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The purpose of this paper is to study the aerodynamic characteristics and uplift force tendencies of pantographs within the operational height span of 1,600–2,980 mm, aiming to offer valuable insights for research concerning the adaptability of pantograph-catenary systems on double-stack high container transportation lines.

Eight pantograph models were formulated based on lines with the contact wire of 6,680 mm in height. The aerodynamic calculations were carried out using the SST k-ω separated vortex model. A more improved aerodynamic uplift force method was also presented. The change rule of the aerodynamic uplift force under different working heights of the pantograph was analyzed according to the transfer coefficients of the aerodynamic forces and moments.

The results show that the absolute values of the aerodynamic forces and moments of the upper and lower frame increase with the working height, whereas those of the collector head do not change. The absolute values of the transfer coefficients of the lower frame and link arm were significantly larger than those of the upper frame. Therefore, the absolute value of the aerodynamic uplift force increased and then decreased with the working height. The maximum value occurred at a working height of 2,400 mm.

A new method for calculating the aerodynamic uplift force of pantographs is proposed. The specifical change rule of the aerodynamic uplift force of the pantograph on double-stack high container transportation lines was determined from the perspective of the transfer coefficients of the aerodynamic forces and moments.

The purpose of this study is to investigate the impact of customer concentration on the provision of reverse trade credit at the firm level.

Utilizing unbalanced panel data of Chinese A-share listed firms from 2007 to 2022 as the study sample, this paper employs a fixed-effects model to investigate the association between customer concentration and firms’ reverse trade credit.

This study finds that firms with higher customer concentration receive less reverse trade credit. Heterogeneity tests reveal a significant amplification of reverse trade credit in high-tech firms but a detrimental impact in large-sized, competitive and high-analyst-following firms. Further studies conclude that firms’ motivations, including bargaining power, financing and transaction guarantee motivations, collectively influence the extent of reverse trade credit acquisition.

To our knowledge, this paper represents the first attempt to conduct a comprehensive investigation of reverse trade credit, specifically through the lens of customer concentration, utilizing firm-level panel data sourced from a singular country.

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 study examines the interdependent relationships between green supply chain management (GSCM), carbon neutrality capability (CNC), digital transformation (DT) and firm performance (FP) among enterprises listed on the Chinese stock market. The primary objective is to provide a scholarly examination that may help these organisations to enhance their GSCM practices significantly.

Drawing on data from mainland Chinese publicly listed firms over the period from 2014 to 2021, this study posits and methodically evaluates four hypotheses: (1) GSCM practices are positively associated with an increase in CNC; (2) GSCM practices have a beneficial impact on FP; (3) DT moderates the GSCM–FP relationship and (4) CNC mediates the effect of GSCM on FP.

Contrary to initial assumptions, the findings suggest that GSCM practices may initially have a negative impact on FP. However, a concerted focus on CNC has the potential to convert this negative trajectory into a positive influence on FP. The findings further identify that DT has a significant moderating effect on the GSCM–FP relationship.

The findings of this study enrich the academic discourse concerning the symbiotic effects of GSCM, CNC and DT on FP. By systematically analysing these dynamics, the study underscores the critical importance of CNC and DT in the successful application of GSCM practices, thus offering valuable contributions to the literature on sustainable corporate operations.

Considering two types of subsidies for producers (supplier and manufacturer) and one for consumers based on product greenness and sales quantity, this study aims to formulate optimal supply chain green innovation and subsidy strategies, and to achieve this goal with the support of information systems.

This study introduces a composite green-product supply chain where suppliers focus on green innovation for component greenness and manufacturers focus on green innovation for manufacturing process greenness. Game theory modeling is applied to investigate the differences of product greenness, supply chain members’ profit and social welfare under different government subsidy strategies.

Increasing the unit greenness subsidy coefficient can boost product greenness and supply chain members’ profits, but does not always raise social welfare. When the government exclusively offers subsidies to producers, subsidies should be allocated to suppliers when there is a significant disparity in supply chain green innovation costs. Conversely, it is more beneficial to subsidize manufacturers. Consumer subsidies have the potential to enhance both environmental and economic performance in the supply chain compared with producer-exclusive subsidies, but may not always maximize social welfare when supply chain members have low unit costs associated with green innovation.

This study examines the optimal decisions for green supply chain innovation and government subsidy strategies. Supply chain members and the government can use the information system to collect and evaluate the cost of upstream and downstream green innovation, and then develop reasonable collaborative green innovation and subsidy strategies.

