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To investigate the influence of logistics and transportation workers’ perceptions of their management’s simultaneous safety and operations focus (or lack thereof) on related worker safety and operational perceptions and behaviors.

This multi-method research consisted of two studies. Study 1 aimed to establish correlational relationships by evaluating the impact of individual-level worker perceptions of operationally focused routines (as a moderator) on the relationship between worker perceptions of safety-related routines and workers’ self-reported safety and in-role operational behaviors using a survey. Study 2 aimed to establish causal relationships by evaluating the same conceptual relationships in a behavioral-type experiment utilizing vehicle simulators. After receiving one of four pre-task briefings, participants completed a driving task scenario in a driving simulator.

In Study 1, the relationship between perceived safety focus and safety behavior/in-role operational behavior was strengthened at higher levels of perceived operations focus. In Study 2, participants who received the balanced pre-task briefing committed significantly fewer safety violations than the other 3 treatment groups. However, in-role driving deviations were not impacted as hypothesized.

This research is conducted at the individual (worker) level of analysis to capture the little-known perspectives of logistics and transportation workers and explore the influence of balanced safety and operational routines from a more micro perspective, thus contributing to a deeper understanding of how balanced routines might influence worker behavior when conducting dynamic tasks to ensure safe, effective outcomes.

This study aims to develop a framework that explains how and when telework is related to emotional exhaustion and task performance, by conceiving work overload as a mediator and self-leadership as a moderator. For this purpose, two studies were conducted. Study 1 aims to understand whether telework would be related to emotional exhaustion and task performance and if work overload would mediate such relationships. Study 2 aims to analyze whether self-leadership was a significant moderator of the mediated relations found in Study 1.

The hypotheses were tested in a sample of 207 (in Study 1) and 272 (in Study 2) participants, which were exclusively teleworking. The results were analyzed using PROCESS macro in SPSS.

The results of Study 1 showed that telework dimensions were negatively related to work overload, which consequently decreased emotional exhaustion and increased task performance. In Study 2, self-leadership moderated the indirect effect of work overload on the relationship between telework and emotional exhaustion, such that the indirect effect was stronger for those who scored higher in self-leadership. However, it was not significant for task performance.

This paper adds to research on telework by focusing on the employee's mental health and performance, in the context of mandatory confinement. The authors identified telework dimensions that may act as resources to cope with the increased work overload inherent to telework, as well as the importance of personal resources in these relationships.

This study draws on the affective events theory (AET) to understand how telework may influence workers' well-being. Hence this study aimed to (1) analyze the indirect relationship between telework and well-being via daily micro-events (DME), and (2) test whether procrastination would moderate this indirect effect.

To test the goals, data were gathered from a sample of teleworkers in the IT sector (N = 232). To analyze the data, a moderated mediation analysis was performed in SPSS with PROCESS macro.

The results showed that micro-daily events mediated the positive relationship between telework and well-being; however, this relation was conditional upon the levels of workers' levels of procrastination, that is, this link became weaker for those who were procrastinators.

By highlighting the importance of telework, DME and procrastination, this study offers managers distinct strategies for enhancing their employees' well-being.

Despite the existing research investigating the effect of telework on well-being, studies investigating the intervening mechanisms between these two constructs are scarce. Moreover, there is a lack of research investigating the moderating effect of procrastination in these relations. Hence, this study fills these gaps and advances knowledge on the process that explains how (via DME) and when (when procrastination is low) teleworking influences workers' well-being.

Playful work design (PWD) is a set of proactive strategies implementing fun and self-challenge at work to actively create better work conditions. Following the job demands-resources theory, this study aims to investigate the effects of PWD’s dimensions – i.e. “designing fun” and “designing competition” – on task and contextual performance (Study 1) and on the dimensions of organizational citizenship behaviors (OCBs) – i.e. altruism, conscientiousness and civic virtue (Study 2). Furthermore, the present research investigates the mediating role of work engagement (WE) for both studies.

Two samples of 339 and 141 Italian workers participated by filling in a self-report questionnaire. Measuring models and hypotheses have been tested by structural equation models.

Results suggest that WE partially mediates the relationship of the “designing competition” subdimension of PWD with task and contextual performance (Study 1) and with conscientiousness and civic virtue of OCBs, while “designing fun” shows a positive direct relationship only with altruism (Study 2).

This paper contributes to expanding knowledge about PWD’s effectiveness in facilitating performance and positive behaviors. Furthermore, it disentangles the different effects of PWD’s dimensions on performance. In light of the results, both employees and managers should be aware of the beneficial consequences of introducing fun and self-competitiveness when completing their own work activities.

Technostress reduces employees' work performance and increases their turnover intentions, such that technostress harms organizations' success. This paper investigates how the digital mindset of employees, reflecting their cognitive filter while using digital technologies, influences reactions to techno-stressors.

In this quantitative study, the authors conducted a survey among 151 employees who regularly use digital technologies and encounter various techno-stressors in their daily work. To build this research model and evaluate the influence of employees’ digital mindset on technostress, the authors followed arguments from the transactional model of stress. The authors evaluated our research model using the covariance-based structural equation model.

The study findings reveal that employees’ digital mindset influences technostress. Employees with high levels of digital mindset react with less adverse effects on perceived techno-stressors. Further, the authors find that employees with high levels of digital mindset perform well and are satisfied with their job. The authors contribute to technostress research by revealing that digital mindset buffers the adverse effects of techno-stressors. The authors also contribute to research on digital mindset by showing that it influences psychological and behavioral reactions to techno-stressors.

This study develops and empirically tests an integrated model of technostress to explain how digital mindset mitigates technostress. The study findings outline relevant research avenues for studies investigating employees’ characteristics and technostress.

