Workplace resources to improve both employee well-being and performance: A systematic review and meta-analysis

Organisations are becoming increasingly aware of the importance of employees in gaining and maintaining competitive advantage. The happy worker–productive worker thesis suggests that workers who experience high levels of well-being also perform well and vice versa; however, organisations need to know how to ensure such happy and productive workers. The present review and meta-analysis identifies workplace resources at the individual, the group, the leader, and the organisational levels that are related to both employee well-being and organisational performance. We examine which types of resources are most important in predicting both employee well-being and performance. We identified 84 quantitative studies published in print and online from 2003 to November 2015. Resources at either of the four levels were related to both employee well-being and performance. We found no significant differences in employee well-being and organisational performance between the four levels of workplace resources, suggesting that interventions may focus on any of these levels. Cross-sectional studies showed stronger relationships with well-being and performance than longitudinal studies. Studies using objective performance ratings provided weaker relationships between resources and performance than self-rated and leader/third-party-rated studies.     

Dynamic Assignment of Flexible Service Resources

Resource flexibility is an important tool for firms to better match capacity with demand so as to increase revenues and improve service levels. However, in service contexts that require dynamically deciding whether to accept incoming jobs and what resource to assign to each accepted job, harnessing the benefits of flexibility requires using effective methods for making these operational decisions. Motivated by the resource deployment decisions facing a professional service firm in the workplace training industry, we address the dynamic job acceptance and resource assignment problem for systems with general resource flexibility structure, i.e., with multiple resource types that can each perform different overlapping subsets of job types. We first show that, for systems containing specialized resources for individual job types and a versatile resource type that can perform all job types, the exact policy uses a threshold rule. With more general flexibility structures, since the associated stochastic dynamic program is intractable, we develop and test three optimization‐based approximate policies. Our extensive computational tests show that one of the methods, which we call the Bottleneck Capacity Reservation policy, is remarkably effective in generating near‐optimal solutions over a wide range of problem scenarios. We also consider a model variant that requires dynamic job acceptance decisions but permits deferring resource assignment decisions until the end of the horizon. For this model, we discuss an adaptation of our approximate policy, establish the effectiveness of this policy, and assess the value of postponing assignment decisions.     

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.     

数据赋能驱动制造业企业实现敏捷制造案例研究

  世界经济的发展呼唤先进制造理念和制造技术,敏捷制造受到学者的广泛关注。制造业企业通过了解实现敏捷制造的过程机理,可以使其灵活地运用各种先进生产技术促成敏捷制造。然而,已有对制造业企业实现敏捷制造过程的研究缺少契合当前情景的视角以及完整、清晰的探究。         鉴于此,引入赋能概念,从数据驱动的视角对青岛酷特智能公司的研发、生产和营销3个阶段进行深入分析,结合扎根理论的3级编码技术,构建制造业企业通过数据赋能实现敏捷制造的过程模型。在已有研究基础上,构建敏捷制造的开放式概念框架,通过调研访谈、实地考察等方式获得分析数据,分析并构建制造业企业实现敏捷制造的过程模型,结合已有研究对该模型进行进一步讨论和完善。研究过程严格遵循理论构建的理论-实践-理论研究逻辑。         研究结果表明,企业的敏捷制造能力可以通过高效对接消费者需求与资源以及提高中间对接环节的效率来打造。从数据驱动视角看,数据化、标准化和联网化是制造业企业实现敏捷制造的核心所在。一方面,数据化和标准化可以提高数据的可接入性和流通性,减少制造加工环节的延缓;另一方面,联网化可以让需求数据直接对接企业的资源和制造过程的设备,进而实现资源的自动整合,打造企业高响应速度、高质量、低成本的供给。         从数据驱动视角构建的敏捷制造过程模型系统详细地解释了制造业企业通过数据赋能实现敏捷制造的过程,完善和拓展了关于敏捷制造的研究,为未来敏捷制造实证研究提供了一定的研究基础和启示。此外,为了给企业实践提供更加详细、明确的指导,给出基于数据赋能驱动制造业企业实现敏捷制造的实践指导步骤。     

面向我国国立研究机构的人力资源配置模型研究

当今世界,科学技术作为第一生产力的作用日益突出,科学技术作为人类文明进步的基石和原动力的作用日益凸显,而国立研究机构作为中国科研体系的国家队和中坚力量,它的地位和规模在整个科研体系中是举足轻重的,因此合理配置国立研究机构的人力资源具有重大的理论和现实意义。目前的人力资源配置研究多针对企业,而中国的国立研究机构有其自身的特点,不能套用企业的人力资源配置方法。中国科学院作为国家在科学技术方面的最高学术机构,作为科技事业的国家队和火车头,具有代表性,因此本文以中国科学院为例,利用问卷调查、专家访谈、文献调研等方法,对影响我国国立研究机构人力资源配置的因素进行研究,并将人力资源的配置看作一个决策问题,综合考虑了发展战略、人均经费当量、人员结构、学科建设等多个约束,采用自上而下和自下而上相结合的方法,建立了面向国立研究机构的人力资源配置模型。该模型克服了以往国立研究机构对子机构人员数量通过简单趋势外推等方法进行预测的做法,集成了历史数据和专家经验,既不脱离历史情况又能够反映机构的发展战略,是一种适合国立研究机构的人力资源配置方法。该方法在中国科学院的应用实践,验证了模型的有效性。     

企业家认知资源与管理创新决策:理论与案例实验

本文旨在探讨企业家认知资源的异质性及其对管理创新决策的影响。运用案例实验法进行了实证检验,研究结果表明:企业家的经验和社会资本是企业家的异质性认知资源,引致了企业家和非企业家管理决策方案在创新性和适用性上的异质性;在没有社会资本的支持下,企业家经验与管理决策方案创新性之间呈倒U型关系,对方案的适用性有正向影响;而在社会资本可得的情况下,企业家经验与社会资本均对方案的创新性和适用性有显著的增强效应。     

基于GERT网络的应急抢险过程资源优化配置模型研究

针对应急抢险过程中资源需求与供应不匹配的问题,通过定义应急抢险过程GERT网络的基本单元,建立了一种综合考虑灾害自身演化过程及外界作用相互关系的应急抢险过程GERT网络,设计了求解不同资源配置情况下突发事件状态转移概率的极大熵模型;研究了应急抢险过程GERT网络的简化性质,给出了基于GERT网络的应急抢险过程资源最优配置的求解算法。为应急资源配置提供了定性与定量结合的分析框架与工具,为灾害发展态势的预测及其资源配置提供了新的研究方法和研究思路。     

基于ARTⅡ网络的煤炭资源资产分类研究

本文建立了用于煤炭资源资产分类的ARTⅡ神经网络模型,编制了相应的计算机和软件,并将ARTⅡ模型与模糊分类模型和基于BP网络的分类模型进行了对比分析,实例运行结果表明,用ARTⅡ网络进行分类具有分类稳定、结果可靠等特点。     

在国家创新系统内优化配置科技资源

科技资源、科技财力资源和科技人力资源是当今的“第一资源”. 因而如何优化配置科技 资源已成为决策者、管理者提高国家竞争力、企业竞争力的核心问题. 本文提出在“国家创新系 统”中优化配置科技资源的观点, 并从实践方面, 包括我国科研院所转制、中国科学院的知识创 新工程和科技中介机构建设等加以论证.