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This study aims to examine the effects on student motivation and perception of technological interventions within undergraduate mechanical engineering and product design and manufacture programs at a Sino-foreign international university. The authors use an augmented reality game application within a class on Design for Manufacturing and Assembly (DfMA) that was developed using the approaches of microlearning and digital game-based learning (DGBL).

Structured as design-based research, the study reports on developing innovative educational interventions and provides an empirical investigation of their effectiveness. Data were collected using a mixed methods approach, using pre- and post-tests and questionnaires, together with researcher observations and participant interviews.

Through two rounds of playtests, the game positively affected intrinsic motivation and encouraged higher-order cognitive learning, critical thinking, communication and collaboration. Collaborative learning plays a significant role, DGBL is preferred over traditional methods and microlearning reduces information density and cognitive overload.

The study contributes to our understanding of digital game-based interventions on students’ intrinsic motivation and provides insights into effective ways to design instructional materials in similar teaching and learning settings.

To make the robot that have real autonomous ability is always the goal of mobile robot research. For mobile robots, simultaneous localization and mapping (SLAM) research is no longer satisfied with enabling robots to build maps by remote control, more needs will focus on the autonomous exploration of unknown areas, which refer to the low light, complex spatial features and a series of unstructured environment, lick underground special space (dark and multiintersection). This study aims to propose a novel robot structure with mapping and autonomous exploration algorithms. The experiment proves the detection ability of the robot.

A small bio-inspired mobile robot suitable for underground special space (dark and multiintersection) is designed, and the control system is set up based on STM32 and Jetson Nano. The robot is equipped with double laser sensor and Ackerman chassis structure, which can adapt to the practical requirements of exploration in underground special space. Based on the graph optimization SLAM method, an optimization method for map construction is proposed. The Iterative Closest Point (ICP) algorithm is used to match two frames of laser to recalculate the relative pose of the robot, which improves the sensor utilization rate of the robot in underground space and also increase the synchronous positioning accuracy. Moreover, based on boundary cells and rapidly-exploring random tree (RRT) algorithm, a new Bio-RRT method for robot autonomous exploration is proposed in addition.

According to the experimental results, it can be seen that the upgraded SLAM method proposed in this paper achieves better results in map construction. At the same time, the algorithm presents good real-time performance as well as high accuracy and strong maintainability, particularly it can update the map continuously with the passing of time and ensure the positioning accuracy in the process of map updating. The Bio-RRT method fused with the firing excitation mechanism of boundary cells has a more purposeful random tree growth. The number of random tree expansion nodes is less, and the amount of information to be processed is reduced, which leads to the path planning time shorter and the efficiency higher. In addition, the target bias makes the random tree grow directly toward the target point with a certain probability, and the obtained path nodes are basically distributed on or on both sides of the line between the initial point and the target point, which makes the path length shorter and reduces the moving cost of the mobile robot. The final experimental results demonstrate that the proposed upgraded SLAM and Bio-RRT methods can better complete the underground special space exploration task.

Based on the background of robot autonomous exploration in underground special space, a new bio-inspired mobile robot structure with mapping and autonomous exploration algorithm is proposed in this paper. The robot structure is constructed, and the perceptual unit, control unit, driving unit and communication unit are described in detail. The robot can satisfy the practical requirements of exploring the underground dark and multiintersection space. Then, the upgraded graph optimization laser SLAM algorithm and interframe matching optimization method are proposed in this paper. The Bio-RRT independent exploration method is finally proposed, which takes shorter time in equally open space and the search strategy for multiintersection space is more efficient. The experimental results demonstrate that the proposed upgrade SLAM and Bio-RRT methods can better complete the underground space exploration task.

This article aims to develop and validate a theoretical model via survey data to identify the affordances and challenges influencing metaverse adoption. We specifically examine the impact of immersion on users' adoption decisions and identify which affordances predict this immersion. Additionally, this paper assesses the importance of perceived risks in users' decision-making processes regarding future metaverse engagement.

Using regression models applied to 198 survey responses, we tested our proposed model. To deepen our insights, we also conducted a qualitative analysis.

The findings confirm that users' perceptions of immersion and perceived risks are critical determinants in adoption decisions. Social presence, influenced by factors such as ubiquity and interoperability, emerges as a key component of immersion. From the qualitative data, we identified two potential strategies to enhance metaverse immersion: technical improvements and offline device-assisted strategies.

Our study contributes to the literature on information systems (IS) adoption and provides practical insights for practitioners on crucial considerations in metaverse design.

Supervisor consultation is conducive to promoting employee voice. This research examines an underlying mediating mechanism and a boundary condition that strengthens the influence of supervisor consultation.

