Air Cargo Research Articles

The Impact of Cartel Dissolution on Prices: Evidence from the Air Cargo Cartel

The Impact of Cartel Dissolution on Prices: Evidence from the Air Cargo Cartel

Passenger and cargo throughput forecast of China's three major airports

China is a large civil aviation country in the world. With the continuous development of China's economy, the demand for air cargo transportation and passenger transportation is constantly rising in many cities. In this paper, the grey-forecast model GM (1,1) is adopted to forecast the passenger and cargo throughput of Beijing Capital(PEK), Shanghai Pudong(PVG) and Guangzhou Baiyun (CAN) Airport in the next few years. Based on the predicted data, we analyzed the future traffic development trend, and found out the advantages and disadvantages of the three airports. Finally, we put forward corresponding suggestions for the future development of the three airports in order to promote the sustainable development of the airports.

Price and Income Elasticity of the Demand in the Inbound Air Cargo Market - the Case of the Incheon International Airport-

Price and Income Elasticity of the Demand in the Inbound Air Cargo Market - the Case of the Incheon International Airport-

Design and analysis of hybrid electric multi-lobed airship for cargo transportation

Though a lot of curiosity has been developed towards a sustainable mode of cargo transportation, multi-lobed hybrid airships are touted to be a viable alternative to the conventional aircraft. The advantages of these Lighter Than Air (LTA) vehicles can further be boosted by incorporating a renewable source of energy. The requirements of high power in cargo airships and the current technological barriers call for the development of a hybrid propulsion system that can couple the best of both conventional and electric propulsion. The electric propulsion system is established by integrating solar arrays with fuel cells, which is then combined with conventional engines in a parallel power train architecture ensuring minimum transfer of energy and compact size. A solar irradiance model is adopted, to evaluate the amount of energy generated by the solar arrays installed over the airship envelope. A multi-lobed hybrid airship model is presented whose aerodynamic characteristics are obtained using computational fluid dynamic tools, which are then utilized to evaluate the power requirements through flight performance analysis. The hybrid propulsion system is then modified in accord with the power needs of the hybrid airship. Finally, detailed weight distribution between hybrid-powered and conventional hybrid-airship is presented displaying significant reduction in fuel weight of ∼350 kg due to the hybrid propulsion system.

Evaluating Freight Forwarders in the Air Cargo Industry

Freight forwarders are of great importance in the air cargo industry. As the cargo revenue constitutes an important source for airline companies, the evaluation of freight forwarders is vital for airlines’ success. This study employs DEMATEL method in order to prioritize the determined criteria for evaluating freight forwarders from the point of view of an airline. The calculated importance weights are used in an illustrative problem where the ranking of freight forwarders are obtained by employing the simple additive weighting method.

A hybrid ensemble learning-based prediction model to minimise delay in air cargo transport using bagging and stacking

Manufacturing productivity is inextricably linked to air freight handling for the global delivery of finished and semi-finished goods. In this article, our focus is to capture the transport risk associated with air freight which is the difference between the actual and the planned time of arrival of a shipment. To mitigate the time-related uncertainties, it is essential to predict the delays with adequate precision. Initially, data from a case study in the transportation and logistics sector were pre-processed and divided into categories based on the duration of the delays in various legs. Existing datasets are transformed into a series of features, followed by extracting important features using a decision tree-based algorithm. To predict the delay with maximum accuracy, we used an improved hybrid ensemble learning-based prediction model with bagging and stacking enabled by characteristics like time, flight schedule, and transport legs. We also calculated the dependency of accuracy on the point in time during business process execution is examined while predicting. Our results show all predictive methods consistently have a precision of at least 70 per cent, provided a lead-time of half the duration of the process. Consistently, the proposed model provides strategic and sustainable insights to decision-makers for cargo handling.

Bibliometric Analysis on Air Cargo Transportation for Two Decades

This study examines the scientific studies on Air Cargo via bibliometric analysis for two decades. The aim of study is determining the intellectual structure of the air cargo focused studies, reveal its evolutionary development in the area and identify the research gaps or topics for further studies may be needed. Dimensions database was used to obtain bibliometric data. “Air Cargo” OR “Air Freight” AND “Supply Chain Management” keyword combination was selected to define the primary focused area. “Commerce, Management and Tourism” or “Transportation and Freight Services” or “Business and Management” sub-categories defined as research content. 492 journal articles were analysed with bibliometric techniques and WosViewer software used for visualization. Analysis indicates that most of citied and majority of published articles had found place on interdisciplinary researches. Studies which are linked to production, management and international supply chain operations got more attention compared to focused solely on air cargo ones. Besides, USA, UK and China were determined as most productive countries and Cranfield University was ranked first among institutions. According to another result, two main clusters were also observed in collaborations between universities/institutions as Eastern and Western settled. International Journal of Physical Distribution and Logistics Management was determined the leader of journals. Only journal which focused solely aviation research is Journal of Air Transport Management. With rising trend and new developments in both aviation and supply chain management are foreseen that researches in the area will sustain its rising trend in the future. Especially environmental, e-trade, labour and other interdisciplinary issues will need to be examined deeply.

