Air cargo company selection under a state of chaos: An integrated bayesian BWM and WASPAS approach.

Depending on whether or not there is a chaotic condition, the outcomes of decision problems and the factors determining the outcomes of the problem may differ. Different criteria can be introduced for decision makers' preferences in chaotic conditions, and the importance levels of the criterion can fluctuate. Despite the fact that the COVID-19 epidemic has had an impact on the aviation industry, air cargo transportation has performed well during this time. From this perspective, the impact of chaotic events on the selection of an air freight firm is investigated in this study. With Multi-Criteria Decision Making (MCDM) methodologies, a new decision-making framework is proposed, which is an effective solution method for choice makers to finalize decision problems. The Bayesian BWM (Best-Worst) method, which is one of the new ways, is used to establish the criterion weights, while the WASPAS method is utilized to rank the air cargo businesses, due to the more sensitive reaction of the newly proposed methods. As a result, these two approaches are combined, and the ranking results are compared to the TOPSIS and COPRAS methods, with the outcomes examined. As a result, in a chaotic environment, the most essential consideration for selecting an air freight company appears to be economic criteria. (English) [ FROM AUTHOR] Karar problemlerinin sonuçları ve bu sonuçları etkileyen faktörler, herhangi bir kaos durumunun bulunup bulunmamasına göre değişiklik gösterebilmektedir. Kaos durumları altında, karar alıcıların tercihleri için farklı kriterler eklenebilmekte ve kriterlerin önem düzeyleri değişebilmektedir. COVID-19 pandemisi her alanda olduğu gibi havacılık sektörünü de etkilemiş olmasına rağmen hava kargo taşımacılığı bu dönemde güçlü bir performans göstermektedir. Bu noktadan hareketle, bu çalışmada kaos durumlarının hava kargo şirketi seçimine yansıması incelenmektedir. Karar vericilerin, karar problemlerini sonuçlandırmasında etkili bir çözüm yöntemi olan Çok Kriterli Karar Verme (ÇKKV) yöntemleri ile yeni bir karar verme çerçevesi önerilmektedir. Yeni önerilen yöntemlerin daha hassas yanıt vermesinden dolayı, hava kargo şirketi seçiminde etkili olan kriter ağırlıklarının belirlenmesinde yeni yöntemlerden olan Bayesian BWM (En Íyi-En Kötü) yöntemi kullanılırken, hava kargo şirketlerinin sıralanmasında ise WASPAS yöntemi kullanılmaktadır. Böylece bu iki yöntem bütünleştirilmekte ve aynı zamanda sıralama sonuçları TOPSIS ve COPRAS yöntemi ile kıyaslanarak sonuçlar analiz edilmektedir. Elde edilen sonuçlara göre, kaos ortamında hava kargo şirketi seçimi için en önemli kriter ekonomik kriterler olarak görünmektedir. (Turkish) [ FROM AUTHOR] Copyright of Journal of the Faculty of Engineering & Architecture of Gazi University / Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, is the property of Gazi University, Faculty of Engineering & Architecture and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Impact of COVID-19 on the Dutch Flower Trade-Logistics Node

Cut, cooled, packed, transported and traded all over the world, flowers represent a showcase of a worldwide integrated trade-logistics system. As one of the most perishable, vulnerable and time-critical products, speed is everything in harvesting, moving and trading of flowers. In the international trade of flowers and logistics of florticulture products, the Netherlands is the largest center of trade and logistics of flowers, taking a share of more than 40% in global cut flower export volume. When COVID-19 hit the world, this ever-moving system came to a full stop. What did this mean for the trade and logistics system? Which players were hit most? Did the crises change the system, just interrupt it or has it set the stage for developments already under way to strengthen and accelerate? This chapter presents and discusses the international position of the Dutch trade-logistics system as the most dynamic part of a worldwide flower industry. It sketches key trends in the industry over the last decade and draws a line towards possible post-COVID-19 scenarios for the worldwide flower industry and the international position of the Netherlands. The Dutch flower industry has shown incredible resilience to the external shock of COVID-19, but the crisis also has uncovered some weaknesses of the international flower industry. However, the chapter concludes that it is unlikely that these weaknesses will change the direction of developments in the sector, some of which already started to take shape in the 1970s. The chapter is based on pre-COVID-19 research and literature on the trade-logistics hub of the Netherlands, an analysis of trade and logistics data from around 2000 up to the first months of 2021, and existing economic scenarios for the flower industry and world trade. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.

