air cargo demand management
167809126
Prioritisation of performance indicators in air cargo demand management: an insight from industry
Purpose Real operational data are used to optimise the performance measurement of air cargo capacity demand management at Virgin Atlantic Cargo by identifying the best KPIs from the range of outcome based KPIs in current use. Design/methodology/approach Intelligent fuzzy multi criteria methods are used to generate a ranking order of key outcome based performance indicators. More specifically, KPIs used by Virgin Atlantic Cargo are evaluated by experts against various output criteria. Intelligent fuzzy multi criteria group making decision making methodology is then applied to produce rankings. Findings A useful ranking order emerges from the study albeit with the important limitation that the paper looked solely at indices focussing exclusively on outcomes while ignoring behavioural complexity in the production of outcomes. Originality/value This paper offers a practical overview of the development of performance measures useful for air cargo capacity demand management.
Alexander R May Adrian Anslow Yuehua Wu Udechukwu Ojiako Maxwell Chipulu Alasdair J Marshall
54769547
Optimisation of key performance measures in air cargo demand management
This article sought to facilitate the optimisation of key performance measures utilised for demand management in air cargo operations. The focus was on the Revenue Management team at Virgin Atlantic Cargo and a fuzzy group decision making method was used. Utilising intelligent fuzzy multi criteria methods, the authors generated a ranking order of ten key outcome based performance indicators for Virgin Atlantic air cargo Revenue Management. The result of this industry driven study showed that for Air Cargo Revenue Management, 'Network Optimisation' represents a critical outcome based performance indicator. This collaborative study contributes to existing logistics management literature, especially in the area of Revenue Management, and it seeks to enhance Revenue Management practice. It also provides a platform for Air Cargo operators seeking to improve reliability values for their key performance indicators as a means of enhancing operational monitoring power.
Alexander R May Adrian Anslow Udechukwu Ojiako Yue Wu Alasdair J Marshall Maxwell Chipulu
107546266
Development of Discrete Event Simulation Model for Air Cargo Demand Management
In this study, a discrete event simulation model is developed to estimate load factors and the corresponding revenues under different pricing and dispatching policies. The model has been employed to forecast the inbound and the outbound air cargo demands of the major Northeastern Chinese cities, and the simulation results were compared to the actual demands obtained from real life airline operations. The statistical analysis confirms that the simulation model is able to provide accurate estimates for air cargo demands, and thus, the model may be employed to be a useful tool for air cargo demand management.
Kwang-Ryul Lee Ki-sung Hong Chulung Lee
55935656
Improving demand forecasting in the air cargo handling industry: a case study
ABSTRACT Air transportation plays a crucial role in the agile and dynamic environment of contemporary supply chains. This industry is characterised by high air cargo demand uncertainty, making forecasting extremely challenging. An in depth case study has been undertaken in order to explore and untangle the factors influencing demand forecasting and consequently to improve the operational performance of an air cargo handling company. It has been identified that in practice, the demand forecasting process does not provide the necessary level of accuracy, to effectively cope with the high demand uncertainty. This has a negative impact on a whole range of air cargo operations, but especially on the management of the workforce, which is the most expensive resource in the air cargo handling industry. Besides forecast inaccuracy, a range of additional hidden factors that affect operations management have been identified. A number of recommendations have been made to improve demand forecasting and workforce management.
Uriel Magana S Afshin Mansouri Virginia L M Spiegler
222092289
A matheuristic approach to the air cargo recovery problem under demand disruption
Air cargo transport is subject to unpredictable changes in expected demand, necessitating adjustments to itinerary planning to recover from such disruptions. We study a flight rescheduling problem to react to cargo demand disruptions in the short run. To increase flexibility, we consider two different cargo assignment policies. We propose a matheuristic approach to solve the problem that provides high quality solutions in a short computational time, based on column generation in which each subproblem is solved using an ad hoc heuristic. The approach is tested on demand disruption instances containing up to 75 air cargo orders with different penalty levels. The results show that the proposed method improves profit by 54% over the solution generated by a commercial MIP solver within a 1 h time limit, and by 15% over the solution with the routes fixed as in the original flight planning that only allows cargo to be re routed. We also show that there exist incremental benefits in the range of 3 5% by allowing cargo for a given order to be transported by various aircraft.
