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This study investigates how the maximum cultural intelligence (Max CQ) within a team – defined as the highest cultural intelligence level of an individual member – affects intra-team communication, conflict dynamics and, ultimately, team satisfaction and performance in global virtual teams (GVTs).

Utilizing quantitative research methods, this investigation draws on a dataset comprising 3,385 participants, which forms a total of 686 GVTs.

The study reveals that MaxCQ significantly enhances team communication, which in turn mitigates conflict, increases satisfaction and improves performance. It is noteworthy that the influence of MaxCQ on GVT success is more significant than the average cultural intelligence (CQ) of team members, providing critical insights for effective GVT management strategies.

The findings suggest that managers may optimize team dynamics not by uniformly increasing each member’s CQ but by concentrating on maximizing the CQ of one individual who can act as an influencer within the team. Strategically placing individuals with high CQ in GVTs can enhance overall team function.

While existing literature primarily examines the individual effects of CQ on communication and conflict management, this study sheds light on the collective interplay between MaxCQ, communication and conflict. It highlights the importance of MaxCQ, along with the frequency of team communication and conflict, in influencing team satisfaction and performance in GVTs.

By exploring the impact of digital knowledge resources (DKR) on the carbon emission intensity of the pig industry (PCEI), this study aims to reveal the role of DKR in reducing PCEI.

Based on provincial panel data in China from 2011 to 2021, this study uses the entropy and Intergovernmental Panel on Climate Change coefficient methods to calculate the evaluation index system of DKR and PCEI, respectively. Empirical analysis using a panel fixed-effects model examines the influence of DKR on PCEI and its underlying mechanisms.

DKR can significantly reduce PCEI. This conclusion still holds even after undergoing endogeneity treatment and a series of robustness tests. Mechanism test results indicate that DKR can operate indirectly through the mediation mechanism of rural human capital (RHC) and pig breeding technology innovation (PTI), while environmental regulation intensity (ERI) plays a positive moderating role in the relationship between DKR and PCEI. The magnitude of the impact of DKR on PCEI depends on ERI. Further studies found that the impact of DKR on PCEI has obvious heterogeneity characteristics, and the promotion effect is more obvious in regions with good integration degrees and high development potential.

This paper divides DKR into three dimensions: digital technology knowledge (DTK), digital management knowledge (DMK) and digital application knowledge (DAK), providing a new framework for research and enriching the understanding of the relationship between DKR and PCEI. Furthermore, the research results reveal the application potential of DKR in the pig industry, particularly in terms of resource allocation efficiency. This is of great significance for promoting low-carbon development in the pig industry and provides insights for the low-carbon transformation of other industries. In addition, the study emphasizes the moderating effect of ERI on the mechanism of carbon reduction in the pig industry through DKR. This offers a new perspective for understanding the relationship between knowledge management and environmental governance, providing a reference basis for policy formulation in related fields.

This paper further enriches the role of DKR in the livestock industry. Integrating DKR with traditional industries promotes knowledge innovation, information distribution and utilization and scientific decision-making. This has significant value in promoting the development and application of carbon reduction technologies, enhancing industrial competitive advantages, and other aspects.

The bridge expansion joint (BEJ) is a key device for accommodating spatial displacement at the beam end, and for providing vertical support for running trains passing over the gap between the main bridge and the approach bridge. For long-span railway bridges, it must also be coordinated with rail expansion joint (REJ), which is necessary to accommodate the expansion and contraction of, and reducing longitudinal stress in, the rails. The main aim of this study is to present analysis of recent developments in the research and application of BEJs in high-speed railway (HSR) long-span bridges in China, and to propose a performance-based integral design method for BEJs used with REJs, from both theoretical and engineering perspectives.

The study first presents a summary on the application and maintenance of BEJs in HSR long-span bridges in China representing an overview of their state of development. Results of a survey of typical BEJ faults were analyzed, and field testing was conducted on a railway cable-stayed bridge in order to obtain information on the major mechanical characteristics of its BEJ under train load. Based on the above, a performance-based integral design method for BEJs with maximum expansion range 1600 mm (±800 mm), was proposed, covering all stages from overall conceptual design to consideration of detailed structural design issues. The performance of the novel BEJ design thus derived was then verified via theoretical analysis under different scenarios, full-scale model testing, and field testing and commissioning.

