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Within the current institutional landscape, characterized by increased societal and governmental emphasis on environmental preservation, there is growing interest in the potential of digital transformation (DT) to advance the circular economy (CE). Nonetheless, the empirical substantiation of the connection between DT and CE remains limited. This study seeks to investigate the impact of DT on CE at the organizational level and examine how various institutional factors may shape this relationship within the Chinese context.

To scrutinize this association, we construct a research framework and formulate hypotheses drawing on institutional theory, obtaining panel data from 238 Chinese-listed high-tech manufacturing firms from 2006 to 2019. A regression analysis approach is adopted for the sample data.

Our regression analysis reveals a positive influence of DT on CE performance at the organizational level. Furthermore, our findings suggest that the strength of this relationship is bolstered in the presence of heightened regional institutional development and industry competition. Notably, we find no discernible effect of a firm’s political connections on the DT–CE performance nexus.

This study furnishes empirical evidence on the relationship between DT and CE performance. By elucidating the determinants of this relationship within the distinct context of Chinese institutions, our research offers theoretical and practical insights, thus laying the groundwork for subsequent investigations into this burgeoning area of inquiry.

This paper aims to investigate the performance of two novel numerical methods, the face-based smoothed finite element method (FS-FEM) and the edge-based smoothed finite element method (ES-FEM), which employ linear tetrahedral elements, for the purpose of strength assessment of a high-speed train hollow axle.

The calculation of stress for the wheelset, comprising an axle and two wheels, is facilitated through the application of the European axle strength design standard. This standard assists in the implementation of loading and boundary conditions and is exemplified by the typical CRH2 high-speed train wheelset. To evaluate the performance of these two methods, a hollow cylinder cantilever beam is first used as a benchmark to compare the present methods with other existing methods. Then, the strength analysis of a real wheelset model with a hollow axle is performed using different numerical methods.

The results of deflection and stress show that FS-FEM and ES-FEM offer higher accuracy and better convergence than FEM using linear tetrahedral elements. ES-FEM exhibits a superior performance to that of FS-FEM using linear tetrahedral elements, showing accuracy and convergence close to FEM using hexahedral elements.

This study channels the novel methods (FS-FEM and ES-FEM) in the static stress analysis of a railway wheelset. Based on the careful testing of FS-FEM and ES-FEM, both methods hold promise as more efficient tools for the strength analysis of complex railway structures.

This study aims to evaluate the effect of thermal aging temperature on the properties of Cu/Al joints.

A new method in which 1 µm Zn-particles and SAC0307 with a particle size of 25–38 µm were mixed to fill the joint and successfully achieved the micro-joining of Cu/Al under ultrasonic-assisted at 200°C, and then, the effect of aging temperature on the properties of Cu/Al joints at different aging times was researched.

The results showed that the Cu interface intermetallic compounds (IMCs) had the same composition and had two layers with Cu₅Zn₈ near the Cu substrate and CuZn₅ near the solder. As the aging time increased, CuZn₅ gradually transformed to Cu₅Zn₈, and the thickness of the CuZn₅ layer gradually decreased until CuZn₅ disappeared completely. There was a Sn–Zn solid solution at the Al interface, and the composition of the Al interface of the Cu/Al joints did not change with changing temperature. The IMC thickness at the Cu interface of the joints continued to increase, and the shear strength of the Cu/Al joints decreased with increasing aging temperature and time. Compared with the as-received samples, the IMC thickness of the Cu interface of joints increased by 371.8% and the shear strength of the Cu/Al joints was reduced by 83.2% when the joints were aged at 150°C for 24 h. With an increase in aging temperature, the fracture mode of the Cu/Al joints changed from being between solder balls and Zn particles to between Zn particles.

With increasing aging temperature, the shear strengths of the Cu/SACZ/Al joints decreased at the same aging time, the shear strength of Cu/SACZ/Al joints at 150°C for 24h decreased by 83.2% compared with that of the as-received joints.

The paper's purpose is to investigate the effects of digital finance on the risk of stock price crashes and the underlying transmission mechanisms, and to provide suggestions to inhibit the stock crash risk (CR).

This paper selects all companies that were listed on the Shanghai Stock Exchange and the Shenzhen Stock Exchange from 2011 to 2020. It then uses the two-way fixed effect model and the intermediary effect model to verify such effects.

The overall outcomes demonstrate such a result that the CR of listed companies in China can be significantly reduced by the development of digital finance, and the overall transparency of business financial information and the equity pledge of controlling shareholders are the two underlying transmission mechanisms that digital finance can cause effects on the CR of stocks.

The main limitations are that there may exist some problems in the method for evaluating the CR of stocks. And there may be a problem of endogeneity caused by the empirical model cannot control all correlation variables.

This paper would provide policy implications, for different roles, to inhibit the stock CR and to make the development of the economy more stabilize.

Digital finance can promote economic development while restraining financial risks at the same time. Therefore, although this study is based on the relevant data from China, it can also provide a reference for other economies with different basic conditions from China, to promote the overall development of the world economy.

The current academic research on digital finance or stock price CR has been relatively sufficient, but there are few papers that combined both. By combining digital finance with stock CR, this paper researches the influence of digital finance on the CR of stocks through empirical analysis. So, this paper would provide new research ideas and evidence for potential influence factors of the CR of stocks, fill the gap in this research field and provide certain help for subsequent scholars to conduct relevant research.

