Resource Model Research Articles

Effect of Supportive Leadership on Job Burnout and Occupational Commitment: The Mediating Role of Intrinsic Motivation

Abstract Based on the job demands–resources model, self-determination theory, and social exchange theory, this study examines the influence of supportive leadership on job burnout and occupational commitment. The study also investigates the mediating role of intrinsic motivation. This study collected 221 valid questionnaires from 5 insurance companies in southern Taiwan and applied structural equation modeling using confirmatory factor analysis and bootstrapping to verify the proposed hypotheses. Extensive validation processes are also conducted to verify the fitness of the measurement model. The results confirm that supportive leadership directly affects job burnout and occupational commitment, and that intrinsic motivation significantly mediates the effect of supportive leadership on job burnout and occupational commitment. Finally, the study provides practical insights for researchers and professionals and proposes directions for future research. Keywords: Supportive leadership, Intrinsic motivation, Job burnout, Occupational commitment, Taiwan insurance industry.

RESTORATION OF RESOURCES FOR TEACHERS AND STUDENTS OF BORYS GRINCHENKO KYIV UNIVERSITY DURING THE FIRST YEAR OF THE WAR IN UKRAINE

The article is aimed at highlighting the problems of restoring the resources of teachers and students during the first year of hostilities in Kyiv, Ukraine. Modern scientific views on the concepts of “resources”, “human resources” in the context of the impact of the war on the condition of teachers and students are analyzed. The research is based on the “BASIC Ph” resource model developed by Mouli Laad and Ofra Ayalon (Israel). The focus is not on the negative consequences of the war for the participants of the survey, but on the ability to recover, to open up new opportunities for the ability to live on, to live a full life, as much as possible in the changed circumstances during the war. The article presents the results of the study of the content and features of the restoration of the resources of teachers and students of Borys Grinchenko Kyiv University during the first year of the war in Ukraine. The authors present an analysis of the features and significance of each component of the resource model for teachers and students, compare the results and draw conclusions. This article can be useful for everyone who is interested in the consequences of military conflicts on civilians, on their ability to overcome crisis situations and rebuild a new life.

When experiencing nice interactions at work: Good sleep quality via well-being.

Based on the Work-Home Resources Model and Conservation of Resources Theory, we develop dual mechanisms by which nice interactions (patients' compliments and coworkers' informational support) predict sleep quality. Specifically, we expect these nice interactions to help individuals conserve their personal energy in the form of less cognitive depletion (a cognitive process) and diminished physical fatigue (a physical process). Further, we propose employees utilise their energy resources to experience better sleep quality. To test the proposed model, we utilised an experience-sampling method by recruiting 223 female nurses working in a regional university hospital in South Korea. Specifically, we measured nice interactions and personal resources at 3 PM on Dayt and sleep quality at 5-6 AM on Dayt+1, and we administered the questionnaire for 10 consecutive days. Overall, after removing 79 invalid observations (not completing questionnaire in a timely manner), we had a final total of two-wave 1997 daily observations from 223 nurses. Receiving more compliments from patients and more information from coworkers positively affects nurses' cognitive energy (less cognitive depletion) and physical energy (less physical fatigue), which predicts better sleep quality. Finally, results supported indirect effects of these nice interactions on sleep quality via cognitive and physical processes.

Bridging Quantitative and Qualitative Science for BECCS in Abandoned Croplands

AbstractBioenergy with carbon capture and storage (BECCS) plays a vital role in most climate change mitigation scenarios, where a solution for sustainable near‐term bioenergy expansion is to grow energy crops such as perennial grasses on recently abandoned cropland. There is a need to combine model‐based insights into theoretical potential and future biomass supply with more fine‐grained sociotechnical analysis to move toward realistic policies and innovation strategies. We combine natural science insights anchored in quantitative bioenergy modeling with qualitative social science anchored in the multi‐level perspective. Using these mixed methods enables a global‐to‐local‐to‐global level assessment of near‐term bioenergy recultivation opportunities for abandoned cropland. Norway is the local case. There are three main findings. First, the ongoing recultivation trends for food/feed production risks making gains in aboveground carbon stocks from natural regrowth on the mapped abandoned cropland over a 30‐year evaluation period almost negligible. Second, delaying a BECCS recultivation of abandoned cropland will make it impossible to reach high‐end mitigation potentials, and an accelerated BECCS recultivation guided by a policy push is needed to ensure stronger mitigation. Third, we unravel several real‐world challenges associated with bioenergy resource and supply modeling. Remote‐sensing techniques alone cannot capture actual land availability for land‐based climate change mitigation strategies. Local‐level sociotechnical conditions are generally found insufficiently supportive to align with the rapid near‐term bioenergy crop expansion found in 2°C scenarios from integrated assessment. The integration of mixed quantitative and qualitative methods is key to better understand the role of BECCS in climate change mitigation.

