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Fault-related monitoring variables selection is a process of obtaining a subset of variables from the original set, which is of great significance for reducing information redundancy and improving the performance of the fault diagnosis models. This paper aims to propose a novel variables selection approach based on complex networks.

Firstly, a dual-layer correlation networks (DlCN) which consists of mechanism-oriented correlation sub-network (MoCSN) and data-oriented correlation sub-network (DoCSN) is constructed. Secondly, an algorithm for identifying critical fault-related monitoring variables based on dual correlations is introduced. In the algorithm, the topological attributes of the MoCSN and correlation threshold of the DoCSN are used successively.

In the experiments of vertical elevator fault diagnosis, the critical fault-related monitoring variables selected by the DlCN-based approach is more effective than the traditional approaches. It indicates that fusion mechanism-oriented correlation can enhance the comprehensiveness of variable correlation analysis. Moreover, the approach has been proved to be adaptable to different fault diagnosis models.

In the DlCN-based variables selection approach, the mechanism-oriented correlation and data-oriented correlation are comprehensively considered. It improves the precision of variables selection. Meanwhile, it is an unsupervised and model-agnostic approach which addresses the shortcomings of some conventional approaches that require data labels and have insufficient adaptability for fault diagnosis models.

Under the guidance of Professor Wang Zhuquan’s channel-based working capital management concept, this paper, using a sample of A-listed companies from 2007 to 2013, aims to explore the possibility of measuring vendor relationships from the supply chain (channel) perspective for the first time, making universal testing for working capital management based on vendor relationships. Through systematically answering the question of who is the biggest beneficiary of working capital management based on vendor relationships and to discuss whether suppliers are more willing to provide “timely help” to weak enterprises or to exert an “icing on the cake” effect on strong enterprises, this paper provides a systematic explanation of the causes and economic consequences of working capital management based on vendor relationships.

The authors constructed three models to test the hypotheses of this study. Model (1) explores the cause of working capital management based on vendor relationship from three angles: market position, industry competition degree and property right. Models (2) and (3) examine the economic consequences of working capital management based on vendor relationship from the two aspects of alleviating financing constraints and improving enterprises’ sustained growth capability.

Working capital management based on vendor relationships has a more significant “timely help” effect on weak companies, which was proved by the inclination of companies with lower market positions, higher industrial competition and private ownerships to adopt working capital management based on vendor relationships. From the perspective of economic consequences, while China’s listed companies benefit generally from working capital management based on vendor relationships, the weak enterprises are the biggest beneficiaries. Based on vendor relationships, the weak enterprises can relieve financing constraints and improve continuous growth capacity. It provides further evidence that suppliers could provide “timely help” to weak enterprises.

The results of this study find that the competition between supply chains replaces the competition among enterprises, and suppliers are more willing to provide “timely help” to weak enterprises rather than to exert an “icing on the cake” effect on strong enterprises. In addition, the working capital management based on vendor relationships facilitates the cooperation of enterprises and suppliers and improves the overall efficiency of the supply chain.

This study intends to explore the opportunities and roles of Macao's universities in the education and training development of Hengqin under the General Plan of the Development of the Guangdong–Macao In-Depth Cooperation Zone in Hengqin promulgated in August 2021.

This study is intended to analyze the role of Macao’ universities in Hengqin development, based on data collected through interviewing with dozens of scholars and government officials from Macao and Hengqin, and government reports, news reports and other relevant data.

The General Plan provides Macao's universities with opportunities to develop education and training in Hengqin. On the one hand, Hengqin can be the locus of Macao's tertiary education diversification; Macao's universities can jointly establish technological research institutions and set up postdoctoral research centers and university branches to enroll master's and doctoral students from Mainland China. On the other hand, Macao's universities can set up a branch of professional training and open training courses in Hengqin. These efforts are designed to promote technological innovation and cultural diffusion in Macao.

This study analyses the potential role of Macao's universities in developing education and training in Hengqin since the central policy was announced last August. This study will be of interest to scholars as well as policymakers.

The authors point out that the existing research confuses the operational liabilities formed based on the “transaction” relationship with the financial liabilities formed based on the “investment” relationship, which not only exaggerates the value of leverage but also underestimates the level of protection that companies provide for creditors alone. That is, the confusion of concepts not only triggers the problem of leverage misestimate but also triggers the short-term financial risk misestimate. The performance of “nominal leverage” and “nominal short-term solvency” based on total assets calculation cannot reflect the real leverage level and the real short-term financial risk of enterprises.

To distinguish the concepts of “assets” and “capital” and rationalize the relationship between “transactions” and “investments”, authors systematically design the “real leverage” indicators and “real short-term solvency” indicators, and measure the degree of misestimate of leverage and short-term financial risk indicators by traditional research. On this basis, this paper describes and analyses the trends of leveraged misestimate and short-term financial risk misestimate of listed companies in China and analyses which companies have more serious leverage misestimate. And it helps readers to form an objective understanding of the leveraged misestimate and short-term financial risk misestimate of listed companies in China.

