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Logistics and supply chain management (L&SCM) scholars and practitioners have devoted extensive efforts to advancing green logistics practices (GLPs), yet the intersection between the two domains in relation to the topic remains underexplored. To accelerate GLPs’ development amid the escalating climate crisis, this research examines this intersection by comparing the responsiveness of academia and practice to the call for green logistics over time.

To compare between academia and practice, we combined a systematic literature review on the development of GLPs in L&SCM journals (N = 122) with a content analysis of annual and sustainability reports published by the four major global logistics service providers (LSPs: DHL, DB Schenker, UPS and FedEx; N = 156) over the past three decades.

This research reveals that all the GLPs covered in the L&SCM literature have already been applied and reported by practitioners, both consistently and over a significant period of time. Academic progress, in turn, is delayed by slow-paced empirical methods, elevated research quality standards, prolonged funding and recruitment processes, and extended peer-review intervals. Further, a tendency toward reactive knowledge creation rather than proactive knowledge transfer is evident, obscuring the role of L&SCM scholars in steering the industry’s green advancement.

Recommendations are offered to L&SCM authors, editors, reviewers and university departments to advance pracademic endeavors in green logistics research and increase its responsiveness to global events.

This is one of the first studies to scrutinize the intersection between academia and practice on the evolution of GLPs. The revealed gaps prompted us to suggest a transformative paradigm for academia-practice collaborations targeting the L&SCM discipline at large, combining a bold proactive research stream aimed at knowledge transfer with a more traditional reactive stream aimed at knowledge creation.

The objective of this study is to investigate the impact of longitudinal forces on extreme-long heavy-haul trains, providing new insights and methods for their design and operation, thereby enhancing safety, operational efficiency and track system design.

A longitudinal dynamics simulation model of the super long heavy haul train was established and verified by the braking test data of 30,000 t heavy-haul combination train on the long and steep down grade of Daqing Line. The simulation model was used to analyze the influence of factors on the longitudinal force of super long heavy haul train.

Under normal conditions, the formation length of extreme-long heavy-haul combined train has a small effect on the maximum longitudinal coupler force under full service braking and emergency braking on the straight line. The slope difference of the long and steep down grade has a great impact on the maximum longitudinal coupler force of the extreme-long heavy-haul trains. Under the condition that the longitudinal force does not exceed the safety limit of 2,250 kN under full service braking at the speed of 60 km/h the maximum allowable slope difference of long and steep down grade for 40,000 t super long heavy-haul combined trains is 13‰, and that of 100,000 t is only 5‰.

The results will provide important theoretical basis and practical guidance for further improving the transportation efficiency and safety of extreme-long heavy-haul trains.

This paper analyzes two external costs often associated with port development, cost to fisheries from marine dredge disposal and damages from air pollution, using estimates of development and operation for a proposed (but since cancelled) container port as a case study. For dredge disposal, a bio-economic model was used to assess short- and long-term and indirect (joodweb) damages to fisheries from marine disposal of clean sediments. In the case of air pollution, estimates of annual activity levels and emission coefficients are used to estimate incremental annual emissions of three key pollutants (NOx, HC and CO) for trucks, trains, yard vehicles, and vessels. These estimates allow for phasing in of strict new air pollution regulations. For both external costs, sensitivity analyses are used to reflect uncertainty. Estimates of shadow values in year 2002 dollars amount from $0.094 per cubic yard to $0.169 per cubic yard of clean dredged material for the selected disposal site and from $0.0584 per mile (jor current control standards) to $ 0. 0023 per mile (after phasing in of new regulations) for air pollution from heavy trucks.

This study aims to investigate the safety effects of work zone advisory systems. The traditional system includes a dynamic message sign (DMS), whereas the advanced system includes an in-vehicle work zone warning application under the connected vehicle (CV) environment.

A comparative analysis was conducted based on the microsimulation experiments.

The results indicate that the CV-based warning system outperforms the DMS. From this study, the optimal distances of placing a DMS varies according to different traffic conditions. Nevertheless, negative influence of excessive distance DMS placed from the work zone would be more obvious when there is heavier traffic volume. Thus, it is recommended that the optimal distance DMS placed from the work zone should be shortened if there is a traffic congestion. It was also revealed that higher market penetration rate of CVs will lead to safer network under good traffic conditions.

Because this study used only microsimulation, the results do not reflect the real-world drivers’ reactions to DMS and CV warning messages. A series of driving simulator experiments need to be conducted to capture the real driving behaviors so as to investigate the unresolved-related issues. Human machine interface needs be used to simulate the process of in-vehicle warning information delivery. The validation of the simulation model was not conducted because of the data limitation.

It suggests for the optimal DMS placement for improving the overall efficiency and safety under the CV environment.

A traffic network evaluation method considering both efficiency and safety is proposed by applying traffic simulation.

This study aims to introduce the achievements and benefits of applying wheel/rail-force–based maintenance interval extension of the C80 series wagon in China.