Air cargo company selection under a state of chaos: An integrated bayesian BWM and WASPAS approach

Depending on whether or not there is a chaotic condition, the outcomes of decision problems and the factors determining the outcomes of the problem may differ. Different criteria can be introduced for decision makers' preferences in chaotic conditions, and the importance levels of the criterion can fluctuate. Despite the fact that the COVID-19 epidemic has had an impact on the aviation industry, air cargo transportation has performed well during this time. From this perspective, the impact of chaotic events on the selection of an air freight firm is investigated in this study. With Multi-Criteria Decision Making (MCDM) methodologies, a new decision-making framework is proposed, which is an effective solution method for choice makers to finalize decision problems. The Bayesian BWM (Best-Worst) method, which is one of the new ways, is used to establish the criterion weights, while the WASPAS method is utilized to rank the air cargo businesses, due to the more sensitive reaction of the newly proposed methods. As a result, these two approaches are combined, and the ranking results are compared to the TOPSIS and COPRAS methods, with the outcomes examined. As a result, in a chaotic environment, the most essential consideration for selecting an air freight company appears to be economic criteria. (English) [ FROM AUTHOR] Karar problemlerinin sonuçları ve bu sonuçları etkileyen faktörler, herhangi bir kaos durumunun bulunup bulunmamasına göre değişiklik gösterebilmektedir. Kaos durumları altında, karar alıcıların tercihleri için farklı kriterler eklenebilmekte ve kriterlerin önem düzeyleri değişebilmektedir. COVID-19 pandemisi her alanda olduğu gibi havacılık sektörünü de etkilemiş olmasına rağmen hava kargo taşımacılığı bu dönemde güçlü bir performans göstermektedir. Bu noktadan hareketle, bu çalışmada kaos durumlarının hava kargo şirketi seçimine yansıması incelenmektedir. Karar vericilerin, karar problemlerini sonuçlandırmasında etkili bir çözüm yöntemi olan Çok Kriterli Karar Verme (ÇKKV) yöntemleri ile yeni bir karar verme çerçevesi önerilmektedir. Yeni önerilen yöntemlerin daha hassas yanıt vermesinden dolayı, hava kargo şirketi seçiminde etkili olan kriter ağırlıklarının belirlenmesinde yeni yöntemlerden olan Bayesian BWM (En Íyi-En Kötü) yöntemi kullanılırken, hava kargo şirketlerinin sıralanmasında ise WASPAS yöntemi kullanılmaktadır. Böylece bu iki yöntem bütünleştirilmekte ve aynı zamanda sıralama sonuçları TOPSIS ve COPRAS yöntemi ile kıyaslanarak sonuçlar analiz edilmektedir. Elde edilen sonuçlara göre, kaos ortamında hava kargo şirketi seçimi için en önemli kriter ekonomik kriterler olarak görünmektedir. (Turkish) [ FROM AUTHOR] Copyright of Journal of the Faculty of Engineering & Architecture of Gazi University / Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, is the property of Gazi University, Faculty of Engineering & Architecture and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