Firstly, the overall high level of leverage of listed companies in China in the traditional sense is largely because of the misestimate of indicators. And this kind of misestimate is more serious among firms that have advantages in trading, such as state-owned enterprises and firms with higher market shares. Secondly, for most firms with normal solvency, traditional research systematically overestimated the negative impact of “nominal leverage” on financial risk indicators (represented by short-term solvency). The overestimation is significant in firms with serious leverage misestimate. Thirdly, indicators’ misestimate of the traditional research makes the banks cannot make effective credit decisions according to the firm's “real leverage” and “real short-term solvency”.

Firstly, clarify the differences between the concepts of “assets” and “capital”, and clarify the level of “real leverage” of listed companies in China, which is conducive to the process of “de-leveraging”. Secondly, revise the problem of misestimate of related indicators, so that financial institutions can clearly identify the true profitability and real risk level of the entity domain, and thus improve the effectiveness of credit decisions.

Modern meat processing requires automation and robotisation to remain sustainable and adapt to future challenges, including those brought by global infection events. Automation of all or many processes is seen as the way forward, with robots performing various tasks instead of people. Meat cutting is one of these tasks. Smart novel solutions, including smart knives, are required, with the smart knife being able to analyse and predict the meat it cuts. This paper aims to review technologies with the potential to be used as a so-called “smart knife” The criteria for a smart knife are also defined.

This paper reviews various technologies that can be used, either alone or in combination, for developing a future smart knife for robotic meat cutting, with possibilities for their integration into automatic meat processing. Optical methods, Near Infra-Red spectroscopy, electrical impedance spectroscopy, force sensing and electromagnetic wave-based sensing approaches are assessed against the defined criteria for a smart knife.

Optical methods are well established for meat quality and composition characterisation but lack speed and robustness for real-time use as part of a cutting tool. Combining these methods with artificial intelligence (AI) could improve the performance. Methods, such as electrical impedance measurements and rapid evaporative ionisation mass spectrometry, are invasive and not suitable in meat processing since they damage the meat. One attractive option is using athermal electromagnetic waves, although no commercially developed solutions exist that are readily adaptable to produce a smart knife with proven functionality, robustness or reliability.

This paper critically reviews and assesses a range of sensing technologies with very specific requirements: to be compatible with robotic assisted cutting in the meat industry. The concept of a smart knife that can benefit from these technologies to provide a real-time “feeling feedback” to the robot is at the centre of the discussion.

This paper aims to research, identify and discuss the benefits and overall role of big data and artificial intelligence (BDAI) in the tourism sector, as this is depicted in recent literature.

A systematic literature review was conducted under the McKinsey’s Global Institute (Talwar and Koury, 2017) methodological perspective that identifies the four ways (i.e. project, produce, promote and provide) in which BDAI creates value. The authors enhanced this analysis methodology by depicting relevant challenges as well.

The findings imply that BDAI create value for the tourism sector through appropriately identified disseminations. The benefits of adopting BDAI strategies include increased efficiency, productivity and profitability for tourism suppliers combined with an extremely rich and personalized experience for travellers. The authors conclude that challenges can be bypassed by adopting a BDAI strategy. Such an adoption will stand critical for the competitiveness and resilience of existing established and new players in the tourism sector.

Besides identifying the benefits that BDAI brings in the tourism sector, the research proposes a guidebook to overcome challenges when introducing such new technologies. The exploration of the BDAI literature brings important implication for managers, academicians and consumers. This is the first systematic review in an area and contributes to the broader e-commerce marketing, retailing and e-tourism research.

本论文旨在研究、指出、和讨论大数据和人工智能（BDAI）在旅游业中的优势和整体作用。这些方面也在近文献中有所提到。

本论文采用系统综述方式, 在McKinsey’s Global Institute方法论的指导下, 确认BDAI可以在四种方面（预测、产出、提高、以及提供）创造价值。我们也通过阐述相关挑战来增强这个分析方法。

本论文结果显示BDAI通过适当的传播方式来为旅游业中创造价值。采用BDAI战略的好处包括：对旅游提供商带来高效、多产、盈利, 以及对旅游者们带来极度丰富和个性化的旅游体验。我们还总结了采取BDAI战略带来的诸多挑战。采用BDAI战略对旅游业中现有和新参与者的竞争力和弹性起到至关重要的作用。

除了指出了旅游业中BDAI带来的优势, 本论文还提出了一个指南, 来指导当新科技被引进时如何克服挑战。本论文通过对BDAI文献的梳理, 其文献综述结果对经理、学者、和消费者都有重要的启示作用。本论文是首篇在BDAI领域的系统综述, 对拓展电子商务营销、零售、和电子旅游科研有着重大贡献。

Discussions about digital tourism continue to increase among scholars as Information Communication and Technology (ICT) infrastructure develops. Dynamic changes due to technological aspects have given rise to various developments in the tourism industry. Therefore, this study aims to evaluate the scientific structure of the development of digital tourism topics through a bibliometric analysis approach. In total, 102 publications from research on digital tourism were taken from Scopus database between 2001 and 2021, for further bibliometric analysis using the VOSviewer application. Interesting findings describe the most cited digital tourism publications, the contribution of digital tourism by various authors, institutions, countries, co-citation analysis, bibliographic coupling, and co-occurrence for the main trends of digital tourism. This study compiles a detailed review of digital tourism research. This article adds substantial value to the digital tourism topic by analyzing bibliometric data. It provided scientific information regarding digital tourism for other researchers and future research.