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Several job characteristics have been suggested to influence workers’ well-being. For example, Herzberg (1968) differentiated job characteristics that offset dissatisfaction such as social relations from job aspects that foster job satisfaction such as opportunities for advancement. While Hackman and Oldham (1976) focused on the motivational potential of job characteristics such as task identity and feedback, Karasek (1979) accentuated time pressure as a pivotal job demand. Together these models point out that various job characteristics may influence workers’ functioning.

In this chapter, we discuss the impact of business trips on travelers and their families from the perspective of respite, thus embedding business trips in stress theories. We begin by reviewing the literature on respite and recovery. Focusing on the role of travelers’ resources, we relate the phenomenon of business trips to conservation of resources (COR) and job demands-resource (JD-R) theories. We then discuss the negative and positive characteristics and outcomes of business trips. We offer evidence from interviews with business travelers regarding the special characteristics and consequences of business trips. We summarize by addressing the question of whether business trips are a special kind of respite.

Recent years have seen an explosion in the study of emotions in organizations, and although emotions play a central role in the job stress process, their role is largely neglected in empirical stressor–strain studies. Our chapter aims to build consensus in the literature by showing that discrete emotions provide a mechanism through which stressors exert their impact on well-being. By examining a larger domain of stressors, emotions, and well-being, we begin to develop and expand upon the nomological network of emotions. In an effort to build on the job demands–resources (JD-R) model, which includes both job demands (i.e., negative stimuli such as time pressure) and resources (i.e., positive stimuli such as autonomy), we include both negative and positive discrete emotions with the expectation that negative emotions will generally be linked to demands and positive emotions will be linked to resources. We also propose that there may be circumstances where demands trigger negative discrete emotions and lead to greater experienced strain, and conversely, where resources arouse positive discrete emotions, which would positively affect well-being. The model in our chapter sheds light on how discrete emotions have different antecedents (i.e., job demands and resources) and outcomes (e.g., satisfaction, burnout, performance), and as such, respond to calls for research on this topic. Our findings will be of particular interest to organizations where employees can be trained to manage their emotions to reduce the strain associated with job stressors.

This study investigates work and non-work antecedents for the work–life balance (WLB) development of remote employees during the COVID-19 pandemic. Longitudinal data (N = 1,146, T1; N = 737, T2) was collected in May–June 2020 and December 2020 in one multinational company (MNC) in Finland. In data analysis, structural equation modeling (SEM) with a cross-lagged panel model was utilized. The results revealed that during the pandemic, WLB slightly decreased. The quantitative job demands increased and predicted a decreased WLB at T2. Job autonomy decreased but did not have an effect on WLB development or buffer the negative effect of quantitative job demands on WLB. Time saved from commuting was positively related to WLB development, but the number of children living at home and the age of the youngest child had no statistically significant link to WLB development over time (similar finding for men and women). Although care responsibilities from the gender perspective is not the focus of our study, the additional analysis show that WLB at T1 was more challenging for women the more children they had, or the younger the youngest child was. For men, children did not make a difference for their WLB at T1. This finding indicates that WLB has been more challenging for mothers compared to fathers already when our first data had been collected, and the continuance of the pandemic did not change the situation in any direction. This research contributes to the knowledge about work and non-work related demands and resources as antecedents for WLB development during the pandemic. As a practical implication during the pandemic, the authors suggest that employers should follow development for employees’ WLB as a measure of well-being in remote work. In addition, the workload of remote employees should be followed, and time saved from commuting should be preserved as employees’ non-work time and protected from work-related tasks.

In this chapter, we use the job demands–resources (JD-R) model (Demerouti, Bakker, Nachreiner, & Schaufeli, 2001) and the transactional model of stress (Lazarus & Folkman, 1984) to provide a theoretical framework with which to examine information and communication technology (ICT) as both a demand and a resource. We review specific characteristics of ICT that may either increase or decrease employee stress and well-being. Specifically, we examine the extent that ICT increases accessibility of workers and access to information, the extent to which it improves communication and control over one's job and life, and the extent to which it is used to monitor employees or provide feedback. Finally, we examine the organizational, job, and individual factors that may mitigate or exacerbate the impact of ICT demands on individual outcomes.

The application of positive psychology to the context of work has attracted enormous interest within both academic and practitioner domains over the past decade (e.g., Keyes & Haidt, 2003; Linley, Harrington, & Garcea, 2010; Luthans, 2002). From a practitioner perspective, there has been a proliferation of organizational development, human resource, talent management, leadership development, team development and coaching programs, initiatives, and interventions that have positive psychological principles at their core. The Gallup organization, for instance, has administered the Clifton Strengths Finder in thousands of organizations across the globe, aiming to help people learn about and build upon their talents and strengths to enhance all facets of their working experience (see Clifton & Harter, 2003).

Psychosocial risks in the workplace include occupational risks such as stress, harassment, burnout, and workplace violence that affect the physical integrity and mental health of employees (Bunker et al., 2003). Work-related psychosocial risks are relevant to the design and management of the job and its social and organizational contexts (Leka, Griffiths, & Cox, 2003). In this study, it was investigated which factors are effective in the psychosocial risk assessments of blue-collar workers in Turkey and whether there is a significant effect of gender in these assessments. The sample of the research consists of 663 employees working in a production facility in Tekirdag. The results showed that cognitive demands, the meaning of work, and development opportunity variables differed by gender from psychosocial risks. Women evaluate lower scores than men in expressions related to cognitive demands, the meaning of work, and development opportunities. Quantitative demands, emotional demands, burnout, and job satisfaction did not differ significantly by gender. The findings provide an understanding of the potential risks in the working conditions of blue workers in Turkey and provide the basis for future research.

This survey study among 111 teleworkers in a bank organization investigated the relationship between telework intensity and individual productivity, and whether this relationship was mediated by employees’ intrinsic motivation. Also the moderating role of office hours in the model’s associations was studied. Based on the Job Demands-Resources Model (Bakker & Demerouti, 2007) and the professional isolation literature (e.g., Golden, Vega, & Dino, 2008), we developed and tested a set of hypotheses. Partly in line with expectations, we found a direct curvilinear relationship between telework intensity and individual productivity, characterized by a slight, non-significant positive association at the low telework intensity end, and a significant negative association for the high telework intensity end. Strikingly, we neither found support for a mediating role of intrinsic motivation, nor for a moderation effect of the number of office hours in the relationship between telework intensity and intrinsic motivation. However, the direct relationship between telework intensity and individual productivity appeared to be moderated by the number of office hours. It was concluded that consequences for productivity are contingent on telework intensity, and that the number of office hours has an important impact on the consequences of different telework intensities. The study’s outcomes can inform management and HR practitioners to understand how to implement and appropriately make use of telework.