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The purpose of this paper is to have a deeper understanding of the nonlinear relationship between the impact of climate change on tourism development. Current studies on the effects of climate change on tourism development primarily rely on linear correlation assumptions.

Based on the New Institutional Economics theory, the institutional setting inherently motivates and ensures the growth of the tourism industry. For a precise evaluation of the nonlinear consequences of climate change on tourism, this paper concentrates on Chinese cities between 2011 and 2021, methodically analyzing the influence of climate change on tourism.

The study findings suggest that there is an “inverse U”-shaped nonlinear relationship between climate change and tourism development, initially strengthening and subsequently weakening. Based on these findings, the research further delves into how institutional contexts shape the nonlinear association between climate change and tourism growth. It was found that in a higher institutional backdrop, the “inverse U” curve tends to flatten and surpass the curve adjusted for a lesser institutional context. Upon deeper mechanism analysis, it was observed that cities with more advanced marketization, improved industrial restructuring and enhanced educational growth exhibit a more evident “inverse U”-shaped nonlinear connection between climate change and tourism evolution.

First, previous studies on climate change and tourism development largely rely on questionnaire data (Hu et al., 2022). In contrast to these studies, this paper uses dynamic panel data, which to some extent overcomes the subjectivity and difficulty of causality identification in questionnaire data, making our research conclusions more accurate and reliable. Second, this study breaks through the linear relationship hypothesis of previous literature regarding climate change and tourism development. By evaluating the nonlinear relationship of climate change to tourism development from the institutional pressure perspective, it more intricately delineates their interplay mechanism, expanding and supplementing the research literature on the relationship mechanism between climate change and tourism development. Thirdly, the conclusions of this study are beneficial for policymakers to better understand and assess the scope of climate change impacts. It also aids relevant departments in clarifying the direction of institutional environment optimization to elevate the level of tourism development when faced with adverse impacts brought about by climate change.

Attention is one of the most important factors to affect the academic performance of students. Effectively analyzing students' attention in class can promote teachers' precise teaching and students' personalized learning. To intelligently analyze the students' attention in classroom from the first-person perspective, this paper proposes a fusion model based on gaze tracking and object detection. In particular, the proposed attention analysis model does not depend on any smart equipment.

Given a first-person view video of students' learning, the authors first estimate the gazing point by using the deep space–time neural network. Second, single shot multi-box detector and fast segmentation convolutional neural network are comparatively adopted to accurately detect the objects in the video. Third, they predict the gazing objects by combining the results of gazing point estimation and object detection. Finally, the personalized attention of students is analyzed based on the predicted gazing objects and the measurable eye movement criteria.

A large number of experiments are carried out on a public database and a new dataset that is built in a real classroom. The experimental results show that the proposed model not only can accurately track the students' gazing trajectory and effectively analyze the fluctuation of attention of the individual student and all students but also provide a valuable reference to evaluate the process of learning of students.

The contributions of this paper can be summarized as follows. The analysis of students' attention plays an important role in improving teaching quality and student achievement. However, there is little research on how to automatically and intelligently analyze students' attention. To alleviate this problem, this paper focuses on analyzing students' attention by gaze tracking and object detection in classroom teaching, which is significant for practical application in the field of education. The authors proposed an effectively intelligent fusion model based on the deep neural network, which mainly includes the gazing point module and the object detection module, to analyze students' attention in classroom teaching instead of relying on any smart wearable device. They introduce the attention mechanism into the gazing point module to improve the performance of gazing point detection and perform some comparison experiments on the public dataset to prove that the gazing point module can achieve better performance. They associate the eye movement criteria with visual gaze to get quantifiable objective data for students' attention analysis, which can provide a valuable basis to evaluate the learning process of students, provide useful learning information of students for both parents and teachers and support the development of individualized teaching. They built a new database that contains the first-person view videos of 11 subjects in a real classroom and employ it to evaluate the effectiveness and feasibility of the proposed model.

This paper examines the direct and indirect effects of CEO intellectual capital on sustainable growth of small and medium-sized enterprises (SMEs) in China.

