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The aerodynamic differences between the head car (HC) and tail car (TC) of a high-speed maglev train are significant, resulting in control difficulties and safety challenges in operation. The arch structure has a significant effect on the improvement of the aerodynamic lift of the HC and TC of the maglev train. Therefore, this study aims to investigate the effect of a streamlined arch structure on the aerodynamic performance of a 600 km/h maglev train.

Three typical streamlined arch structures for maglev trains are selected, i.e. single-arch, double-arch and triple-arch maglev trains. The vortex structure, pressure of train surface, boundary layer, slipstream and aerodynamic forces of the maglev trains with different arch structures are compared by adopting improved delayed detached eddy simulation numerical calculation method. The effects of the arch structures on the aerodynamic performance of the maglev train are analyzed.

The dynamic topological structure of the wake flow shows that a change in arch structure can reduce the vortex size in the wake region; the vortex size with double-arch and triple-arch maglev trains is reduced by 15.9% and 23%, respectively, compared with a single-arch maglev train. The peak slipstream decreases with an increase in arch structures; double-arch and triple-arch maglev trains reduce it by 8.89% and 16.67%, respectively, compared with a single-arch maglev train. The aerodynamic force indicates that arch structures improve the lift imbalance between the HC and TC of a maglev train; double-arch and triple-arch maglev trains improve it by 22.4% and 36.8%, respectively, compared to a single-arch maglev train.

This study compares the effects of a streamlined arch structure on a maglev train and its surrounding flow field. The results of the study provide data support for the design and safe operation of high-speed maglev trains.

Visual feedback control is a promising solution for robots work in unstructured environments, and this is accomplished by estimation of the time derivative relationship between the image features and the robot moving. While some of the drawbacks associated with most visual servoing (VS) approaches include the vision–motor mapping computation and the robots’ dynamic performance, the problem of designing optimal and more effective VS systems still remains challenging. Thus, the purpose of this paper is to propose and evaluate the VS method for robots in an unstructured environment.

This paper presents a new model-free VS control of a robotic manipulator, for which an adaptive estimator aid by network learning is proposed using online estimation of the vision–motor mapping relationship in an environment without the knowledge of statistical noise. Based on the adaptive estimator, a model-free VS schema was constructed by introducing an active disturbance rejection control (ADRC). In our schema, the VS system was designed independently of the robot kinematic model.

The various simulations and experiments were conducted to verify the proposed approach by using an eye-in-hand robot manipulator without calibration and vision depth information, which can improve the autonomous maneuverability of the robot and also allow the robot to adapt its motion according to the image feature changes in real time. In the current method, the image feature trajectory was stable in the camera field range, and the robot’s end motion trajectory did not exhibit shock retreat. The results showed that the steady-state errors of image features was within 19.74 pixels, the robot positioning was stable within 1.53 mm and 0.0373 rad and the convergence rate of the control system was less than 7.21 s in real grasping tasks.

Compared with traditional Kalman filtering for image-based VS and position-based VS methods, this paper adopts the model-free VS method based on the adaptive mapping estimator combination with the ADRC controller, which is effective for improving the dynamic performance of robot systems. The proposed model-free VS schema is suitable for robots’ grasping manipulation in unstructured environments.

Digital platforms (DP) are transforming service delivery and affecting associated actors. The position of DPs is impacted by the regulations. However, emerging economies often lack the regulatory environment to support DPs. This paper aims to explore the regulatory developments for DPs using the multi-level perspective (MLP).

The paper explores regulatory developments of ride-hailing platforms (RHPs) in India and their impacts. This study uses qualitative interview data from platform representatives, bureaucrats, drivers, experts and policy documents.

Regulatory developments in the ride-hailing space cannot be explained as a linear progression. The static institutional assumptions, especially without considering the multi-actors and multi-levels in policy formulation, do not serve associated actors adequately in different times and spaces. The RHPs regulations must consider the perspective of new RHPs and the support available to them. Non-consideration of short- and long-term perspectives of RHPs may have unequal outcomes for established and new RHPs.