Two-wave survey data were collected from 302 full-time employees. Path analysis was adopted to test the hypotheses.

Supervisor consultation is positively related to employee voice. Employee felt obligation for constructive change (FOCC) serves as a mediating mechanism. Supervisor consultation is more positively related to employee FOCC and subsequent voice when managerial openness is higher than lower.

This study highlights the incremental mediating effect of FOCC beyond that of two alternative mediators between supervisor consultation and employee voice and the moderating role of managerial openness in affecting the influence of supervisor consultation.

Drawing upon socio-technical system theory, this study intends to investigate the effects of the congruence and incongruence between artificial intelligence (AI) and explorative learning on supply chain resilience as well as the moderating role of organizational inertia.

Using survey data collected from 170 Chinese manufacturing firms, we performed polynomial regression and response surface analyses to test our hypotheses.

We find that the congruence between AI and explorative learning enhances firms’ supply chain resilience, while the incongruence between these two factors impairs their supply chain resilience. In addition, compared with low–low congruence, high–high congruence between AI and explorative learning improves supply chain resilience to a greater extent. Moreover, organizational inertia attenuates the positive influence of the congruence between AI and explorative learning on supply chain resilience, while it aggravates the negative influence of the incongruence between these two factors on supply chain resilience.

Our study expands the literature on supply chain resilience by demonstrating that the congruence between a firm’s AI (i.e. technical aspect) and explorative learning (i.e. social aspect) boosts its supply chain resilience. More importantly, our study sheds new light on the role of organizational inertia in moderating the congruent effect of AI and explorative learning, thereby extending the boundary condition for socio-technical system theory in the supply chain resilience literature.

Based on stakeholder theory, this study aims to examine the impact of family firm succession on corporate philanthropy while considering the potential role of the clan cultural context, industry context, and the stage of succession.

Data were based on a sample of 7,502 firm-year observations from listed family firms in China’s A-share markets between 2007 and 2018. Several Tobit models are used for analysing the data. Difference-in-difference regression method and propensity score matching method are used for robustness tests.

Family firms undergoing succession tend to spend more on corporate philanthropy compared to non-succession counterparts. This effect is more pronounced among polluting industry firms and weaker in regions with strong clan cultures and after the process of succession is complete.

This study sheds new light on the relationship between inter-generational succession and corporate philanthropy. By considering the moderating effect of the clan cultural context, industry context, and the stage of succession, this study further advances the understanding of the role of corporate philanthropy in managing family firm succession.

The purpose of this paper is to provide small and medium-sized enterprises (SMEs) in emerging markets with an updated Purchasing Portfolio Matrix (PPM) specifically for international sourcing. This data-driven PPM matrix is designed to provide a dynamic and process perspective that can help SMEs survive the disruptions caused by emergency situations such as the global COVID-19 pandemic.

This research reports on qualitative interviews with experienced informants from 15 SMEs in the manufacturing industry. The authors follow process-based research using a combination of retrospective and real-time case study approaches to gradually unveil the dynamics in segmentation and sourcing strategies in the international sourcing context during the COVID-19 pandemic.

The findings reveal the dynamics of segmentation and international sourcing strategies during global disruptions and unpack the underlying logic behind the dynamics that is specific to SMEs in emerging economies.

Existing literature on PPM predominantly focuses on static and normal sourcing circumstances. This paper addresses this gap by adopting a dynamic approach to study how sourcing strategies of SMEs from emerging economies evolve in a highly volatile environment from an international sourcing perspective.

The importance of the agri-food supply chain in both food production and distribution has made the issue of its development a critical concern. Based on configuration theory and congruence theory, this research investigates the complex impact of supply chain concentration on financial growth in agri-food supply chains.

The cluster analysis and response surface methodology are employed to analyse the data collected from 207 Chinese agri-food companies from 2010 to 2022.

The results indicate that different combination patterns of supply chain concentration can lead to different levels of financial growth. We discover that congruent supplier and customer concentration is beneficial for companies’ financial growth. This impact is more pronounced when the company is in the agricultural production stage of agri-food supply chains. Post-hoc analysis indicates that there exists an inverted U-shaped relationship between the overall levels of supply chain concentration and financial growth.

Our research uncovers the complex interplay between supply chain base and financial outcomes, thereby revealing significant ramifications for agri-food supply chain managers to optimise their strategies for exceptional financial growth.

This study proposes a combined approach of cluster analysis and response surface analysis for analysing configuration issues in supply chain management.

