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Air Cargo
Published in Milica Kalić, Slavica Dožić, Danica Babić, Introduction to the Air Transport System, 2022
Milica Kalić, Slavica Dožić, Danica Babić
In addition to the factors that stimulate the growth of air cargo demand, there are certain factors that can adversely affect air cargo transport, such as (Boeing 2014): Economic recession, which usually causes reduction in production, reduction in demand for certain goods, reduction in international trade, etc., which further results in air cargo demand decrease.Barriers to trade, such as customs barriers and different kinds of protection of domestic production that restrict free trade.Regulations related to aircraft, such as noise levels and emissions reduction, as well as increasing safety. For example, implementation of noise reduction equipment can reduce aircraft payload, and consequently the amount of paid cargo that can be transported.Competition of other modes of transport, especially in shorter distances, where air cargo transport is considerably more expensive compared to road or rail cargo transport.
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Published in Anming Zhang, George W.L. Hui, Lawrence C. Leung, Waiman Cheung, Yer Van Hui, Air Cargo in Mainland China and Hong Kong, 2017
Anming Zhang, George W.L. Hui, Lawrence C. Leung, Waiman Cheung, Yer Van Hui
There are two measurement problems with the above data. First, though a variable such as passenger traffic is supposed to represent all passenger traffic in China, the statistical agencies actually include only the passenger traffic of domestic carriers. In other words, the passenger traffic of foreign carriers has been omitted. The other three variables all carry similar defects. Passenger and cargo throughput, the two remaining variables in Table 2.1, are measured, so to speak, at the ground level (e.g., at an airport) and do not carry the same deficiency. Second, the generally accepted definition of air cargo (or freight) refers to anything carried in an aircraft excepting mail or luggage carried under a passenger ticket and baggage check but including baggage moving under an air waybill or shipment record (IATA RP 1601 – Conditions of Carriage for Cargo).2 Until the early 1990s, the freight variables for China – freight traffic, tonne-kilometres performed, cargo throughput – all included air cargo, mail and luggage, and as a result are not comparable with international figures. We refer to cargo throughput that includes cargo, mail and luggage as cargo (plus) and the alternative that is consistent with international convention as cargo (only). Disaggregated data only started to be provided systematically from 1993 onwards.
Economic and technical regulation
Published in Peter S. Morrell, Thomas Klein, Moving Boxes by Air, 2018
Peter S. Morrell, Thomas Klein
There are regulations on the screening of air cargo carried on passenger flights in many countries following terrorist attacks on international air passenger services. These also fall under the SARPs covered under ICAO Annex 18. This is usually designed to avoid focusing all checks at airports. The US Transportation Security Administration (TSA) is the agency that is responsible for screening; in the EU common standards have been agreed with implementation performed by each member country. In the US 100% screening was incorporated in the law through ‘Implementing Recommendations of the 9/11 Commission Act of 2007 on August 3, 2007. All cargo was to be screened at a piece level, with compliance completed by August 2010 (see Figure 3.1).
Closed-loop digital twin system for air cargo load planning operations
Published in International Journal of Computer Integrated Manufacturing, 2021
Eugene Y. C. Wong, Daniel Y. Mo, Stuart So
Air cargo load planning operations require airlines and the air cargo terminal to fulfil international safety requirements and regulations. Air cargo loading involves complex considerations of centre of gravity (CG), payload and yield maximisation, and computation time. Previous studies have attempted to develop models and tools to solve these problems. Amiouny et al. (1992) analysed a one-dimensional loading problem with a constraint requiring the aircraft to be balanced. Their model considers the variety of loading containers, their one-dimensional positions and loading sequence prioritisation. It provides insights and useful findings about the safety requirements to be incorporated into a cargo load planning model but does not include details about yield optimisation and time elements. Limbourg, Schyns, and Laporte (2011) developed a mixed integer linear programming model to optimise loading containers and pallets into a compartmentalised cargo aircraft, with the objective of reducing fuel consumption and increasing aircraft efficiency. These optimisation models mainly focus on common ULDs, but not on oversize or awkward cargo. Son and Kim (2016) proposed a simulated annealing algorithm and compared the results and performance with Kim et al. (2011), the study incorporated stability restriction constraints, including cumulative load limit, location load limit, lateral load imbalance limit and CG.
