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The purpose of this paper is to explore the impact of ChatGPT on the development of corporate social responsibility (CSR).

Based on the current applications of ChatGPT in enterprises and existing challenges in CSR, the paper analyzes how the tool promotes corporate sustainable development and what potential risks and challenges are in the practical application.

This paper finds that ChatGPT can promote the development of CSR from four aspects: to support social responsibility activities, to strengthen internal control, to promote external supervision and to convey the notion of sustainability and other corporate philosophies for enterprises.

This paper provides the ground for applying ChatGPT to CSR and includes the potential risks and challenges of the practical applications that enterprises can use for reference.

ChatGPT is becoming increasingly popular and mature, but its applications and effectiveness are less mentioned in CSR. In the future, the research in this area needs to be further advanced.

This paper makes contributions to the link between ChatGPT and CSR. To the best of the authors’ knowledge, this is one of the first studies that explore the applications, impacts, challenges and opportunities of the technology in the area of social responsibility.

The study examines how process/organizational innovation and R&D spending mediate the relationship between financial performance and the resource dependence theory in Fintech, providing insights into effective innovation strategies for achieving sustainable financial performance.

Data from 191 financial firms in Taiwan was collected from annual reports using the Taiwan Economic Journal (TEJ), a financial information provider. Content analysis was used to measure innovation activities and financial performance, with process and organizational innovation defined. R&D expenditures were also collected and used in statistical analysis to explore the relationship between variables.

This study on the financial services industry shows that process innovation and R&D expenditure positively impact firm performance, while organizational innovation may have a negative short-term effect but could have long-term benefits.

Limitations of this study include vulnerability to spurious effects and the use of data from only listed financial service firms. Future research should use more short-term performance data and include unlisted firms in the financial services industry to extend the study’s coverage.

This study extends resource dependence theory to financial services and explores the effects of process and organizational innovation on firm performance. Results show that internal process management boosts performance, while external collaboration with startups enhances Fintech innovation and efficiency, with positive short-term effects. The study highlights the importance of interacting with external organizations to access resources and improve performance in financial services.

Drought is the primary disaster that negatively impacts agricultural and animal husbandry production. It can lead to crop reduction and even pose a threat to human survival in environmentally sensitive areas of China (ESAC). However, the phases and periodicity of drought changes in the ESAC remain largely unknown. Thus, this paper aims to identify the periodic characteristics of meteorological drought changes.

The potential evapotranspiration was calculated using the Penman–Monteith formula recommended by the Food and Agriculture Organization of the United Nations, whereas the standardized precipitation evaporation index (SPEI) of drought was simulated by coupling precipitation data. Subsequently, the Bernaola-Galvan segmentation algorithm was proposed to divide the periods of drought change and the newly developed extreme-point symmetric mode decomposition to analyze the periodic drought patterns.

The findings reveal a significant increase in SPEI in the ESAC, with the rate of decline in drought events higher in the ESAC than in China, indicating a more pronounced wetting trend in the study area. Spatially, the northeast region showed an evident drying trend, whereas the southwest region showed a wetting trend. Two abrupt changes in the drought pattern were observed during the study period, namely, in 1965 and 1983. The spatial instability of moderate or severe drought frequency and intensity on a seasonal scale was more consistent during 1966–1983 and 1984–2018, compared to 1961–1965. Drought variation was predominantly influenced by interannual oscillations, with the periods of the components of intrinsic mode functions 1 (IMF1) and 2 (IMF2) being 3.1 and 7.3 years, respectively. Their cumulative variance contribution rate reached 70.22%.

The trend decomposition and periods of droughts in the study area were analyzed, which may provide an important scientific reference for water resource management and agricultural production activities in the ESAC. However, several problems remain unaddressed. First, the SPEI considers only precipitation and evapotranspiration, making it extremely sensitive to temperature increases. It also ignores the nonstationary nature of the hydrometeorological water process; therefore, it is prone to bias in drought detection and may overestimate the intensity and duration of droughts. Therefore, further studies on the application and comparison of various drought indices should be conducted to develop a more effective meteorological drought index. Second, the local water budget is mainly affected by surface evapotranspiration and precipitation. Evapotranspiration is calculated by various methods that provide different results. Therefore, future studies need to explore both the advantages and disadvantages of various evapotranspiration calculation methods (e.g. Hargreaves, Thornthwaite and Penman–Monteith) and their application scenarios. Third, this study focused on the temporal and spatial evolution and periodic characteristics of droughts, without considering the driving mechanisms behind them and their impact on the ecosystem. In future, it will be necessary to focus on a sensitivity analysis of drought indices with regard to climate change. Finally, although this study calculated the SPEI using meteorological data provided by China’s high-density observatory network, deviations and uncertainties were inevitable in the point-to-grid spatialization process. This shortcoming may be avoided by using satellite remote sensing data with high spatiotemporal resolution in the future, which can allow pixel-scale monitoring and simulation of meteorological drought evolution.