PROSPECTS AND PROBLEMS OF ROBOTIC DELIVERY OF THE LAST MILE. THE RELEVANCE OF THE PROBLEM AND THE CONCEPT OF THE SOLUTION. PART I.

The express delivery market in recent years has been growing at the level of 3-4%, and even in these conditions, not only is it not saturated, but the demand for it is growing. According to Oxford Economics, the growth of the air cargo market, which determines the volume of the express delivery market, accelerated at times up to 7% per year from 2013 to 2018 [1].
 The biggest changes took place in 2016-17 due to a technological breakthrough in the field of logistics with the introduction of services such as drone delivery, processing orders on the blockchain, calculation of the delivery mode using artificial intelligence, etc. It was expected that due to the growing demand on fast delivery guaranteed, the number of express delivery employees worldwide will grow to 4.5 million over the next few years. But the coronavirus pandemic has accelerated this process.
 In the study “The Future of Freight Transportation. How new technologies and new thinking can change the movement of goods”, presented by the international network of consulting companies Deloitte in 2017, states that carriers have already solved many of the problems associated with the transportation of goods. But the “last mile delivery” stage has remained limiting the development of the delivery service. At this stage, companies suffer losses due to the concentration of logistics, algorithmic and kinematic tasks that cannot be automated with modern means and technologies for replacing human labor.
 Consequently, the use of alternative, unconventional technologies at this stage is a key condition for the mass development of delivery.

Covid-19 and ISO9001 practices in air cargo transportation

Air cargo transportation in international trade stands out with its speed, reliability, safety, interaction with other transportation types, intensive use of information technologies, and global standards. During the Covid-19 pandemic, various negativities have emerged in air cargo transportation, as in many sectors. In this study, the difficulties caused by the Covid-19 pandemic in air cargo transportation business processes are evaluated within the scope of the ISO9001 Quality Management System standard so that they do not adversely affect the service quality. In this context, a case study was conducted on the implementation of the ISO 9001 Quality Management System standard in dealing with the difficulties arising from the pandemic in the cargo operations of an air transportation company. As a result of the implementation, the cargo ecosystem has been expanded, the carrying capacity has been increased, and the storage and cargo transportation efficiency has been increased by making use of information and communication technologies. Thus, it was easier to overcome the difficulties arising from the pandemic in the business processes of the company, and it was seen that sustainability in line with commercial expectations was ensured by rising to fifth place in world air cargo transportation in 2020.

Developing a model to optimise the cost of consolidated air freight considering the varying scenarios

ABSTRACT This paper considers a freight forwarder service problem by optimising the total shipping cost including inventory, processing, and transportation cost along with other miscellaneous costs such as trucking, storing, shipment planning, etc. by satisfying the constraints related to perishability, capacity, and reduced carbon emission. A mathematical model is developed for effective cargo handling to minimise the total cost incur while transporting goods via air cargo. To capture the key characteristics such as integration and consolidation of shipments, the delivery time of goods, scheduled time, volume/ weight of shipments, container temperature balance, emission reduction, the problem is solved using two variants of the evolutionary algorithm. For the dataset optimality has been validated using an exact method and sensitivity analysis is carried out to assist the impact of the number of shipments, agents, and destinations. Finally, a few managerial insights are drawn to discuss the benefits of this model in optimising cost.

The concept of national integrated risk management of aviation transport of Ukraine

In the context of modern conditions of air transport development, the concept of the national air transport integrated risk management system is substantiated. The concept is based on the definition of risk as the probability of occurrence of events in a complex of hazards of different nature, manifestations of safety vulnerabilities, consequences of past negative phenomena and explains the danger of the threat due to determination "maximum potential energy". Its remaining part is subsequently converted into kinetic energy, which affects the safety management system of air transport and has a negative impact on the sustainable development of the national economy as a whole. At the same time, priority attention is paid to the list of hazards by the criterion of deviation from the point of sustainable development, the importance of the impact of threats on the coefficient of elasticity, which allows more adequate assessment of hazards and respond to them. The classification of the main risks in the functioning of Ukrainian air transport has been developed, which includes the negative consequences of the COVID-19 pandemic, reduction of export-import operations in the economic downturn, number of flights and air passenger traffic, low congestion of airports and air infrastructure. Risks are identified in the following areas of operation and development of air transport in Ukraine: export-import operations, aviation infrastructure, air cargo, airports, air navigation service providers and general aviation, which allows early detection of risks and response to them. The concept was implemented by the State Aviation Regulation Department of the Ministry of Defense of Ukraine, the State Civil Aviation Agency of Azerbaijan, Almaty International Airport (Kazakhstan), Ukraine-Air Alliance, ICAO NAU Institute, Georgian Aviation Training Center (Georgia).