The COVID-19 impacts on air transport – a case study of Hong Kong

The COVID-19 pandemic has hit the transport industry across the world since February 2020. Using data from the Hong Kong International Airport, we obtained seasonal autoregressive integrated moving average models for passenger movements and air cargo for 2005–2019. The COVID-19 impacts on passenger movements and air cargo were estimated based on differences between the predicted and actual monthly values in 2020. We found that the total number of passenger movements dropped by 86.2% while the total volume of air cargo dropped by 6% in 2020. Additionally, the GHG emission due to the use of aviation kerosene was 10.5 Mt of CO2-eq in 2020;down from 20.8 Mt of CO2-eq in 2019 (i.e., a drop of 49.5%). We also found the significant improvement of visibility at the airport – a rare upside of the COVID-19 pandemic. The COVID-19 pandemic has led to high unemployment rate in the transport and tourism-related sectors and has a negative economic impact on the aviation sector. Copyright © 2023 Inderscience Enterprises Ltd.

The impact of security oversight on air cargo price and demand

This paper examines the effect of security oversight on air cargo price and demand. We exploit variations in security oversight instituted by the International Civil Aviation Organization (ICAO). We estimate a simultaneous equation model using proprietary operations data from a major airline in South Korea over the period 2009–2013. This study explores the shipping-charge behavior of a service provider through a modeling approach that considers air cargo security. Our findings show that security oversight increases air cargo demand, controlling for the effect of price. Improving security measures increases the air cargo price, but the magnitude of this increase is small. Our results should help policymakers gauge the benefit of improved security and help airlines design an effective model to determine future air cargo shipping charges under high uncertainty to mitigate short- and long-term financial risks.

Air cargo company selection under a state of chaos: An integrated bayesian BWM and WASPAS approach.

Depending on whether or not there is a chaotic condition, the outcomes of decision problems and the factors determining the outcomes of the problem may differ. Different criteria can be introduced for decision makers' preferences in chaotic conditions, and the importance levels of the criterion can fluctuate. Despite the fact that the COVID-19 epidemic has had an impact on the aviation industry, air cargo transportation has performed well during this time. From this perspective, the impact of chaotic events on the selection of an air freight firm is investigated in this study. With Multi-Criteria Decision Making (MCDM) methodologies, a new decision-making framework is proposed, which is an effective solution method for choice makers to finalize decision problems. The Bayesian BWM (Best-Worst) method, which is one of the new ways, is used to establish the criterion weights, while the WASPAS method is utilized to rank the air cargo businesses, due to the more sensitive reaction of the newly proposed methods. As a result, these two approaches are combined, and the ranking results are compared to the TOPSIS and COPRAS methods, with the outcomes examined. As a result, in a chaotic environment, the most essential consideration for selecting an air freight company appears to be economic criteria. (English) [ FROM AUTHOR] Karar problemlerinin sonuçları ve bu sonuçları etkileyen faktörler, herhangi bir kaos durumunun bulunup bulunmamasına göre değişiklik gösterebilmektedir. Kaos durumları altında, karar alıcıların tercihleri için farklı kriterler eklenebilmekte ve kriterlerin önem düzeyleri değişebilmektedir. COVID-19 pandemisi her alanda olduğu gibi havacılık sektörünü de etkilemiş olmasına rağmen hava kargo taşımacılığı bu dönemde güçlü bir performans göstermektedir. Bu noktadan hareketle, bu çalışmada kaos durumlarının hava kargo şirketi seçimine yansıması incelenmektedir. Karar vericilerin, karar problemlerini sonuçlandırmasında etkili bir çözüm yöntemi olan Çok Kriterli Karar Verme (ÇKKV) yöntemleri ile yeni bir karar verme çerçevesi önerilmektedir. Yeni önerilen yöntemlerin daha hassas yanıt vermesinden dolayı, hava kargo şirketi seçiminde etkili olan kriter ağırlıklarının belirlenmesinde yeni yöntemlerden olan Bayesian BWM (En Íyi-En Kötü) yöntemi kullanılırken, hava kargo şirketlerinin sıralanmasında ise WASPAS yöntemi kullanılmaktadır. Böylece bu iki yöntem bütünleştirilmekte ve aynı zamanda sıralama sonuçları TOPSIS ve COPRAS yöntemi ile kıyaslanarak sonuçlar analiz edilmektedir. Elde edilen sonuçlara göre, kaos ortamında hava kargo şirketi seçimi için en önemli kriter ekonomik kriterler olarak görünmektedir. (Turkish) [ FROM AUTHOR] Copyright of Journal of the Faculty of Engineering & Architecture of Gazi University / Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, is the property of Gazi University, Faculty of Engineering & Architecture and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Air cargo company selection under a state of chaos: An integrated bayesian BWM and WASPAS approach.