This research has implications for the digital economy regulatory ecosystem, DPs and implications for policymakers. Though the data from legal documents and qualitative interviews is adequate, transactional data from the RHPs and interviews with judiciary actors would have been insightful.

The study provides insights into critical aspects of regulatory evolution, governance and regulatory impact on the DPs’ ecosystem. The right balance of regulations according to the business models of DPs allows DPs to have space for growth and development of the platform ecosystem.

This research shows the interactions in the digital space and how regulations can impact various actors. A balanced policy can guide the paths of DPs to have equal opportunities.

DP regulations have a complex structure. The paper studies regulatory developments of DPs and the impacts of governance and controls on associated players and platform ecosystems.

By using a wide range of macro and micro factors, this paper aims to provide a new assessment of the recent literature on inbound tourism demand models.

This study examines the determinants and spatial effects of inbound tourism using Hausman–Taylor and spatial econometric models.

Several important factors were identified, including local economic growth, openness to the outside world, regional size, geographic distance, foreign direct investment, level of innovation and average annual temperature. In addition, the study found strong cross-city competition effects on tourism resource endowment and hotel infrastructure.

Inbound tourism is a crucial link in achieving high-quality economic development. However, previous studies have mainly focused on the analysis of single influencing factors, ignoring the spatial spillover effects of factors.

This research is aimed to examine how environmental pollution affects consumers' preference for self-improvement products.

Through a series of three experimental studies, this research substantiates our hypotheses by employing various manipulations of environmental pollution and examining different types of self-improvement products.

The research demonstrates that environmental pollution enhances consumers' preference for self-improvement products via the mediation of perceived environmental responsibility. And the effect is negatively moderated by social equity sensitivity.

The recurrent incidence of environmental pollution has elicited significant concern among the general public and academic scholars. An overwhelming majority of research examining the impact of pollution on consumer behavior has concentrated on its influence on environmentally friendly and healthy consumption patterns. Nevertheless, the current research proposes that pollution fosters a preference for products associated with self-improvement, mediated by perceived environmental responsibility, with the effects being moderated by social equity sensitivity.

Purpose: This chapter examines the effect of green banking practices (GBPs) on environmental performance (EP), specifically focussing on the Sri Lankan banking industry. Additionally, the study explores the mediating impact of green finance in the association between GBPs and the EP of banks listed in the Colombo Stock Exchange in Sri Lanka.

Methodology: The survey included 233 banking employees from Sri Lanka, and data for this study were collected via questionnaires. The formulated hypotheses were tested employing a regression analysis.

Findings: GBPs such as employee, customer, operation, and policy-related practices significantly predicted the banks’ EP. Furthermore, the study highlights that green finance partially mediates the relationship between GBPs and banks’ EP in Sri Lanka.

Implications of the study: The study’s results indicate that banks should prioritise integrating GBPs in their organisations to enhance environmental and overall performance. Moreover, strategically utilising green financing techniques might be a substantial channel for banks to further strengthen their ecological dedication and influence.

Originality: This is the first study to investigate the impact of GBPs on banks’ EP with the mediating effect of green finance in the Sri Lankan context.

By introducing the mass customization service mode into the cloud logistics environment, this paper studies the joint optimization of service provider selection and customer order decoupling point (CODP) positioning based on the mass customization service mode to provide customers with more diversified and personalized service content with lower total logistics service cost.

This paper addresses the general process of service composition optimization based on the mass customization mode in a cloud logistics service environment and constructs a joint decision model for service provider selection and CODP positioning. In the model, the two objective functions of minimum service cost and most satisfactory delivery time are considered, and the Pareto optimal solution of the model is obtained via the NSGA-II algorithm. Then, a numerical case is used to verify the superiority of the service composition scheme based on the mass customization mode over the general scheme and to verify the significant impact of the scale effect coefficient on the optimal CODP location.

