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To reconceptualize the organizational environment in a comprehensive manner, it is important to specify not just the velocity but also other aspects of turbulent environments. Concurrently, the purpose of this paper is to also propose that organizational adaptability and, particularly, the speed of adaptations are critical to moderate the impact of turbulence in the environment on organizational performance.

This paper uses a conceptual methodology to fully specify turbulent environments and commensurate managerial response appropriate for such environments. Based on a perspective borrowed from the field of fluid dynamics used to specify the phenomenon of turbulence, the authors develop a conceptual model with research propositions. Four dimensions that describe turbulence in fluid flow when applied metaphorically offer a comprehensive view of the organizational environment.

An extreme, unanticipated, sudden onslaught resulting in a prolonged disrupted environment such as during the recent coronavirus crisis is best characterized as having caused turbulent environmental conditions. Management theories have addressed disruptions as high-velocity environments in the context of rapid changes in information technology. With a broadened conceptualization of the organizational environment to better capture extreme disruptions, the authors provide a comprehensive model appropriate for turbulent environmental conditions and offer research directions for scholarly pursuit.

This paper provides a new perspective from the physical sciences to better conceptualize organizational environments during extreme disruptions such as in turbulent environmental conditions.

This study aims to answer the following question: Why might home-based work duties be perceived by female academics as extreme?

We employed a qualitative research method through semi-structured interviews with 33 female academics from three public universities selected from amongst 26 public institutions of higher education in Egypt. Thematic analysis was subsequently used to determine the main ideas in the transcripts.

We find that the sudden implementation of home-based work makes the academic duties of female academics extreme. Moreover, the following four factors help explain the extremity/intensity of the home-based work of female academics: mental and physical fatigue resulting from WFH, the inability to adequately meet family commitments when working from home (WFH), poor resources for home-based work and reduced ability to focus on the obstacles facing them in their academic career.

This paper contributes by filling a gap in human resources management and higher education in which empirical studies on female academics WFH and extreme academic duties have been limited so far.

The present study used the job-demands and resources (JD-R) framework to understand how the training is transferred to an extreme working context through the analysis of job and personal resources (social support from the leader and colleagues and adaptability). Specifically, the authors tested the mediating role of motivation to transfer in the relationship (1) between the perceived support from the supervisor and colleagues and performance after training and (2) between adaptability and performance in an extreme context of the pandemic crisis – the first peak of COVID-19 in Portugal. Further, an inspection of the factors that predicted knowledge transfer and adaptability under an extreme context was carried out.

To do so, necessary training about the new safety rules regarding the pandemic crisis of COVID-19 was implemented in a healthcare institution as a strategy to help healthcare workers deal with the increasing uncertainty and complexity that was threatening their work. It consisted of three sessions (each with one hour of training) regarding procedures, rules and safety norms. The training occurred in May 2020. Overall, 291 healthcare workers participated in the study and answered one online questionnaire one week after training completion.

The results showed that the motivation to transfer had a significant indirect effect on the relationship between colleagues' and supervisors' support and performance and between adaptability and performance. Additionally, complementary analyses showed that the mediations depended on the levels of self-efficacy in such a way that the indirect relationships were stronger when self-efficacy was higher. Thus, adaptability and support, both from colleagues and the supervisor, are determining factors for knowledge transfer and resultant performance in extreme contexts, such as the COVID-19 pandemic crisis. Lastly, the results showed that the most significant predictors of transference were self-efficacy and the motivation to transfer the learned knowledge. On the other hand, self-efficacy, peer support and the opportunity to use the knowledge were the most significant predictors of adaptability.

These findings provide support for the role of employee motivation to transfer as a mechanism connecting both perceived support and adaptability to performance outcomes under extreme working contexts.

This study, conducted in the middle of the COVID-19 pandemic context – an extreme and uncertain working context – shows the relevance of both job and individual factors to predict employees' adaptability to such contexts.

Aged-care work has become an extreme form of work. Anti-violence HRM, comprising practices to combat workplace violence, is important in an industry with widespread violence. In this paper, we employ social exchange theory to better understand the effect of anti-violence HRM and trust in the manager on perceived nurse and PCA cynicism working in Australian aged care facilities and their subsequent intention to leave.

This study used a mixed method with two stages. Stage 1 comprised semi-structured interviews with 10 managers and 50 nurses and PCAs working in Australian aged care facilities. Stage 2 comprised a survey of nurses and PCAs with a total of 254 completed responses in Time 1 (first wave) and 225 completed responses in Time 2 (second wave).