Ex-Ante Flooding Damages’ Monetary Valuation Model for Productive and Environmental Resources

The floods caused by river flooding are increasingly at the center of public attention and government agencies. This is due to climate change, a higher risk consciousness of settled populations, as well as the deteriorating state of water basins caused by the persistent absence of appropriate controls on the use of mountain and hilly territories. In Italy, the risk of flooding is particularly high, posing a significant social problem due to the number of victims and the damage inflicted on properties, industries, and infrastructure. This paper aims to examine the principles and methods of evaluating the damage caused to the territory by river flooding. Two evaluation models are developed for the formal definition of the variation law of damage caused by flooding, considering the return period of the flood event. The first model allows the evaluation of damage to the productive part of the territory affected by floods, while the second considers damage related to the environmental aspects.

Variability modeling of products, processes, and resources in cyber–physical production systems engineering

Cyber-Physical Production Systems (CPPSs), such as automated car manufacturing plants, execute a configurable sequence of production steps to manufacture products from a product portfolio. In CPPS engineering, domain experts start with manually determining feasible production step sequences and resources based on implicit knowledge. This process is hard to reproduce and highly inefficient. In this paper, we present the Extended Iterative Process Sequence Exploration (eIPSE) approach to derive variability models for products, processes, and resources from a domain-specific description. To automate the integrated exploration and configuration process for a CPPS, we provide a toolchain which automatically reduces the configuration space and allows to generate CPPS artifacts, such as control code for resources. We evaluate the approach with four real-world use cases, including the generation of control code artifacts, and an observational user study to collect feedback from engineers with different backgrounds. The results confirm the usefulness of the eIPSE approach and accompanying prototype to straightforwardly configure a desired CPPS.

The double-edged sword effect of mega sport event strength on volunteer performance

Purpose This study aims to use event system theory and job demands–resources (JD-R) model to examine the double-edged sword effect of event strength of Beijing Winter Olympics (BWO) on volunteers’ in-role performance and proactive behavior as mediated by work overload and meaningfulness. Design/methodology/approach The sample included 193 volunteer–leader dyads working at one BWO venue. The authors conducted a multitime and multisource study using Mplus 8 to examine the hypotheses. Findings Volunteers’ perceived BWO event strength was positively related to work overload, which reduced in-role performance and proactive behavior. Volunteers’ perceived BWO event strength was also positively related to work meaningfulness, which promoted in-role performance and proactive behavior. Perceived organizational support served as a moderator by mitigating the positive relationship between perceived BWO event strength and work overload; however, it did not strengthen the positive relationship between perceived BWO event strength and work meaningfulness. Originality/value This study developed a comprehensive model of how BWO event strength affected volunteers’ performance from the perspective of event system theory and the JD-R model, which enriches theoretical application and research in the context of mega sport events.

A Dynamic Adaptive and Resource-Allocated Selection Method Based on TOPSIS and VIKOR in Federated Learning

Federated learning (FL) is a decentralized and privacy-preserving machine learning technique that protects data privacy by learning models locally and not sharing datasets. However, due to limited computing resources on devices and highly heterogeneous data in practical situations, the training efficiency and resource utilization of federated learning is low. In order to resolve these challenges, we introduce a blockchain-assisted dynamic adaptive and personalized federated learning framework (TV-FedAvg) in the presence of restricted computing power resources and data heterogeneity. After each round of local training, we utilize an improved scoring model based on VIKOR and TOPSIS to comprehensively score the devices. The scores are then utilized to choose devices for participation in global aggregation and to carry out model aggregation through blockchain consensus. Furthermore, resources are reallocated for the next round to enhance resource efficiency, model fairness, and performance. Finally, we demonstrate through experimentation that TV-FedAvg outperforms other models such as pFedMe, FedAvg, Per-FedAvg, and TOPSIS in terms of both efficiency and performance.

