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The purpose of this paper is to provide an overview of the evolution of service supply chain management from a behavioural operations perspective, pointing out future research directions for scholars.

This study searched five databases for relevant literature published between 2009 and 2018, selecting 64 papers for this review. The selected literature was categorised according to two dimensions: a service supply chain link perspective and a behavioural factor perspective. Comparative analysis was used to identify gaps in the literature, and five future research agendas were proposed.

In terms of the perspective of service supply chain link, extant literature primarily focuses on service supply and service co-ordination management, and less on service demand and integration management. In terms of the behavioural factor’s perspective, most focus on classic behaviour factors, with less attention paid to emerging behaviour factors. This paper thus proposes five research agendas: demand-oriented management and integrated supply chain-oriented behavioural research; broadening the understanding of the scope of behavioural operations; integrating the latest backgrounds and trends of service industry into the research; greater attention to behavioural operations in service sub-industries; and multimethod combination is encouraged to be used to dig into the interesting research problems.

This study constitutes the first systematic review of service supply chain research from a behavioural perspective. By categorising the literature into two dimensions, the state of existing research is evaluated with an eye towards future research avenues.

The wavelet neural network (WNN) has the drawbacks of slow convergence speed and easy falling into local optima in data prediction. Although the artificial bee colony (ABC) algorithm has strong global optimization ability and fast convergence speed, it also has the drawbacks of slow speed while finding the optimal solution and weak optimization ability in the later stage.

This article uses an ABC algorithm to optimize the WNN and establishes an ABC-WNN analysis model. Based on the example of the Jinan Yuhan underground tunnel project, the deformation of the surrounding rock of the double-arch tunnel crossing the fault fracture zone is predicted and analyzed, and the analysis results are compared with the actual detection amount.

The comparison results show that the predicted values of the ABC-WNN model have a high degree of fitting with the actual engineering data, with a maximum relative error of only 4.73%. On this basis, the results show that the statistical features of ABC-WNN are the lowest, with the errors at 0.566 and 0.573, compared with the single back propagation (BP) neural network model and WNN model. Therefore, it can be derived that the ABC-WNN model has higher prediction accuracy, better computational stability and faster convergence speed for deformation.

This article uses firstly the ABC-WNN for the deformation analysis of double-arch tunnels. This attempt laid the foundation for artificial intelligence prediction in deformation analysis of multi-arch tunnels and small clearance tunnels. It can provide a new and effective way for deformation prediction in similar projects.

This paper aims to systematically review, discuss and synthesize the current state of research in the realm of hedge fund activism (HFA). By exploring HFA-related literature through a transparent and rigorous method, this study identifies unexplored areas for future research to develop a comprehensive understanding of the subject.

The authors perform a systematic database survey procedure as recommended in the prior literature. The review includes 74 articles published in high-impact journals from 2008 to January 2024, sourced from the Web of Science and Scopus databases and filtered using several exclusion/inclusion criteria.

This review offers a detailed analysis of the selected papers, highlighting trends in HFA research, the most influential journals and authors and additional insights into current studies. By systematically presenting the state-of-the-art, this paper categorizes the current research into three main streams and provides a critical evaluation of existing knowledge, identifying gaps and potential directions for future research.

This study makes two significant contributions to the literature. First, this study systematically reviews HFA-related research and provides a comprehensive examination of our existing scientific understanding of the factors shaping activism and its implications. Especially, this paper adopts a rigorous methodological protocol to ensure transparency and replicability in the review process, while earlier reviews focus on specific areas and are primarily narrative. Second, this study identifies research gaps and questions across all three streams of literature, offering valuable insights for future scholars aiming to expand our knowledge of the dynamic and evolving nature of HFA.

To investigate the influence of vehicle operation speed, curve geometry parameters and rail profile parameters on wheel–rail creepage in high-speed railway curves and propose a multi-parameter coordinated optimization strategy to reduce wheel–rail contact fatigue damage.

Taking a small-radius curve of a high-speed railway as the research object, field measurements were conducted to obtain track parameters and wheel–rail profiles. A coupled vehicle-track dynamics model was established. Multiple numerical experiments were designed using the Latin Hypercube Sampling method to extract wheel-rail creepage indicators and construct a parameter-creepage response surface model.

Key service parameters affecting wheel–rail creepage were identified, including the matching relationship between curve geometry and vehicle speed and rail profile parameters. The influence patterns of various parameters on wheel–rail creepage were revealed through response surface analysis, leading to the establishment of parameter optimization criteria.

This study presents the systematic investigation of wheel–rail creepage characteristics under multi-parameter coupling in high-speed railway curves. A response surface-based parameter-creepage relationship model was established, and a multi-parameter coordinated optimization strategy was proposed. The research findings provide theoretical guidance for controlling wheel–rail contact fatigue damage and optimizing wheel–rail profiles in high-speed railway curves.

High-speed maglev technology can address the issues of adhesion, friction, vibration and high-speed current collection in traditional wheel-rail systems, making it an important direction for the future development of high-speed rail technology.

This paper elaborates on the demand and significance of developing high-speed maglev technology worldwide and examines the current status and technological maturity of several major high-speed maglev systems globally.

This paper summarizes the challenges in the development of high-speed maglev railways in China. Based on this analysis, it puts forward considerations for future research on high-speed maglev railways.

This paper describes the development status and technical maturity of several major high-speed maglev systems in the world for the first time, summarizes the existing problems in the development of China's high-speed maglev railway and on this basis, puts forward the thinking of the next research of China's high-speed maglev railway.