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Metaverse is a virtual application spawned by digital technology that is becoming increasingly relevant to our lives. However, for the opportunities created and challenges posed by the metaverse, its important elements and future evolution trend remain largely unknown. Thus, this paper aims to understand the current status of metaverse research and its future research directions.

Based on the analysis of the literature data on the metaverse both in English and Chinese using Latent Dirichlet allocation (LDA) topic modeling and bibliometrics, this study discussed the related research and development trend of the metaverse. The authors first defined the concept of the metaverse and analyzed 1,378 English articles from seven publishers and 590 Chinese articles from the CNKI database. Following that, the authors summarized three important themes from the current studies: virtual world, metaverse technologies and metaverse applications. Finally, a framework of future directions on metaverse research was proposed.

The review found that during the rapid development of the metaverse, opportunities and challenges coexisted. In the virtual world, metaverse technologies drive the implementation of application scenarios, and in turn, applications promote the improvement of technologies. The interrelationship between technology and application lays the foundation for the development of the metaverse. Future metaverse research will generate different research directions.

This review provides a valuable, systematic perspective for individuals who want to understand the metaverse. The conceptual framework on metaverse research proposed in this paper offers a comparison of literature analysis from domestic and international perspectives and brings new insights into the development of the metaverse.

Building on social identity theory, the purpose of this paper is to examine how European managers construct their multiple identities after being acquired by a Chinese firm and to determine the key factors contributing to the changing dynamics of multiple organizational identities.

The paper presents a qualitative, single case study of a Chinese acquisition of a European manufacturing firm at two points in time.

We find that multiple identities initially trigger ambivalence toward the acquisition, but over time, the ambivalence diminishes. The reduction of ambivalence results from concurrent integration and separation: a newly constructed boundary spanning the organization separates positive identities from negative ones, and integration interventions foster the development of a new, shared identity.

The findings reveal that organizational identity change is facilitated by the aligning of a post-merger identity with the acquired organization's historical identity and by creating an ambivalent boundary spanning identity.

This study aims to investigate the impact of supply chain concentration (SCC) on corporate research and development (R&D) investment and determine the moderating roles of industry concentration and financing constraints on the relationship between SCC and R&D investment.

The study collected data from Chinese listed companies, used the fixed effects model to test the research hypotheses and further used the two-stage Heckman test and propensity score matching (PSM) to address potential endogeneity issues.

The result reveals a negative impact of SCC on corporate R&D investment. In addition, industry concentration mitigates the negative impact of SCC on corporate R&D investment, but financing constraints strengthen the negative impact.

This study introduces the concept of SCC and empirically tests its effect on R&D investment, further explaining the lack of corporate innovation. This study inspires companies to strengthen SC management and weigh the level of SCC with environmental factors.

This paper aims to analyze the bearing characteristics of the high speed train window glass under aerodynamic load effects.

In order to obtain the dynamic strain response of passenger compartment window glass during high-speed train crossing the tunnel, taking the passenger compartment window glass of the CRH3 high speed train on Wuhan–Guangzhou High Speed Railway as the research object, this study tests the strain dynamic response and maximum principal stress of the high speed train passing through the tunnel entrance and exit, the tunnel and tunnel groups as well as trains meeting in the tunnel at an average speed of 300 km·h-1.

The results show that while crossing the tunnel, the passenger compartment window glass of high speed train is subjected to the alternating action of positive and negative air pressures, which shows the typical mechanic characteristics of the alternating fatigue stress of positive-negative transient strain. The maximum principal stress of passenger compartment window glass for high speed train caused by tunnel aerodynamic effects does not exceed 5 MPa, and the maximum value occurs at the corresponding time of crossing the tunnel groups. The high speed train window glass bears medium and low strain rates under the action of tunnel aerodynamic effects, while the maximum strain rate occurs at the meeting moment when the window glass meets the train head approaching from the opposite side in the tunnel. The shear modulus of laminated glass PVB film that makes up high speed train window glass is sensitive to the temperature and action time. The dynamically equivalent thickness and stiffness of the laminated glass and the dynamic bearing capacity of the window glass decrease with the increase of the action time under tunnel aerodynamic pressure. Thus, the influence of the loading action time and fatigue under tunnel aerodynamic effects on the glass strength should be considered in the design for the bearing performance of high speed train window glass.