The purpose of this study is to examine the impact of experience dimensions on the engagement in pro-environmental behaviour (PEB) within nature-based tourism in China. The focus was on sustainable/responsible consumer behaviour by the Chinese Gen Z (18–26 years).

Firstly, a conceptual model was suggested, drawn on experiential marketing approach. Secondly, an empirical study (online survey) with a sample of 580 young persons was conducted and data were analysed using structural equation modeling (SEM).

It was revealed that the act and feel dimensions significantly influence experiential value (EV), and EV positively affects satisfaction, significantly impacting arousal and memory. Positive outcomes of experience impact Gen Z members’ engagement in PEBs. Furthermore, arousal and memory play a similar and partial mediating role between satisfaction and engagement in PEB.

The insights gained give support and guidance to tourism destinations and suppliers to promote environmentally friendly behaviour among tourists. This understanding is valuable and useful to industry practitioners in elaborating and implementing the appropriate strategies to stimulate, motivate and promote tourists’ PEB.

This study elaborates an integrative framework, drawn on a marketing approach and establishing a relationship between experiential dimensions and engagement in PEB through the mediating factors of perceived EV, satisfaction, memory and arousal. It provides tourism researchers with new perspective and insights on tourism experience and consumption behaviour.

本研究证实了体验维度对于中国自然旅游地游客的亲环境旅游行为(PEB)的影响。研究对象聚焦于中国Z世代(18 至26 岁)游客的亲环境行为。

本研究基于体验营销, 提出了一个概念模型, 对580名Z世代游客进行了实证研究(在线调查), 并采用结构方程模型（SEM）对数据进行分析。

结果表明, 行动维度和情感维度显著影响体验价值, 体验价值正向影响满意度, 满意度显著影响唤醒度和记忆。体验后的积极结果会影响Z世代游客的亲环境行为的参与。此外, 唤醒度和记忆在满意度和亲环境行为参与之间起平行的部分中介作用。

研究结果可为旅游目的地的管理者和从业者提供借鉴和参考, 以促进游客的环保行为。这对于旅游业从业者制定和采取恰当的策略来促进和激励游客的亲环境行为也具有重要意义。

本研究基于营销方法, 构建了一个整合框架, 并通过体验价值、满意度, 记忆和唤醒度等中介, 建构了体验维度和参与亲环境行为之间的关系, 拓展了旅游体验及消费行为的研究视角。

El propósito de este estudio fue examinar el impacto de las dimensiones de la experiencia en el comportamiento turístico proambiental (CTP) en el turismo de naturaleza en China, centrándose en el comportamiento sostenible y responsable de la Generación Z china (entre 18 y 26 años).

Se propuso un modelo conceptual basado en el enfoque del marketing experiencial. Posteriormente, se llevó a cabo un estudio empírico mediante una encuesta en línea a 580 jóvenes, y los datos obtenidos se analizaron utilizando SEM (Modelado de Ecuaciones Estructurales).

Se encontró que las dimensiones “actuar” y “sentir” tienen una influencia significativa en el valor experiencial, y este último impacta positivamente en la satisfacción, lo cual a su vez influye en la excitación y la memoria. Los resultados positivos de la experiencia turística tienen un efecto en el compromiso de los miembros de la Generación Z con el comportamiento turístico proambiental. Además, tanto la excitación como la memoria desempeñan un papel parcialmente mediador entre la satisfacción y el compromiso en el CTP.

Los conocimientos obtenidos en este estudio brindan apoyo y orientación a los actores del sector turístico para fomentar un comportamiento respetuoso con el medio ambiente entre los turistas y visitantes. Esta comprensión es valiosa y útil para los profesionales del sector al diseñar e implementar estrategias adecuadas que estimulen, motiven y promuevan el comportamiento turístico proambiental.

Este estudio presenta un marco integrador basado en el enfoque del marketing experiencial, estableciendo una relación entre las dimensiones experienciales y el compromiso en el CTP a través de factores mediadores como el valor experiencial percibido, la satisfacción, la memoria y la excitación. Proporciona a los investigadores del turismo una nueva perspectiva y conocimientos sobre la experiencia turística y el comportamiento de consumo.

This study aims to contribute to understandings of how international universities in China construct institutional narratives to attract Chinese students by leveraging themes of global citizenship and international mobility.

Qualitative analysis of web and other university materials, and mixed-method analysis of social media (WeChat) to identify and quantify recurring themes in the universities’ student-facing presentation.

Despite differing operational models, both universities emphasize Western education’s prestige and global citizenship, primarily appealing to affluent families and positioning themselves as pathways to international postgraduate study.

The research provides new insights into the student recruitment strategies of international universities in China, contributing to the broader understanding of higher education internationalization in non-Western contexts.