국제항공화물 공급망 보안 강화를 위한 보안과 세관의 협조체계 구축방안에 관한 연구

The International Civil Aviation Organization (ICAO) and the World Customs Organization (WCO) emphasize securing supply chain security through mutual cooperation between aviation security and customs by establishing a standardized security system by regulations, procedures and practices of international air cargo. Accordingly, in accordance with the Aviation Security Act, the known consignors system aims to secure cargo security before loading air cargo into the aircraft, while the customs AEO system is a public-private cooperation program that focuses on simplification of customs clearance procedures. These systems basically have the same purpose of effectively identifying high-risk cargo through a risk-based approach in international air cargo transportation and preventing risks in advance, and the content that a common basic standard for cargo security must be established is also similar. Therefore, it is necessary to establish a cooperation system by simplifying problems such as cumbersome and redundant authentication procedures and on-site verification through coordination of security requirements for mutual recognition between the two systems. As a result, it is necessary to establish a process for coordinating security and customs

머신러닝(Machine Learning) 기법을 활용한 제주국제공항의 운항 지연과의 상관관계 분석 및 지연 여부 예측모형 개발

Due to the recent rapid increase in passenger and cargo air transport demand, the capacity of Jeju International Airport has been approaching its limit. Even though in COVID-19 crisis which has started from Nov 2019, Jeju International Airport still suffers from strong demand in terms of air passenger and cargo transportation. However, it is an undeniable fact that the delay has also increased in Jeju International Airport. In this study, we analyze the correlation between weather and delayed departure operation based on both datum collected from the historical airline operation information and aviation weather statistics of Jeju International Airport. Adopting machine learning techniques, we then analyze weather condition Jeju International Airport and construct a delay prediction model. The model presented in this study is expected to play a useful role to predict aircraft departure delay and contribute to enhance aircraft operation efficiency and punctuality in the Jeju International Airport.

Global cargo gravitation model: airports matter for forecasts

The reliability of forecast models in the aviation sector is an important factor for industry and policy makers likewise. Expanding airports and fleets usually is a cost and time intensive process, and in order to maintain efficient market behavior, accurate anticipation of future demand and structural changes is attempted. We present a new quantitative approach to air cargo forecasts utilizing global airport-dyadic ICAO CASS data in general linearized airport fixed effects gravity models. While the strong explanatory power of our time invariant constant model has its natural difficulties predicting a variety of smaller indicators from previous models found in literature, we achieve very good results for selected time variant variables as gross domestic product per capita or kerosene prices. This makes our model a perfect tool for forecast simulations: extrapolating general economic forecast data provided by IHS Markit yield similar results to Boeing cargo forecasts (2020), with a slight decrease in the long run. Additionally, we do not need to split or control our sample in regional groups due to airport fixed effects, which makes the model on the other hand suitable for country- and airport level forecasts as well. The utilization of a large unique bilateral freight data set also helps answering classical gravity model questions in aviation: we track the distance effect to a matter of sample selection, finding no significant interaction following state of the art gravity econometrics.

Structural Efficiency and Robustness Evolution of the US Air Cargo Network from 1990 to 2019

As the US air cargo network (USACN) becomes a crucial part of the economy, it is pivotal to understand the structural evolution of the network and how it would be affected by unexpected events. We investigated the network structure, efficiency, and robustness of the USACN from 1990 to 2019 due to targeted attacks based on complex network theory from a dynamic and spatiotemporal perspective. Our results suggest that the USACN has enhanced robustness. Moreover, we find that attacks based on betweenness centrality are the most effective way to cause a collapse compared with attacks based on degree and closeness centrality. In addition, airports of the USACN have formed an increasing number of communities with geographical ties, and airports in the noncontiguous regions are more vulnerable than other communities in the lower 48 states. Further, we discover that the average path lengths have increased, and the overall efficiency has decreased from 0.7 to 0.4 due to the dependency of the hub-and-spoke structure. This paper complements previous studies on the dynamic structure evolution of air cargo networks through the lens of complex network theory with spatial-temporal data.

Will COVID-19 Threaten the Survival of the Airline Industry?