The value of Blockchain technology implementation in international trades under demand volatility risk
Published in International Journal of Production Research, 2020
Jiho Yoon, Srinivas Talluri, Hakan Yildiz, Chwen Sheu
Of course, air cargo requires a higher premium cost compared to ocean cargo. In US imports, costs per kg., shipped via air are, on average, 5.7 times higher than those shipped by sea. (Hummels and Schaur 2010). Despite this premium cost, air transport is widely utilised in international trades because the potential for lost sales is recognised as a huge risk by the manufacturing firms. Ocean transport looks very attractive in terms of cost, but the inherent slowness, due to physical speed of the vessels and/or time-consuming stops at seaports and/or terminals, makes it unattractive from the time perspective. It takes 1–3 business days to clear air cargo shipments, while it takes 3–5 days, on average, to clear ocean cargo shipments through US Customs and border protection stations. If shipments are chosen for an intensive exam, the shipments must be transported to an examination station, and an additional 5–10 days will be added to their clearance time.1 In the case of ocean transport, port-to-port transit takes, on average, 18–26 days, based on direct freight, and door-to-door transit takes, on average, 30–38 days, depending on delays in clearing customs. On the other hand, port-to-port transit takes, on average, 3–5 days, and door-to-door transit takes 5–7 days, on average, in the case of air transport.2 Because of these obvious pros and cons of air and ocean transports, a considerable amount of goods is shipped via a mixture of ocean and air transport in international trades.
A hybrid ensemble learning-based prediction model to minimise delay in air cargo transport using bagging and stacking
Published in International Journal of Production Research, 2022
Rosalin Sahoo, Ajit Kumar Pasayat, Bhaskar Bhowmick, Kiran Fernandes, Manoj Kumar Tiwari
The air cargo sector dominates a significant part of the logistics industry due to the fastest shipping and fewer physical barriers, despite being an expensive mode of transportation. Due to the involvement of multiple factors, the risk associated with this sector is immense, which has been studied by many researchers worldwide to overcome the significant challenges (Rodríguez-Sanz et al. 2019). While ensuring transport risk is the foremost challenge facing the air cargo sector, different researchers (Han, Knott, and Egbelu 2007; Ross, Jayaraman, and Robinson 2010; Zúñiga, Piera, and Narciso 2011; Chan et al. 2014; Pathak, Thakur, and Rahman 2019; Tsolakis et al. 2021) closely examine the shipping process to reduce risk factors. Flight delays caused by system congestion and other reasons have been a constant source of business losses and monetary deprivation in the aviation industry in the past few years (Archetti and Peirano 2019). The concept of various risks in air transport operations has been investigated by, Choi et al. (2019), and Neal and Koo (2020), focusing on the commercial and safety risks. Flight departure delay has been estimated by Tu, Ball, and Jank (2008) to solve the disparity between the expected time of departure and the real-time of departure. Metzger et al. (2015a) demonstrated the potential of predictive monitoring in the air cargo industry, and as a solution to increase business profitability and sustainability, a new cloud and services-based collaboration and convergence model have been proposed. The authors also studied risk management in the air cargo sector and evaluated the strategies that will benefit the shippers and the forwarders. A study on perishable air cargo has been conducted by Azadian, Murat, and Chinnam (2012), and a framework is proposed to account for the real-time information inaccuracy. Shang, Dunson, and Song (2017) and Wen et al. (2019) also focused on air transport risk considering the delay in shipment as a significant factor and solved their models using different solution approaches.