Job Resources Research Articles

Resources of emotional resilience and its mediating role in teachers’ well-being and intention to leave

The continuing attention of scholars and practitioners to the teaching profession, teachers and teaching is based above all on the fact that societal progress is impossible without an effective education system. Teachers are the “soft” dynamic, and at the same time, a driving force in this constantly changing system, and research into the prerequisites for their effective performance requires constant attention. In this study, the main phenomenon under analysis is the emotional resilience of teachers–the internal capacity to adapt, manage or cope with emotionally demanding situations. The purpose was to investigate work-related and personal resources that contribute to teachers’ emotional resilience and its role in the links between resources, teacher well-being, and the intention to leave. Data were collected using convenience sampling and included 522 teachers working in Lithuanian primary and secondary schools. An online self-administered questionnaire consisted of scales that assessed teachers’ job resources, self-efficacy, well-being, and intention to leave. The research revealed that perceived workplace characteristics – performance feedback, autonomy, social support, and opportunities for professional growth–along with self-efficacy were positively related and predicted teacher emotional resilience. Emotional resilience was found to be a direct positive predictor of teacher well-being along with job resources and self-efficacy and have a mediating effect on the relationships between work-related resources and self-efficacy as independent variables and teacher wellbeing as a dependent variable. Contrary to well-being is teachers’ intention to leave a school, which is usually an undesirable outcome for an organization. The study revealed that this intention is negatively affected by job resources and self-efficacy, however emotional resilience did not impact teachers’ intention to quit. Based on the results, the article outlines avenues for further research and provides implications for strengthening teachers’ emotional resilience.

Today, tomorrow, and then forever: Exploring how workflow experience is sustained from a work–home perspective

Abstract This study explores how employees’ flow experience at work emerges, is sustained, and continuously grows over time. Based on the job demand-resource model, we propose the intraday upward spiral of flow: Challenging demands and job resources activate employees’ flow experience, further encouraging them to seek more challenges and resources. Furthermore, drawing on the perseverative cognition theory and spill-crossover model, we propose the inter-day upward spiral of flow: The antecedents (or consequences) of flow can overflow from work to the family domain and result in employees’ positive rumination, thus promoting the next-day flow experience. Our diary study generated 1,208 data points from 142 employees over 10 working days. We found that in the morning, challenging demands and job resources positively affected the participants’ flow, further encouraging them to pursue more challenging demands and job resources in the afternoon and thus enter this state again. Moreover, the afternoon’s challenging demands and job resources promoted the respondents’ problem-solving pondering at night, which further increased their next-morning challenging demands, job resources, and, thus, their flow. Through this study, we expand the emerging literature on positive organizational behavior and provide information for practitioners on how to build and sustain employees’ peak states.

There Is Hope in Safety Promotion! How Can Resources and Demands Impact Workers’ Safety Participation?

Promoting workplace safety is crucial in occupational health and safety (OHS). However, existing studies have primarily concentrated on accident prevention, overlooking the role of resources in encouraging safety. This research investigates the impact of a personal resource, namely hope, on safety participation, considering its interaction with job resources and job demands using the Job Demands-Resources (JD-R) model in the context of safety. A cross-sectional study was conducted in a large company managing European shopping centers (N = 262). Of the sample, 52.3% of participants were female. Data were collected through an online questionnaire and analyzed using model 92 of Andrew F. Hayes’ Process Macro to test the hypothesized moderate serial mediation model. Our results highlighted that (1) hope directly correlates with safety participation, (2) hope and job dedication mediate the relationship between autonomy and safety participation, and (3) high job demands can undermine the beneficial effects of resources (i.e., autonomy, hope, and job dedication) on safety participation. These results suggest that workers with personal resources like hope are more likely to engage in safety practices, displaying increased dedication and focus on safety. However, excessive job demands can challenge the effectiveness of these resources in promoting safety participation. This study offers a novel perspective by integrating safety participation into the JD-R model framework.