This study aims to investigate the relationships between the perceived neighborhood walkable environment (PNWE), neighborhood interaction (NI) and residents’ mental health, with a focus on examining differences among residents of different age groups.

Using an electronic survey questionnaire, data on PNWE, NI and mental health were collected from 1,159 residents across 205 communities in Shanghai, China. Our study utilized a structural equation modeling (SEM), employing the maximum likelihood estimation method. The structural equation model was fitted using the MPLUS software.

The mental health of young and middle-aged adults is generally poor, and they are at higher risk of depression than children and older adults. The effects of PNWE and NI on the mental health of residents varied among different age groups. As residents get older, their mental health is more affected by the PNWE. In addition, the influence of the PNWE on children and older adults’ mental health is direct and not mediated by NI. For young and middle-aged adults, the influence of the PNWE on their mental health needs to be mediated by NI.

This study marks the first examination of the relationship between PNWE, NI and mental health among different age groups of residents in China. The findings of this research can assist policymakers in gaining a deeper understanding of the underlying mechanisms by which PNWE affects mental health. Furthermore, it can contribute to the development of more targeted walkable environment designs aimed at enhancing mental health among various age groups.

Artificial Intelligence (AI) is revolutionizing the world. Despite the numerous advantages of AI in terms of faster processing and higher efficiency, AI hasn’t been widely accepted by humans yet. This study aims to shed light on this phenomenon by exploring the Dunning–Kruger Effect in AI knowledge and examining how AI knowledge affects AI acceptance through AI-related self-efficacy.

By collecting data from 179 managers, we examined the Dunning–Kruger Effect in AI knowledge and used mediation analysis to explore the mechanisms by which AI knowledge leads to AI acceptance.

Our findings indicated the presence of the Dunning–Kruger Effect in AI knowledge. Furthermore, our results revealed that AI knowledge has a nonlinear effect on AI acceptance through AI-related self-efficacy.

In contrast to previous research that posited a linear link between knowledge and acceptance of technology, this study offers a new framework for the nonlinear relationships between AI knowledge, AI-related self-efficacy and AI acceptance by extending the Dunning–Kruger effect to the AI field.

The study explores the pivotal role of green information technology and sustainable business processes and their impact on organizational value in an underdeveloped economy. It aims to develop a comprehensive model for driving organizational value through sustainable initiatives.

Data was gathered through 474 survey instruments (41% response rate) from top managers of IT firms using a convenience sampling technique. After ensuring reliability and validity, hypotheses were tested using structural equation modeling. Data analysis utilized SPSS and AMOS 21.0.

The study revealed a significant positive impact of green information technology initiatives on financial and non-financial aspects, enhancing overall organizational value. Similarly, green information technology significantly influences sustainable business processes. Furthermore, sustainable business processes, encompassing economic, social, and environmental dimensions, enhance organizational value, including financial and non-financial performance. Consequently, a multifaceted sustainable model has been developed to optimize organizational value, providing new insights.

The findings imply that firms should focus on acquiring new green technologies and adopting sustainable processes, leading to enhanced profits and non-financial gains. This study aids managers in strategy development and implementation and guides policymakers in formulating context-specific policies. It enriches the existing literature on green IT, business process management, and organizational value.

The study rigorously tested a framework for fostering organizational value through green information technology and sustainable business processes in information technology firms. The proposed framework was validated using structural equation modeling.

This research paper aims to shed light on Amman’s stairways and explore the potential of being successful urban spaces. It tries to identify critical design factors that contribute to making these stairs livable urban spaces to help further develop this type of urban space.

Three popular stairs were identified, for which a series of exploratory visits were conducted to document the morphological characteristics and essential activities around each stairway. This was followed by administering a questionnaire to measure users’ satisfaction with four criteria, including protection, comfort, attractiveness and functionality, to identify the strengths and weaknesses of each stair.

Results confirmed the presence of essential design aspects that encourage users to come and practice certain activities that enhance urban social life. Aspects of concern include security and protection, aesthetic quality, uniqueness, variety of activities, room to walk, sit and socialize and good management of space.

Results can be taken as a departure frame for future research to conduct deeper analysis to comprehend the stairways’ physical, contextual and social characteristics. Understanding the settings of such vital urban spaces will help revive their roles and bring back their brilliance to restore the city’s liveliness and maintain a better life quality for its residents.

Research interests almost lack studies addressing urban stairways aiming to understand the qualities that enable them to attract people and activities. The manuscript presents beneficial research that tackles the vitality of urban stairways, as an example of linear public spaces. Enhancing the quality of these spaces will help stimulate pedestrian movement and activate walking as an essential sustainable means of commuting at the city level.