Depending on whether or not there is a chaotic condition, the outcomes of decision problems and the factors determining the outcomes of the problem may differ. Different criteria can be introduced for decision makers' preferences in chaotic conditions, and the importance levels of the criterion can fluctuate. Despite the fact that the COVID-19 epidemic has had an impact on the aviation industry, air cargo transportation has performed well during this time. From this perspective, the impact of chaotic events on the selection of an air freight firm is investigated in this study. With Multi-Criteria Decision Making (MCDM) methodologies, a new decision-making framework is proposed, which is an effective solution method for choice makers to finalize decision problems. The Bayesian BWM (Best-Worst) method, which is one of the new ways, is used to establish the criterion weights, while the WASPAS method is utilized to rank the air cargo businesses, due to the more sensitive reaction of the newly proposed methods. As a result, these two approaches are combined, and the ranking results are compared to the TOPSIS and COPRAS methods, with the outcomes examined. As a result, in a chaotic environment, the most essential consideration for selecting an air freight company appears to be economic criteria. (English) [ FROM AUTHOR] Karar problemlerinin sonuçları ve bu sonuçları etkileyen faktörler, herhangi bir kaos durumunun bulunup bulunmamasına göre değişiklik gösterebilmektedir. Kaos durumları altında, karar alıcıların tercihleri için farklı kriterler eklenebilmekte ve kriterlerin önem düzeyleri değişebilmektedir. COVID-19 pandemisi her alanda olduğu gibi havacılık sektörünü de etkilemiş olmasına rağmen hava kargo taşımacılığı bu dönemde güçlü bir performans göstermektedir. Bu noktadan hareketle, bu çalışmada kaos durumlarının hava kargo şirketi seçimine yansıması incelenmektedir. Karar vericilerin, karar problemlerini sonuçlandırmasında etkili bir çözüm yöntemi olan Çok Kriterli Karar Verme (ÇKKV) yöntemleri ile yeni bir karar verme çerçevesi önerilmektedir. Yeni önerilen yöntemlerin daha hassas yanıt vermesinden dolayı, hava kargo şirketi seçiminde etkili olan kriter ağırlıklarının belirlenmesinde yeni yöntemlerden olan Bayesian BWM (En Íyi-En Kötü) yöntemi kullanılırken, hava kargo şirketlerinin sıralanmasında ise WASPAS yöntemi kullanılmaktadır. Böylece bu iki yöntem bütünleştirilmekte ve aynı zamanda sıralama sonuçları TOPSIS ve COPRAS yöntemi ile kıyaslanarak sonuçlar analiz edilmektedir. Elde edilen sonuçlara göre, kaos ortamında hava kargo şirketi seçimi için en önemli kriter ekonomik kriterler olarak görünmektedir. (Turkish) [ FROM AUTHOR] Copyright of Journal of the Faculty of Engineering & Architecture of Gazi University / Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, is the property of Gazi University, Faculty of Engineering & Architecture and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Air cargo company selection under a state of chaos: An integrated bayesian BWM and WASPAS approach

