Reciprocal relationships between psychosocial work characteristics and sleep problems: A two-wave study

Sleep problems are common and impair the health and productivity of employees. Work characteristics constitute one possible cause of sleep problems, and sleeping poorly might influence wellbeing and performance at work. This study examines the reciprocal associations between sleep problems and psychosocial work characteristics. The participants were 1744 full-time employed individuals (56% women; mean age 38 years in 2007) from the Young Finns study who responded to questionnaires on work characteristics (conceptualised by the demand–control model and effort–reward imbalance model) and sleep problems (Jenkins Sleep Scale) in 2007 and 2012. Cross-lagged structural equation models are used to examine the associations. The results show that low control and low rewards at baseline predicted sleep problems. Baseline sleep problems predicted higher effort, higher effort–reward imbalance, and lower reward. Sleep problems also predicted lower odds for belonging to the low (rather than high) job strain group and active jobs group. The association between work characteristics and sleep problems appears to be reciprocal, with a stressful work environment increasing sleep problems, and sleep problems influencing future work characteristics. The results emphasise the importance of interventions aimed at both enhancing sleep quality and reducing psychosocial risks at work.     

The Use of Simulation to Reduce the Domain of “Black Swans” with Application to Hurricane Impacts to Power Systems

Recently, the concept of black swans has gained increased attention in the fields of risk assessment and risk management. Different types of black swans have been suggested, distinguishing between unknown unknowns (nothing in the past can convincingly point to its occurrence), unknown knowns (known to some, but not to relevant analysts), or known knowns where the probability of occurrence is judged as negligible. Traditional risk assessments have been questioned, as their standard probabilistic methods may not be capable of predicting or even identifying these rare and extreme events, thus creating a source of possible black swans. In this article, we show how a simulation model can be used to identify previously unknown potentially extreme events that if not identified and treated could occur as black swans. We show that by manipulating a verified and validated model used to predict the impacts of hazards on a system of interest, we can identify hazard conditions not previously experienced that could lead to impacts much larger than any previous level of impact. This makes these potential black swan events known and allows risk managers to more fully consider them. We demonstrate this method using a model developed to evaluate the effect of hurricanes on energy systems in the United States; we identify hurricanes with potentially extreme impacts, storms well beyond what the historic record suggests is possible in terms of impacts.     

A reference activity model for smart factory design and improvement

Smart manufacturing systems (SMSs) are envisioned to contain highly automated and IT-driven production systems. To address the complexity that arises in such systems, a standard and holistic model for describing its activities and their interrelationships is needed. This paper introduces a factory design and improvement (FDI) activity model and illustrates a case study of FDI in an electromechanical component factory. In essence, FDI is a reference activity model that encompasses a range of manufacturing system activities for designing and improving a factory during its initial development and also its operational phases. The FDI model shows not only the dependency between activities and manufacturing control levels but also the pieces of information and software functions each activity relies on. We envision that the availability of these pieces of information in digital form to integrate across the software functions will increase the agility of factory design and improvement projects. Therefore, our future work lies in contributing to standards for exchanging such information.     

The implementation of digital technologies for operations management: a case study for manufacturing apps

Abstract

Manufacturing applications address business to business (B2B) with highly customised applications developed for specific requirements, offering highly specialised solution-oriented and service-based software components, systems, and digital tools that aim at a fast and accurate decision-making support system. The purpose of this paper is to describe the implementation of digital technologies for operations management using manufacturing or engineering apps (eApps), for product design and manufacturing processes. In particular, starting from the specific needs of two companies from mature European industries as automotive and food, this work depicts how this kind of solutions can support companies and improve their operations. In particular, related benefits and challenges faced for the full implementation of the developed tools are highlighted. Moreover a business model to exploit the manufacturing apps is also proposed. The business model proposed for the exploitation of the eApps supports the commercialisation of all the revenue streams offered by this rapidly growing sector taking into account the specific needs of the concerned stakeholders through a diversified value proposition.     

Open innovation and quality management: the moderating role of interorganisational IT infrastructure and complementary learning styles

This study seeks to explain the influence of quality management on the relationship between open innovation and performance. We propose that, to contribute to open innovation performance, an organisation’s commitment to quality improvement must rely on the combination of its own resources and capabilities and its open innovation partners’ resources and capabilities. Specifically, we examine the moderating role of an interorganisational IT infrastructure and the complementarity of learning styles among an organisation committed to quality improvement and its supply network. Using data from 270 managers of European firms, our results show that the negative effects of quality management on open innovation performance can be overcome by complementing the organisation’s learning style with that of its open innovation partner, particularly, its supply network, and, most importantly, obtaining information technologies compatible with those of its supply network members.     

