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Artificial intelligence (AI) can enhance human resource resiliency (HRR) by providing the insights and resources needed to adapt to unexpected changes and disruptions. Therefore, the present research attempts to develop a framework for future researchers to gain insights into the actions of AI to enable HRR.

The present study used a systematic literature review, bibliometric analysis, and network analysis followed by content analysis. In doing so, we reviewed the literature to explore the present state of research in AI and HRR. A total of 98 articles were included, extracted from the Scopus database in the selected field of research.

The authors found that AI or AI-associated techniques help deliver various HRR-oriented outcomes, such as enhancing employee competency, performance management and risk management; enhancing leadership competencies and employee well-being measures; and developing effective compensation and reward management.

The present research has certain implications, such as increasing the HR team's proficiency, addressing the problem of job loss and how to fix it, improving working conditions and improving decision-making in HR.

The present research explores the role of AI in HRR following the COVID-19 pandemic, which has not been explored extensively.

Although there is growing research on the relationship between servant leadership and job performance, limited research examined conditions under which servant leadership is more effective. The purpose of this paper is to investigate whether employee-oriented human resource policy is shaping the relation between servant leadership and job performance.

Empirical research was carried out among 263 organizations operating in Poland. To verify formulated hypotheses, statistical reasoning with moderator was made using model 1 of SPSS Macro Process.

The present study has proved that employee-oriented human resource policy may act as a moderator between servant leadership and job performance strengthening this relation. Integrating human resource policy with leadership is important to reach a better understanding of how human resource and leadership can influence employee performance.

The current study provides a practical implication for organizations to train managers with leadership skills to improve the job performance of their employees.

Many experts suggest that the human being explore marine resources and marine new energy sources to alleviate the shortage of land resources and the ecological degradation. However, island coastal zones are considered to be fragile ecosystems; their geographical location and natural characteristics, their biodiversity and associated ecosystems, and their exposure to diverse land and sea conditions all make them highly vulnerable to environmental changes and human activities. Therefore, it is necessary to achieve the goals of environmental protection and sustainable development on the basis of a comprehensive evaluation and understanding of islands.

Due to the importance of island groups, this paper conducts evaluation studies on them. Using the Delphi, AHP and TOPSIS methods, this study evaluated quantitatively the comprehensive development level and comprehensive development potential of island groups in terms of resources, natural environment, economy and society. Innovatively using them as two subsystems, the present study combined the coupling coordination model and the obstacle factor calculation method.

The prospective index of comprehensive development was applied to the Changdao Island Group in Yantai, Shandong Province as an example, and the final evaluation revealed that the comprehensive development prospect of this island group had an upward trend from 2010 to 2017. Future efforts should be made to improve its economic and social conditions and economic development status, apart from promoting its comprehensive development by improving human resources management, increasing the GDP growth rate, and improving fresh water and electricity supply.

This study takes the integrated development level of the island and the integrated development potential of the island as two subsystems, and the innovative application of the coupling coordination degree model is used to calculate the integrated development index of the island to understand the development status of the island area. On the basis of this model, the obstacle factor identification method is designed to identify the main obstacle factors, and on the basis of evaluation and identification, specific measures to ensure the sustainable development of the island area are effectively proposed.

The relationship between man and nature varies with different stages of the development of human society. The destructive consequences brought about in the early stage of industrialization sparked serious concerns about ecological and environmental issues.

The worldwide controversy aroused by The Limits to Growth published in 1972 made people realize that the carrying capacity of the ecosystem was limited, as were the resources. In the long run, scientific and technological progress can constantly discover new energy and resources.

However, in every specific stage of human society, the energy and resources crises are always a severe challenge that human beings should face. It is the core contents of sustainable development to change the old economic growth model and explore a new economic growth model.

The relationship between man and nature is one of the most fundamental relationships in human society and economic development. How to deal with it is also one of the most fundamental issues in human society and economic development. From the perspective of the historical process of human society, the relationship has roughly gone through the following stages.

This study explores how compassionate managerial leadership style can help to mitigate workplace stressors and alleviate stress experiences among employees — particularly in an extreme situation, such as the current global COVID-19 pandemic. The study's context is Nigeria's banking, manufacturing and healthcare sectors, which have a history of high employee stress levels.

Using a qualitative, interpretive methodology, the study adopts the thematic analysis process (TAP) to draw and analyse data from semi-structured telephone interviews with 10 banking, 11 manufacturing and 9 frontline healthcare workers in Nigeria.

It was found that a compassionate managerial leadership can drive a considerate response to employees' “fear of job (in)security”, “healthcare risk” and concerns about “work overload, underpayment and delayed payment”, which respondents considered to be some of the key causes of increased stress among employees during the current COVID-19 pandemic.

The study is limited to exploring the relationship between compassionate managerial leadership and an organisation's ability to manage employee stress in the COVID-19 situation, using 30 samples from organisations operating in three Nigerian cities and sectors. Future studies may involve more Nigerian cities, sectors and samples. It may also possibly include quantitative combination to allow generalisation of findings.

In order to survive in extreme situations, such as the COVID-19 pandemic, organisations are forced to take drastic and often managerialist-driven work measures which can trigger high stress levels, low productivity and absenteeism among employees. Hence, organisations would benefit from implementing compassion-driven policies that are more inclusive and responsive to the workplace stressors facing employees.

