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The objective of this paper is to evaluate whether the data from consignors, logistics service providers (LSPs) and consignees contribute to the prediction of air transport shipment delays in a machine learning application.

The research database contained 2,244 air freight intercontinental shipments to 4 automotive production plants in Latin America. Different algorithm classes were tested in the knowledge discovery in databases (KDD) process: support vector machine (SVM), random forest (RF), artificial neural networks (ANN) and k-nearest neighbors (KNN).

Shipper, consignee and LSP data attribute selection achieved 86% accuracy through the RF algorithm in a cross-validation scenario after a combined class balancing procedure.

These findings expand the current literature on machine learning applied to air freight delay management, which has mostly focused on weather, airport structure, flight schedule, ground delay and congestion as explanatory attributes.

The purpose of this paper is to develop a better understanding of the factors that influence a shipper's decision to choose air cargo as a mode of shipment.

A disaggregate multinomial discrete choice model is developed using freight shipment survey data to identify critical factors influencing air cargo mode choice. Disaggregate revealed preference data is obtained from surveying 347 manufacturers, freight forwarders, and other third-party service providers.

The empirical model developed in this research shows that the rate of shipment, time of transit, cost-per-pound shipped, quantity shipped, perishability and delay rate of the mode are significant factors that influence mode choice.

The discrete choice model developed can be improved by taking into account logistics costs not considered in this research. Perhaps more in-depth surveys of the shippers and freight forwarders are needed. Additionally, improving the mode choice model by including stated preference data and subsequently incorporating service quality latent variables would be beneficial.

Identifying the sensitivity of the shippers to various factors influencing mode selection enables transportation planners make better demand forecast for each mode of transportation.

This paper extends previous mode choice studies by analyzing mode selection between air cargo and other modes. Better forecasting is achieved by replacing the logit model with probit, heteroscedastic extreme value and mixed logit models.

This is the first of a series of three papers discussing a major benchmarking initiative in the air cargo freight industry sector. The project itself focused on nine major competitors in the cargo industry and included organisations known to be leaders in the areas of service excellence. The methodology used for establishing comparisons was an adaptation of the Malcolm Baldrige National Quality Award (MBNQA) (1996 version). A questionnaire was used with prompts covering various areas of quality management, people involvement in continuous improvement, service excellence aspects, customer focus and satisfaction aspects and finally business and operational performance aspects. Paper 1 discusses the changes that are taking place in the air cargo freight industry and sets the scene by presenting profiles of all of the competitors used in this study.

Accurately estimating the severity of derailment is a crucial step in quantifying train derailment consequences and, thereby, mitigating its impacts. The purpose of this paper is to propose a simplified approach aimed at addressing this research gap by developing a physics-informed 1-D model. The model is used to simulate train dynamics through a time-stepping algorithm, incorporating derailment data after the point of derailment.

In this study, a simplified approach is adopted that applies a 1-D kinematic analysis with data obtained from various derailments. These include the length and weight of the rail cars behind the point of derailment, the train braking effects, derailment blockage forces, the grade of the track and the train rolling and aerodynamic resistance. Since train braking/blockage effects and derailment blockage forces are not always available for historical or potential train derailment, it is also necessary to fit the historical data and find optimal parameters to estimate these two variables. Using these fitted parameters, a detailed comparison can be performed between the physics-informed 1-D model and previous statistical models to predict the derailment severity.

The results show that the proposed model outperforms the Truncated Geometric model (the latest statistical model used in prior research) in estimating derailment severity. The proposed model contributes to the understanding and prevention of train derailments and hazmat release consequences, offering improved accuracy for certain scenarios and train types

This paper presents a simplified physics-informed 1-D model, which could help understand the derailment mechanism and, thus, is expected to estimate train derailment severity more accurately for certain scenarios and train types compared with the latest statistical model. The performance of the braking response and the 1-D model is verified by comparing known ride-down profiles with estimated ones. This validation process ensures that both the braking response and the 1-D model accurately represent the expected behavior.