We tested three hypotheses and reported that interestingly anti-violence HRM was positively associated with organisational cynicism. Organisational cynicism mediated the relationship between anti-violence HRM and intention to leave. Worker trust in the manager moderated the relationship between anti-violence HRM practices and organisational cynicism, such that high levels of trust in the manager increased the effect of anti-violence HRM practices to reduce organisational cynicism and subsequently reduce intention to leave.

We find evidence that in aged care, workers' trust in their managers is critical for effectual anti-violence HRM. We argue that implementation of HRM practices may be more complex in extreme work settings. It is crucial to study HRM in situ and understand the root of social exchange(s) as a foundation for HRM to influence employee attitudes and behaviour.

This research aims to propose a model for the complex decision-making involved in the ecological restoration of mega-infrastructure (e.g. railway engineering). This model is based on multi-source heterogeneous data and will enable stakeholders to solve practical problems in decision-making processes and prevent delayed responses to the demand for ecological restoration.

Based on the principle of complexity degradation, this research collects and brings together multi-source heterogeneous data, including meteorological station data, remote sensing image data, railway engineering ecological risk text data and ecological restoration text data. Further, this research establishes an ecological restoration plan library to form input feature vectors. Random forest is used for classification decisions. The ecological restoration technologies and restoration plant species suitable for different regions are generated.

This research can effectively assist managers of mega-infrastructure projects in making ecological restoration decisions. The accuracy of the model reaches 0.83. Based on the natural environment and construction disturbances in different regions, this model can determine suitable types of trees, shrubs and herbs for planting, as well as the corresponding ecological restoration technologies needed.

Managers should pay attention to the multiple types of data generated in different stages of megaproject and identify the internal relationships between these multi-source heterogeneous data, which provides a decision-making basis for complex management decisions. The coupling between ecological restoration technologies and restoration plant species is also an important factor in improving the efficiency of ecological compensation.

Unlike previous studies, which have selected a typical section of a railway for specialized analysis, the complex decision-making model for ecological restoration proposed in this research has wider geographical applicability and can better meet the diverse ecological restoration needs of railway projects that span large regions.

The purpose of this paper is to investigate dynamics of causal interactions and financial risk contagion among BRICS stock markets under rare events.

Two methods are adopted: The new causal inference technique, namely, the Liang causality analysis based on information flow theory and the dynamic causal index (DCI) are used to measure the financial risk contagion.

The causal relationships among the BRICS stock markets estimated by the Liang causality analysis are significantly stronger in the mid-periods of rare events than in the pre- and post-periods. Moreover, different rare events have heterogeneous effects on the causal relationships. Notably, under rare events, there is almost no significant Liang's causality between the Chinese and other four stock markets, except for a few moments, indicating that the former can provide a relatively safe haven within the BRICS. According to the DCIs, the causal linkages have significantly increased during rare events, implying that their connectivity becomes stronger under extreme conditions.

The obtained results not only provide important implications for investors to reasonably allocate regional financial assets, but also yield some suggestions for policymakers and financial regulators in effective supervision, especially in extreme environments.

This paper uses the Liang causality analysis to construct the causal networks among BRICS stock indices and characterize their causal linkages. Furthermore, the DCI derived from the causal networks is applied to measure the financial risk contagion of the BRICS countries under three rare events.

This study aims to evaluate and compare the quality of work life (QWL) of nurses, in pre- and post-COVID-19 pandemic situations.

The study adopts a descriptive research design. Data were collected during the pre- and post-pandemic periods. The target sampling unit of the study comprises nurses working in Bangalore city, Karnataka, India. The minimum sample size was determined (Bartlett et al., 2001) as 385. The scale validation is carried out. The factors for the present study were explored using exploratory factor analysis and confirmed by confirmatory factor analysis. Model fitness (proposed measurement model) is ensured by using fit indices. The linear regression method was used to measure the level of QWL of nurses.

The present study noted that key factors that affects the QWL of nursing staff are work condition; work environment; work-life balance; compensation and reward; career development; job satisfaction and security; organization culture; relationship among co-workers and stress. Further, it is noticed that QWL of nurses pre-COVID-19 pandemic is 87.2%, while post-COVID-19 pandemic, it is 67%.

Present study can be extended to address the same research question by considering sampling unit such as therapist, technicians and sanitarians who have equally undergone tremendous pressure during pandemic.

The study outcome provides references for organizations engaged in health services to understand the extreme job conditions posed by pandemic. The constructive inspiration (physio-social and organizational support) reinforces the nurses to continue in their professions by decreasing negative impact.