(1) Under the cloud logistics mode, the implementation of the logistics service mode based on mass customization can not only reduce the total cost of logistics services by means of the scale effect of massive orders on the cloud platform but also make more efficient use of a large number of logistics service providers gathered on the cloud platform to provide customers with more customized and diversified service content. (2) The scale effect coefficient directly affects the total cost of logistics services and significantly affects the location of the CODP. Therefore, before implementing the mass customization logistics service mode, the most reasonable clustering of orders on the cloud logistics platform is very important for the follow-up service combination.

The originality of this paper includes two aspects. One is to introduce the mass customization mode in the cloud logistics service environment for the first time and summarize the operation process of implementing the mass customization mode in the cloud logistics environment. Second, in order to solve the joint decision optimization model of provider selection and CODP positioning, this paper designs a method for solving a mixed-integer nonlinear programming model using a multi-layer coding genetic algorithm.

Introduction: In the modern period, environmental degradation has had negative effects on people’s health as well as the regular business environment. As a result, embracing a ‘Go Green’ philosophy has gained widespread acceptance among individuals and corporations worldwide. Going green is referred to as promoting eco-friendly ways and banks are essential in protecting the environment to improve our quality of life.

Purpose: This study will focus on the correlation between green banking practices (GBP), employee green behaviour (EGB), and banks’ sustainability performance and how this relationship will give a competitive edge in terms of sustainability to the banks adopting these GBP.

Methodology: EGB between GBP and bank sustainability occurrence is clarified by this study. The current study is descriptive and finds the relationship through previous literature reviews.

Findings: Employees are expected to be crucial in this transformation as the modern banking system adopts green banking initiatives and updates traditional banking processes. Employees help banks perform more sustainably by encouraging environmentally friendly banking practices.

Practical Implications: By understanding the mechanism, between GBP and bank sustainability, banks can adopt more effective strategies to enhance their sustainability performance while promoting environmentally friendly practices.

The purpose of this paper is to clarify the influence of low earth orbit space environment on the wear mechanism of TC4 alloy material and crank rocker mechanism.

In this study, friction experiments were carried out on TC4 alloy friction discs and crank rocker mechanisms, both before and after exposure to atomic oxygen and proton irradiation. Nanoindentation, grazing incidence X-ray diffraction (GIXRD), and X-ray photoelectron spectroscopy were employed to systematically characterize alterations in mechanical properties, surface phase, and chemical composition.

The results show that the wear mechanism of TC4 alloy friction disc is mainly adhesive wear in vacuum environment, while the wear mechanism of crank rocker mechanism includes not only adhesive wear but also abrasive wear. Atomic oxygen exposure leads to the formation of more oxides on the surface of TC4 alloy, which form abrasive particles during the friction process. Proton irradiation will lead to a decrease in fatigue performance and an increase in hardness on the surface of TC4 alloy, thus causing fatigue wear on the surface of TC4 alloy, and more furrows appear on the crank rocker mechanism after proton irradiation. In the three environments, the characteristics of abrasive wear of the crank rocker mechanism are more obvious than those of the TC4 alloy friction disc.

These results highlight the importance of understanding the subtle effects of atomic oxygen and proton irradiation on the wear behavior of TC4 alloy and provide some insights for optimizing its performance in space applications.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-02-2024-0051/

Due to the rapid increase in global warming and environmental disasters, destination management and tourists' environmental awareness have increased. This increase in environmental awareness has led destinations to prioritize green practices that reduce environmental pollution. Moreover, in recent years, with the rapid development of technology, artificial intelligence technology has also been used in applications that reduce environmental pollution in destinations. This is because environmentally friendly products and services offered by destinations have started to have an impact on tourists' travel choices. Additionally, tourists' awareness and loyalty towards environmentally friendly destinations have started to increase, resulting in the formation of brand value for destinations. Therefore, green practices and AI technologies play a role in the formation of consumer-based destination green brand value.