Abnormal behaviors such as rework, backlog, changes and claims generated by project organizations are unavoidable in complex projects. When abnormal behaviors emerge, the previously normal state of interactions between organizations will be altered to some extent. However, previous studies have ignored the associations and interactions between organizations in the context of abnormal organizational behaviors (AOBs), making this challenging to cope with AOBs. As a result, the objective of this paper is to explore how to reduce AOBs in complex projects at the organizational level from a network perspective.

To overcome the inherent limitations of a single case study, this research integrated two data collection methods: questionnaire survey and expert scoring method. The questionnaire survey captured the universal data on the influence possibility of AOBs between complex project organizations and the expert scoring method got the influence probability scores of AOBs between organizations in the case. Using these data, four organizational influence network models of AOBs based on a case were developed to demonstrate how to destroy AOBs networks in complex projects using network attack theory (NAT).

First, the findings show that controlling AOBs generated by key organizations preferentially and improving the ability of key organizations can weaken AOBs network, enabling more effective coping strategies. Second, the owners, government, material suppliers and designers are identified as key organizations across all four influence networks of AOBs. Third, change and claim behaviors are more manageable from the organizational level.

Project managers can target specific organizations for intervention, weaken the AOBs network by applying NAT and achieve better project outcomes through coping strategies. Additionally, by taking a network perspective, this research provides a novel approach to comprehending the associations and interactions between organizations in the context of complex projects.

This paper proposes a new approach to investigating AOBs in complex projects by simultaneously examining rework, backlog, change and claim. Leveraging NAT as a novel tool for managing the harmful effects of influence networks, this study extends the knowledge body in the field of organizational behavior (OB) management and complex project management.

This chapter illustrates the concept of organisational innovation leadership (OIL) through a case study of the organisational transformation of Eddyfi Technologies to achieve superior innovative capacity through synergetic centralisation. The case study focusses on the real challenges faced when effecting organisational transformation, and how innovation leadership practices provided constructive resolutions that culminated in a successful reorganisation. We find that effective innovation leadership is conveyed primarily through establishing close relationships, open communication, and setting the example in a consistent and strict manner.

This study aims to acquire the influence mechanism of gas film adaptive adjustment (GFAA) acted on the dynamic characteristics of spiral groove dry gas seal (S-DGS) and then propose a sealing stability enhancement measure.

The gas film dynamic stiffness and damping of S-DGS are obtained by numerically solving the transient Reynolds equation based on perturbation method and finite difference method. The dynamic coefficients in GFAA model and constant gas film thickness (CGFT) model are compared and analyzed.

There is the risk to misestimate the instability of DGS with rotational speed or medium pressure grows under the condition of CGFT assumption. Based on GFAA model, increasing balance ratio B properly is an effective measure to improve the stability of DGS. The balance ratio can stimulate the sensitivity of gas film dynamic coefficients to the variation of rotational speed. Increasing medium pressure in small balance ratio range will be conducive to reducing the risk of angular instability.

The influence mechanism of GFAA on S-DGS dynamic characteristics is analyzed. The interactions between rotational speed and balance ratio, medium pressure and balance ratio acted on gas film dynamic characteristics are explored based on the GFAA model.

This paper aims to concentrate on recent innovations in flexible wearable sensor technology tailored for monitoring vital signals within the contexts of wearable sensors and systems developed specifically for monitoring health and fitness metrics.

In recent decades, wearable sensors for monitoring vital signals in sports and health have advanced greatly. Vital signals include electrocardiogram, electroencephalogram, electromyography, inertial data, body motions, cardiac rate and bodily fluids like blood and sweating, making them a good choice for sensing devices.

This report reviewed reputable journal articles on wearable sensors for vital signal monitoring, focusing on multimode and integrated multi-dimensional capabilities like structure, accuracy and nature of the devices, which may offer a more versatile and comprehensive solution.

The paper provides essential information on the present obstacles and challenges in this domain and provide a glimpse into the future directions of wearable sensors for the detection of these crucial signals. Importantly, it is evident that the integration of modern fabricating techniques, stretchable electronic devices, the Internet of Things and the application of artificial intelligence algorithms has significantly improved the capacity to efficiently monitor and leverage these signals for human health monitoring, including disease prediction.

The view that supply chain learning (SCL) has become a fundamental capability that supply chains must employ to innovate and improve their financial, technological, operational, environmental and social performance is widely accepted. However, the SCL phenomenon is still understudied and not fully understood by scholars, decision-makers and government representatives. This article aims to make sense of the existing literature and to identify important research directions that require further attention.

This article reviews the diversity of SCL in the literature, proposes a typology of such a phenomenon, provides an overview of key articles in the literature and identifies a series of recommendations for the future development of the field.

This article combines two fundamental dimensions from the literature (i.e. SCL driver and SCL network) to produce a typology of four types of SCL: Captive, Consortium, Selective and Distributed.

The typology proposed here offers an important framework for supply chain decision-makers to rely on when implementing SCL initiatives. The implications of each type of SCL offer a robust rationale for decision-makers to adopt the most appropriate type of SCL or combinations of SCL types, given each situation. In addition, the typology supports policy-makers in further understanding the SCL phenomenon and creating effective innovation, economic development and sustainability policies through supply chains.

This article offers a novel typology that the authors hope will help scholars to advance the field of SCL in order to understand this important phenomenon. There is no good/bad/better/worse SCL type in the proposed typology, but the critical element for the success of SCL efforts is the level of fit between the type of SCL, the type of knowledge to be created and diffused, and the outcome supply chains aim to achieve with that learning effort. In addition, the authors coin the construct of “the learning supply chain”, which refers to a supply chain that learns constantly by employing all four types of SCL simultaneously.