Two major types of BEJs, deck-type and through-type, are used in HSR long-span bridges in China. Typical BEJ faults were found to mainly include skewness of steel sleepers at the bridge gap, abnormally large longitudinal frictional resistance, and flexural deformation of the scissor mechanisms. These faults influence BEJ functioning, and thus adversely affect track quality and train running performance at the beam end. Due to their simple and integral structure, deck-type BEJs with expansion range 1200 mm (± 600 mm) or less have been favored as a solution offering improved operational conditions, and have emerged as a standard design. However, when the expansion range exceeds the above-mentioned value, special design work becomes necessary. Therefore, based on engineering practice, a performance-based integral design method for BEJs used with REJs was proposed, taking into account four major categories of performance requirements, i.e., mechanical characteristics, train running quality, durability and insulation performance. Overall BEJ design must mainly consider component strength and the overall stiffness of BEJ; the latter factor in particular has a decisive influence on train running performance at the beam end. Detailed BEJ structural design must stress minimization of the frictional resistance of its sliding surface. The static and dynamic performance of the newly-designed BEJ with expansion range 1600 mm have been confirmed to be satisfactory, via numerical simulation, full-scale model testing, and field testing and commissioning.

This research provides a broad overview of the status of BEJs with large expansion range in HSR long-span bridges in China, along with novel insights into their design.

The purpose of this study is to scrutinize the relationship between the founder’s control level over the startup and the startup’s board size on fundraising efficiency, in addition to examining how these factors are influenced by different resource combinations that the startup attracts.

A sample of 1356 firm-year observations is collected from both the startup database of Business Next Media Corp. in Taiwan and the Company Registration and Business Registration Database of Taiwan’s Ministry of Economic Affairs’ Department of Commerce. The panel data analytic approach with fixed effect is used for hypothesis testing.

The founder’s shareholding negatively correlates with fundraising efficiency; such a negative relationship can be alleviated by incorporating foreign investors. The board size positively correlates with fundraising efficiency; such a positive relationship can be mitigated by the inclusion of external corporate directors.

While a conventional understanding posits that startups with diverse, multiplex and symmetrical boards can rapidly construct a diverse alliance portfolio, henceforth always being beneficial to growth, this research challenges this notion by probing the possible adverse effects of having an excessive number of outside corporate directors on a startup’s fundraising efficiency.

This study aimed to optimize the dyeing scheduling process with uncertain job completion time to reduce resource consumption and wastewater generation, and while reconciling the conflicting objectives of minimizing the makespan and the need to limit the production on specific machines to minimize rework.

We employed a UNISON framework that integrates fuzzy decision tree (FDT) to optimize dyeing machine scheduling by minimizing the makespan and water consumption, in which the critical attributes such as machine capacity and processing time can be incorporated into the scheduling model for smart production.

An empirical study of a high-tech textile company has shown the validity and effectiveness of the proposed approach in reducing the makespan and water consumption by over 8% while high product quality and efficiency being maintained.

High-tech textile industry is facing the challenges in reducing the environmental impact of the dyeing process while maintaining product quality and efficiency for smart production. Conventional scheduling approaches have not addressed the relationship between machine groups and reworking, resulting in difficulty in controlling the makespan and water consumption and increasing costs and environmental issues. The proposed approach has addressed uncertain job completion via integrating FDT into the scheduling process to effectively reduce makespan and wastewater. The results have shown practical viability of the developed solution in real settings.

The purpose of this paper is to establish a maturity evaluation model for the application of construction steel structure welding robotics suitable for the actual situation and specific characteristics of engineering projects in China and then to assess the maturity level of the technology in the application of domestic engineering projects more scientifically.

The research follows a qualitative and quantitative analysis method. In the first stage, the structure of the maturity model is constructed and the evaluation index system is designed by using the ideas of the capability maturity model and WSR methodology for reference. In the second stage, the design of the evaluation process and the selection of evaluation methods (analytic hierarchy process method, multi-level gray comprehensive evaluation method). In the third stage, the data are collected and organized (preparation of questionnaires, distribution of questionnaires, questionnaire collection). In the fourth stage, the established maturity evaluation model is used to analyze the data.

The evaluation model established by using multi-level gray theory can effectively transform various complex indicators into an intuitive maturity level or score status. The conclusion shows that the application maturity of building steel structure welding robot technology in this project is at the development level as a whole. The maturity levels of “WuLi – ShiLi – RenLi” are respectively: development level, development level, between starting level and development level. Comparison of maturity evaluation values of five important factors (from high to low): environmental factors, technical factors, management factors, benefit factors, personnel and group factors.

In this paper, based on the existing research related to construction steel structure welding robot technology, a quantitative and holistic evaluation of the application of construction steel structure welding robot technology in domestic engineering projects is conducted for the first time from a project perspective by designing a maturity evaluation index system and establishing a maturity evaluation model. This research will help the project team to evaluate the application level (maturity) of the welding robot in the actual project, identify the shortcomings and defects of the application of this technology, then improve the weak links pertinently, and finally realize the gradual improvement of the overall application level of welding robot technology for building steel structure.

