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This study aims to investigate the relationship between individual-level psychological resources and team resilience in the context of expatriate project management teams. It seeks to understand how personal psychological resources contribute to team resilience and explore the dynamic evolution mechanism of team resilience. The goal is to enhance team resilience among expatriates in a BANI (Brittle, Anxious, Nonlinear, and Incomprehensible) world, where organizations face volatile and uncertain conditions.

An online survey was applied for data collection, and 315 valid samples from Chinese expatriates in international construction projects were utilized for data analysis. A structural equation model (SEM) examines the relationships between personal psychological resources and team resilience. The study identifies five psychological factors influencing team resilience: Employee Resilience, Cross-cultural Adjustment, Self-efficacy, Social Support, and Team Climate. The hypothesized relationships are validated through the SEM analysis. Additionally, a fuzzy cognitive map (FCM) is constructed to explore the dynamic mechanism of team resilience formation based on the results of the SEM.

The SEM analysis confirms that employee resilience, cross-cultural adjustment, and team climate positively impact team resilience. Social support and self-efficacy also have positive effects on team climate. Moreover, team climate is found to fully mediate the relationship between self-efficacy and team resilience, as well as between social support and team resilience. The FCM model provides further insights into the dynamic evolution of team resilience, highlighting the varying impact effects of antecedents during the team resilience development process and the effectiveness of different combinations of intervention strategies.

This study contributes to understanding team resilience by identifying the psychological factors influencing team resilience in expatriate project management teams. The findings emphasize the importance of social support and team climate in promoting team resilience. Interventions targeting team climate are found to facilitate the rapid development of team resilience. In contrast, interventions for social support are necessary for sustainable, long-term high levels of team resilience. Based on the dynamic simulation results, strategies for cultivating team resilience through external intervention and internal adjustment are proposed, focusing on social support and team climate. Implementing these strategies can enhance project management team resilience and improve the core competitiveness of contractors in the BANI era.

Platform-based enterprises, as micro-entities in the platform economy, have the potential to effectively promote the low-carbon development of both supply and demand sides in the supply chain. Therefore, this paper aims to provide a multi-criteria decision-making method in a probabilistic hesitant fuzzy environment to assist platform-type companies in selecting cooperative suppliers for carbon reduction in green supply chains.

This paper combines the advantages of probabilistic hesitant fuzzy sets (PHFS) to address uncertainty issues and proposes an improved multi-criteria decision-making method called PHFS-DNMEREC-MABAC for aiding platform-based enterprises in selecting carbon emission reduction collaboration suppliers in green supply chains. Within this decision-making method, we enhance the standardization process of both the DNMEREC and MABAC methods by directly standardizing probabilistic hesitant fuzzy elements. Additionally, a probability splitting algorithm is introduced to handle probabilistic hesitant fuzzy elements of varying lengths, mitigating information bias that traditional approaches tend to introduce when adding values based on risk preferences.

In this paper, we apply the proposed method to a case study involving the selection of carbon emission reduction collaboration suppliers for Tmall Mart and compare it with the latest existing decision-making methods. The results demonstrate the applicability of the proposed method and the effectiveness of the introduced probability splitting algorithm in avoiding information bias.

Firstly, this paper proposes a new multi-criteria decision making method for aiding platform-based enterprises in selecting carbon emission reduction collaboration suppliers in green supply chains. Secondly, in this method, we provided a new standard method to process probability hesitant fuzzy decision making information. Finally, the probability splitting algorithm was introduced to avoid information bias in the process of dealing with inconsistent lengths of probabilistic hesitant fuzzy elements.

This study aims to investigate the critical success factors of digital transformation in the construction industry and identify whether the respondents' profiles influence their perceptions of critical success factors for digital transformation.

To achieve the objectives, a literature review was first conducted based on technology-organization-environment (TOE) framework. Then a questionnaire survey was carried out. A total of 86 people were surveyed in this study, mainly from the construction industry. At the level of data processing, SPSS was used for analysis. Among the main tests used were the Shapiro–Wilk test, reliability analysis, mean rank analysis, Kruskal–Wallis test and Mann–Whitney U test.

The study identified 15 critical success factors of digital transformation and found the three most important factors of digital transformation. Furthermore, respondents with different years of experience, enterprises with different sizes and different years made no difference in the perception of factors. Respondents' different occupations and types of enterprises created a bias in the perception of factors for digital transformation.

Firstly, the small sample size of the questionnaire limits the reference value of data analysis for certain groups. In addition, this study focuses broadly on construction enterprises without specifically examining different types of enterprises, thus lacking depth in its findings.