It adopts a quantitative approach based on 3,474 unbalanced panel data in 836 Chinese listed SMEs from 2008 to 2017.

The findings reveal a significant positive relationship between CEO intellectual capital and sustainable growth of SMEs. The findings also reveal that dual innovation (exploitative innovation and exploratory innovation) has a partial mediating effect on the relationship.

It further provides an original contribution to identifying and testing the mediating effect of dual innovation on the relationship between CEO intellectual capital and sustainable growth of SMEs.

In contrast to most of the extant literature, which considers intellectual capital as a whole at the organizational level or focuses on employee intellectual capital, this paper highlights the role of CEO intellectual capital for SMEs’ growth. It provides an original contribution to identifying and testing the mediating effect of dual innovation on the relationship between CEO intellectual capital and sustainable growth of SMEs.

This study social based on cognitive theory (SCT), aims to better understand how transformational leadership affects team-level knowledge sharing and absorptive ability in the construction industry. It also examines the moderating influence of the AI-based virtual assistant on the indirect relationship between transformational leadership and team innovation through knowledge sharing and absorptive ability at the team level.

This study used a simple random sample approach to gather data from several small and medium-sized construction firms in Anhui Province, China. A total of 407 respondents, including 89 site engineers and 321 team members, provided their responses on a five-point Likert scale questionnaire.

The findings showed that AI-based virtual assistants significantly moderated the direct and indirect association between transformational leadership and knowledge sharing, and subsequently with team innovation. Unexpectedly, the findings showed that AI-based virtual assistant did not moderate the direct relationship between transformational leadership and team-level absorptive capacity.

This study adds a fresh perspective to the literature on construction management by examining team innovation driven by transformational leadership through an underlying mechanism. It is unique in that it uses the team adaptation theory to investigate the understudied relationship between transformational leadership and team innovation in the construction industry.

The purpose of this study is to investigate the evolving perceptions and human resource (HR) responses of owners and HR managers of Chinese small and medium-sized enterprises (SMEs) towards local labour markets in the context of the impact of the coronavirus disease 2019 (COVID-19) pandemic.

This study adopts a two-stage longitudinal qualitative approach involving 52 interviews with owners and HR managers of Chinese SMEs in the pre- and post-pandemic time periods.

The findings reveal a shift from the perceptions of a general labour shortage to perceptions of specialised talent shortages and increasing geographical disparities in local labour markets. They further reveal that SMEs are increasingly likely to adopt efficiency-oriented, flexibility-enhancing HR practices in the face of high uncertainty.

The findings provide insights into the nature of the constraints of SMEs' sustainable development that need to be addressed by policymakers, SME owners and HR managers when they devise and implement policies relating to structure optimisation, labour market integration and mobility enhancement.

In contrast to extant literature that has examined the labour market at the national level, this study explores the views of SMEs (the demand side) by taking a localised perspective on how SMEs have responded to change through their HR practices.

This study aims to investigate the link between information technology capabilities (ITC) and organizational performance (OP) in the hospitality industry by focusing on the indirect effect of sustainability practices, service innovation (SINO), service improvement (SIMP) and the moderating role of top management support (TMS).

Time-lagged survey data from 488 hotel managers in the United Arab Emirates was used in this study to examine the hypotheses by the PROCESS Macro.

The authors found significant support for our framework, demonstrating that ITC are linked with OP. The study found that ITC and OP are sequentially mediated by sustainability practices, SINO and SIMP. Additionally, the influence of information technology (IT) capabilities on OP is moderated by TMS, whereas TMS also enhances the sequential mediating effect of sustainability practices, SINO and improvement, such that the sequential mediating effect is stronger when TMS is at a high level.

To the best of the authors’ knowledge, this paper is the first to examine the sequentially moderated mediating effect of sustainability practices and then SINO and SIMP between ITC and OP using a time-lagged design in the hospitality industry.

This paper aims to explore the impact of enterprise niche on dual innovation performance and the moderating role of innovation openness on the relationship between enterprise niche and dual innovation performance.