Coping with administrative tasks: A cross‐country analysis from a street‐level perspective

AbstractAdministrative tasks often are an unavoidable aspect of the daily work of street‐level bureaucrats (SLBs). These burdensome tasks are job demands that can cause stress and put a strain on SLBs' working experience and performance. So far, few studies have searched for job resources that can help SLBs cope with this aspect of their daily work. This study analyzes how performing administrative tasks results in job stress. Participation in organizational decision‐making is presented as a job resource that mitigates this impact—although, we hypothesize, less so in countries with high power distance. Using a survey dataset of 113,210 teachers across 46 countries, we find that participation in organizational decision‐making indeed reduces the impact of spending time on administrative tasks on job stress. Power distance does not influence this moderation significantly but does have cross‐level interactions with both the time spent on administrative tasks and the level of participation separately.

Job demands, job resources and postdoctoral job satisfaction: An empirical study based on the data from 2020 Nature global postdoctoral survey.

Postdocs encounter numerous hurdles in terms of their professional survival and academic development, as a result of institutional reform and the prevailing academic environment. These challenges significantly impact their job satisfaction, which in turn plays a crucial role in shaping their scientific research career trajectory. To facilitate the advancement of relevant systems and augment the job satisfaction of postdocs, this study employs the 2020 Nature Global Postdoctoral Survey data to conduct a comprehensive analysis. Utilizing descriptive statistics, correlation analysis, and regression analysis, the impact of job characteristic elements on postdoctoral job satisfaction was examined within the theoretical framework of the Job Requirements-Resources (JD-R) model, as well as the mechanisms by which job characteristic elements impact postdoctoral job satisfaction. It was found that job demands and job resources negatively and positively predicted postdoctoral job satisfaction, respectively, with job burnout and job engagement playing a partial mediating role. Job demands can drive postdocs to develop negative coping psychology and limit the motivating effect of job resources on job engagement; job resources can act as a buffer to reduce the probability of postdocs experiencing job burnout as a result of job demands. The aforementioned findings generally support the applicability of the JD-R model to postdocs, theoretically revealing the intrinsic psychological mechanisms by which job characteristics influence postdoctoral job satisfaction and providing theoretical supplements and practical references for postdoctoral training and management.

Exploring teacher wellbeing in educational reforms: a Chinese perspective.

Teaching is a demanding profession and maintaining teacher wellbeing is significant in ensuring educational quality. However, teacher wellbeing is easily affected by educational reforms, and systematic research on this topic is still relatively rare. In China, with the enactment of the Double Reduction Policy in 2021, the job characteristics of primary and secondary school teachers have undergone various changes. Thus, the current study examined the new job characteristics that China's Double Reduction Policy imposed on the wellbeing of school teachers and their relationships with teachers' inner world (i.e., emotional regulation and mindset). A cross-sectional study was carried out from June to October 2022 across China, employing self-reporting questionnaires for data collection and analysis. With a random sample of 902 teachers, we investigated the associations between teacher wellbeing, job characteristics, emotional regulation strategies, and mindset. The results indicated that teachers showed a lower level of wellbeing after the educational reform. Higher job resources contributed positively to predicting teacher wellbeing, while higher job demands contributed negatively. Genuinely expressing had positive impacts on teacher wellbeing while surface acting had negative impacts and deep acting none. Mindset was found to affect emotional regulation strategies and teacher wellbeing simultaneously. These findings shed light on how teachers can appropriately regulate emotions and maintain wellbeing in the wake of educational reforms.

Region-aware dynamic job scheduling and resource efficiency for load balancing based on adaptive chaotic sparrow search optimization and coalitional game in cloud computing environments

Uneven distribution of workloads represents a significant challenge in cloud data centers, negatively impacting the efficient utilization of resources. To address this problem and optimize the performance-to-profit (PP) ratio, we introduced the Regional Awareness dynamic Scheduling Algorithm (RASA) through a three-phase approach. In the initial phase, tasks are categorized based on critical parameters like CPU usage, memory utilization, and I/O operations, using a task classification model. The second phase involves estimating the CPU, memory, and I/O capacities of each node. Subsequently, a unique merge-and-split-based coalitional game-theoretic process is employed to group nodes into clusters. In the final phase, we have improved task placement by introducing an enhanced Sparrow Search Algorithm (ISSA) to overcome the slow convergence and local optimization issues found in the traditional SSA. We have incorporated the Tent chaotic mapping approach to enhance both global and local search efficiency during this stage. Additionally, we have fine-tuned fair load distribution using the Cauchy mutation process. We performed simulations using the CloudSim toolkit, and the results underscore the RASA algorithm’s superiority in terms of how quickly it converges its precision in task placement and its ability to distribute workloads fairly. Our proposed algorithm achieves a 9% reduction in latency overhead, a 14% decrease in processing time, a 15% reduction in workload imbalance, a 19% decrease in energy consumption, and a 26% decrease in idle periods. Furthermore, it enhances resource availability and efficiency by 22% and 27% respectively, while simultaneously boosting service throughput by 32%.