This study establishes a connection between TOE theory and the construction industry through an extensive literature review, identifying relevant factors and providing a reference for future research.

The study's results would enrich the research on digital transformation in the construction industry and provide a reference for the digital transformation of construction enterprises.

Grey target decision-making serves as a pivotal analytical tool for addressing dynamic multi-attribute group decision-making amidst uncertain information. However, the setting of bull's eye is frequently subjective, and each stage is considered independent of the others. Interference effects between each stage can easily influence one another. To address these challenges effectively, this paper employs quantum probability theory to construct quantum-like Bayesian networks, addressing interference effects in dynamic multi-attribute group decision-making.

Firstly, the bull's eye matrix of the scheme stage is derived based on the principle of group negotiation and maximum satisfaction deviation. Secondly, a nonlinear programming model for stage weight is constructed by using an improved Orness measure constraint to determine the stage weight. Finally, the quantum-like Bayesian network is constructed to explore the interference effect between stages. In this process, the decision of each stage is regarded as a wave function which occurs synchronously, with mutual interference impacting the aggregate result. Finally, the effectiveness and rationality of the model are verified through a public health emergency.

The research shows that there are interference effects between each stage. Both the dynamic grey target group decision model and the dynamic multi-attribute group decision model based on quantum-like Bayesian network proposed in this paper are scientific and effective. They enhance the flexibility and stability of actual decision-making and provide significant practical value.

To address issues like stage interference effects, subjective bull's eye settings and the absence of participative behavior in decision-making groups, this paper develops a grey target decision model grounded in group negotiation and maximum satisfaction deviation. Furthermore, by integrating the quantum-like Bayesian network model, this paper offers a novel perspective for addressing information fusion and subjective cognitive biases during decision-making.

The relation between metal corrosion behavior and double-layer capacity remains unclear. This study aims to put forward a novel method to measure double-layer capacity.

A novel model based on generalized Frumkin–Butler–Volmer equation was put forward. Combining this model with potentiodynamic polarization test and electrochemical impedance spectroscopy, the structure of double-layer capacity can be characterized.

This study found that the corrosion rate of iron increased with NaCl solution concentration and temperature at the experimental range, but an essential difference existed. The capacity of the diffuse layer and Stern layer increased with temperature and decreased with NaCl solution concentration. The ratio of diffuse layer capacity and Stern layer capacity influences the corrosion rate directly, which can be regarded as one of the judging criteria for corrosion resistance of metal materials.

The convenient means of double-layer structure characterization is still blank. With this method, the corrosion behavior of metal materials can be further analyzed, especially in high-temperature and pressure environments.

The smart contract provides an opportunity to improve existing contract management practices in the construction projects by replacing traditional contracts. However, translating the contracts into computer languages is considered a major challenge which has not been investigated. Thus, it is necessary to: (1) identify the obstructing clauses in real-world contracts; and (2) analyze the replacement's technical and economic feasibility. This paper aims to discuss the aforementioned objectives.

This study identified the flexibility clauses of traditional contracts and their corresponding functions through inductive content analysis with representative standard contracts as materials. Through a speculative analysis in accordance to design science paradigm and new institutional economics, the economic and technical feasibility of existing approaches, including enumeration method, fuzzy algorithm, rough sets theory, machine learning and artificial intelligence, to transform respective clauses (functions) into executable codes are analyzed.

The clauses of semantic flexibility and structural flexibility are identified from the contracts. The transformation of semantic flexibility is economically and/or technically infeasible with existing methods and materials. But with more data as materials and methods of rough sets or machine learning, the transformation can be feasible. The transformation of structural flexibility is technically possible however economically unacceptable.

Given smart contracts' inability to provide the required flexibility for construction projects, smart contracts will be more effective in less relational contracts. For construction contracts, the combination of smart contracts and traditional contracts is recommended. In the long run, with the sharing or trading of data in the industry level and the integration of machine learning or artificial intelligence reducing relevant costs, the automation of contract management can be achieved.

This study contributes to the understanding of the smart contract's limitations in industry scenarios and its role in construction project management.

The Singapore construction sector is promoting performance improvement by implementing collaborative contracting (CC). For CC's successful implementation, there is a need to sieve out the critical success factors (CSFs). Hence, this paper aims to explore factors influencing the adoption of CC and investigate the potential performance improvement by implementing CC.

Based on the literature review, 23 CSFs were identified and packaged to a questionnaire to evaluate the CSF's priority as well as CC's potential impact on the project performance. After prior validation, 165 potential respondents were drawn from survey list by using simple random sampling. Finally, 31 valid responses were received.

