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The purpose of this empirical study is to explore the factors that influence college students' intention to engage in online gamified learning in Guangdong and Macao.

This study analyzed 289 valid questionnaires to statistically explore the factors that affect college students' intention to engage in online gamified learning.

The study discovered that extroverted learning style, perceived usefulness and perceived enjoyment have a positive and significant impact on students' intent to participate. Moreover, perceived usefulness and perceived enjoyment partially mediate the effect of extroverted learning style on the intention to engage in online gamified learning. Additionally, the impact of perceived usefulness on intention is moderated by different cultural backgrounds, with the moderation effect being stronger for Macao students than for non-Macao students.

This empirical study, based on the technology acceptance model (TAM), explores the factors that influence college students' intention to engage in online gamified learning in Guangdong and Macao and constructs a gamification acceptance model.

The objective of this study is to utilize empirical research and analysis to examine the coupling coordination relationship between new quality productivity and higher vocational education sustainable development.

To this end, an evaluation index system for the new quality productivity and higher vocational education sustainable development was constructed. The panel data of 30 Chinese provinces from 2016 to 2022 were then analyzed using the entropy method, the coupling coordination degree model, the Tobit regression model and Dagum’s Gini coefficient.

The findings indicate that the coupling coordination degree of new quality productivity and higher vocational education sustainable development exhibited an upward trend, though significant regional disparities were observed, with the highest coupling coordination degree recorded in the eastern region and the lowest in the northeastern region.

The study’s findings further suggest that the three factors of technological innovation level, rationalization of industrial structure and advanced industrial structure have a significant positive influence on the coupling coordination degree, while the level of government intervention has a significant negative influence on the Coupling Coordination Degree. The study posits that augmenting policy support, optimizing the government’s role, reinforcing the drive for technological innovation, and enhancing regional cooperation and exchange are imperative to foster high-quality development of the integration of industry and education between new quality productivity and higher vocational education.

The purpose of this paper is to explore the knowledge infrastructure of destination food research based on a systematic literature review. This bibliometric analysis involves authors, institutions, countries and co-citation networks and discloses trending developments in the field.

This study is based on 176 articles published in hospitality and tourism journals during the period 2000–2018 and bibliometric data downloaded from the ISI Web of Science. This review applies bibliometric analysis, citation network analysis and content analysis to examine the structure and networks of destination food knowledge so as to provide destination food researchers with a reference guide to the context, methods and focus of previous studies.

The findings demonstrate the development and trends of destination food research. This is the first study to address the limitations of prior systematic literature reviews by applying network analysis to reveal the interrelated structures and properties of the destination food research domain.

Practitioners can also discover trends in the design of development strategies, as well as identify extended themes that may be integrated with research in the field of destination food at present.

As a summary of key characteristics, this report is a useful reference guide to previous studies for researchers. This study presents core content about the destination food field and identifies development trends within destination food research. Based on the results, further research directions are provided.

This study aims to enhance the assessment of green governance in energy projects along the Belt and Road, reduce the influence of fuzzy judgment, and construct a grey network analysis model from the perspective of Environmental, Social, and Governance (ESG).

The ESG concept is used to establish an evaluation indicator system. The Analytic Network Process (ANP) and the Grey System Theory are applied sequentially to determine the green governance grade of energy projects, exemplified by an evaluation of five projects.

The Karot hydropower project has the best green governance status among the five projects and is of excellent grade. This is followed by the Hongfeng photovoltaic project, the De Aar wind power project, and the Yamal liquefied natural gas project, which are of good grade. The Lamu coal power station project has the worst green governance and is at a medium level.

This study can assist Belt and Road energy projects in identifying their deficiencies and promoting sustainable development by providing a robust framework for green governance evaluation.

The indicator system developed in this study includes social and project governance aspects in addition to environmental performance, reflecting the comprehensive green governance status of projects. The combined use of ANP and grey system theory fully considers the mutual influence relationship between indicators and improves the objectivity of green governance grade judgment.

The authors provide a comprehensive empirical examination on the impact of earnings quality on stock price crash risk in China.

The authors acknowledge and distinguish two-dimensional proxies for earnings quality – accounting-based (earnings management degree) and market-based (earnings transparency) known in accounting and finance literature.

The authors find that both generally indicate that better earnings quality is associated with less crashes. However, extremely high earnings transparency interacted with insider trading profit can also actually exacerbate stock price crashes.

This study is the first to highlight the pertinence of accounting-based measures to proxy for earnings quality in a fast-growing emerging market environment such as China.

In a dual-robot system, the relative position error is a superposition of errors from each mono-robot, resulting in deteriorated coordination accuracy. This study aims to enhance relative accuracy of the dual-robot system through direct compensation of relative errors. To achieve this, a novel calibration-driven transfer learning method is proposed for relative error prediction in dual-robot systems.