How do customer-related characteristics influence frontline bank employees' boundary spanning behaviors?

PurposeThis study investigated the influence of ambiguous customer expectations and customer demandingness, which reflect hindrance and challenge demands, on the boundary spanning behaviors (BSBs) of frontline bank employees (FBEs) through person-job fit and work engagement. It also examined the moderating effect of customer stewardship between job demands and work engagement.Design/methodology/approachData of 296 FBEs in the retail banking industry in the Republic of Korea were collected through an online survey and analyzed.FindingsAmbiguous customer expectations acted as hindrance demands and negatively affected FBEs' psychological process. Additionally, customer demandingness positively affected FBEs' psychological process as challenge demands. Moreover, person-job fit and work engagement improved the BSBs of FBEs as a psychological motivation process. Lastly, customer stewardship buffered the negative influence of ambiguous customer expectations on work engagement while strengthening the positive influence of customer demandingness on work engagement.Originality/valueThis study contributes to the marketing literature by presenting customer-related characteristics influencing the BSBs of FBEs and exploring the psychological response processes. First, this study presents empirical evidence that ambiguous customer expectations and customer demandingness play the role of hindrance and challenge demands, respectively. Second, it confirms that customer-related characteristics affect the BSBs of FBEs through psychological processes. Finally, it enriches the authors' understanding of customer stewardship as a job resource by exploring the role of customer stewardship in moderating the relationship between different types of job demands and work engagement.

Motivational drivers of heavy work investment: intercultural comparison between USA and Egypt

Purpose The purpose is to identify the underlying motives of heavy work investment (HWI) types (i.e. workaholism and work engagement) based on self-determination theory, while controlling for job demands and resources. The role of four cultural differences (i.e. individualism, power distance, uncertainty avoidance and masculinity) in moderating the motivational correlated relationships is also explored using data retrieved from two distinct cultures (i.e. the USA and Egypt).Design/methodology/approach Full-time employees (N = 595) in the USA and Egypt were surveyed. Multiple regression analyses were used to test the associations between the two HWI types and four types of motivation (i.e. intrinsic, extrinsic, introjected and identified motivations). Furthermore, moderation analyses were conducted to explore potential effects of four cultural dimensions (i.e. individualism, power distance, uncertainty avoidance and masculinity) on the motivationalcorrelated relationships.Findings Workaholism positively relates to the controlled types of motivation (i.e. extrinsic and introjected regulation), while work engagement positively relates to the autonomous ones (i.e. intrinsic and identified regulation) and negatively associates with extrinsic motivation. Moreover, cultural masculinity moderated the relationship between work engagement and extrinsic motivation, as well as the association between workaholism and extrinsic motivation.Practical implications A clear differentiation of motivation behind both types of HWI is required by occupational health practitioners to design interventions that stimulate employee engagement rather than fuel workaholism. Multinational organizations could also benefit from understanding the interaction between cultural dimensions, motives and HWI, thereby planning more effective work engagement strategies among different cultures.Originality/value This is the first study to investigate the motivational correlates of HWI types across two contrasting cultures.