Mindfully and confidently digital: A mixed methods study on personal resources to mitigate the dark side of digital working.

A growing body of research demonstrates the potential of mindfulness to reduce employee stress. However, with work increasingly migrating from the physical to the digital workplace, evidence is lacking on how mindfulness might help employees live healthy digital working lives. In addition, employees' confidence when using the digital workplace is seen as important for productivity but may also play a role in reducing well-being impacts from digital working. Using the Job-Demands Resources model as a theoretical foundation, 142 workers were surveyed regarding their levels of trait mindfulness and digital workplace confidence, along with their experiences of the dark side effects (stress, overload, anxiety, Fear of Missing Out and addiction) and well-being outcomes (burnout and health). 14 workers were also interviewed to provide qualitative insights on these constructs. Results from regression analyses indicated that more digitally confident workers were less likely to experience digital workplace anxiety, while those with higher mindfulness were better protected against all of the dark side of digital working effects. Interview data indicated ways in which digital mindfulness helps protect well-being, as well as how digital workplace confidence enables healthier digital habits.

Managing Web-based Information Resources Under Uncertainty: A Probabilistic Approach

“Uncertainty” is related to working with inaccurate data, imprecise and incomplete information, and unreliable results that can lead to irrational decisions. Several approaches to managing uncertain data on the Web have been proposed in the literature to resolve this problem. These approaches have failed to find the solution to this problem with accuracy and performance. Our study aims to propose a new probabilistic approach to manage Web information resources in an uncertain large-scale cloud environment. Our approach is based on three main steps: (1) modelling uncertain Web resources, (2) computing HTTP request model, and (3) interpretation and evaluation of uncertain Web resources in a context of classic hypertext navigation. The experimental study shows that the analysis of the execution time necessary for the composition of the services, by our approach, is negligible, compared to that of the other studied approaches. The algorithm that deals with the impact of the variation in the number of nodes, which we have proposed, has also been evaluated and checks all the possibilities in polynomial time and can adapt to many possibilities of multiplexing of values.

Humble leadership and work–family enrichment: promotion focused and thriving

PurposeDrawing upon work-home resources model, this study aims to investigate how and when humble leadership influences followers’ work–family enrichment. Specifically, this study focuses on the mediating role of thriving at work and moderating role of promotion focus.Design/methodology/approachData were collected from 292 employees of science and technology enterprises in China through a three-wave questionnaire survey. Hierarchical regression analysis and bootstrapping approach were employed to test hypotheses.FindingsThis study found that thriving at work significantly mediated the relationship between humble leadership and work–family enrichment. Promotion focus strengthened the positive relationship between humble leadership and thriving at work and the indirect effect of humble leadership on work–family enrichment through thriving at work.Practical implicationsThe findings of this study offer guidance for managers to enhance thriving at work and improve employees’ work–family experiences.Originality/valueFirst, this study explores the work-to family spillover effects of humble leadership by examining the family outcomes of humble leadership. Second, this study further uncovers the underlying mechanism between humble leadership and work–family enrichment by demonstrating the mediating role of thriving at work. Third, by exploring the moderating role of promotion focus, this study provides insight into the boundary conditions of the impact of humble leadership.

KARAKTERISTIK PRIBADI DALAM PERKEMBANGAN HUMANRELATIONS

This article describes a healthy personality and its characteristics, as well as human relations activities and applications in practice. This research uses a qualitative approach. The purpose of making this article is to know about personal with good human relations, know about the application of human relations in practice and know the characteristics of a healthy personality. The results of the research show that there are three models of motivational communication in personal good human relations, namely the traditional model, the human relations model, and the resource model.

Totally asymmetric simple exclusion process with local resetting in a resource-constrained environment.

Inspired by the process of mRNA translation, in which the stochastic degradation of mRNA-ribosome machinery is modeled by the resetting dynamics, we study an open totally asymmetric simple exclusion process with local resetting at the entry site in a resource-constrained environment. The effect of constrained resources on the stationary properties of the system has been comprehended in the form of the filling factor. The mean-field approximations are utilized to obtain stationary state features, such as density profiles and phase diagrams. The phase diagram possesses pure phases as well as coexisting phases, including a low-density-high-density phase separation, which did not manifest under periodic boundary conditions despite the system being closed there as well. The role of the resetting rate has been investigated on the stationary properties of the system, depending on how the filling factor scales with the system size. In contrast to the resetting model for infinite resources, two distinct phase transitions are observed for the smaller values of the filling factor leading to a change in the topology of the phase diagram. The impact of the resetting rate along with the finite-size effect has also been examined on the shock dynamics. All the mean-field results are found in remarkable agreement with the Monte Carlo simulations.