Journal of Air Transport Management
Felipe Delgado Julio Cesar Rojas Mora
25309675
Forecasting Air Cargo Demand in India
Air cargo industry in India has an important role in nation's trade and economy because of its significant contribution for the economic prosperity and well being of the country. Transporting goods via air except perishable or sensitive products, was once costly affair for the businesses to afford in frequent basis but due to the recent forces of globalization, liberalisation, privatisation and cut throat competition among the companies, have changed the face of global logistics and supply chain management throughout the world. In today's competitive environment, efficient logistics planning and managing supply chain in a most cost efficient manner such as initiating JIT (just in time) production and distribution approach that enables companies to reduce inventory carrying cost, are among the key factors for company's success and existence in local and international market and which in turn have made air cargo the most lucrative option than other mode of cargo transportation. This paper evaluates the growth potential of air cargo industry by analyzing the relationship between air cargo and major factors influencing cargo growth. Multiple linear regression analysis substantiates the strength of association between air freight, gross domestic product (GDP) foreign trade and jet fuel price. Furthermore to assess and examine growth potential of Indian air cargo industry, various forecasting techniques such as double exponential smoothing, trend analysis are carried out along with proposed econometric model of forecasting to derive results from non stationary data and finally the predictive ability of the models is assessed based on statistical criteria. I. INTRODUCTION Indian economy is one of the fastest growing economies in the world and fourth largest in terms of purchasing power parity. In order to maintain this sustainable economic development, country has to improve its transportation and infrastructure sector. Air transportation is indispensable for crossing international and national boundaries and consequently stimulates expansion of trade and economic growth. According to Boeing, India is the largest submarket in Southwest Asia, comprising about 63% of international flows in the region, and it possesses a vibrant domestic market as well (3) India's air cargo business is having much more potential in revenue generation than passenger business but still air cargo market is untapped. Statistics indicate that airlines spend more than 75% on transporting passengers, while only 25% is spent on cargo. According to the Airport Authority of India, the total cargo volume is expected to increase by 11.5% from 2007 08 to 2011 12 in which international cargo traffic expected to increase 12.1% of CAGR and domestic cargo by 10.1% CAGR during the same period. However the rising fuel cost is one of the major concerns which can dampen the growth as fuel accounts for 20 30% of the operating cost. The purpose of this study is to foresee the future demand and potential in Indian air cargo industry based on the historical data pattern and by critically examining the factors on which the growth of air cargo is dependent on. The study will help the industry, stakeholders in decision making and planning future action as well as for the government to implement policy that will drive the growth much faster.
Munmun Basak Martin West
216240436
Recovering from demand disruptions on an air cargo network
Abstract In this work we introduce the Air Cargo Schedule Recovery Problem (ACSRP) In this problem, a carrier airline has to reschedule flights and requests to adapt to last minute demand changes. We consider three different possible crew management policies that translate into three different way to evaluate the costs of deviating from the original schedule. We formulated the ACSRP as a mixed integer linear programming problem, and tested our implementation on 24 original schedules with up to 30 orders and 8 airports, and 4 different disruption scenarios for each one. Our results show that, against a benchmark recovery policy where only cargo is re routed, recovery can yield savings of roughly 10%
Felipe Delgado Cristobal Sirhan Mathias Katscher Homero Larrain
8926020
The effect of buy back policy in air cargo revenue management
In order to hedge against demand fluctuation after an intermediary has booked cargo space from an asset provider, buy back policy has been applied in revenue management. This practice allows both the asset provider and the intermediary to buy back or sell reserved capacity options. This study seeks to apply the financial buy back concept into the logistics domain by incorporating the Hellermann's capacity option model into the Black Scholes pricing model. The proposed model was verified by practical air cargo booking data. The experiment results showed that the buy back policy is capable of increasing the revenues from both the aspects of asset provider and intermediary. The developed model serves as a potential framework for the air cargo participants to handle their booking capacity during the period of order release and order execution.
2015 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)
Danping Lin Cedric K M Lee Jilin Yang
69357805
Regulator Perspective on Halal Air Cargo Warehouse Compliance
In establishing a successful Halal supply chain, Syariah compliancy has emerged as a key issue. Halal transport and Halal warehouse play a significant role in maintaining the integrity of the Halal products from point of origin to end of consumption. The escalating demand for halal food has encouraged warehouse operators to devise a new business plan to cater to the present business trend. Warehousing or storage is a critical factor where cross contamination may occur. As such, this study explored the Halal warehouse compliance from the perspective of regulators. This study adopted the qualitative approach by carrying out interview sessions, document review, and observation as the primary methods for data collection. The outcomes pointed out eight main factors that ascertain Halal warehouse compliance from the perspective of regulator, which are: management member, comprehensive training, Halal standard adoption, supplier, standard operating procedure (SOP) internal halal committee, documentation, and knowledge. This study appears to be a pioneer that probes into Halal warehouse compliance in Malaysia.
Muhamad Munzir Khairuddin Nor Aida Abdul Rahman Mohammad Fakhrulnizam Mohammad Zawiah Abdul Majid Fauzi Ahmad
13272340
Shipment Planning, Capacity Contracting, and Revenue Management in the Air Cargo Industry: A Literature Review
A wide variety of goods nowadays is transported by air, especially those of high value to weight ratio such as electronics and luxury goods and those perishable such as cut flowers and fish. The contemporary logistics practices that require shipping more frequently with smaller quantities also favor air transport. However, decision making in air cargo business is challenging. Air cargo demand is highly unstable and sensitive to global economic conditions. The shipping process typically involves many parties, such as carriers, forwarders, trucking companies, and terminals; poor coordination between them might cause considerable delay. Furthermore, the special characteristics such as demand imbalance and capacity 2 dimensinality also raise issues in both strategic and operational decisionmaking. Due to such challenges, practitioners and academic researcher have begun to apply operations research/management science (OR/MS) to the air cargo industry in recent years. In this paper, we review academic papers in three categories, namely, shipment planning, capacity contracting/booking, and revenue management. Other related literature and some possible future research directions are also discussed.
Jeff Hoi Yan Mui Kitty Yeung Wen He