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This study aims to improve the corrosion resistance of TA2-welded joints by superhydrophobic surface modification using micro-arc oxidation technology and low surface energy substance modification.

The microstructure and chemical state of the superhydrophobic film layer were analyzed using scanning electron microscopy, energy dispersive X-ray spectroscopy, three-dimensional morphology, X-ray diffraction, X-ray photoelectron spectroscopy and Fourier transform infrared absorption spectroscopy. The influence of the superhydrophobic film layer on the corrosion resistance of TA2-welded joints was investigated using classical electrochemical testing methods.

The characterization results showed that the super hydrophobic TiO₂ ceramic membrane was successfully constructed on the surface of the TA2-welded joint, and the construction of the super hydrophobic film greatly improved the corrosion resistance of the TA2-welded joint.

The superhydrophobic TiO₂ ceramic membrane has excellent corrosion resistance. The micro nanostructure in the superhydrophobic film can intercept air to form an air layer to prevent the corrosion medium from contacting the surface, thus, improving the corrosion resistance of the sample.

The purpose of this study is to examine the impact of managerial short-termism on green innovation of firms and the moderating role of digital transformation of enterprises in the association between managerial short-termism and green innovation.

This study uses data from Chinese A-share listed companies from 2001 to 2021 and employ panel fixed model and moderating effect model to examine the impact of managerial short-termism on green innovation of firms and the moderating role of digital transformation of enterprises in the association between managerial short-termism and green innovation.

The findings of this study reveal that managerial short-termism exerts negative influence on green innovation. Digital transformation enables firms to reduce the adverse effect of managerial short-termism on green innovation because digital transformation enhances information processing ability and then improves internal corporate governance and analyst coverage. Moreover, the moderating role of digital transformation is more prominent for firms with lower internal corporate governance, for firms with less analyst coverage and for non-state-owned enterprises.

This paper intends to address the following two questions: what is the impact of managerial short-termism on green innovation and what is the role of digital transformation in the two variables’ association? By using data of Chinese A-share listed companies from 2001 to 2021 and developing two individual indexes to measure managerial short-termism and digital transformation, the authors empirically test these above two questions. The results of this study indicate that: First, drawn on time-oriented theory and upper echelon theory, managerial short-termism has an adverse effect on firms’ green innovation. Second, digital transformation enables firms to reduce the negative effect of managerial short-termism on green innovation. Furthermore, the moderating mechanism tests show that the corporate governance effects of digital transformation play a supervisory role that impels managers to reduce short-term investments and promote firms’ green R&D investments, which helps to reduce the negative effect of managerial short-termism on green innovation. Additionally, the heterogeneity checks show that the moderating role of digital transformation in the relation between managerial short-termism and green innovation is more prominent for firms with lower internal corporate governance, with less analyst coverage and for non-state-owned enterprises.

The purpose of this paper is to develop a novel interval Multi-Objective Optimization by a Ratio Analysis plus the Full Multiplicative Form(MULTIMOORA) with combination weights to evaluate the employment quality of college graduates, where the criteria are expressed by interval numbers and the weights of criteria are completely unknown.

Firstly, considering the subjective uncertainty of the weights of the criteria, the interval best worst method (I-BWM) was present to determine the subjective weights of the criteria. Secondly, by the improved interval number distance measure, an improved interval deviation maximization method (I-MDM) was introduced to detemine the objective weights. In the following, based on the I-BWM and the improved I-MDM, a combination weighting method that takes into account the subjective and objective weights is proposed. Finally, a multi-criteria decision-making method based on the interval MULTIMOORA with combination weights is present to evaluate the employment quality of college graduates, and then a comparative analysis with some of the existing distance measures of interval numberswas conducted to illustrate the flexibility.

According to the data of the Report on Employment Quality of Chinese College Graduats released by Mycos Research Institute in 2016–2020 and 2021–2022, the proposed method was used to evaluate the employment quality of college graduates during the period before and after the COVID-19 epidemic. The results verify that the method is more reasonable because the subjective and objective weights of the criteria can be fully considered. Finally, the feasibility and practicability of the proposed method are further verified by varying parameters.

Present an evaluation method on the employment quality of college graduates based on the Interval MULTIMOORA with combination weights considering the subjective and objective weights. And the proposed method is proved that it can provide a more reasonable evaluation results. At the same time, it is verified that the feasibility and the practicability of the proposed method are affected by varying parameters in the paper.