Optimizing Cloud Computing Applications with a Data Center Load Balancing Algorithm

Delivering scalable and on-demand computing resources to users through the usage of the cloud has become a common paradigm. The issues of effective resource utilisation and application performance optimisation, however, become more pressing as the demand for cloud services rises. In order to ensure efficient resource allocation and improve application performance, load balancing techniques are essential in dispersing incoming network traffic over several servers. The workload balancing in the context of cloud computing, particularly in the Infrastructure as a Service (IaaS) model, continues to be difficult. Due to available virtual machines and the limited resources, efficient job allocation is essential. To prevent prolonged execution delays or machine breakdowns, cloud service providers must maintain excellent performance and avoid overloading or underloading hosts. The importance of task scheduling in load balancing necessitates compliance with Service Level Agreement (SLA) standards established by cloud developers for consumers. The suggested technique takes into account Quality of Service (QoS) job parameters, VM priorities, and resource allocation in order to maximise resource utilisation and improve load balancing. The proposed load balancing method is in line with the results in the body of existing literature by resolving these problems and the current research gap. According to experimental findings, the Dynamic LBA algorithm currently in use is outperformed by an average resource utilisation of 78%. The suggested algorithm also exhibits excellent performance in terms of accelerated Makespan and decreased execution time.

GPARS: Graph predictive algorithm for efficient resource scheduling in heterogeneous GPU clusters

Efficient resource scheduling in heterogeneous graphics processing unit (GPU) clusters are critical for maximizing system performance and optimizing resource utilization. However, prior research in resource scheduling algorithms typically employed machine learning (ML) algorithms to estimate job durations or GPU utilization in the cluster based on training progress and task speed. Regrettably, these studies often overlooked the performance variations among different GPU types within these clusters, as well as the presence of spatiotemporal correlations among jobs. To address these limitations, this paper introduces the graph predictive algorithm for efficient resource scheduling (GPARS) designed specifically for heterogeneous clusters. GPARS leverages spatiotemporal correlations among jobs and utilizes graph attention networks (GANs) for precise job duration prediction. Building upon the prediction results, we develop a dynamic objective function to allocate suitable GPU types for newly submitted jobs. By conducting a comprehensive analysis of Alibaba’s heterogeneous GPU cluster, we delve into the impact of GPU capacity and type on job completion time (JCT) and resource utilization. Our evaluation, using real traces from Alibaba and Philly, substantiates the effectiveness of GPARS. It achieves a remarkable 10.29% reduction in waiting time and an average improvement of 7.47% in resource utilization compared to the original scheduling method. These findings underscore GPARS’s superior performance in enhancing resource scheduling within heterogeneous GPU clusters.

Occupational Stress and Job Satisfaction: Differences Among Racial/Ethnic and Immigration Groups.

The current study aimed to investigate the factors contributing to long-term care workers' job satisfaction by examining the association between occupational stress (including job resources and job demands) and job satisfaction, and the differences among racial/ethnic and immigration groups. Data of 2,763 nursing assistants were retrieved from the National Nursing Assistant Survey. Guided by the job demands-resources model, we found that high job resources and low job demands contributed to job satisfaction. Our findings also suggest that occupational stress works differently based on race/ethnicity and immigration status. Long-term care providers looking to recruit and retain workers should include multiple job resources tailored to their diverse workforce. Designing existing workplace environments to promote job resources and reduce job demands is a useful way to lessen the adverse effects of occupational stress within the workplace. [Journal of Gerontological Nursing, 49(11), 42-52.].

Do employees involved in career accidents experience greater work engagement? The moderating role of job resources

PurposeThis study investigated whether job resources (i.e. strengths use support, career self-management and person–job [PJ] fit) moderate the relationship between perceived involvement in a career accident (PICA) and work engagement.Design/methodology/approachThe study adopted a time-lagged design (N = 398; 69% male), and data were collected at two-point of measurements among Nigerian university academics.FindingsResults of the present study indicated that employees with higher PICA scores reported low work engagement. Strength use support had significant direct positive main effects on employee work engagement and also produced a significant moderation effect between PICA and work engagement. Career self-management (CSM) was positively related to employee work engagement. The moderation effect of CSM on the relationship between PICA and work engagement was also significant. Results of the present study further indicated that P-J fit was related positively to work engagement and also moderated the negative relationship between PICA and work engagement.Originality/valueDearth of employment opportunities has led individuals to choose their career by chance, but empirical studies that validate this assertion are lacking. Few available studies on career accident were exclusively conducted in Western European contexts. The current study therefore deepens the understanding of career accident and work engagement in a neglected context such as Nigeria.