Depending on whether or not there is a chaotic condition, the outcomes of decision problems and the factors determining the outcomes of the problem may differ. Different criteria can be introduced for decision makers' preferences in chaotic conditions, and the importance levels of the criterion can fluctuate. Despite the fact that the COVID-19 epidemic has had an impact on the aviation industry, air cargo transportation has performed well during this time. From this perspective, the impact of chaotic events on the selection of an air freight firm is investigated in this study. With Multi-Criteria Decision Making (MCDM) methodologies, a new decision-making framework is proposed, which is an effective solution method for choice makers to finalize decision problems. The Bayesian BWM (Best-Worst) method, which is one of the new ways, is used to establish the criterion weights, while the WASPAS method is utilized to rank the air cargo businesses, due to the more sensitive reaction of the newly proposed methods. As a result, these two approaches are combined, and the ranking results are compared to the TOPSIS and COPRAS methods, with the outcomes examined. As a result, in a chaotic environment, the most essential consideration for selecting an air freight company appears to be economic criteria. © 2023 Gazi Universitesi Muhendislik-Mimarlik. All rights reserved.

Air cargo company selection under a state of chaos: An integrated bayesian BWM and WASPAS approach

Depending on whether or not there is a chaotic condition, the outcomes of decision problems and the factors determining the outcomes of the problem may differ. Different criteria can be introduced for decision makers' preferences in chaotic conditions, and the importance levels of the criterion can fluctuate. Despite the fact that the COVID-19 epidemic has had an impact on the aviation industry, air cargo transportation has performed well during this time. From this perspective, the impact of chaotic events on the selection of an air freight firm is investigated in this study. With Multi-Criteria Decision Making (MCDM) methodologies, a new decision-making framework is proposed, which is an effective solution method for choice makers to finalize decision problems. The Bayesian BWM (Best-Worst) method, which is one of the new ways, is used to establish the criterion weights, while the WASPAS method is utilized to rank the air cargo businesses, due to the more sensitive reaction of the newly proposed methods. As a result, these two approaches are combined, and the ranking results are compared to the TOPSIS and COPRAS methods, with the outcomes examined. As a result, in a chaotic environment, the most essential consideration for selecting an air freight company appears to be economic criteria. © 2023 Gazi Universitesi Muhendislik-Mimarlik. All rights reserved.

Air transportation encounters inflationary headwinds on its recovery from pandemic

Puranik et al discuss air transportation which encounters inflationary headwinds on its recovery from pandemic. A strong and growing global air travel demand, supported by the lifting of air travel restrictions in most countries, fueled the global airline industry's continued recovery this year from the impacts of covid-19. In June, the International Air Transport Association projected a total of 3.8 billion passengers for the year--83% of pre-pandemic levels--and a record high air cargo volume of more than 68 million tons, resulting in a global airline industry loss of $9.7 billion this year down from $42.1 billion in 2021. Only the North America region was expected to achieve profitability, with an estimated $8.8 billion profit. In October, member states of the International Civil Aviation Organization adopted the goal of achieving net-zero carbon emissions by 2050, a target that IATA member airlines had committed to in Oct 2021.

The impact of COVID-19 on air cargo logistics and supply chains

The impact of the COVID-19 pandemic on international air cargo logistics and supply chains has been, and remains, both complex and dynamic. Unlike the air passenger sector which witnessed demand reductions of over 95%, global air cargo demand proved more resilient and, in some markets, actually increased during the first wave of the pandemic in 2020. During this period, the sector witnessed a capacity shortfall in some markets as cargo could not be transported in the holds of scheduled passenger services as these flights had been suspended. As a result, a number of airline operators temporarily switched from providing passenger flights to cargo services by reconfiguring their aircraft to transport freight in the passenger cabin. This chapter examines COVID’s implications for global air cargo logistics and supply chains from a demand and supply side perspective. The chapter concludes by discussing the pandemic’s medium- to longer-term implications for the future provision and operation of air cargo logistics and supply chains.

Exploring factors affecting airport selection during the COVID-19 pandemic from air cargo carriers' perspective through the triangular fuzzy Dombi-Bonferroni BWM methodology.