Under the background of continuous global warming, the climate in arid and semiarid areas of China has shown a trend of warming and wetting. It means that the plant environment in this region is getting better. In the future, the project of afforestation and returning farmland to forest and grassland in this region can increase the planting proportion of water-loving tree species to obtain better ecological benefits. Meanwhile, this study found that in the relatively water-scarce regions of China, drought duration was dominated by interannual oscillations (3.1a and 7.3a). This suggests that governments and nongovernmental organizations in the region should pay attention to the short drought period in the ESAC when they carry out ecological restoration and protection projects such as the construction of forest reserves and high-quality farmland.

The findings enhance the understanding of the phasic and periodic characteristics of drought changes in the ESAC. Future studies on the stress effects of drought on crop yield may consider these effects to better reflect the agricultural response to meteorological drought and thus effectively improve the tolerance of agricultural activities to drought events.

The chapter introduced stealth construction as a transformative concept emerging in the construction industry, emphasising resilience and efficiency through innovative technologies, cutting-edge materials, and advanced methodologies. Drawing parallels to stealth aircraft, stealth construction aims to create buildings and infrastructure that blend seamlessly into their environments, minimising environmental impact and enhancing sustainability. This approach integrates smart materials, strategic planning, and covert practices throughout all construction stages, ensuring robust, adaptive, and discreet structures. Stealth construction represents a significant paradigm shift by prioritising energy efficiency, environmental responsibility, and resilience against natural disasters and cyber threats. It combines modern aerospace engineering principles with diverse construction practices to achieve construction invincibility, setting new standards for the industry regarding sustainability, security, and aesthetics.

Carbon emissions trading is an effective instrument in reducing greenhouse gas emissions. There is a notable scarcity of comprehensive reviews on the modelling techniques within carbon trading research in construction.

This paper reviews 68 relevant articles published in 19 peer-reviewed journals using systematic search. Scientometric analysis and content analysis are undertaken.

Generally, China was the largest contributor to carbon trading research using quantitative models (representing 36% of the total articles). From the results, the modelling techniques identified were multi-objective grasshopper optimisation algorithm; system dynamics; interpretive structural modelling; multi-agent-based model; decision-support model; multi-objective chaotic sine cosine algorithm; optimised backpropagation neural network; sequential panel selection method; Granger causality test; and impulse response analysis. Moreover, the advantages and disadvantages of these techniques were identified. System dynamics was recommended as the most suitable modelling technique for carbon trading in construction.

This study is significant, and through this review paper, practitioners can easily be more familiar with the significant modelling techniques, and this will motivate them to better understand their uses.

This study explores the influence of core self-evaluation (CSE) on students’ academic self-efficacy, anxiety and interpersonal responses. It investigates how internal beliefs impact academic success among Chinese higher education students.

A qualitative research design was employed, using semi-structured interviews with 30 students from various disciplines at H University. The thematic analysis was utilized to interpret the data.

The findings suggest that students with higher levels of CSE exhibit greater academic confidence and can manage academic-related stress and depression. Positive interpersonal responses enhanced academic self-efficacy, confidence and inner motivation, serving as a buffer against the negative effects of anxiety. Moreover, students’ perceptions of their emotional stability and control contributed significantly to their academic confidence and resilience.

The study is limited by its qualitative nature and the sample size, which is restricted to one university. These limitations may affect the generalizability of the findings. Future research could employ a mixed-methods approach to corroborate these findings across different cultural settings and educational systems.

The study highlights the importance of a supportive educational environment that fosters positive self-evaluations and interpersonal responses to enhance students' academic self-efficacy. Educational institutions should consider integrating psychological support mechanisms and opportunities for developing interpersonal skills within their curricula.

This research contributes to the limited literature on the impact of core self-evaluation in Chinese higher education, particularly highlighting the complex relationship between personal beliefs, emotional management and social interactions in shaping academic outcomes.

