Engaging leader – Engaged employees? A cross-lagged study on employee engagement

The goal of this study is to provide a cross-lagged examination of the relationships between engaging leadership, job resources and employee work engagement. We propose a mediation model and we postulate that engaging leadership can increase perceptions of three specific job resources (i.e. autonomy, support from colleagues and opportunities for learning and development) which theoretically correspond to the three facets of engaging leadership (i.e., inspiring, connecting and strengthening, respectively). Subsequently, in keeping with the extant body of Job Demands-Resources (JD-R) research, we link job resources to employee work engagement. Our hypotheses were tested on data collected at two time-points – T1 (N = 759) and T2 (N = 273) –from employees working for a hotel chain in the Netherlands. In line with our expectations, engaging leadership showed a significant cross-lagged relationship with autonomy and support from colleagues, but did not predict learning opportunities and work engagement across time. While we formulated specific hypotheses, we also tested reversed causation relationships. We found no direct effect from engaging leadership on employee work engagement, however, the reversed effect was significant; employee perceptions of engaging leadership were shaped by their own engagement experiences. Importantly, engaged employees at T1 reported more job resources at T2. By providing a cross-lagged examination of our model, we showed that engaging leaders as well as employees’ positive affective state of being engaged, are essential to shaping a resourceful work context. A comprehensive view on the triggers and outcomes of work engagement and engaging leadership is needed, as the traditional unidirectional cause-effect rationale fails to explain how these concepts relate to one another and to employee experiences of job resources.     

Conditional time-dependent nonparametric estimators with an application to healthcare production function

ABSTRACT

By using the probabilistic framework of production efficiency, the paper develops time-dependent conditional efficiency estimators performing a non-parametric frontier analysis. Specifically, by applying both full and quantile (robust) time-dependent conditional estimators, it models the dynamic effect of health expenditure on countries’ technological change and technological catch-up levels. The results from the application reveal that the effect of per capita health expenditure on countries’ technological change and technological catch-up is nonlinear and is subject to countries’ specific income levels.     

德行领导对员工创新行为的影响---工作繁荣与情感承诺的作用*

研究表明，德行领导作为家长式领导的核心维度，对员工行为有重要影响，但现有研究忽视了员工工作状态的重要作用。本文基于自我决定理论，以员工工作繁荣为中介，探讨德行领导对员工创新行为的影响，并从社会认同的情感视角出发，考察了情感承诺在上述关系间的调节作用。研究表明，德行领导对员工工作繁荣与创新行为均存在显著正向影响；员工工作繁荣对其创新行为存在显著正向影响；员工工作繁荣在德行领导与创新行为之间起部分中介作用；情感承诺调节了德行领导对员工创新行为的影响，情感承诺越高，德行领导对员工创新行为的影响越显著。     

学校领导干部的自我发展素质及培养

自我发展素质是学校领导干部综合素质的重要组成部分 ,它反映了社会发展、领导职位和人的本性发展的要求。形成学校领导干部自我发展素质的主要方式是干部培训和教育实践中的探索与反思     

论公共管理实践中的“试点”方法

试点是我国公共管理实践中常用的一种方法,是政策制定的一个有机组成部分,为各级公共管理部门所广泛采用。当前我国公共管理部门所开展的试点越来越多,一方面说明试点是一种有效的公共管理方法,有利于提高制度设计的精度和可控性;另一方面也反映当前改革难度日趋加大,改革的不确定性逐渐增强。在实践中,试点方法又面临诸多挑战,影响了试点的内在效度和外在效度。因此,需要加强相关制度建设,以提高试点方法的内在效度与外在效度。     

梁启超的理性精神与学术态度

从“不为古人所欺，不为世法所挠”、“我物我格，我理我穷”，以及“除心奴”，反“依傍”三个层次论述了梁启超与西方启蒙主义相通的理性精神与学术态度。从理性精神的角度对众所周知的梁启超一生“多变”作了新的阐释。并认为，梁启超与王国维一样，具有“独立之精神，自由之思想”，只不过表现方式有所不同罢了。     

对建构主义教学观的几点认识

围绕建构主义教学观与传统教学观、建构主义教学策略、建构主义教学模式等几个方面 ,就数学教学谈了对建构主义教学观的几点认识     

中共三代领导集体国防教育思想的历史探索

研究表明，中国共产党的三代领导集体对国防教育都很重 视，特别是在和平建设年代，中共领导人能随着国际国内形势的变化而适时调整其国防教育 思想的主要内容，从而使党的国防教育思想更趋成熟，向科学化、系统化、制度化迈进。     

纪念邓小平《党和国家领导制度的改革》发表22周年

本文重温邓小平同志１９８０年８月关于《党和国家领导制度的改革》的讲话，概括指出：一、其三个方面的内容：实行党政分开；适当分权；改革干部人事制度。二、政治体制改革的原则方针：改革必须坚持社会主义方向；改革必须要有利于坚持和加强党的领导。三、政治体制改革的目标取向：发展社会主义民主，走民主的制度化、法制化道路。深刻领会该讲话精神，对于推动我国新世纪的政治体制改革具有重要的理论意义和现实意义。     

A Bayesian Adjustment for Covariate Misclassification with Correlated Binary Outcome Data

Estimated associations between an outcome variable and misclassified covariates tend to be biased when the methods of estimation that ignore the classification error are applied. Available methods to account for misclassification often require the use of a validation sample (i.e. a gold standard). In practice, however, such a gold standard may be unavailable or impractical. We propose a Bayesian approach to adjust for misclassification in a binary covariate in the random effect logistic model when a gold standard is not available. This Markov Chain Monte Carlo (MCMC) approach uses two imperfect measures of a dichotomous exposure under the assumptions of conditional independence and non-differential misclassification. A simulated numerical example and a real clinical example are given to illustrate the proposed approach. Our results suggest that the estimated log odds of inpatient care and the corresponding standard deviation are much larger in our proposed method compared with the models ignoring misclassification. Ignoring misclassification produces downwardly biased estimates and underestimate uncertainty.