商业企业社会责任现状分析

本文在界定商业企业社会责任的基础上,着重探讨了商业企业的责任管理体系建设、产品质量安全管理、消费者权益保护、提升消费者社会责任意识、责任采购、员工权益保护六个方面的社会责任议题。在此基础上,又通过社会责任发展指数定量研究中国商业企业社会责任发展水平。由此得出,中国商业企业应树立社会责任意识、加强社会责任管理、提高社会责任信息披露水平、主动披露负面社会责任信息。     

企业社会责任的价值相关性研究述评

以往企业社会责任的价值相关性研究的结果显示,两者间的关系是模拟两可的、矛盾的和不确定的。本文在归纳和分析国内外相关研究的多样化结果及其产生原因的基础上,从引入中介变量、考虑时间跨度和解构社会责任三个角度梳理该领域研究的新发展,并提出目前研究中急需进一步解决的问题,为未来研究提供方向性的指引。     

自我效能感与工作资源匹配模型的实证研究——对工作要求—资源模型的扩展

工作要求—资源模型的缓压效应受到组织与学者的关注,文章就该模型以压力主体无差异性为前提下实证结果的不一致性,引入个体能力信念变量——自我效能感,从个体与环境匹配的角度,提出自我效能感与工作资源的匹配,扩展工作要求—资源模型。问卷分析结果显示,自我效能感与工作资源对工作要求与工作压力关系的联合调节效应显著,进而得出以下结论:高自我效能感员工有能力且有意愿利用丰富的工作资源积极应对压力刺激;低自我效能感员工对自身能力缺乏信心且态度消极,在低工作资源情境即组织对工作资源代为控制下,更能有效缓解压力刺激。     

农民工定居决策的影响因素分析——以南京市为例

调查发现,农民工定居城市意愿并不十分强烈,反映出定居决策影响因素的多样性和层次性。农民工定居决策主要受务工收入影响,但也受制于社会的、文化的、心理的和个人特征因素。     

CSR领域对顾客购买意愿影响的实证研究

企业社会责任(CSR)涵盖了不同领域,消费者对企业社会责任不同领域的关注重点各有差异。因此,探索企业社会责任不同领域对消费者购买意愿的影响无疑是一个很好的切入点,也是有利于企业获得竞争力的一种新来源。构建一个包含企业社会责任不同维度、感知质量、企业形象以及消费者购买意愿的概念模型,探索不同领域企业社会责任对消费者购买意愿的影响,以及感知质量和企业形象作为中介变量的合理性。运用SPSS 20.0和AMOS 21.0进行检验,结果显示不同领域企业社会责任对消费者购买意愿具有显著性影响,感知质量和企业形象在不同领域企业社会责任对消费者购买意愿的影响中起到了部分中介效用。     

The role of corporate social responsibility (CSR) and internal CSR communication in predicting employee engagement: Perspectives from the United Arab Emirates (UAE)

This study examined relationships among employees’ perception of CSR, three models of internal CSR communication and employee engagement. The findings, based on 516 valid survey responses from employees across different sectors in the United Arab Emirates, revealed that internal communication of CSR, both one-way and two-way symmetrical, predicted employee perceptions of CSR, with two-way asymmetrical communication being a negative predictor; perceptions of CSR predicted employee engagement; social and sustainable dimensions of CSR most strongly predicted social and affective dimensions of employee engagement; and both two-way symmetrical communication of CSR and employee perceptions of CSR strongly predicted employee engagement. Implications for theory and practice are discussed.     

Statistical modeling for Bayesian extrapolation of adult clinical trial information in pediatric drug evaluation

Children represent a large underserved population of “therapeutic orphans,” as an estimated 80% of children are treated off‐label. However, pediatric drug development often faces substantial challenges, including economic, logistical, technical, and ethical barriers, among others. Among many efforts trying to remove these barriers, increased recent attention has been paid to extrapolation; that is, the leveraging of available data from adults or older age groups to draw conclusions for the pediatric population. The Bayesian statistical paradigm is natural in this setting, as it permits the combining (or “borrowing”) of information across disparate sources, such as the adult and pediatric data. In this paper, authored by the pediatric subteam of the Drug Information Association Bayesian Scientific Working Group and Adaptive Design Working Group, we develop, illustrate, and provide suggestions on Bayesian statistical methods that could be used to design improved pediatric development programs that use all available information in the most efficient manner. A variety of relevant Bayesian approaches are described, several of which are illustrated through 2 case studies: extrapolating adult efficacy data to expand the labeling for Remicade to include pediatric ulcerative colitis and extrapolating adult exposure‐response information for antiepileptic drugs to pediatrics.     

Community-Based Services and Depression from Person-Environment Fit Perspective: Focusing on Functional Impairments and Living Alone

ABSTRACT

Guided by the Person-Environment Fit perspective, we investigated the extent to which personal and environmental factors influence depression among community-dwelling adults. The data came from the special section about community-based service utilization in the 2012 Health and Retirement Study (N=1,710). Although community-based service was not significantly associated with depression after controlling for covariates, respondents with functional limitations and living alone were less likely to be depressed when using community-based services. This study demonstrates the different associations between community-based services and depression depending on personal needs. It discusses the importance of community-based services for aging-in-place policy, particularly among vulnerable populations.     

The effect of different data structures,sample sizes on model fit measures

In this study, our aim was to investigate the changes of different data structures and different sample sizes on the structural equation modeling and the influence of these factors on the model fit measures. Examining the created structural equation modeling under different data structures and sample sizes, the evaluation of model fit measures were performed with a simulation study. As a result of the simulation study, optimization and negative variance estimation problems have been encountered depending on the sample size and changing correlations. It was observed that these problems disappeared either by increasing the sample size or the correlations between the variables in factor. For upcoming studies, the choice of RMSEA and IFI model fit measures can be suggested in all sample sizes and the correlation values for data sets are ensured the multivariate normal distribution assumption.     

Asymptotic distribution of regression correlation coefficient for Poisson regression model

This study treats an asymptotic distribution for measures of predictive power for generalized linear models (GLMs). We focus on the regression correlation coefficient (RCC) that is one of the measures of predictive power. The RCC, proposed by Zheng and Agresti is a population value and a generalization of the population value for the coefficient of determination. Therefore, the RCC is easy to interpret and familiar. Recently, Takahashi and Kurosawa provided an explicit form of the RCC and proposed a new RCC estimator for a Poisson regression model. They also showed the validity of the new estimator compared with other estimators. This study discusses the new statistical properties of the RCC for the Poisson regression model. Furthermore, we show an asymptotic normality of the RCC estimator.