This study aims to investigate the daily performance of the proposed microgrid (MG) that comprises photovoltaic, wind turbines and is connected to the main grid. The load demand is a residential area that includes 20 houses.

The daily operational strategy of the proposed MG allows to vend and procure utterly between the main grid and MG. The smart metre of every consumer provides the supplier with the daily consumption pattern which is amended by demand side management (DSM). The daily operational cost (DOC) CO2 emission and other measures are utilized to evaluate the system performance. A grey wolf optimizer was employed to minimize DOC including the cost of procuring energy from the main grid, the emission cost and the revenue of sold energy to the main grid.

The obtained results of winter and summer days revealed that DSM significantly improved the system performance from the economic and environmental perspectives. With DSM, DOC on winter day was −26.93 ($/kWh) and on summer day, DOC was 10.59 ($/kWh). While without considering DSM, DOC on winter day was −25.42 ($/kWh) and on summer day DOC was 14.95 ($/kWh).

As opposed to previous research that predominantly addressed the long-term operation, the value of the proposed research is to investigate the short-term operation (24-hour) of MG that copes with vital contingencies associated with selling and procuring energy with the main grid considering the environmental cost. Outstandingly, the proposed research engaged the consumers by smart meters to apply demand-sideDSM, while the previous studies largely focused on supply side management.

Although numerous signal modalities are available for emotion recognition, audio and visual modalities are the most common and predominant forms for human beings to express their emotional states in daily communication. Therefore, how to achieve automatic and accurate audiovisual emotion recognition is significantly important for developing engaging and empathetic human–computer interaction environment. However, two major challenges exist in the field of audiovisual emotion recognition: (1) how to effectively capture representations of each single modality and eliminate redundant features and (2) how to efficiently integrate information from these two modalities to generate discriminative representations.

A novel key-frame extraction-based attention fusion network (KE-AFN) is proposed for audiovisual emotion recognition. KE-AFN attempts to integrate key-frame extraction with multimodal interaction and fusion to enhance audiovisual representations and reduce redundant computation, filling the research gaps of existing approaches. Specifically, the local maximum–based content analysis is designed to extract key-frames from videos for the purpose of eliminating data redundancy. Two modules, including “Multi-head Attention-based Intra-modality Interaction Module” and “Multi-head Attention-based Cross-modality Interaction Module”, are proposed to mine and capture intra- and cross-modality interactions for further reducing data redundancy and producing more powerful multimodal representations.

Extensive experiments on two benchmark datasets (i.e. RAVDESS and CMU-MOSEI) demonstrate the effectiveness and rationality of KE-AFN. Specifically, (1) KE-AFN is superior to state-of-the-art baselines for audiovisual emotion recognition. (2) Exploring the supplementary and complementary information of different modalities can provide more emotional clues for better emotion recognition. (3) The proposed key-frame extraction strategy can enhance the performance by more than 2.79 per cent on accuracy. (4) Both exploring intra- and cross-modality interactions and employing attention-based audiovisual fusion can lead to better prediction performance.

The proposed KE-AFN can support the development of engaging and empathetic human–computer interaction environment.

This chapter provides an overview on the traditions and values of teaching students with traumatic brain injury (TBI). First, we discuss the prevalence, identification, and characteristics associated with TBI and how those characteristics affect learning, behavior, and daily life functioning. Next, we focus on instructional and behavioral interventions used in maintaining the traditions in classrooms for working with students with TBI. Findings from a review of the literature conclude that there are no specific academic curriculums designed specifically for teaching students with TBI; however, direct instruction and strategy instruction have been shown to be effective educational interventions. Current research on students with TBI is predominately being conducted in medical centers and clinics focusing on area of impairments (e.g., memory, attention, processing speed) rather than academic achievement and classroom interventions. Finally, we conclude with a list of accommodations and a discussion of recommendations for future work in teaching students with TBI.

Using role stress theory, this study examines how work connectivity behavior (WCB) blurs the lines between employees' work and personal lives, thereby encouraging procrastination at work (PAW). The study also investigates the importance of role stress and remote work self-efficacy (RWSE) as mediating and moderating factors, respectively.

The study examines the direct and indirect relationships between WCB and PAW using hierarchical regression and data from 415 Chinese teleworkers. RWSE is also estimated as a second-stage moderator.

The findings indicate that WCB has a direct and indirect (via role stress) positive influence on PAW; however, these effects are weaker among employees with higher (vs lower) RWSE.

This study assists managers and organizations in developing more efficient ways of maximizing employee and organizational performance while minimizing the counterproductive behaviors associated with excessive technology use.

By investigating the links between WCB and PAW in the post-pandemic context, this study adds a new perspective on how excessive technology use for work and non-work purposes can be counterproductive.

Companies are concerned about the well-being of workers in their supply chains, but conventional audits fail to uncover critical problems. Yet, if the happy worker – productive worker thesis is correct, it would benefit factories in fast-developing countries, particularly China which is key to many global supply chains, to ensure the well-being of their workers. The authors set out to better understand the relationship between well-being and performance in four Chinese factories.

Over 12-months the authors collected digital diaries from 466 workers in four factories, and monthly data about the performance of their factories. The authors used this data to gain insights into the well-being of workers in these factories; to design experimental interventions to improve this; and to consider any effects these had on factory performance.

The experiments showed that training interventions to improve workers' well-being through their work relationships and individual skills improved not just a factory's general worker well-being, but also some aspects of its performance and worker retention. Thus, it brought benefits not only for the workers but also for the factory owners and their client companies.

While there is a significant body of research investigating the happy worker – productive worker thesis, this was not conducted in Chinese factories. The authors’ work demonstrates that in this and similar environments, workers' eudaimonic well-being is more important than might be assumed, and that in this context there is a relationship between well-being and performance which can be practically addressed.