Chinese wagons' existing maintenance strategy had left a certain safety margin for the characteristics of widely running range, unstable service environment and submission to transportation organization requirements. To reduce maintenance costs, China railway (CR) has attempted to extend the maintenance interval since 2020. The maintenance cycle of C80 series heavy haul wagons is extended by three months (no stable routing) or 50,000 km (regular routing). However, in the meantime, the alarming rate of the running state, a key index to reflect the severe degree of hunting stability, by the train performance detection system (TPDS) for the C80 series heavy haul wagons has increased significantly.

The present paper addresses a big data statistical way to evaluate the risk of allowing the C80 series heavy haul wagons to remain in operation longer than stipulated by the maintenance interval initial set. Through the maintenance and wayside-detector data, which is divided into three stages, the extension period (three months), the current maintenance period and the previous maintenance period, this method reveals the alarming rate of hunting was correlated with maintenance interval. The maintainability of wagons will be achieved by utilizing wagon performance degradation modeling with the state of the wheelset and the often-contact side bearing. This paper also proposes a statistical model to return to the average safety level of the previous maintenance period's baseline through correct alarming thresholds for unplanned corrective maintenance.

The paper proposes an approach to reduce safety risk due to maintenance interval extension by effective maintenance program. The results are expected to help the railway company make the optimal solution to balance safety and the economy.

Recently, interest in sustainability has grown globally in the heavy vehicle and equipment industry (HVEI). However, this industry's complexity poses a challenge to the implementation of generic sustainable supply chain management (SSCM) practices. This study aims to identify SSCM's barriers, practices and performance (BPP) indicators in the HVEI context.

The results are derived from case studies of four multinational manufacturers. Within-case and cross-case analyses were conducted to categorise the SSCM BPP indicators that are unique to HVEI supply chains.

This study's analysis revealed that supply chain cost implications and a deficient information flow between focal firms and supply chain partners are the key barriers to SSCM in the HVEI. This analysis also revealed a set of policies, programmes and procedures that manufacturers have adopted to address SSCM barriers. The most common SSCM performance indicators included eco-portfolio sales to assess economic performance, health and safety indicators for social sustainability and carbon- and energy-related measures for environmental sustainability.

The insights can help HVEI firms understand and overcome the typical SSCM barriers in their industry and develop, deploy and optimise their SSCM strategies and practices. Managers can use this knowledge to identify appropriate mechanisms with which to accelerate their transition into a sustainable business and effectively measure performance outcomes.

The extant SSCM literature has focused on the light vehicle industry, and it has lacked a concrete examination of HVEI supply chains' sustainability BPP. This study develops a framework that simultaneously analyses SSCM BPP in the HVEI.

Purpose – The purpose of this study is to develop a numerical framework to predict the time-dependent probability of failure of a bridge subjected to multiple vehicle impacts. Specially, this study focuses on investigating the inter-relationship between changes in life-cycle parameters (e.g., damage size caused by vehicle impact, loss of initial structural capacity, and threshold intervention) and bridges probability of failure.

Design/Methodology/Approach – The numerical procedure using MATLAB program is developed to compute the probability failure of a bridge. First, the importance and characteristics of life-cycle analysis is described. Then, model for damage accumulation and life cycle as a result of heavy vehicle impacts is discussed. Finally, the probability of failure of a bridge subjected to vehicle impacts as a result of change in life-cycle parameters is presented.

Findings – The results of study show that damage size caused by both vehicle impacts and loss of initial structural capacity have a great impact on the long-term safety of bridges. In addition, the probability of failure of a bridge under different threshold limits indicates that the structural intervention (e.g., repair or maintenance) should be undertaken to extend the service life of a bridge.

Research Limitations/Implications – The damage sizes caused by heavy vehicle impacts are based on simple assumptions. It is suggested that there would be a further study to estimate the magnitude of bridge damage as a result of vehicle impact using the full-scale impact test or computational simulation.

Practical Implications – This will allow much better predictions for residual life of bridges which could potentially be used to support decisions on health and maintenance of bridges.

Originality/Value – The life-cycle performance for assessing the time-dependent probability of failure of bridges subjected to multiple vehicle impact has not been fully discussed so far.

This paper presents a case study examining the emissions impacts of a modal shift from on-road trucks to rail for goods movement through the Southern California ports region, one of the severest non-attainment areas in terms of national air quality standards. Recent completion of the Alameda Corridor, a 20-mile rail expressway that connects the Ports of Long Beach and Los Angeles with rail mainlines near downtown Los Angeles, provides substantial reserve capacity for port traffic to be diverted from the severely congested road network to the rail line. On-road vehicles emissions were estimated using California mobile-source emissions model, ‘EMFAC’ that incorporates a set of emissions factors for each vehicle type and an estimate of vehicle activity. These emissions were then compared with the emissions generated from trains increased to carry freight volume diverted from truck traffic. On the basis of year 2000 traffic level, it was estimated that for a 20 percent modal shift of port traffic, mobile-source emissions can be reduced up to 0.86 tons for nitrogen oxides and 16 kg for particulate matter per day. The analysis results indicate that encouraging the modal shift for port-related freight traffic should be an integral part of overall air quality improvement initiatives for the study area.