Exploring the Effectiveness of Self-and Other-Focused Happiness: The Moderating Role of Job Resources.

This paper aims to redefine happiness goals and explore the conditions and mechanisms through which these redefined happiness goals influence work-related outcomes. The study developed and validated scales for self-focused happiness and other-focused happiness through exploratory factor analyses of 244 employees and confirmatory factor analyses of 300 employees. The proposed theoretical model was subsequently tested using a time-lagged analysis with data from 556 supervisor-employee dyads. The findings provide strong evidence for the categorization of happiness goals into self-focused happiness and other-focused happiness. Furthermore, both self-focused and other-focused happiness significantly contribute to work-related vigor, subsequently influencing employee creativity. Additionally, the impact of these happiness goals on vigor and creativity is contingent upon the availability of job resources. This study highlights the substantial role of self-focused and other-focused happiness in enhancing employee vigor and creativity. However, the extent of these effects depends on the level of available job resources. These outcomes carry notable implications for the fields of positive psychology, positive organizational behavior, and creativity.

A Study on Job Burnout and Job Enthusiasm of Hair Beauty Industry Employee's: Based on the Job Demands-Resources Model

This study analyzed the effect of job characteristics on job bunout, job enthusiasm, job satisfaction, and organizational commitment using the job demand-resource model for workers in the beauty industry. Based on literature research, 203 copies of data were collected from workers in the beauty industry by developing research models and hypotheses, and the data were analyzed using a structural equation model (SEM) for hypothesis verification. Looking at the results of this study, first, it was found that job demand had a significant positive (+) effect on job burnout and job enthusiasm, and job resources had a significant positive (+) effect on job enthusiasm. Second, job burnout had a significant negative (-) effect on organizational commitment, and job enthusiasm had a significant positive (+) effect on job satisfaction and organizational commitment. In order for the job demands required for workers in the beauty industry to lead to enthusiasm rather than job bunout, it is thought that support of appropriate job resources for job performance should be strategically provided.

Configuration-Driven No-Code Data Ingestion Engine with RuleBased Processing

The efficient management of batch processes is critical for modern data-driven organizations, especially within the context of complex data ingestion and processing workflows. This abstract explores the essential components and functionalities required to streamline batch job execution within such environments. Firstly, a robust batch management system is essential, providing capabilities for job scheduling, dependency management, and error handling. Such a system orchestrates the execution of batch jobs, ensuring they run in the appropriate sequence and handle dependencies effectively. Additionally, real-time event-driven triggers enable immediate batch job initiation upon file drops, ensuring timely processing of incoming data and swift response to business needs. Conversely, scheduled batch executions provide predictability and automation, allowing organizations to optimize resource utilization and maintain operational efficiency by running batches at predetermined intervals or specific times. Furthermore, the abstract delves into the necessity of a comprehensive configuration setup to support various data formats, transformation requirements, and validation criteria. A rich configuration engine allows for seamless mapping, transformation, and validation of incoming data, enabling flexibility and adaptability to diverse data sources and requirements. It also emphasizes the importance of containerization for batch job execution, ensuring scalability, resource isolation, and efficient utilization of computing resources. Lastly, the provision of job IDs facilitates seamless invocation of batch jobs by external systems, enabling streamlined interaction and integration across different platforms. Together, these components form a cohesive framework for efficient batch job management, empowering organizations to optimize data processing workflows and derive actionable insights from their data assets.

Influence of servant leadership on the life satisfaction of basic education teachers: the mediating role of satisfaction with job resources.

Life satisfaction is essential for teachers' work performance and student learning. Additionally, servant leadership has been shown to be one of the best leadership practices as it promotes employee well-being and satisfaction. Moreover, satisfaction with job resources acts as a mediator in the relationship between servant leadership and life satisfaction by influencing individual and collective performance in the organization. This research aimed to evaluate the mediating role of satisfaction with job resources in the relationship between servant leadership and life satisfaction. The study was cross-sectional and explanatory. 620 teachers aged between 20 and 62 years (M = 35 and SD = 9.49) participated in the study. Structural Equation Modeling (SEM) was used to measure life satisfaction, service leadership, and job resource satisfaction through the use of questionnaires. The results indicated that the model obtained an adequate fit, χ2 = 2,658, df = 551, p < 0.001, CFI = 0.941, TLI = 0.936, RMSEA = 0.079, SRMR = 0.070. The results confirm the positive influence of leadership on satisfaction with resources and life satisfaction. Additionally, a positive influence of satisfaction with job resources on life satisfaction was observed. Moreover, the mediation of job resources in servant leadership and life satisfaction was confirmed. Servant leadership, supported by satisfaction with job resources, can reduce effort and associated costs, stimulate personal growth and learning, and improve the well-being of teachers.

