, but in terms of social policy, an improved welfare system may be the most effective way forward.     

Consumer trust repair: A critical literature review

Consumers are fundamental to organisational functioning and survival. Their loyalty, commitment, product acceptance and good long-term relationships with firms and brands are underpinned by their trust. Unfortunately, over the last decade or so, we have witnessed some of the more spectacular violations of consumer trust in the history of business. This has led to negative consequences, such as loss of competitive advantage, rage, lack of commitment and decrease in turnover. Consequently, study of trust repair has become an important theoretical concern for a growing number of trust scholars. This article reviews and synthesises existing theory and research on the topic. It first sketches general characteristics of the consumer trust repair literature, including its meta-theoretical underpinning. It then identifies specific strategies associated with consumer trust repair and synthesises them into five categories of trust repair strategies. In addition, this paper highlights theoretical processes that explain why/how trust repair strategies work. Third, the paper proposes six fruitful avenues for future research. This study contributes to the field of consumer trust repair research by critically reviewing and synthesising emerging theory and research on strategies associated with consumer trust repair, by showing why and how these strategies work and by identifying most fruitful research areas.     

Some Results Based on a Version of the Generalized Dynamic Entropies

We propose new dynamic measures of uncertainty based on the notion of generalized dynamic entropy introduced in Di Crescenzo and Longobardi (2006). These can uniquely determine distribution functions in continuous and discrete cases, and the characterizations of some well-known distributions are provided. We also define some orderings and aging notions based on the generalized dynamic measures, and prove some of their properties, obtaining as corollaries results that have recently appeared in the literature.     

Coalition-building and the forging of solidarity across difference and inequality

Diverse coalitions hold great potential for social movements, but they also face tremendous challenges. In this article, I review the literature on diverse alliances with a focus on how trust, commitment, and ultimately, solidarity can be developed and sustained across divides. The article begins by discussing the needs of diverse alliances to build trust and commitment, and the coalitional characteristics deemed vital for doing so, with a focus on shared neutral space, ongoing interaction, and social ties and bridgebuilders. Five coalitional processes and practices are identified and discussed that have been empirically found or theorized to be imperative for cultivating solidarity across difference and inequality. These processes include (a) uniting around shared principles while engaging difference; (b) acknowledging and managing inequalities; (c) making space for each other; (d) attention to managing conflicts; and (e) actions that confirm the shared commitments and negotiated identity. I conclude by evaluating the state of research on developing and sustaining alliances across divides.     

The performance of alternative estimators for the probit model with first-order serial correlation 1

The purpose of the paper is to evaluate the relative performance of two generalized conditional moment (GCM) estimators in terms of their mean squared errors, for the Probit model with first-order serial correlation. The first estimator is a linearized one-step estimator described by Poirier and Ruud (1988). The second one is defined in the present paper. Monte Car10 experiments suggest that the GCM estimators outperform the ordinary Probit estimator. The two GCM estimators do almost equally well, except that the second one may be easier to calculate, especially in large samples.     

Results concerning the generalized partially linear single-index model

The central topic of this article is the estimation of parameters of the generalized partially linear single-index model (GPLSIM). Two numerical optimization procedures are presented and an S-plus program based on these procedures is compared to a program by Wand in a simulation setting. The results from these simulations indicate that the estimates for the new procedures are as good, if not better, than Wand's. Also, this program is much more flexible than Wand's since it can handle more general models. Other simulations are also conducted. The first compares the effects of using linear interpolation versus spline interpolation in an optimization procedure. The results indicate that by using spline interpolation one gets more stable estimates at a cost of increased computational time. A second simulation was conducted to assess the performance of a method for estimating the variance of alpha. A third set of simulations is carried out to determine the best criterion for testing that one of the elements of alpha is equal to zero. The GPLSIM is applied to a water quality data set and the results indicate an interesting relationship between gastrointestinal illness and turbidity (cloudiness) of drinking water.     

Tests for generalized exponential laws based on the empirical Mellin transform

Recently, many standard families of distributions have been generalized by exponentiating their cumulative distribution function (CDF). In this paper, test statistics are constructed based on CDF–transformed observations and the corresponding moments of arbitrary positive order. Simulation results for generalized exponential distributions show that the proposed test compares well with standard methods based on the empirical distribution function.     

Bayesian analysis of multivariate stochastic volatility with skew return distribution

Multivariate stochastic volatility models with skew distributions are proposed. Exploiting Cholesky stochastic volatility modeling, univariate stochastic volatility processes with leverage effect and generalized hyperbolic skew t-distributions are embedded to multivariate analysis with time-varying correlations. Bayesian modeling allows this approach to provide parsimonious skew structure and to easily scale up for high-dimensional problem. Analyses of daily stock returns are illustrated. Empirical results show that the time-varying correlations and the sparse skew structure contribute to improved prediction performance and Value-at-Risk forecasts.