Determinants and Consequences of Social Trust*

This article provides an overview of social trust, examining its various aspects and components. Trust is best understood in a sociological sense by focusing on its important relational characteristic. Following this lead, the article discusses briefly how social trust relates to social capital and examines factors that shape the development of social trust, along with outcomes related to variations in trust, classifying them by analytical level (i.e., individual, community, group, organizational, and societal). The article concludes by assessing the strengths and weaknesses of existing research and by identifying some important questions that have not yet been adequately addressed.     

Maximum Likelihood Inference for Log-linear Models Subject to Constraints of Double Monotone Dependence

To model an hypothesis of double monotone dependence between two ordinal categorical variables A and B usually a set of symmetric odds ratios defined on the joint probability function is subject to linear inequality constraints. Conversely in this paper two sets of asymmetric odds ratios defined, respectively, on the conditional distributions of A given B and on the conditional distributions of B given A are subject to linear inequality constraints. If the joint probabilities are parameterized by a saturated log-linear model, these constraints are nonlinear inequality constraints on the log-linear parameters. The problem here considered is a non-standard one both for the presence of nonlinear inequality constraints and for the fact that the number of these constraints is greater than the number of the parameters of the saturated log-linear model.This work has been supported by the COFIN 2002 project, references 2002133957_002, 2002133957_004. Preliminary findings have been presented at SIS (Società Italiana di Statistica) Annual Meeting, Bari, 2004.     

Personality and psychopathological profiles in individuals exposed to mobbing

Increasingly, mental health and medical professionals have been asked to assess claims of psychological harm arising from harassment at the workplace, or "mobbing." This study assessed the personality and psychopathological profiles of 146 individuals exposed to mobbing using validity, clinical, and content scales of the Minnesota Multiphasic Personality Inventory 2. Profiles and factor analyses were obtained. Two major dimensions emerged among those exposed to mobbing: (a) depressed mood, difficulty in making decisions, change-related anguish, and passive-aggressive traits (b) somatic symptoms, and need for attention and affection. This cross-sectional pilot study provides evidence that personality profiles of mobbing victims and psychological damage resulting from mobbing may be evaluated using standardized assessments, though a longitudinal study is needed to delineate cause-and-effect relationships.     

Drivers of fish assemblage structures in a Neotropical urban watershed

Urban Ecosystems - Urbanization results in major changes in stream morphology, hydrology, and water quality; the consequences on fish assemblage of Neotropical urban streams remain poorly...     

Theoretical results on the discrete Weibull distribution of Nakagawa and Osaki

In this paper, we discuss some theoretical results and properties of the discrete Weibull distribution, which was introduced by Nakagawa and Osaki [The discrete Weibull distribution. IEEE Trans Reliab. 1975;24:300–301]. We study the monotonicity of the probability mass, survival and hazard functions. Moreover, reliability, moments, p-quantiles, entropies and order statistics are also studied. We consider likelihood-based methods to estimate the model parameters based on complete and censored samples, and to derive confidence intervals. We also consider two additional methods to estimate the model parameters. The uniqueness of the maximum likelihood estimate of one of the parameters that index the discrete Weibull model is discussed. Numerical evaluation of the considered model is performed by Monte Carlo simulations. For illustrative purposes, two real data sets are analyzed.     

Efficient Bayesian inference in generalized inverse gamma processes for stochastic volatility

This paper develops a novel and efficient algorithm for Bayesian inference in inverse Gamma stochastic volatility models. It is shown that by conditioning on auxiliary variables, it is possible to sample all the volatilities jointly directly from their posterior conditional density, using simple and easy to draw from distributions. Furthermore, this paper develops a generalized inverse gamma process with more flexible tails in the distribution of volatilities, which still allows for simple and efficient calculations. Using several macroeconomic and financial datasets, it is shown that the inverse gamma and generalized inverse gamma processes can greatly outperform the commonly used log normal volatility processes with Student’s t errors or jumps in the mean equation.     

Agency and fatalism in older Appalachian women’s information seeking about gynecological cancer

Researchers consider older women in rural Appalachia to have low levels of agency and high levels of fatalism regarding decision making about cancer treatment. Using the life course perspective, we examined older women’s agency with information seeking about gynecological cancer. Semistructured interviews with 20 White women living in central Appalachia revealed four trajectories: Surrendering Control, Accepting Death, Self-Care, and Advocacy, each with its own forms of agency. Some women experienced personal transformation, increased self-efficacy, and a passion for community empowerment. Fatalism was not understood apart from placing trust in medical expertise. We implore researchers to further explore rural expressions of agency.     

Data‐Driven Supply Chain Orientation and Financial Performance: The Moderating Effect of Innovation‐Focused Complementary Assets

Drawing on the complementary assets framework, this study explores the moderating effect of innovation‐focused complementary assets (CA‐I) on the relationship between a data‐driven supply chain orientation (DDSCO) and firm financial performance. To test the moderating effect, survey data gathered from 329 manufacturing firms in China were analysed using a moderated regression analysis. The results indicate that DDSCO has a significant positive effect on financial performance, and that capabilities for product and process innovation function as complementary assets moderating the DDSCO–performance relationship. The findings suggest that innovation‐focused complementary assets are performance differentiators when paired with a DDSCO and explain why some firms obtain financial benefits from the development of a DDSCO while others do not. Specifically, competitive advantage from a DDSCO may not be realized unless CA‐I and potentially other complementary assets are harnessed, thus providing useful practical guidance to managers. Hence, the study provides empirical support for the complementary assets framework.     

Ecohydrological model for the quantification of ecosystem services provided by urban street trees

Urban green spaces have been recognized as an important source of ecosystem services, whose quantification requires the determination of quantities related to energy, water, carbon and soil nutrient content. In this paper we propose a stochastic ecohydrological model that couples two existing models for water and nutrients in urban soil at the single street-tree scale. The model input are rainfall and irrigation, for water, and deposition and fertilization, for nitrogen, while the output are evapotranspiration, runoff and deep percolation, for water, and plant uptake and leaching, for nitrogen. The various terms are related to the amount of paved and impervious surfaces that surround the tree trunk and regulate the water and nutrient fluxes in and out the soil. Particular attention is paid to the effects of seasonal variations on plant water and nutrients through a temporal variation of the hydrologic variables (i.e., temperature and rainfall intensity and frequencies). The average model outputs are preliminarily compared with the scant existing literature data, supporting the model application to cities with different climatic conditions. The model results are used to estimate the potential for ecosystem services like tree cooling effects, soil carbon sequestration or storm-water management. Because of the minimal structure of the proposed model, it requires a very low amount of data, while accounting for the stochastic input of rainfall. In the context of climate change and increasing urbanization, the model may offer useful indications to urban planners to enhance ecosystem services while minimizing irrigation, fertilization and their related costs.