The COVID-19 pandemic has created unexpected demand for air cargo in terms of rapid mobility of critical basic needs. Air cargo carriers aim to maximize their profits by taking advantage of the current demand and using their limited capacity in the right place. At this point, some of the qualifications of the airports in the places where demand plays a crucial role in this decision of the carriers. Thus, evaluating the factors considered in the airport selection for air cargo carriers during the COVID-19 period is curious. This study proposes a triangular fuzzy Dombi-Bonferroni best-worst method (BWM) framework with vast flexibility to establish the priority preferences of factors considered in selecting airports. The fuzzy BWM model becomes a superior decision support system by combining the Bonferroni mean operator's ability to consider interrelationships between attributes and the flexibility of the Dombi operator. In this sense, we highlight eighteen criteria based on five airport aspects: location, physical features, performance, costs, and reputation. Findings reveal that the foremost aspects are location and costs, whereas the most crucial factors are airport charges and handling charges. The study suggests that airports should follow a low-price policy for airport-related charges without compromising their sustainability to have a share of the increasing number of air cargo flights, especially during the COVID-19 period, when airline passenger flights are decreased. The study is crucial in deciding the strategy and policy of air cargo carriers and airports during the pandemic period.

Famine risk for millions in second locust wave

Cyril Ferrand, FAO resilience team leader for East Africa Swarms have “been damaging crops and pastures and crippling communities in the Greater Horn of Africa, Arabian Peninsula and Southwest Asia” since October, explained World Resources Institute climate programme research analyst Tina Huang. See PDF] FAO desert locust global forecast May-July 2020 The level of threat in West Africa could also change significantly in the next few weeks based on rainfall, winds and the locust situation in Arabia and East Africa, the FAO says. “The biggest challenge we are facing at the moment is the supply of pesticides and we have delays because global air freight has been reduced significantly,” says Cyril Ferrand, the FAO's resilience team leader for East Africa.

Design of a n+1 feeder aircraft for regional cargo airlines

This paper study suggests the specifications for high-efficiency, short-haul utility aircraft. This class of aircraft is used extensively in the multinational express package delivery service. Concurrent with the COVID 19 pandemic upending passenger travel, there has been a broad increase in the demand for air cargo. We forecast a need for more efficient short and medium range aircraft that offer route time savings and lower operating costs. Using current market planes designed with similar mission requirements, payloads, and engines – a general plane was created and optimized around the operating model of the present-day FedEx package delivery feeder fleet. The modification and optimization process was completed using a Model-Based-Systems-Engineering (MBSE) approach utilizing Phoenix Integration’s ModelCenter, Excel, MATLAB, and SOLIDWORKS. The final design achieved 40% improvement in fuel efficiency over the current fleet, and improvements in speed, payload, and range while in compliance with FAA regulations as a class E cargo aircraft certified under 14 CFR Part 25. © 2022, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

Air Cargo Transport development in Central and Eastern Europe and Baltic countries

The economic and social development in the Central and Eastern Europe (CEE) and Baltic countries in the last ten years, the admission of first 10 countries from this area in European Union has an important impact on the evolution of air transport in this area. We present the approach used by the airlines for choosing an airport for air cargo operation, step by step: chose of the region of operation, then the economic analysis of the region and of the airports, analysis of possible constraints for operations and individual performances of airport. The interest of airlines for an airport is generated by the growth of the county or of the region, the trade, the foreign investments and the labor market development, all indicators being analyzed in the paper. The diversification of the trade business model, the development of e-commerce has had an important impact on the development of cargo traffic in the world and of course also in CEE. The features of the air cargo transport market have had a great influence on governmental policies for airport cargo capacity development in CEE and in Baltic Countries. In order to provide airports with strategic information for building development strategies, this paper presents a comparative analysis of the evolution and demands of air cargo transport using external and internal benchmarking approach. The target group is represented by capitals' airports from Bulgaria, Croatia, Czech Republic, Estonia, Hungary, Latvia, Lithuania, Poland and Romania. © 2022 IEEE.