雾霾感知风险与公众应对行为的实证分析

通过在雾霾严重时期收集的大规模问卷调查数据,建立了雾霾感知风险等因素与应对行为之间关系的结构方程模型.分析显示,对环境信息越敏感、雾霾感知风险越大、对雾霾知识了解越多、雾霾感知可控性越大的公众会采取更多的防护与应对措施,他们对相关防护产品的购买意愿也越强.特别是,感知风险在环境信息与应对行为以及环境满意度之间起着重要的中介变量作用,即当雾霾污染引起人们的感知风险时,会促使他们采取更多的应对行为,并且对环境满意度评价产生负面影响.另外,雾霾感知可控性在雾霾知识熟悉度与应对行为以及环境满意度之间起着部分中介变量的作用.     

基于活动方法的瓶颈模型与拥挤收费问题研究

Vickrey提出的基于出行的瓶颈模型以出行作为分析单位,没有考虑出行与活动之间的相互关联.本文对Vickrey的瓶颈模型进行了拓展,提出了基于活动的瓶颈模型来研究通勤者早晨上班出发时间决策问题,模型考虑了通勤者对出行负效用与活动效用之间的权衡.在基于活动的瓶颈模型的基础上,分别研究了常数和线性边际活动效用下瓶颈动态拥挤收费和阶梯收费问题,并与传统的瓶颈模型的解进行比较.结果表明,当活动的边际效用为线性函数时,瓶颈处最优动态收费曲线不再呈分段线性关系,而是分段二次曲线;与基于活动的瓶颈模型相比,传统的基于出行的瓶颈模型将高估瓶颈处的排队延误、阶梯收费水平,以及早高峰的开始和结束时间;基于出行的瓶颈模型和常数边际活动效用下的瓶颈模型导致的最优阶梯收费是最优动态收费最大值的一半,并且刚好消除瓶颈处排队延误的一半;与线性边际活动效用下的瓶颈模型相比较,两者低估了阶梯收费能消除的瓶颈排队,从而低估了阶梯收费的效率.     

生产还是消费——中国股市生产资本资产定价模型实证检验

生产资本资产定价模型从企业利润最大化角度出发,推出资产的均衡价格.相较于消费资本资产定价模型,生产资本资产定价模型能更好的满足信息完全和决策者理性的假设条件.本文从生产资本资产定价模型出发,利用现值模型将生产的系统性风险因子,即生产的贝塔因子分解为现金流贝塔和折现率贝塔,并采用社会总投资和股市数据进行实证检验.本文发现生产-现金流贝塔是中国股市的重要定价因子,可较好地解释股权溢价的截面差异.相比之下,消费资本资产定价模型对不同资产之间风险溢价的解释能力较弱.     

房价波动、 收入水平对住房消费的影响——基于SYS-GMM估计方法的区域差异分析

基于生命周期-持久收入假说,在一般随机Ramsey模型的基础上,推导包含房价、收入和财富的住房消费函数,利用2002年至2013年31个省直辖市的面板数据,采用两步System-GMM估计方法考察我国房价波动和居民收入水平对住房消费的影响.实证结果表明:房价波动对全国居民住房消费具有显著的抑制作用;其中,滞后期和当期房价波动与当期住房消费负相关,挤出效应明显;未来一期房价波动与住房消费变化方向一致,存在积极的财富效应;此外,房价波动对东中西部各地区居民住房消费的抑制作用存在较大差异,西部地区抑制效应最为明显;滞后期住房消费与当期住房消费变动方向一致,人均可支配收入波动和人均年底储蓄余额对我国人均住房消费都起着重要的支撑作用.     

一种新的金融动态横截面估计方法——基于中国股票市场条件定价模型评估的应用与扩展

大多数资产定价模型常常用静态横截面回归(the static cross-sectional regression)进行定价表现评估,从而投资组合回报率的时间变化性并不能被时变的风险承载或者(和)时变的风险溢价所解释.本文从经济学的角度,运用一种新的金融动态横截面回归(the dynamic cross-sectional regression),首次考察了基于中国股票市场和美国股票市场的条件资产定价模型的定价表现:股票市场投资组合回报率的时变性是否能被时变的风险溢价所解释.本文发现,短期收益反转和流通市值加权市场换手率为条件变量的条件资本资产定价模型和基于消费的条件资本资产定价模型,能更好的解释中国股票投资组合的回报时变性,其时变性主要来自于时变的风险溢价.另外,本文发现一些拥有持续(persistence)和缓慢变化(slow-moving)特性的条件变量更能够解释横截面投资组合的时变回报.