The CL60 steel wheels of subway vehicles operating on specific lines require frequent refurbishment due to rapid wear and tear. Considering this issue, MoS₂-based and graphite-based solid lubricants are used to reduce the wear rate of subway wheels and extend their service life.

Under laboratory conditions, the effect of MoS₂-based and graphite-based solid lubricants on the friction and wear performance of subway wheels and rails was evaluated using a modified GPM-60 wear testing machine.

Under laboratory conditions, MoS₂-based solid lubricants have the best effect in reducing wheel/rail wear, compared to the control group without lubrication, at 2 × 105 revolutions, the total wheel-rail wear decreased by 95.07%. However, when three types of solid lubricants are used separately, the hardness evolution of the wheel-rail contact surface exhibits different characteristics.

The research results provide important support for improving the lifespan of wheel and rail, extending the service cycle of wheel and rail, reducing the operating costs of subway systems, improving the safety of subway systems and providing wear reduction maintenance for other high wear mechanical components.

The experiment was conducted through the design and modification of a GPM-60 testing machine for wear testing. The experiment simulated the wheel-rail contact situation under actual subway operation and evaluated the effects of three different solid lubricants, MoS₂-based and graphite-based, on the wear performance and surface hardening evolution of subway wheel-rail.

Drawing on the self-cognitive theory, this study aims to propose a conceptual model that links customer mistreatment with different types of helping behaviors through the self-efficacy mechanism.

The empirical analysis made use of the original data of three hotels located in southern China. The authors tested the hypotheses with a three-wave survey of a sample of 430 frontline workers in 95 groups.

Customer mistreatment may reduce employees’ self-efficacy, which has both positive and negative effects depending on the type of helping. Moreover, the coworkers’ supporting climate buffered the influence of self-efficacy on autonomous and dependent helping.

The authors resolve the ambiguity surrounding customer mistreatment-helping and self-efficacy-helping relations. Thus, the authors extend the knowledge on the influence of customer mistreatment and self-efficacy on helping behaviors by establishing that both positive and negative effects may exist depending on the type of helping. Moreover, this study identifies the predictive role of self-efficacy in autonomous and dependent helping.

Viewing the domestic downside risk as a “pushing” factor for outward foreign direct investment (OFDI), this study aims to examine the surge in Chinese cross-border acquisitions (CBAs) between 2008 and 2017, a unique window when private firms in China were allowed to conduct CBAs.

This study examines the effect of down-side risk on cross-border acquisition performance by using the sample of Chinese A-share listed companies from 2008 to 2017. Specifically, this study considers three kinds of systemic risk, systematic risk and idiosyncratic risk, and respectively examines their impact on CBAs activities; this study also investigates their subsequent results after CBAs activities. The contingency effect of state ownership on the above relationship is also discussed.

The findings reveal that pre-CBA systemic risk explains the volume of CBA activities; CBAs are followed by a reduction in systemic risk; the interactions between systemic risk and CBAs decrease with the level of state ownership; and the above results do not hold for traditional risk measures (i.e. systematic risk and idiosyncratic risk).

This study contributes to the literature by revealing the role of systemic risk as a “pushing” factor in the context of OFDI and suggesting an alternative explanation for CBAs from China: Chinese firms (especially private firms) took advantage of the rare opportunity between 2008 and 2017 given by the government to transfer assets overseas through CBA.

The purpose of this study is to examine how the implementation of edge computing can enhance the progress of the circular economy within supply chains and to address the challenges and best practices associated with this emerging technology.

This study utilized a streamlined evaluation technique that employed Latent Dirichlet Allocation modeling for thorough content analysis. Extensive searches were conducted among prominent publishers, including IEEE, Elsevier, Springer, Wiley, MDPI and Hindawi, utilizing pertinent keywords associated with edge computing, circular economy, sustainability and supply chain. The search process yielded a total of 103 articles, with the keywords being searched specifically within the titles or abstracts of these articles.

There has been a notable rise in the volume of scholarly articles dedicated to edge computing in the circular economy and supply chain management. After conducting a thorough examination of the published papers, three main research themes were identified, focused on technology, optimization and circular economy and sustainability. Edge computing adoption in supply chains results in a more responsive, efficient and agile supply chain, leading to enhanced decision-making capabilities and improved customer satisfaction. However, the adoption also poses challenges, such as data integration, security concerns, device management, connectivity and cost.

This paper offers valuable insights into the research trends of edge computing in the circular economy and supply chains, highlighting its significant role in optimizing supply chain operations and advancing the circular economy by processing and analyzing real time data generated by the internet of Things, sensors and other state-of-the-art tools and devices.