领导风格对员工知识隐藏行为的影响:心理安全感的中介效应和动机氛围的调节效用

企业知识隐藏行为会抑制创新与合作氛围,探究员工知识隐藏行为的诱因对企业团队氛围和价值实现具有重要意义。本研究基于社会交换理论,探索不同类型领导风格与员工知识隐藏行为之间的关系以及内在影响机制,具体包括:剖析谦卑型领导和辱虐型领导与员工知识隐藏行为之间的关系;探究员工心理安全感是否发挥中介作用;分析心理安全感与知识隐藏的关系是否受到不同类型团队动机氛围的调节影响。本研究通过对长三角地区某省的6家科技型公司共820名员工进行问卷调查,利用层次回归模型进行数据处理,结果显示:不同风格的领导行为对知识隐藏行为都产生影响,心理安全感发挥着重要的中介作用。具体而言,谦卑型领导通过心理安全感对知识隐藏行为产生负向影响,辱虐型领导通过心理安全感对知识隐藏行为产生正向影响。此外,动机氛围起到调节作用,其中绩效氛围正向调节员工心理安全感与其知识隐藏行为之间的关系,掌控氛围负向调节员工心理安全感与其知识隐藏行为之间的关系。本研究从领导力视角深化了对于员工知识隐藏行为诱因的认识,从情境视角为心理安全感和知识隐藏的关系构建了边界条件,进一步丰富了领导力、组织行为管理等理论;同时,本研究也为企业知识隐藏行为管理提供了一条清晰的解决思路。为了最大限度抑制知识隐藏行为,企业领导者需要多展示谦卑型的特质,对员工观点持开放态度,愿意吸纳和听取他人意见;要培养员工的心理安全感,让员工在知识分享中能够毫无顾忌;采用鼓励竞争的方式营造团队氛围,提升团队的绩效氛围等。未来将进一步采用多变量来源、多样化情境进行验证,将相关研究结论从中国科技型企业推广到其他研究情境中,从而提高研究结论的外部有效性。     

企业战略联盟风险防范体系的架构研究

在对企业战略联盟存在的风险及规避措施进行理论透析的基础上,给出了企业战略联盟伙伴选择机制的权值排序模型。提出了企业战略联盟的3种风险防范整合架构,并论述了三者之间的相关关系。最后通过实例对企业战略联盟伙伴选择机制的权值排序模型和风险防范整合体系进行了验证。     

业务外包风险分析与控制

结合现代企业理论中的交易费用理论和“委托-代理”理论,对业务外包风险进行了深入的剖析,详细分析了外包决策和执行两个阶段的风险,并提出了相应的风险控制策略。     

论概率安全评价中的组织风险因素

核电站组织风险已经成为核电站安全运行重要的影响因素,在概率安全评价中考虑组织风险因素是核电安全研究的重要课题。文章在建立组织风险因素与PSA之间转换的概念框架的基础上,对组织风险因素进行分类。分类后的组织风险因素受人员行为形成因子的影响,其影响在人因可靠性分析中进行分析。计算和评估这些人员行为形成因子对于事故后操纵员的影响可以计算组织因素对核电站安全的影响。     

会计核算软件逆向操作的利弊分析

为了迎合财务会计的需求,软件公司开发了不少带有逆向操作功能的软件,虽然在使用中对更正会计差错、减少系统数据冗余和提高工作质量等起到了一定的作用,但同样也给财务会计系统的安全带来了威胁。这里在简略介绍会计核算软件逆向操作内涵和功能作用的基础上,针对其可能产生的隐患和危害等进行了分析,并针对其弊端和可能的风险提出了防范性完善措施。     

Community Wise: The Development of an Anti-Oppression Model to Promote Individual and Community Health

Communities with histories of oppression have shown great resilience, yet few health interventions focus on structural oppression as a contributor to health problems in these communities. This article describes the development and active ingredients of Community Wise, a unique behavioral health intervention designed to reduce substance use frequency, related health risk behaviors, and recidivism among individuals with a history of incarceration and substance abuse residing in distressed and predominantly African American communities. Community Wise, developed through the collaborative efforts of a board of service providers, researchers, consumers, and government officials, is a 12-week group intervention that aims to address behavioral health problems by raising critical consciousness in distressed communities.     