Inland shipping has been extensively recognised as a sustainable, efficient and good alternative to rail and road modes of transportation. In recent years, various authorities and academic researchers have advocated shifting from road to other sustainable modes like inland waterway transport (IWT) or rail transport. Academic work on modernisation and technological innovations to enhance the effectiveness and efficiency of waterborne transportation is becoming apparent as a growing body of literature caused by the need to achieve a sustainable transport system. Thus, it became apparent to explore the research trends on IWT.

A systematic and structured literature review study was employed in this paper to identify the challenges and concepts in modernising inland waterways for freight transportation. The review analysed 94 articles published in 54 journals from six well-known databases between 2010 and 2022.

The key findings of this review are that despite various challenges confronting the sector, there have been successful cases of technological advancement in the industry. The main interest among scholars is improving technical and economic performance, digitalisation, and safety and environmental issues. The review revealed that most of the literature is fragmented despite growing interest from practitioners and academic scholars. Academic research to address the strategic objectives, including strengthening competitiveness (shipbuilding, hydrodynamics, incorporating artificial intelligence into the decision-making process, adopting blockchain technology to ensure transparency and security in the transactions, new technologies for fleets adaptation to climate change, more effective handling, maintenance and rehabilitation technologies), matching growth and changing trade patterns (intermodal solutions and new logistics approaches) are major causes of concerns.

By employing the approach of reviewing previously available literature on IWT review papers, this review complements the existing body of literature in the field of IWT by providing in a single paper a consolidation of recent state-of-the-art research on technological developments and challenges for inland waterways freight transport in the intermodal supply chain that can act as a single resource to keep researchers up to date with the most recent advancements in research in the domain of inland waterway freight transport. Additionally, this review identified gaps in the literature that may inspire new research themes in the field of IWT.

TO say that the Twenty‐fourth S.B.A.C. Show was an unqualified success is perhaps to gild the lily. True there were disappointments— the delay which kept the TSR‐2 on the ground until well after the Show being one—but on the whole the British industry was well pleased with Farnborough week and if future sales could be related to the number of visitors then the order books would be full for many years to come. The total attendance at the Show was well over 400,000—this figure including just under 300,000 members of the public who paid to enter on the last three days of the Show. Those who argued in favour of allowing a two‐year interval between the 1962 Show and this one seem to be fully vindicated, for these attendance figures are an all‐time record. This augurs well for the future for it would appear that potential customers from overseas are still anxious to attend the Farnborough Show, while the public attendance figures indicate that Britain is still air‐minded to a very healthy degree. It is difficult to pick out any one feature or even one aircraft as being really outstanding at Farnborough, but certainly the range of rear‐engined civil jets (HS. 125, BAC One‐Eleven, Trident and VCIQ) served as a re‐minder that British aeronautical engineering prowess is without parallel, while the number of rotorcraft to be seen in the flying display empha‐sized the growing importance of the helicopter in both civil and military operations. As far as the value of Farnborough is concerned, it is certainly a most useful shop window for British aerospace products, and if few new orders are actually received at Farnborough, a very large number are announced— as our ’Orders and Contracts' column on page 332 bears witness. It is not possible to cover every exhibit displayed at the Farnborough Show but the following report describes a wide cross‐section beginning with the exhibits of the major airframe and engine companies.

Over the last decades, freight networks and multimodal integration have been shaped by complex driving forces. Globalisation and consumerism in society significantly contributed to intensify the demand for services in freight transport. Technological breakthroughs and the related development of innovation fed the constant search for faster and cheaper services on a global scale. Altogether, these driving forces have boosted a rapid increase in the volume of freight transport by means of road transport. While industry had modified its networks to meet the demand, the pandemic period brought new challenges to freight networks, forcing the different modes of transport to adapt to the unexpected environment. Some of those reactive solutions might have been adopted temporarily. However, others are expected to become permanent and their deployment in the short-medium term remains to be seen.

This chapter presents an overview of the challenges and respective solutions that were initiated throughout the pandemic period, mostly in response to concerns related to social distance and untypical demand needs. This overview allows for a better foretelling of the future directions and developments in the freight network elements. This chapter approaches the way forward for cities and industry regarding the lasting pandemic effects on freight networks. Such an overview is complemented by an input from an expert survey in order to evaluate the social acceptability towards the expected solutions that are emerging. The outcome of the chapter highlights the main guidelines for the freight networks in the future and correlates them with the pandemic’s permanent effects.