Optimisation of containerised air cargo forwarding plans considering a hub consolidation process with cargo loading

Air cargo plays an important role in supporting global supply chains;this becomes more vital when facing uncertainties in a crisis such as the COVID-19 pandemic. This motivates our study on air cargo forwarding plans, considering demand uncertainties and economic conditions. Cargos are placed into air containers based on weights and volumes, and then flown from regional collection points into a hub, for consolidation before transporting to onward destinations. Decisions are made in advance by cargo forwarders as to the containers to book, both in regions and in the hub, since airlines offer discounts on containers booked in advance;however, cargo quantities are uncertain when advance bookings are made. We develop a two-stage stochastic programming model, where the first stage determines both the quantities and types of air containers to book;the second stage deals with ordering any extra containers, at higher cost, or returning unused containers, as well as making loading and consolidation plans. The objective is to minimise the total expected costs. We then extend it into a multistage case and design a genetic algorithm as the solution method. Experimental results demonstrate that the proposed approaches provide a cost-efficient plan and responsive to demand as it arises. © 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

Implications of COVID-19 Pandemic on Air Cargo Transportation

Air cargo transportation is a key determinant in meeting the demand for perishable goods, which is highly dependent on timely imports of inputs and exports of semi-finished or finished products as part of global supply and production networks. Airports, which are the doors of countries to the outside world, have been closed to passenger transportation, but never to cargo planes. Because the entry of the goods needed by the countries is important in terms of raw materials and needs. The aim of this article is to show the current situation of air cargo transportation in the world during the pandemic period and to reveal the importance of air cargo transportation in terms of supply chain.

The Overall Cumulative Impact of Covid-19 and Brexit on European Supply Chains

Supply chains are usually perceived as a stable environment where only local or regionalised disruptions may happen, thus this paper focuses on the unpreceded situation where cumulative impact of Brexit, Covid-19, and Suez Canal blockage on supply chains. Each event has been analysed from different angles to provide a wider view and depiction of complexity of modern supply chains as well as their vulnerability when it comes to cumulative impacts of major disruptions. © 2021 IEEE.

MACHINE LEARNING FOR AFRICAN AIR FREIGHT

Air freight transportation plays a pivotal role in stimulating economic development and enabling supply chains growth. Air cargo drives global trade by carrying more than 6.7 $ trillion of goods’ value. Amid Covid Crisis, airfreight traffic remains essential in carrying nearly 1.5 million metric tons of medical equipment. Compared to normal demand pattern of 2019, air cargo volumes reached the levels of pre-pandemic period. In a dismal world air cargo market, African countries have continued to lead the international growth and reached by 2021 the highest pace of progress with 22.4% of growth. To sustain a positive pattern of development in Africa, it is relevant to develop a forecasting model using machine learning applications. Forecasting future market performance is essential for empowering planning processes. Nevertheless, only few researches have been developed for African countries. The main objective of this paper is to examine the driving factors of air cargo volume in Africa. For this purpose, we have applied machine learning algorithm to enhance the accuracy of data input and develop a reliable forecasting model. Findings and results emphasize that 28265774701 TY market of air cargo volume in Africa will contribute to GDP expansion by 13% over the next 20 years. This performance will help key stakeholders to improve African market and develop further prospects leading its potential growth © 2006-2021 Asian Research Publishing Network (ARPN). All rights reserved.

E-Commerce: Challenges That Lies Ahead of the Future Air Cargo Operation

Air cargo is growing exponentially and can become one of the main revenues for aviation sector. With the COVID-19 crisis, air cargo plays an important role for deliver much-needed products such as vaccine or medical supplies. Moreover, E-commerce is also affecting the growth of air cargo industry. The purpose of this study is to explore the current state of air cargo industry and explore the challenges that air cargo industry will meet after the pandemic ends. The result shows that capacity shortage is the most significant challenges that air cargo need to consider in order to cope with rapid demand. The second factor is speed which is also important since customers demanding for the fast delivery. © 2021 IEEE.