The research results provide data support for the analysis of mechanical characteristics, damage mechanism, strength design and structural optimization of high speed train glass.

The purpose of this study is to explore the relationship between supervisor and coworkers’ workplace incivility and newcomer proactive behaviors. Drawing on conservation of resources (COR) theory, the authors examined resource depletion as a mediator and newcomer proactive personality, as well as their current organizational tenure as moderators of the relationship between workplace incivility toward newcomers and their proactive behaviors.

A time-lagged research design was used to test hypotheses with data covering 322 newcomers and their immediate supervisors in two subsidiaries of a large food processing company in China. Regression analysis using the PROCESS macro in SPSS is used to test the hypotheses.

The results show that workplace incivility toward newcomers is negatively related to their proactive behaviors. This relationship is mediated by resource depletion. Furthermore, newcomers’ proactive personality moderates the relationship between workplace incivility and resource depletion. Moreover, both the direct effect of workplace incivility on resource depletion and its indirect effect on newcomer proactive behaviors are moderated by the combination of newcomer proactive personality and their current organizational tenure.

Drawing on COR theory, a theoretical framework is constructed that specifies the process through which workplace incivility affects proactive behaviors to expand collective understandings of workplace incivility in the newcomer context. Furthermore, the boundary conditions of the underlying process are investigated, which further enhances the contribution of this paper to the extant literature on workplace incivility.

This paper aims to obtain the evolution law of dynamic performance of CR400BF electric multiple unit (EMU).

Using the dynamic simulation based on field test, stiffness of rotary arm nodes and damping coefficient of anti-hunting dampers were tested. Stiffness, damping coefficient, friction coefficient, track gauge were taken as random variables, the stochastic dynamics simulation method was constructed and applied to research the evolution law with running mileage of dynamic index of CR400BF EMU.

The results showed that stiffness and damping coefficient subjected to normal distribution, the mean and variance were computed and the evolution law of stiffness and damping coefficient with running mileage was obtained.

Firstly, based on the field test we found that stiffness of rotary arm nodes and damping coefficient of anti-hunting dampers subjected to normal distribution, and the evolution law of stiffness and damping coefficient with running mileage was proposed. Secondly stiffness, damping coefficient, friction coefficient, track gauge were taken as random variables, the stochastic dynamics simulation method was constructed and applied to the research to the evolution law with running mileage of dynamic index of CR400BF EMU.

The purposes of this research are to study the theory and method of multi-attribute index system design and establish a set of systematic, standardized, scientific index systems for the design optimization and inspection process. The research may form the basis for a rational, comprehensive evaluation and provide the most effective way of improving the quality of management decision-making. It is of practical significance to improve the rationality and reliability of the index system and provide standardized, scientific reference standards and theoretical guidance for the design and construction of the index system.

Using modern methods such as complex networks and machine learning, a system for the quality diagnosis of index data and the classification and stratification of index systems is designed. This guarantees the quality of the index data, realizes the scientific classification and stratification of the index system, reduces the subjectivity and randomness of the design of the index system, enhances its objectivity and rationality and lays a solid foundation for the optimal design of the index system.

Based on the ideas of statistics, system theory, machine learning and data mining, the focus in the present research is on “data quality diagnosis” and “index classification and stratification” and clarifying the classification standards and data quality characteristics of index data; a data-quality diagnosis system of “data review – data cleaning – data conversion – data inspection” is established. Using a decision tree, explanatory structural model, cluster analysis, K-means clustering and other methods, classification and hierarchical method system of indicators is designed to reduce the redundancy of indicator data and improve the quality of the data used. Finally, the scientific and standardized classification and hierarchical design of the index system can be realized.

The innovative contributions and research value of the paper are reflected in three aspects. First, a method system for index data quality diagnosis is designed, and multi-source data fusion technology is adopted to ensure the quality of multi-source, heterogeneous and mixed-frequency data of the index system. The second is to design a systematic quality-inspection process for missing data based on the systematic thinking of the whole and the individual. Aiming at the accuracy, reliability, and feasibility of the patched data, a quality-inspection method of patched data based on inversion thought and a unified representation method of data fusion based on a tensor model are proposed. The third is to use the modern method of unsupervised learning to classify and stratify the index system, which reduces the subjectivity and randomness of the design of the index system and enhances its objectivity and rationality.