This study uses the panel data of the enterprise technology patents of China's Top 100 Electronic Information Enterprises from 2009 to 2018. Multiple regression analyses were used to test the hypotheses.

Niche width has a significant positive impact on exploitative and exploratory innovation performance. Niche overlap has an inverted U-shaped effect on exploitative innovation performance and significantly positively affects exploratory innovation performance. Innovation openness negatively moderates the impact of niche width on exploitative innovation performance and positively moderates the impact of niche overlap on exploitative innovation performance.

This study provides new insights into the effects of enterprise niche on dual innovation performance by showing the moderating role of innovation openness. The study finds a strategic logic of moderate niche overlap, clarifies the innovative effect of different innovation openness modes and reveals the construction and management mechanisms of enterprise niche and innovation openness strategy.

Examine the effects of sudden environmental disasters on the advancement of both renewable and conventional energy technologies.

Utilizing panel data from 31 Chinese provinces spanning 2011 to 2022, the SEM (Spatial Error Model) dual fixed model is utilized to examine the impact of sudden environmental disasters on energy technologies.

The findings reveal that: (1) Sudden environmental disasters exert a markedly positive influence on the Innovation of Renewable Energy Technologies (IRET), while their impact on conventional energy technologies is positively non-significant. (2) Sudden environmental disasters not only significantly enhance innovation in local renewable energy technologies but also extend this positive influence to neighboring regions, demonstrating a spatial spillover phenomenon. (3) Research and Development (R&D) funding serves as a partial mediator in the relationship between sudden environmental disasters and renewable ETI. In contrast, Foreign Direct Investment (FDI) exhibits a masking effect.

Consequently, the study advocates for intensified efforts in post-disaster reconstruction following abrupt environmental events, an elevation in the quality of foreign direct investments, and leveraging research funding to catalyze innovation in renewable energy technologies amid unforeseen environmental crises.

Different information sharing mechanisms and online platform information sharing to different charging models are compared and analyzed.

This paper uses the Stackelberg game model to study the demand information sharing and pricing decisions.

The results show that: (1) the retailer's pricing strategy is the highest when both of them obtain information, while the manufacturer's pricing strategy is affected by the related attributes of different products, such as the sensitivity of consumers to product prices; (2) in the online platform sales model, the demand information data sharing owned by the online platform can bring more expected profits to the whole supply chain and the members of the supply chain, and the higher the accuracy of the information, the higher the expected profit; (3) when the cost of obtaining demand information is zero, that is, the online platform shares the information data about market demand free of charge, the retailer and manufacturer tend to obtain information; (4) for the online platform, charging a certain fee can achieve higher expected profits than free sharing.

Based on the single platform online sales model, this paper uses the Stackelberg game model to study the demand information sharing and pricing decision of a manufacturer and a retailer selling products through the same online platform.

A model for calculating the global overpressure time history of a single cloud detonation from overpressure time history of discrete positions in the range of single cloud detonation is to be proposed and verified. The overpressure distribution produced by multiple cloud detonation and the influence of cloud spacing and fuel mass of every cloud on the overpressure distribution are to be studied.

A calculation method is used to obtain the global overpressure field distribution after single cloud detonation from the overpressure time history of discrete distance to detonation center after single cloud detonation. On this basis, the overpressure distribution produced by multi-cloud under different cloud spacing and different fuel mass conditions is obtained.

The results show that for 150 kg fuel, when the spacing of three clouds is 40 m, 50 m, respectively, the overpressure range of larger than 0.1 MPa is 5496.48 mˆ2 and 6235.2 mˆ2, which is 2.89 times and 3.28 times of that of single cloud detonation. The superposition effect can be ignored when the spacing between the three clouds is greater than 60 m. In the case of fixed cloud spacing, once the overpressure forms continuous effective superposition, the marginal utility of fuel decreases.

A model for calculating the global overpressure time history of a single cloud detonation from overpressure time history of discrete positions in the range of single cloud detonation is proposed and verified. Based on this method, the global overpressure field of single cloud detonation is reconstructed, and the superimposed overpressure distribution characteristics of three cloud detonation are calculated and analyzed.