The research paper extends the contributions of Hwang (2002), Nikeghbal et al. (2021), Howie–Esquivel et al. (2022) and Rania et al. (2023) and add to the existing body of the QWL literature. The outcome of the research records the prevailing conditions of pandemic and its effect on changes in work environment with specific reference to health-care sector.

The main purpose of this study is to provide a comprehensive review and critical insights of the application of fuzzy methods in modeling, assessing and understanding the various aspects of green and sustainable supply chains (SSCs).

The present study conducts a systematic literature review (SLR) and bibliometric analysis of 252 research articles. This study employs various tools such as VOSviewer version 1.6.10, Publish or Perish, Mendeley and Excel that aid in descriptive analysis, bibliometric analysis and network visualization. These tools have been used for performing citation analysis, top authors' analysis, co-occurrence of keywords, cluster and content analysis.

The authors have divided the literature into seven application areas and discussed detailed insights. This study has observed that research in the social sustainability area, including various issues like health and safety, labor rights, discrimination, etc. is scarce. Integration of the Industry 4.0 technologies like blockchain, big data analytics, Internet of Things (IoT) with the sustainable and green supply chain (GSC) is a promising field for future research.

The authors' contribution primarily lies in providing the integrated framework which shows the changing trends in the use of fuzzy methods in the sustainability area classifying and consolidating green and sustainable supply chain management (SSCM) literature in seven major areas where fuzzy methods are predominantly applied. These areas have been obtained after the analysis of clusters and content analysis of the literature presenting key insights from the past and developing the conceptual framework for future research studies.

This paper aims to provide scholars with a deep understanding of the field through the identification of strengths and weaknesses in the literature and support decision-makers in the development of new practices in local risk management based on scientific data. The specific question in this review asks: what are the drivers and barriers to local risk management?

This paper provides an overview of the scientific literature produce over the past 20 years of the divers and barriers to local risk management. This paper presents a scoping review of peer-reviewed articles published between 2000 and 2019 inclusively in the fields of public policy and public administration.

This paper makes three main observations regarding the state of the literature. First, this paper finds that scholars mainly focus on single risk and certain regions of the world. Second, there is multiple approached used by the literature to study risk management at the local level. Third, little attention is given to the political context in which local risk management takes place.

This paper is a complete literature review of more than 500 peer-reviewed articles published in academic journals regarding risk prevention policies over the past two decades. This paper analyzed the main findings of the current literature to provide a general view of the scholarship and improve the collective understanding of risk management at the local level by providing future research avenues.

Within the labor-intensive construction industry characterized by distinctly structural shortages in the labor force worldwide, efficient and effective migration of construction workers across regions is critical for the smooth operation of construction activities. This study aims to investigate how the interregional migration patterns of construction workers are impacted by the disparities in both employment opportunities and environment amenities between the origin and destination provinces.

Drawing on the push and pull theory and the archival data on 13,728 migrant construction workers in China, descriptive analyses are first performed to characterize the interregional migration patterns of the investigated construction workers. Combining regional data in the National Bureau of Statistics of China, this study uses hierarchical regression modeling techniques to empirically test the relative importance of the employment-related and environment-related factors in driving the interregional migration of construction workers after controlling for the effects of related economic and geographic factors.

The results provide evidence that the interregional migration of construction workers is principally driven by the disparities in employment opportunities while disparities in environment amenities (including climate comfort disparity, medical service disparity and educational service disparity) generally play much fewer substantive roles. With regard to the impacts of employment opportunities, the results provide evidence that compared with the disparity in job market size, the disparities in job income and industry development level are more significantly relevant factors, which positively pull and adversely push the interregional migration flows, respectively.

This study contributes to a deepened understanding of how workers specifically balance their employment and amenity needs to make temporary migration decisions in the “laggard” labor-intensive construction industry. This study also adds to the literature on population migration by characterizing the specific characteristics of construction workers and the temporary nature of the workers' migration activities. The findings hold important practical implications for construction organizations and policymakers for effectively managing the mobility of migrant construction workers.

The extant literature on migrant construction workers has primarily focused on the consequences of international migration and the generalization of empirical findings on population migration mechanisms in other domains to the construction industry is substantially limited by the specific characteristics of construction workers and the temporary nature of their migration activities. In addressing this gap, this study represents an exploratory effort to quantitatively characterize the interregional migration patterns of construction workers in the labor-intensive construction industry and examines the roles of employment opportunity and environmental amenity in driving interregional migration.