The survey result showed that the top five CSFs are mutual trust, all parties to commit fully, openness between parties, commitment to a win–win attitude and resource availability. The majority of respondents hold that CC implementation would improve overall project performance, decision effectiveness, cost, time, quality and risk performance.

Directors, project managers, contractor managers and site engineers have different perceptions of CSFs. Also rather than meeting the same requirements in the implementation of CC, there are differences among projects with different values.

This study provides an in-depth understanding of the CSFs for industry practitioners adopting CC and CC's potential impact on project performance. This study is also helpful for authorities to formulate effective policies to push the implementation of CC.

This paper aims to explore the influence of social support and the repatriation intention of expatriates in international constructions in the postpandemic era of COVID-19. Furthermore, test the mediation effect of team climate and individual resilience in this relationship.

A survey of 347 expatriates in international construction projects was conducted. A cross-level chain mediation model was employed to test the moderating effect of social support and repatriation intention. Then, statistical analysis with a bootstrap sample was used to test the mediation effect of the model.

The empirical results support that team climate, individual resilience and the chain mediating effect of team climate to individual resilience is significant among the influences of social support on repatriation intention. Social support can enhance the team climate of construction expatriates, promoting their resilience to reduce the repatriation intention further.

This study provides guidelines for international construction enterprises and managers to decide when and which expatriates should return home and formulate a series of policies to support expatriates and maintain a good team climate.

This study contributes to expatriate management literature by establishing the relationship between social support and repatriation intention. It provides a better understanding of how team-level factors impact individual thought. It takes team climate as one of the protective factors affecting individual psychological resilience. Also it takes social support as the antecedents of team atmosphere in case of emergencies.

Reducing income gap and enhancing welfare of people can be achieved through improved performance regarding socio-economic indicators, which can support sustainable development. People living in villages tend to migrate to the cities with the hope of enhancing their income. People living in cities and income gap among the people in the cities are expected to increase further. Enhanced living conditions in villages can reduce the need for this migration and increase welfare of the people in the villages. This chapter aims to examine drivers for sustainable smart villages and ways for enhancing and supporting their effectiveness in socio-economic development, in enhancing welfare and living conditions of people living in villages, and in reducing income gap between urban and rural people. This chapter investigates potential and roles of sustainable and smart villages in enhancing welfare and living conditions of people living in villages. Furthermore, this chapter emphasises the villages’ roles in sustainable development as well as importance of transformation of villages into the sustainable and smart ones and establishment of sustainable and smart villages so that convergence, social inclusion and socio-economic indicators can be supported. This chapter explains drivers for transformation of the villages into the sustainable and smart ones as well as establishment of new sustainable and smart villages. This chapter provides recommendations for sustainable and smart villages effective in contributing to sustainable and socio-economic development. This chapter can be useful to urban planners, construction industry stakeholders, policy makers and researchers.

The purpose of this paper is to identify the historical trends and status of the national development of artificial intelligence (AI) from a nationwide perspective and to enable governments at different administrative levels to promote AI development through policymaking.

This paper analyzed 248 Chinese AI policies (36 issued by the state agencies and 212 by the regional agencies). Policy bibliometrics, policy instruments and network analysis were used to reveal the AI policy patterns. Three aspects were analyzed: the spatiotemporal distribution of issued policies, the policy foci and instruments of policy contents and the cooperation and citation among policy-issuing agencies.

Results indicate that Chinese AI development is still in the initial phase. During the policymaking processes, the state and regional policy foci have strong consistency; however, the coordination among state and regional agencies is supposed to be strengthened. According to the issuing time of AI policies, Chinese AI development is in accordance with the global situation and has witnessed unprecedented growth in the last five years. And the coastal provinces have issued more targeted policies than the middle and western provinces. Governments at the state and regional levels have emphasized familiar policy foci and played the role of policymakers, along with regional governments that also functioned as policy executors as well. According to the three-dimension instruments coding, the authors found an uneven structure of policy instruments at both levels. Furthermore, weak cooperation appears at the state level, while little cooperation is found among regional agencies. Regional governments cite state policies, thus leading to the formation of top-down diffusion, lacking bottom-up diffusion.

The paper contributes to the literature by characterizing policy patterns from both external attributes and semantic contents, thus revealing features of policy distribution, contents and agencies. What is more, this research analyzes Chinese AI policies from a nationwide perspective, which contributes to clarifying the overall status and multi-level relationships of policies. The findings also benefit the coordinated development of governments during further policymaking processes.