Linking frontline construction workers' perceived abusive supervision to work engagement: job insecurity as the game-changing mediation and job alternative as a moderator

PurposeThis research focuses on exploring a psychological mechanism between abusive supervision and job engagement via job insecurity and job alternative to understand how frontline construction workers' perceived abusive supervision impacts on their work engagement.Design/methodology/approachThis study draws on the conservation of resources theory (COR) to postulate that workers' job insecurity acts as a mediation between abusive supervision and work engagement, and the perception of job alternative moderates the impact of abusive supervision on job insecurity. This study empirically tests survey data from 357 frontline construction workers and adopts partial least square structural equation modeling (PLS-SEM) to test the proposed model.FindingsThis paper proved the dark-side of abusive supervision, dual character of job insecurity and moderating role of job alternative. The game-changing mediation effects of job insecurity were examined, which suggested that work engagement would be higher when abusive supervision stimulates stronger job insecurity. Furthermore, the result indicated that the relationship between abusive supervision and job insecurity should be weaker when job alternative is high.Practical implicationsThis research suggests construction project managers (CPMs) must take steps such as enhancing supervisors' emotional management skills to control frequency of abuse and thus lessen compromising engagement. Moreover, overall understanding frontline workers' job insecurity is meaningful for better construction performance management.Originality/valueThis research contributes to the disputed leadership style (abusive supervision) and positive psychology knowledge (work engagement) in construction projects by unveiling the psychosocial mechanism (game-changing effects of job insecurity) of construction frontline workers positive engaged feeling. This study highlights the function of personal and job resources in process of resource conservation.

High-performance work systems and proactive behavior: the mediating role of customer-oriented behavior

PurposeAlthough high-performance work systems (HPWS) have been shown to promote employees' proactive behavior, only a limited number of studies have examined this process. This study explores how HPWS promote proactive behavior through learning goal orientation (LGO) and customer-oriented behavior (COB).Design/methodology/approachA questionnaire survey was conducted with 279 healthcare workers in nursing homes. Structural equation modeling was conducted to test the hypotheses.FindingsThe results show that HPWS positively influenced proactive behavior through COB and that HPWS positively influenced proactive behavior through LGO and subsequently through COB. The findings indicate that COB is vital in linking HPWS to proactive behavior in healthcare service organizations.Originality/valueThe results suggest that HPWS provide job resources that enable health care workers to take initiatives to change their work environment through performance management, incentive systems and training programs. This study is the first to identify the mediating role of COB in linking HPWS to proactive behavior.

How do technology-driven stressors influence workarounds? Moderating roles of support structures and trait resilience

Despite recognizing the prominent effects of enterprise system (ES) use on organizations and individuals, employees frequently resort to workarounds that run counter to the intention of ES implementation. Building upon the job demands-resources (JD-R) model, we expand the challenge-hindrance stressor framework to encompass technology-driven stressors (TDS) as distinct job demands influencing employees’ workarounds. Additionally, we regard support structures as job resources and trait resilience as personal resources and then examine how the interplay between resources and demands affects workarounds. Our research is underpinned by a comprehensive two-study design. Specifically, Study 1 entailed a longitudinal survey with data gathered from 326 users within a Chinese company. The results show that technology-driven challenge stressors decrease workarounds, whereas technology-driven hindrance stressors increase it. Moreover, job and personal resources play different roles in mitigating the impact of specific TDS on workarounds. In addition, Study 2 utilized qualitative interviews to validate and supplement the findings from the Study 1. This research contributes to both theoretical and practical implications in ES research by extending the JD-R model to explore the influence of various job demands and resources on workarounds.