The Roles of Sales Technologies for Salespeople: Techno Demands and Resources Model Perspective

The purpose of this study is to examine the effects of a salesperson’s techno-demands and techno-resources created by new sales-related information technology on salespersons’ attitudinal and behavioral outcomes such as job burnout, job satisfaction, turnover intention, and sales performance. In order to test the proposed framework, data were collected from 305 salespeople in Korea. The results of a partial least squared structural equation modeling (PLS-SEM) analysis showed that techno-demands have a significant positive effect on salespeople’s job burnout and techno-resources have a significant positive effect on salespeople’s job satisfaction. Salespeople’s job burnout has a significant positive effect on salespeople’s turnover intention, whereas salespeople’s job satisfaction has a significant positive effect on salespeople’s sales performance. Finally, salespeople’s job satisfaction has a negative effect on turnover intention. Theoretically, this study develops a new comprehensive framework of the techno demands–resources model and is empirically tested in the context of salespeople. Managerially, the findings offer important insights to practitioners to leverage techno-resources to accelerate the sales technologies for sales activities.

The Double-Edged Sword of Third-Party Resources: Examining Use and Financial Burden of Extracurricular Tools in Medical Students

Background Since before the COVID-19 pandemic, use of third-party resources (or educational tools separate from the in-house medical curriculum) has been steadily increasing. The transition to virtual learning in 2020 fostered a greater reliance on these mostly online resources during medical training, yet their contributions have rarely been evaluated. Thus, we aimed to review third-party resources and their implications for medical education, particularly their financial burden on students. Methods We examined 31 peer-reviewed articles that discuss third-party resources for medical students and relevant studies related to their equitable access. Results Studies suggest third-party resources are used in a task-dependent manner with a supplemental role to the in-house lectures during the preclinical phase and a primary role for USMLE preparation during the clinical phase. Medical students ubiquitously access these resources out of a perceived necessity to use them to perform well on board exams, prompted by studies demonstrating their efficacy in increasing USMLE Step 1 scores. Though certain resources have been more frequently cited for improving board performance (e.g.,First Aid and UWorld), students may combine multiple third-party resources to best serve their exam preparation. Findings also show the subscription-pricing model of most third-party resources and 12-month access prices range from $100 to $479, suggesting that third-party resource use contributes to an increase financial strain on students. This, coupled with overwhelming medical student debt, may exacerbate existing socioeconomic disparities in medical education. Conclusion Institutions should evaluate third-party resource use among their medical students and consider provisions to increase access to these co-curricular tools.

Emergent competition shapes top-down versus bottom-up control in multi-trophic ecosystems.

Ecosystems are commonly organized into trophic levels-organisms that occupy the same level in a food chain (e.g., plants, herbivores, carnivores). A fundamental question in theoretical ecology is how the interplay between trophic structure, diversity, and competition shapes the properties of ecosystems. To address this problem, we analyze a generalized Consumer Resource Model with three trophic levels using the zero-temperature cavity method and numerical simulations. We derive the corresponding mean-field cavity equations and show that intra-trophic diversity gives rise to an effective "emergent competition" term between species within a trophic level due to feedbacks mediated by other trophic levels. This emergent competition gives rise to a crossover from a regime of top-down control (populations are limited by predators) to a regime of bottom-up control (populations are limited by primary producers) and is captured by a simple order parameter related to the ratio of surviving species in different trophic levels. We show that our theoretical results agree with empirical observations, suggesting that the theoretical approach outlined here can be used to understand complex ecosystems with multiple trophic levels.