Employee stress has been widely explored in many areas, including definitions, stressors, strains, possible interventions and coping strategies. There remains, however, a dearth of scholarship on how management-leadership compassion can help to reduce employee stress levels in extreme conditions, such as the COVID-19 pandemic — particularly in emerging economies.

At present, China’s forestry development is mainly driven by the traditional production factors such as forestry labor force, land resources and capital and thus the top priority of forestry development is to optimize forestry production factors. Scientific and effective forestry labor input has a significant role in promoting the development of forestry industry. Given that the actual input to forestry labor is not clear, the accuracy of the forestry industry development may be slightly affected. Based on the monitoring project of collective forest tenure reform (RCFT), this paper uses the survey data of 3,500 rural households in seven provinces of China from 2010 to 2014 and 2016 to 2017 to measure the actual labor force in China, and empirically analyzes and studies the factors influencing the development of forestry industry based on the provincial data of forestry in China, and further discusses the heterogeneous impact of forestry production factors on the development of forestry industry.

In this paper, the generalized least squares estimation model is used to calculate the actual number of forestry labor in China, and then the Cobb–Douglas production function is selected to explore the influencing factors of forestry industry development.

The results show that the actual number of forestry labor force in China continues to decline and the degree of reduction varies from different regions. The forestry labor is a major factor that promotes the development of the forestry industry, but this promotion is affected by the low matching degree between the forestry production factors and thus further inhibits the development of the forestry industry. Due to the time lag of the reform, the implementation of RCFT first weakens and then promotes the development of forestry production. Further on, the forestry labor input is heterogeneous in land resource endowment, forestry investment source and the proportion of management personnel.

Therefore, researches show that the feasible way to promote the development of forestry industry is to expand the scale of forestry labor force, optimize the mutual allocation of forestry production factors, enhance the input of human capital in forestry and deepen the RCFT.

The current study is designed to investigate the factors that foster the framing of destination competitiveness and establish the factors that drive the contribution of tourism innovations to economic growth in smart tourism destinations.

A four-year panel data were extracted from the World Economic Forum's travel and tourism competitiveness index and data were analysed using Poisson Pseudo Maximum Likelihood regression model.

The findings demonstrate that both the enabling environment and airport infrastructure significantly affect tourism's impact on the economy of the selected smart European tourism destinations. Conversely, human resources and general infrastructure display a negative correlation with tourism's contribution to the economy. However, no data in the sample support the idea that tourism policies, government prioritization or readiness of tourism information and communication technologies impact tourism's contribution to the economy. Additionally, the marginal effects indicate that improving the enabling environment and airport infrastructure can generate additional benefits for the economy through tourism.

The uniqueness of this study is the integration of smart tourism destinations with the measure of destination competitiveness to provide an empirical bridge that links tourism competitiveness to economic growth.

The purpose of this study is to examine the role of human resources management (HRM) on economic sustainability in Jordanian banks. To achieve this goal, data were collected from 23 Jordanian banks listed at the ASE from 2014 to 2019.

A regression model was employed using four independent variables that represent the HRM (i.e. managing the environment of human resources, human resources acquisition and preparation, human resources assessment and development and human resources compensation) and using economic sustainability as the dependent variable. The study also controlled for banks’ age, size, leverage and return on equity.

Results show that all independent variables are positively correlated with economic sustainability. The results imply that HRM is an important tool to enhance economic sustainability within the banking sector.

This study provides practical implications for banks’ managers, future researchers and policymakers. This is achieved by investigating the impact of the independent variables, including managing the human resources environment, the acquisition and preparation of human resources, the assessment and development of human resources and the compensation of human resources on the economic, social and environmental sustainability in Jordanian banks.

On shield tunnel construction (STC) site, human error is widely recognized as essential to accident. It is necessary to explain which factors lead to human error and how these factors can influence human performance. Human reliability analysis supports such necessity through modeling the performance shaping factors (PSFs). The purpose of this paper is to establish and validate a PSF taxonomy for the STC context.

The approach taken in this study mainly consists of three steps. First, a description of the STC context is proposed through the analysis of the STC context. Second, the literature which stretch across the PSF methodologies, cognitive psychology and human factors of STC and other construction industries are reviewed to develop an initial set of PSFs. Finally, a final PSF set is modified and validated based on STC task analysis and STC accidents cases.

The PSF taxonomy constituted by 4 main components, 4 hierarchies and 85 PSFs is established for human behavior modeling and simulation under the STC context. Furthermore, by comparing and evaluating the performance of STC PSF and existing PSF studies, the proposed PSF taxonomy meets the requirement for qualitative and quantitative analysis.

The PSF taxonomy can provide a basis and support for human behavior modeling and simulation under the STC context. Integrating PSFs into a behavior simulation model provides a more realistic and integrated assessment of human error by manifesting the influence of each PSFs on the cognitive processes. The simulation results can suggest concrete points for the improvement of STC safety management.

This paper develops a taxonomy of PSFs that addresses the various unique influences of the STC context on human behaviors. The harsh underground working conditions and diverse resources of system information are identified as key characteristics of the STC context. Furthermore, the PSF taxonomy can be integrated into a human cognitive behavior model to predict the worker’s behavior on STC site in future work.