The pandemic causes social distancing and lockdown, which impedes consumer confidence and contracts the economy. Hence, this study analyzes the corona (COVID-19) impact on the airline industry revenues (ALR) and forecast by the vector autoregression (VAR) method. The results indicate that gross domestic product (GDP) and air cargo are the best predictors of ALR. The forecasting outcomes explore if ALR will decline and expect to back to pre-COVID-19 in 2023. Our results resemble both the V-shaped and U-shaped, which suggests slow gradual recovery with longer lockdown and border disclosure. The government can restore confidence building by providing economic stimulus packages and can encourage the airline to return to travel. Furthermore, softening the passenger rules concerning the refund of unflown ticket, reducing taxes, and reducing overflight taxes, all reduce the costs. Similarly, the mutually recognized global standards are crucial for effective execution, and any temporary measures taken by the government should have a clear exit strategy. The study major limitation includes the lack of relevant research and data availability.

Air transportation as a central component of remote community resilience in northern Ontario, Canada

ABSTRACT This research investigates the role air transportation plays in remote community resilience by examining air cargo delivery and flight operations in northern Ontario, Canada. Building off of the Disaster Resilience of Place (DROP) model for community resilience, we develop a high-level interdependency model that shows the interdependencies between community infrastructure systems and air transportation in the unique context of remote communities that rely on air transportation. Air transportation is the only mode of travel available year-round for the 26 remote communities studied. Alternative modes are seasonal (e.g., winter roads) and threatened by climate change. Analysing 6 years of cargo data highlights infrastructure interdependencies in energy, the built environment, and transportation systems. Flight operations data and semi-structured interviews with airline employees advance our understanding of air transportation infrastructure and operating challenges that impact flight reliability and ultimately remote community resilience.

A simulation approach for aircraft cargo loading considering weight and balance constraints

Air cargo transport is a growing industry in parallel with the growth in world trade and e-commerce. The global air cargo transport traffic getting busier, the importance of timely loading with minimum error is increasing. Therefore, digitalization of the air cargo loading process is needed. Assignment of Unit Load Devices (ULDs) to the specific positions on the freighter is performed by loadmasters by manual or semi-manual methods. This study aims to design a simulation model, which performs the ULD assignment automatically by simulating the loading process performed by the experienced loadmasters under the weight and balance constraints. The SEMMA (sample, explore, modify, model, assess) model is used while generating the simulation model. Fifty real-world loading orders were used to assess the performance of the model. The ULD assignment process by the simulation model and the loadmasters using semi-manual loading were compared with regard to time and center of gravity performance indicators. The results demonstrated that the simulation model can load all the given sets of ULDs, as efficiently as a loadmaster with a similar center of gravity in a shorter period of time. In conclusion, the proposed simulation model provides an efficient solution to the ULD assignment problem. However, the base model generated may be improved to address various real-world scenarios

Optimizing package express operations in China

We explore a novel optimization model to support the planning and operation of an air service network at a package express carrier in China. The model simultaneously considers ground and air transportation, company-owned aircraft capacity and belly capacity purchased on commercial aircraft, multiple service classes for packages, and packages becoming available throughout the day. A column generation based algorithm is devised to solve real-life problems with more than 650,000 timed origin-destination demands (packages), a service network with 150 hubs at airports, and an air cargo fleet of 60 aircraft of varying capacities. An extensive computational study shows the efficacy of the model and algorithm, and provides managerial insight. In particular, we see that considering ground transportation when designing an air service network is critical to improving operational efficiency and company profits as well as to extending service coverage. Furthermore, we find that in an environment with ample and reasonably-priced capacity on commercial aircraft, an air service network design based on single-flight shipments can be more effective than the commonly used star network design with multi-flight shipments.

How Blockchain and IoT-Based Decentralized System Solves ULD Rental Problem of Airlines

This study is devoted to ULD (Unit Load Device) rental among airlines and air cargo terminals at airports through data exchange. When airlines want to rent their partner airline's ULD, they use it after receiving data through its ULD inventory management system. This paper proposes a de-centralized ULD rental solution by combining blockchain technology and IoT (Internet of Things). The airline that wants to rent a partner airline's ULD checks the available inventory information before use and pays the amount according to the time of service. In addition, the smart contract specifies the remittance status to activate IoT on the ULD. Airlines that supply ULDs for partner airlines first create inventory information to provide services. Airlines that want to rent ULDs can check availability and remit rental costs according to usage time in cryptocurrency. The ULD rental service ends when the usage time is over. This ULD rental solution allows all airlines rent out their ULDs to partner airlines in real-time. Also, when a specific airport runs out of its own ULD, it is possible to overcome the difficulties of inventory shortage by renting the inventory of partner air-lines.