The Conditions and Guidelines of Action Learning Resources Through Miang Indigenous Wisdom in Mae Kampong Village, Chiang Mai Thailand

The objectives of this qualitative research were to study the conditions of the action learning resources through Miang indigenous wisdom in Mae Kampong Village, Chiang Mai Thailand, key informants consisted of twenty-six respondents, the instrument used was an unstructured interview form, the data were analyzed by content analysis and summarized into issues, and to study guidelines of the action learning resources through Miang indigenous wisdom in Mae Kampong Village, Chiang Mai Thailand; key informants consisted of twenty-five respondents, the data were analyzed by classifying into items. The research results were as follows: 1. The conditions of the action learning resources through Miang indigenous wisdom in Mae Kampong Village, Chiang Mai Thailand consisted of six aspects including 1.1 The social structure of Mae Kampong Village, Chiang Mai Thailand, 1.2 Ways of life, livelihood, and local wisdom, 1.3 Occupations and living, 1.4 Miang planters as an occupation, 1.5 Characteristics, and 1.6 Economics. 2. Guidelines of action learning resources through Miang indigenous wisdom to promote creative education in Mae Kampong Village, Chiang Mai Thailand consisted of the strengths, weaknesses, opportunities, and threats of the action learning resources applying as derived data to construct a model of action learning resources through Miang indigenous wisdom in Mae Kampong Village, Chiang Mai Thailand.

Emergency resource allocation considering the heterogeneity of affected areas during the COVID-19 pandemic in China

The scientific allocation of emergency resources is crucial to ensure the success of COVID-19 relief operations. However, the heterogeneity of epidemic areas has an important impact on the allocation of emergency resources. Although it is a crucial topic, there has been limited research that considers the heterogeneity of affected areas in the emergency resource allocation. To bridge the gap, this study proposes a multi-period optimal allocation model of emergency resources considering the heterogeneity of affected areas, which aims to make the allocation of resources more equitable, efficient and economical. Then, a typical and representative case of emergency medical resource allocation in Hubei Province, China (where the epidemic occurred earlier and was seriously affected by COVID-19), was selected for a simulation study to verify the effectiveness and feasibility of the proposed model and method. The study finds that considering the heterogeneity such as disaster coefficient and demand urgency in different disaster stricken areas in emergency resource allocation can minimize the negative impact of resource shortfalls, especially in the early period of relief operations with insufficient resource supply. In addition, the proposed model can optimize multi-period emergency resource allocation by simultaneously considering time (efficiency criterion), cost (economic criterion), and loss(equity criterion), which is in line with the actual needs of emergency rescue to the COVID-19 epidemic. The results of this study can be effectively applied to the multi-period optimal allocation of emergency resources for large-scale public health emergencies, and providing insights for the government and relevant management departments to formulate emergency resource allocation policies and plans.

Affective mechanisms linking role ambiguity to employee turnover

PurposeThis study relied on the job demands and resource model to understand employees’ turnover intentions. Recent studies have consistently lent support for the significant association between role ambiguity and turnover intentions; however, only a handful of studies focused on examining the potential mediators in this association. The authors argued that role ambiguity positively influences turnover intentions through affective mechanisms: job involvement and satisfaction.Design/methodology/approachTo test the model, a large sample of working adults participated (N = 505).FindingsStructural equation modeling results showed that role ambiguity, job involvement and job satisfaction were significantly associated with turnover intentions. Moreover, a serial mediation was found among the variables: employees with low levels of role ambiguity tended to report higher job involvement, which further increased their satisfaction with the job and subsequently decreased their turnover intentions.Research limitations/implicationsThe cross-sectional design is a limitation.Practical implicationsPractical suggestions regarding how organizations can reduce employee turnover are discussed.Originality/valueThe findings provide support for theory-driven interventions to address developing the intention to stay at work among working adults.

Modelling the critical determinants of architects’ work-related stress

Architects wearing different hats simultaneously suffer from occupational stress due to different construction characteristics. Decreased productivity, excessive absenteeism, burnout, and turnover intention are all linked to the effects of occupational stress. This study aims to pinpoint the critical stressors experienced by architects within the Turkish construction sector. A systematic literature review was conducted, and a questionnaire incorporating 48 stress factors along with the Work Stress Scale was designed, employing the Job Demand Resource (JD–R) model as a guiding conceptual framework. The survey was conducted on design architects responsible for Turkey’s design process. In total, 320 fully completed questionnaires were returned. The critical stressors (CSs) were determined using normalized mean value analysis. The results revealed 37 CSs and six critical stress factors were identified by exploratory factor analysis. Further, a structural equation model (SEM) was built to critical determinants of architects’ stress. Financial deficiencies, changes in construction projects, and poor communication factors were the most critical determinants of architects’ work-related stress. Within this context, the findings offer two new and original determinants for work-related stress that differ from former studies.