A novel local product of exponential (POE) model with minimal parameters is proposed for error modeling. And a two-step method is presented to identify both geometric and nongeometric parameters for the mono-robots. Using the identified parameters, two calibrated models are established and combined as one dual-robot model, generating error data between the nominal and calibrated models’ outputs. Subsequently, the calibration-driven transfer, involving pretraining a neural network with sufficient generated error data and fine-tuning with a small measured data set, is introduced, enabling knowledge transfer and thereby obtaining a high-precision relative error predictor.

Experimental validation is conducted, and the results demonstrate that the proposed method has reduced the maximum and average relative errors by 45.1% and 30.6% compared with the calibrated model, yielding the values of 0.594 mm and 0.255 mm, respectively.

First, the proposed calibration-driven transfer method innovatively adopts the calibrated model as a data generator to address the issue of real data scarcity. It achieves high-accuracy relative error prediction with only a small measured data set, significantly enhancing error compensation efficiency. Second, the proposed local POE model achieves model minimality without the need for complex redundant parameter partitioning operations, ensuring stability and robustness in parameter identification.

Dynamic low adhesion (DLA) has become an urgent problem for the high-speed wheel-rail system because of continuous decrease of adhesion redundancy in the past decades. This article aims to provide a simulation method to reveal the mechanism of DLA under high-frequency vibrations.

A transient wheel-rail rolling contact model is developed for a typical Chinese high-speed railway system using the explicit finite element (FE) method. Instantaneous adhesion exploitation levels are studied in the time domain, for which driving cases over corrugated rails are taken as an example. A speed up to 500 km/h is considered together with different traction coefficients and corrugation dimensions. DLA is expected when the instantaneous adhesion exploitation level reaches 1.0, that is adhesion saturates and full sliding contact occurs.

The instantaneous adhesion exploitation level can be very high in the presence of corrugation, even at low traction coefficients. DLA is found to occur as great vertical unloading takes place and causes a significant increase of creepage. An approach is further developed to determine the critical depth of corrugation over which DLA occurs.

This study employs the transient wheel-rail rolling contact model to predict the instantaneous adhesion exploitation level under high-frequency vibrations. The presented results reveal a mechanism of DLA being beneficial to guidelines for future railway practice.

This paper's purpose is to suggest that manufacturers strategically place soft orders for assembly materials with suppliers in Silk Road Economic Belt countries who probably doubt the realization of the soft orders placed.

First, a two-stage Stackelberg competition is constructed, taking into account the supplier's trust level in formulating the decision process in the assembly supply chain. The authors then provide a buyback contract to coordinate the supply chain, in which the manufacturer obtains enough supplies by sharing some of the perceived risks of not fully trusted suppliers. Furthermore, the authors conduct a numerical study to investigate the influence of trust under a decentralized case and a buyback contract.

The authors found that all supply chain partners in Silk Road Economic Belt countries experience potential losses due to not fully trusting certain conditions. The study also shows that, in Silk Road Economic Belt countries, operating under a buyback contract is better than being without one in terms of assembly supply chain performance.

On the one hand, the authors only consider the asymmetry of demand information without considering that of cost structure information. On the other hand, a natural extension of the paper is to integrate single-period transactions into the multi-period transaction problem setting. As all these issues require substantial effort, the authors reserve them for future exploration.

Doing business with not-fully-trustworthy partners in Silk Road Economic Belt countries is risky, and this study reveals how trust works in global cooperation and with strategic reactions in situations of partial trust.

This paper aims to recognize whether government policy supervision or social network platform supervision can effectively promote the control of misconducts of web celebrity brand eWOM marketing and to identify the key factors influencing the unhealthy web celebrity marketing environment.

Theoretical research was employed to develop a practical approach for applying evolutionary game theory to eWOM marketing controlling strategies modeling via dynamic visualization, systematic simulation experiments.

Evolutionary game theory combined with dynamic simulation modeling can provide a formal approach to understanding web celebrity brand eWOM marketing decision-making in social media, which can thus support the control of unhealthy web celebrity marketing environment. The results demonstrate that the reasonable control of social platform control costs may be more effective than the government policy on web celebrity fake brand eWOM marketing behaviors.

The study enriches the research on the management and control of eWOM marketing as well as provides guidance for the sustainable development of the web celebrity economy in social media.

The simulated temperature profile of the printed circuit board assembly (PCBA) during reflow soldering process deviates from the actual profile. To reduce this relative deviation, a new strategy based on the Kriging response surface and the Multi-Objective Genetic Algorithm (MOGA) optimizing method is proposed.

The simulated temperature profile of the PCBA during reflow soldering process deviates from the actual profile. To reduce this relative deviation, a new strategy based on the Kriging response surface and the MOGA optimizing method is proposed.

Several critical influencing parameters such as temperature and the convective heat transfer coefficient of the specific temperature zones are selected as the correction parameters. The hyper Latins sampling method is implemented to distribute the design points, and the Kriging response surface model of the soldering process is constructed. The updated model is achieved and validated by the test. The relative derivation is reduced from the initial value of 43.4%–11.8% in terms of the time above the liquidus line.

A new strategy based on the Kriging response surface and the MOGA optimizing method is proposed.