This chapter examines the ‘embodied turn’ in the study of traditional Chinese sports and identifies issues within this area of research. It introduces new interpretative perspectives and approaches within the framework of bodily sociology to elucidate the link between locally-informed sports practices and the formation of socialized individuals. The chapter categorises the current research into three main themes: self-giving, the creation of bodily value and the construction of national identity through sports. It then integrates these themes with the findings of embodied sociology. The chapter compiles and analyzes the existing literature on traditional Chinese sports culture from both Chinese and international scholars, offering insights into the status, rationale and challenges of bodily sociological research. By contextualising the concept of the embodied turn in traditional Chinese sports culture – through concepts such as self-givenness, self-techniques, the generation of value and the creation of collective memory – the chapter discusses the impact of bodily sociology on cultural research. The chapter advocates for further bodily sociological studies of Chinese sports culture, which could enhance the understanding of Chinese studies among Western scholars and contribute to a genuine embodied turn in this field of study. Providing one of the initial explorations of embodied studies in traditional Chinese sports, the chapter reveals a transition from broad cultural interpretations and symbolic, structuralist sociology to a phenomenological approach in sports cultural studies. It posits that the bodily sociology approach is beneficial for sports studies although current research has not yet fully realized the embodied turn.

Nowadays, as organisations and companies increasingly harness the power of artificial intelligence (AI), there is a growing need to ensure future professionals in fields such as business and management can possess relevant necessary knowledge, skills, and mindset for navigating the ethical and social implications of AI technologies. This study evaluated the effects of a specialised AI literacy course designed for business students at a university in Hong Kong. The course aimed to equip participants with a basic understanding of AI concepts via self-paced materials, hands-on activities, case study discussion, and design thinking activities. Through a mixed-methods approach involving evaluation surveys and student and teacher reflections, this case study examined how effectively the course developed the students’ AI literacies as future business leaders and global digital citizens. AI competencies include understanding basic AI and generative AI (GenAI), using AI applications ethically, critically analysing AI-powered systems, identifying potential societal risks, and making data-driven decisions while upholding ethical principles. The findings provide valuable insights into the role of targeted AI education in preparing the next generation of business professionals for navigating the evolving data landscape and contributing to the responsible advancement of these transformative technologies.

The China-plus-one strategy is an increasingly attractive supply chain risk management strategy and has been adopted by many multinational enterprises. However, relevant research remains limited and warrants empirical validation. This paper addresses this research gap by investigating the determinants of emerging multinational enterprises’ adoption of a China-plus-one strategy.

The China-plus-one adoption decision of 1,527 firms was predicted using a logistic model based on Taiwan’s official data – Investigation of Foreign Sales and Manufacturing, for the years 2020–2022. This database is administered by the Department of Statistics of the Ministry of Economic Affairs (DSMEA) in Taiwan. Analysis was conducted using SPSS 25.0.

It is suggested that customer pressure and supplier relocation, functioning as push forces, lead to the China-plus-one strategy adopted by Taiwanese firms. Regarding pull forces, lower production cost has a positive association with China-plus-one adoption, whereas sufficient local workforce supply does not have a significant effect. Finally, in terms of the mooring forces, local sales performance is negatively related to the strategy adoption, whereas local access to components shows a positive association with such strategy.

This research uniquely adopts the push–pull–mooring framework to examine factors affecting supply chain restructuring in international business, representing a novel domain for this framework.

The diagnosis and prediction methods used for estimating the health conditions of the bearing are of great significance in modern petrochemical industries. This paper aims to discuss the accuracy and stability of improved empirical mode decomposition (EMD) algorithm in bearing fault diagnosis.

This paper adopts the improved adaptive complementary ensemble empirical mode decomposition (ICEEMD) to process the nonlinear and nonstationary signals. Two data sets including a multistage centrifugal fan data set from the laboratory and a motor bearing data set from the Case Western Reserve University are used to perform experiments. Furthermore, the proposed fault diagnosis method, combined with intelligent methods, is evaluated by using two data sets. The proposed method achieved accuracies of 99.62% and 99.17%. Through the experiment of two data, it can be seen that the proposed algorithm has excellent performance in the accuracy and stability of diagnosis.

According to the review papers, as one of the effective decomposition methods to deal with nonlinear nonstationary signals, the method based on EMD has been widely used in bearing fault diagnosis. However, EMD is often used to figure out the nonlinear nonstationarity of fault data, but the traditional EMD is prone to modal confusion, and the white noise in signal reconstruction is difficult to eliminate.

In this paper only the top three optimal intrinsic mode functions (IMFs) are selected, but IMFs with less correlation cannot completely deny their value. Considering the actual working conditions of petrochemical units, the feasibility of this method in compound fault diagnosis needs to be studied.

Different from traditional methods, ICEEMD not only does not need human intervention and setting but also improves the extraction efficiency of feature information. Then, it is combined with a data-driven approach to complete the data preprocessing, and further carries out the fault identification and classification with the optimized convolutional neural network.