Emotional Climate in Families Experiencing Homelessness: Associations with Child Affect and Socioemotional Adjustment in School

This study examined associations among family‐level risks, emotional climate, and child adjustment in families experiencing homelessness. Emotional climate, an indirect aspect of emotion socialization, was indexed by parents’ expressed emotion while describing their children. Sociodemographic risk and parent internalizing distress were hypothesized to predict more negativity and less warmth in the emotional climate. Emotional climate was expected to predict observer‐rated child affect and teacher‐reported socioemotional adjustment, mediating effects of risk. Participants were 138 homeless parents (64 percent African‐American) and their four‐ to six‐year‐old children (43.5 percent male). During semi‐structured interviews, parents reported demographic risks and internalizing distress and completed a Five Minute Speech Sample about their child, later rated for warmth and negativity. Children's positive and negative affect were coded from videotapes of structured parent‐child interaction tasks. Socioemotional adjustment (externalizing behavior, peer acceptance, and prosocial behavior) was reported by teachers a few months later. Hypotheses were partially supported. Parent internalizing distress was associated with higher parent negativity, which was linked to more negative affect in children, and parent warmth was associated with children's positive affect. Neither emotional climate nor child affect predicted teacher‐reported externalizing behavior or peer acceptance, but parental negativity and male sex predicted lower prosocial behavior in the classroom. Future research directions and clinical implications are discussed.     

Action,Technology, and the Homogenisation of Place: Why Climate Change is Antithetical to Political Action

According to Hannah Arendt, the concept of ‘political action’ is a fundamental component of the human condition because it encapsulates how the uniqueness of each human being intersects to create unpredictable political initiatives and effects. Recently, despite being one of the most daunting political challenges ever faced by humanity, there has been a noted collective action failure, or inaction, concerning the global threat of anthropogenic climate change. Why? This article seeks to explain this political inaction in a new way: by examining the metaphysical role that technology plays in disclosing the climate as a thinkable and global object. After applying the philosophy of Martin Heidegger to the complex mathematical general circulation models (GCMs) used by the Intergovernmental Panel on Climate Change (IPCC), this article details how the metaphysics underlying GCMs manifests the perceivable world by ‘enframing’ it, or by implicitly representing subjects, objects, and Nature itself, as a predictable, calculable, and orderable relation of static forces. When this metaphysical and mathematical uniformity constructs the climate as a calculable object that is globalised through the IPCC, it is ultimately found to be contradictory to the distinctness and unpredictability necessary for distinct human action to occur. Paradoxically, therefore, political action is argued to be metaphysically antithetical to the technologically enframed science, politics, and discourse, of global climate change itself. The importance of distinct and plural human places, when filtered through GCMs, becomes subsumed by the climate as a homogenous, calculative, and politically inactive, global object.     

Community Resilience and Decision Theory Challenges for Catastrophic Events

Extreme and catastrophic events pose challenges for normative models of risk management decision making. They invite development of new methods and principles to complement existing normative decision and risk analysis. Because such events are rare, it is difficult to learn about them from experience. They can prompt both too little concern before the fact, and too much after. Emotionally charged and vivid outcomes promote probability neglect and distort risk perceptions. Aversion to acting on uncertain probabilities saps precautionary action; moral hazard distorts incentives to take care; imperfect learning and social adaptation (e.g., herd‐following, group‐think) complicate forecasting and coordination of individual behaviors and undermine prediction, preparation, and insurance of catastrophic events. Such difficulties raise substantial challenges for normative decision theories prescribing how catastrophe risks should be managed. This article summarizes challenges for catastrophic hazards with uncertain or unpredictable frequencies and severities, hard‐to‐envision and incompletely described decision alternatives and consequences, and individual responses that influence each other. Conceptual models and examples clarify where and why new methods are needed to complement traditional normative decision theories for individuals and groups. For example, prospective and retrospective preferences for risk management alternatives may conflict; procedures for combining individual beliefs or preferences can produce collective decisions that no one favors; and individual choices or behaviors in preparing for possible disasters may have no equilibrium. Recent ideas for building “disaster‐resilient” communities can complement traditional normative decision theories, helping to meet the practical need for better ways to manage risks of extreme and catastrophic events.     

Inference for Weibull distribution under adaptive Type-I progressive hybrid censored competing risks data

In this paper, a competing risks model is considered under adaptive type-I progressive hybrid censoring scheme (AT-I PHCS). The lifetimes of the latent failure times have Weibull distributions with the same shape parameter. We investigate the maximum likelihood estimation of the parameters. Bayes estimates of the parameters are obtained based on squared error and LINEX loss functions under the assumption of independent gamma priors. We propose to apply Markov Chain Monte Carlo (MCMC) techniques to carry out a Bayesian estimation procedure and in turn calculate the credible intervals. To evaluate the performance of the estimators, a simulation study is carried out.