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This paper, with the tobacco industry as the background, establishes an indicator system for tobacco supply chain performance evaluation using the FAHP method.

Based on the relevant data of tobacco enterprises in Guangxi, the paper calculates the performance values of tobacco companies in various cities of Guangxi, and through the analysis of each indicator and the performance values of each city, the authors find that the improvement ability has a major impact on tobacco supply chain performance. Then, the paper establishes a system dynamics model to further demonstrate the impact of information digitalization on the performance of the tobacco supply chain in Guangxi, thus providing theoretical support for building digital tobacco logistics in Guangxi.

The findings of the study show that the performance of the tobacco supply chains in various cities of Guangxi is generally at the level of “Pass–Good,” which can barely meet the requirements of tobacco supply chain operation, but there is still plenty of room for improvement.

The authors show that digital and IT-based empowerment can maximize the performance of Guangxi's tobacco logistics performance.

This study aims to reveal the challenges and coordination mechanisms in cross-cultural teams.

By conducting in-depth interviews and a theme analysis approach with 15 cross-cultural teams, this qualitative study aims to answer three main questions: What kind of challenges do you face when working in a cross-cultural team? How do you coordinate cross-cultural issues within your team? What are significant things do you consider important when working with a cross-cultural team to improve performance?

The main challenges faced by cross-cultural teams, including cultural differences, task-related issues and management-related obstacles, are identified. Furthermore, adaptive coordination mechanisms, encompassing various levels of explicit and implicit strategies, are found to effectively manage these challenges.

This study contributes to the existing literature by proposing an adaptive coordination framework tailored for cross-cultural teams, addressing the main team challenges while considering contextual factors such as team tenure, team size, cultural intelligence and the nature of team tasks. The findings offer valuable insights for academic research and practical implications for multinational enterprises.

This study examines the impact of China's trade and foreign direct investment (FDI) on Africa's global value chain (GVC) participation and economic upgrading.

The study covered 48 African countries, cutting across the western, eastern, central, southern and northern subregions to cover the heterogeneity of the continent. The study adopted feasible generalized least squares panel VAR-Granger causality Wald test and system generalized methods of moments techniques for estimation.

Overall, China's FDI to Africa and US-Africa trade have a linear relationship with Africa's GVC involvement and economic upgrading. The findings suggest that although China-Africa trade has a positive impact on GVC engagement and upgrading, the marginal effect decreases in the face of US-Africa and EU-Africa trade.

This study provides new evidence on the impact of China's FDI and trade on African economies' GVC participation and economic upgrading. To the best of the authors’ knowledge, this is the first study to empirically explore the effects of China's FDI and trade on Africa's GVC integration and economic upgrading as well as from the perspectives of backward and forward GVC participation. Furthermore, the study empirically examines whether the effects of Africa's economic cooperation with China relative to its GVC engagement differ from those of Europe (EU) and the US via a comparative regression.

Wafer transfer robots play a significant role in IC manufacturing industry and the end effector is an important component of the robots. The purpose of this paper is to improve transfer efficiency of a wafer transfer robot through study of its end effector, and at the same time to reduce wafer deformation.

Finite element method is adopted to analyze wafer deformation. For wafer transfer robot working in vacuum, for the first time, the authors apply the research of microfiber arrays inspired by gecko to the design of robot's end effector, and present equations between robot's transit acceleration and parameters of microfiber arrays. Based on these studies, a kind of micro‐array bump is designed and fixed to a structure optimized end effector. For wafer transfer robot working in atmospheric environment, the authors have analyzed the effects of different factors on wafer deformation. The pressure distributions in absorption area and calculation formula of maximal transfer acceleration are put forward. Finally, a new kind of end effector for atmospheric robot is designed according to these studies.

The experiments results show that transfer efficiency of wafer transfer robot has been significantly improved through application of the research in this paper. Also wafer deformation under absorption force has been controlled.

Through experiments it can be seen that the research in this paper can be used to improve robot transfer ability and decrease wafer deformation in the production environment. Also the studies of end effector lay a solid foundation for further improvement.

This is the first application of the research of gecko‐inspired microfiber arrays to vacuum wafer transfer robot. This paper also carefully analyzes effects of different factors on wafer deformation through finite element method.

This study aims to develop a novel self-powered monitoring system that uses radio frequency (RF) energy harvesting and ultra-low-power management technologies for real-time condition monitoring of switch rails.

The system is designed for integration within the jump wire holes of switch rails, ensuring structural integrity and aesthetic appeal. It features a highly efficient energy harvesting mechanism combined with optimized power management for wireless sensor nodes. An on-board antenna captures ambient RF energy, managed by high-efficiency circuits to ensure stable wireless sensor operation. An ultra-low-power system-on-chip is used to acquire and transmit multimodal data on vibration and temperature from the switch rails. The data collection is enhanced through a two-threshold approach, adapting to harvested energy levels for self-energy balancing.

Testing revealed that the energy harvesting subsystem operated stably at distances up to 2.9 m from the RF source, charging a 200 µF capacitor to 4.2 V in just 220 s. The monitoring subsystem’s average power consumption is in the low microwatt range. Continuous operation over 30 days in real conditions resulted in only a 5 mV reduction in battery voltage, indicating successful self-powered operation and validating long-term reliability in unattended scenarios.