This paper aims to examine the complex balance between enthusiasm and skepticism regarding artificial intelligence (AI) integration in educational practices. It advocates for a cautious, evidence-based approach while addressing both opportunities and challenges, aligning with the United Nations Sustainable Development Goal 4 (SDG4) for Quality Education.

Through critical analysis of current discourse surrounding AI in education, this paper synthesizes existing literature on both supportive and skeptical perspectives. The methodology involves systematic examination of past educational technology trends, current AI developments and their implications for teaching and learning. The paper develops its research agenda through careful consideration of existing empirical studies, theoretical frameworks and identifying gaps in current understanding.

The analysis reveals that while AI offers promising potential for enhancing learning outcomes and educational accessibility, its integration presents significant challenges that require careful consideration. The paper identifies critical tensions between technological innovation and pedagogical values, highlighting areas where enthusiasm for AI adoption must be tempered with empirical evidence and critical evaluation. Current evidence suggests that successful AI integration requires balanced consideration of both opportunities and limitations, with particular attention to maintaining human-centered educational practices.

This viewpoint provides a comprehensive framework for understanding the dialectic between AI’s educational potential and its limitations. By synthesizing both supportive and critical perspectives, it offers a nuanced approach to AI integration that acknowledges both opportunities and challenges. The article’s value lies in its systematic identification of key research priorities and its emphasis on evidence-based implementation strategies that serve educational goals while mitigating potential risks.

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.

The research objective is to establish a smart system for building operation and maintenance using self-organizing map-based cluster merging (SOMCM) algorithm.

The process begins with a thorough literature review to establish the interface framework, followed by its design. An empirical study in Taoyuan City’s industrial park, involving 46 buildings and 3,526 maintenance records, informed development. By integrating the “Shared Facility Management System Equipment Repair Module” and the “Maintenance Management System for Existing Facilities,” 21 enhanced interface components were created. All work orders are stored in a database for aggregation, statistical analysis and clustering using the algorithm SOMCM, aiding repair decision-making.

The outcomes stemming from the proposed methodology culminate in the identification of seven patterns that can significantly enhance the efficiency of maintenance operations: (1) simplify current self-repair to outsourcing; (2) modify the current traditional contract type to open contract type; (3) adopt massive procurement for major facilities (e.g. air conditioning); (4) schedule power supply systems in a systematic and efficient way; (5) establish maintenance patterns as suggested to eliminate warehouse for spares; (6) reallocate maintenance resources in a seasonal cycle; (7) set up a standby team to resolve emergency repairs. The findings can reduce a significant amount of time and cost for the investigated industrial park.

Maintenance work has faced delays, aging equipment has caused component damage, and park structures no longer meet operational needs. Addressing these challenges, the study introduces a novel SOMCM approach for smart building operation and maintenance. This approach emphasizes creating a user-friendly, practical system pivotal to platform success. By integrating demand-driven strategies, it enhances traditional maintenance processes and offers innovative solutions to operational and management issues, ensuring alignment with modern requirements and improved efficiency.

The post-pandemic era has shifted most industries, businesses and consumers online, increasing the demand for electronic devices, mainly laptops. Additionally, most non-Western countries inhabit highly religious but cash-strapped individuals, making them a potential market for second-hand laptops. With this in mind, this study aims to explore the effects of lenient return policy (LRP) and religiosity on consumer confidence in retailer (CCR), consumer well-being and purchase intention.

This paper conducted a between-subjects field experiment comparing two return policy conditions (cash return vs. other return) with a sample of 222 participants. Data were analysed using partial least squares structural equation modelling (PLS-SEM) to test the hypothesised relationships, and multigroup analysis (MGA) was employed to assess the experimental effects based on the return policy conditions. The moderating effects of religiosity were also examined. All analyses were conducted using SmartPLS software.

The results confirm that an LRP positively predicts consumer confidence in retailer, well-being and purchase intention. Religiosity had a moderating effect on LRP outcomes. Additionally, the experiment confirmed that consumers experienced better well-being and were more likely to purchase if offered full cashback.

Retailers of second-hand shopping products should offer LRP (full cashback) to foster consumer confidence, well-being and purchase intention. Additionally, for highly religious consumers, aligning return policies with religious principles should further enhance consumer well-being and purchase intention.

This study is among the earliest to investigate the impact of LRP on CCR and well-being. Moreover, a novel attempt is made to explore the moderating effects of religiosity on LRP outcomes. Likewise, a field experiment to validate the greater effects of cashback on consumer well-being and purchase intention adds to the novelty of this study.