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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.

Testing several approaches for implied volatility modeling and forecasting.

Comparative empirical study with four traded options.

Non-parametric higher-order spline is better than parametric stochastic volatility inspired (SVI) in China.

Our results imply that even though popular on Wall Street, SVI seems not to be utilized by traders and market-makers in China.

Traders may consider higher-order spline as a better method for implied volatility modeling and forecasting.

Propose to model and forecast implied volatility via the fifth-order spline interpolation as a first; initiates studies of the empirical performance of SVI and the fifth-order spline models in implied volatility modeling and forecasting.

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.

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.

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 paper is to present a new hybrid approach based on criticality analysis and optimisation to deal with spare parts inventory management in the initial provisioning phase in the mining industry. Spare parts represent a significant part of mining companies' expenditures, so it is important to develop new approaches to reduce the total inventory value of these items.

This hybrid approach combines qualitative and quantitative methods based on VED (vital, essential and desirable) analysis, analytical hierarchical process (AHP), and e-constraint optimisation method to obtain the spare parts to be stocked. The study was applied to a large mining company. The mineral sector was chosen due to the great importance to the emerging Brazilian economy and the lack of researches in this sector. In addition, the spare parts have a relevant weight on the total inventory cost.

Present a novel approach combining multi-objective optimisation and multi-criteria evaluation approaches to tackle the inventory decision in spare parts management. This work also defines and classifies relevant criteria for spare parts management in the mineral sector validated by specialists. The proposed approach achieves an average increase of 20.2% in the criticality and 16.6% in the number of items to be stocked compared to the historical data of the surveyed company.

This paper applies the proposed approach to a mining company in Brazil. Future research in other companies or regions should analyse the adequacy of the criticality criteria, hierarchy and weights adopted in this paper.

The proposed approach is useful for mining industries that deal with a large variety of resource constraints as it helps in formulating appropriate spare part strategies to rationalise financial resources at both tactical and strategic levels.

The paper presents a new hybrid method combining the AHP a multi-criteria decision making (MCDM) approach coupled with e-constraint optimisation to deal with spare parts inventory management allowing for a better spare parts inventory analysis in the initial provisioning phase and providing managers with a systematic tool to analyse the trade-off between spare parts criticality and total inventory value.

The purpose of this study is to develop an optimization method for charging plans with the implementation of time-of-day (TOD) electricity tariff, to reduce electricity bill.

Two optimization models for charging plans respectively with fixed and stochastic trip travel times are developed, to minimize the electricity costs of daily operation of an electric bus. The charging time is taken as the optimization variable. The TOD electricity tariff is considered, and the energy consumption model is developed based on real operation data. An optimal charging plan provides charging times at bus idle times in operation hours during the whole day (charging time is 0 if the bus is not get charged at idle time) which ensure the regular operation of every trip served by this bus.

The electricity costs of the bus route can be reduced by applying the optimal charging plans.

This paper produces a viable option for transit agencies to reduce their operation costs.

With the rapid development of the pipeline transportation and exploitation of mineral resources, it is urgent requirement for the high-performance polymer matrix composites with low friction and wear to meet the needs of solid material transportation. This paper aims to prepare high-performance ultrahigh molecular weight polyethylene (UHMWPE) matrix composites and investigate the effect of service condition on frictional behavior for composite.

In this study, UHMWPE matrix composites with different content of MoS₂ were prepared and the tribological performance of the GCr15/composites friction pair in various sliding speeds (0.025–0.125 m/s) under dry friction conditions were studied by ball-on-disk tribology experiments.

Results show that the frictional behavior was shown to be sensitive to MoS2 concentration and sliding velocity. As the MoS2 content is 2 Wt.%, composites presented the best overall tribological performance. Besides, the friction coefficient fluctuates around 0.21 from 0.025 to 0.125 m/s sliding speed, while the wear rate increases gradually. Scanning electron microscopy images, energy-dispersive spectroscopy and Raman Spectrum analysis present that the main wear mechanisms were abrasive and fatigue wear.

The knowledge obtained herein will facilitate the design of UHMWPE matrix composites with promising self-lubrication performances which used in slag transport engineering field.

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.

Based on goal orientation theory, this study aims to examine how and when employees' performance goal orientations (PGOs) affect their change-supportive behavior in entrepreneurial firms undergoing change.

A two-wave time-lagged research design was applied to collect data from companies undergoing change in China.

The results showed that employees' performance-proving goal orientation (PPGO) was positively related to change-supportive behavior, and employees' performance-avoiding goal orientation (PAGO) was negatively related to change-supportive behavior. Openness to change played a mediating role in these mechanisms, and employees' learning goal orientation (LGO) played a moderating role.

By solving the mechanism of the relationship between PGOs and change-supportive behavior that has not been explored before, this study answers the question of how and when different PGOs affect support behavior.