This research presents an innovative solution, integrating RF energy harvesting with ultra-low-power technology, which addresses the power and stability challenges faced by traditional monitoring systems.

By adopting learning theory and a guanxi perspective, this study aims to investigate the effects of interpersonal guanxi (interpersonal networks or connections) and relationship learning on companies’ business performance when operating in a large emerging market.

Using a sample of 294 sales managers and salespeople in the Chinese hotel sector, the authors empirically test the authors' arguments through a structural equation modeling (SEM) approach.

The authors' findings indicate that strong interpersonal guanxi tends to generate more positive business performance. Furthermore, the authors find that relationship learning plays a mediating role in the association between interpersonal guanxi and hotel companies’ business performance in a Chinese context. Finally, the authors empirically explore the moderating effect of inter-firm dependence on the contribution of interpersonal guanxi to relationship learning. Findings demonstrate that this effect varies significantly based on inter-firm dependence, with interpersonal guanxi exhibiting a greater positive impact if such dependence is high.

This study enriches our understanding of interpersonal guanxi and of how companies can enhance the companies' business performance in an emerging market context.

Getting high-quality data by removing the noisy data from the user-generated content (UGC) is the first step toward data mining and effective decision-making based on ubiquitous and unstructured social media data. This paper aims to design a framework for revoking noisy data from UGC.

In this paper, the authors consider a classification-based framework to remove the noise from the unstructured UGC in social media community. They treat the noise as the concerned topic non-relevant messages and apply a text classification-based approach to remove the noise. They introduce a domain lexicon to help identify the concerned topic from noise and compare the performance of several classification algorithms combined with different feature selection methods.

Experimental results based on a Chinese stock forum show that 84.9 per cent of all the noise data from the UGC could be removed with little valuable information loss. The support vector machines classifier combined with information gain feature extraction model is the best choice for this system. With longer messages getting better classification performance, it has been found that the length of messages affects the system performance.

The proposed method could be used for preprocessing in text mining and new knowledge discovery from the big data.

The purposes of this paper are to review the impact on food and nutrition security of several pandemic emergencies and the 2018 food price crisis from a global perspective, examine the Chinese experiences and lessons in ensuring food and nutrition security for its citizen and propose policy actions to prevent a global food and nutrition security crisis.

The authors utilize a noncomprehensive review of peer-reviewed and nonpeer-reviewed literature, as well as a case study approach.

Under the ongoing COVID-19, China's food and nutrition are relatively secure in short run largely due to governmental proactive policies but may face uncertainties in livestock production and imports of soybean in the medium and long terms. Given that the disease has spread to almost all countries in the world, global cooperation and coordination are needed to prevent systemic risks to global food and nutrition security.

The review and analysis of this paper will help policymakers in China and other countries to design strategies and actions to prevent food and nutrition security crisis under the ongoing COVID-19 emergency and other similar threats in the future.

This paper provides recommendations to prevent food and nutrition security crisis based on data, evidence and case studies.

The purpose of this paper is to investigate the changes in Chinese workers’ values by comparing the work-related values of the One-Child Generation (OCG), the Social Reform Generation and the Cultural Revolution Generation.

A survey was conducted with 918 Chinese employees, the vast majority of them working for Chinese domestic firms in Guangzhou, Shaoguan and Harbin. The collected data were analysed mainly using ANOVA, Tukey’s pairwise comparison and Kruskall–Wallis tests.

The OCG was found to place less importance on income and job security, while possessing higher tolerance towards the practice of nepotism, than the older two generations. The authors found no significant differences in the levels of intrinsic values and altruism among the three generations. Additionally, the results indicate overall low altruistic values and high extrinsic values across all three generations of Chinese workers.

China’s unprecedented generation of only-children as workers is an unknown factor. It is only now, over a decade after the OCG first entered the job market, that a comparative study between their work values and those of previous generations has become possible. This study exploits the momentum and is one of the first studies to include the OCG in the investigation of work value changes in Chinese society.

Recent years have documented the growing interest in using WhatsApp in higher education. However, the determinants of students’ satisfaction and loyalty towards WhatsApp groups have received less attention. This study aims to extend the Delone and McLean information system success model by incorporating social and emotional factors to investigate the drivers of satisfaction.

Data were collected through questionnaires completed by 308 undergraduate students. The partial least squares technique was used for data analysis.

The findings reveal that information quality, trust in members and social usefulness play crucial roles in shaping students’ satisfaction and loyalty to WhatsApp groups. System quality has no significant effect on satisfaction. Furthermore, emotional connection negatively moderates the relationship between social usefulness and satisfaction.

The findings of this study will be useful for educators and practitioners seeking to integrate WhatsApp into their pedagogical repertoire. The results demonstrate the importance of considering the social and emotional needs of students in addition to the quality of the information provided.

To the best of the authors’ knowledge, this study is the first attempt to integrate system characteristics, particularly with social and emotional factors. Furthermore, this study extends the literature on WhatsApp use in higher education by testing the drivers of students’ satisfaction and loyalty.