Air traffic forecast and its impact on runway capacity. A System Dynamics approach

Tascón, Diana C.; Olariaga, Óscar Díaz

doi:10.1016/j.jairtraman.2020.101946

Cited by 25 publications

(13 citation statements)

References 61 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The SD technique was particularly useful in studying the factors that have a direct effect on demand and forecasting air travel demand by developing a methodical model for future systems [11,[16][17][18][19][20][21][22].…”

Section: Forecasting With System Dynamics "Sd"mentioning

confidence: 99%

System Dynamic Model for Simulating Aviation Demand: Baghdad International Airport as a Case Study

Albayati¹,

Zehawi²

2022

MMEP

View full text Add to dashboard Cite

The aviation authorities have long been impacted by fluctuations in demand, which are often caused by the aviation industry's cyclical nature. It is affected mainly by many endogenous or exogenous variables. Despite that, the airport authorities and air carrier management make significant efforts to deal with fluctuating demand. This paper analyzed the factors influencing demand at Baghdad International Airport, based on the pertinent local socio-economic data such as "population size," "GDP," and "terrorism effect," as well as system-based factors related to aviation activities and airport characteristics for the past ten years, to develop a system dynamics simulation model by which the causes of fluctuation are highlighted in order to predict the magnitude and timing of the increment or decline in an offer to minimize losses to all parties in the airport system. The simulation results demonstrated very high goodness of fit with the actual data, producing R2 values of 0.865 and 0.86 for the departing and arriving passengers, respectively. Even though Iraq's unstable political and economic situation led to the interaction between the different demand drivers, external factors have a bigger effect on the country's need for air travel, causing demand shocks that take a long time to recover from.

show abstract

Section: Forecasting With System Dynamics "Sd"mentioning

confidence: 99%

System Dynamic Model for Simulating Aviation Demand: Baghdad International Airport as a Case Study

Albayati¹,

Zehawi²

2022

MMEP

View full text Add to dashboard Cite

show abstract

“…Through qualitative and quantitative methods, SD has been successfully applied to many different fields of studies (e.g., climate change, physics, engineering, environmental sciences, economics, management, etc.). In the field of transportation, some scholars have used SD to assess airport terminal performance [32,33], to evaluate the impact of future demand on the runway capacity of the airport [34], to analyze airlines' aging aircraft cost and develop a practical policy for maintenance cost reduction, to holistically represent and critically assess the different facets of MRO operations, and to help airlines analyze various decision scenarios [35]. Some scholars have used SD to study the sustainable development of civil aviation.…”

Section: Literature Reviewmentioning

confidence: 99%

Research on the Sustainable Development and Dynamic Capabilities of China’s Aircraft Leasing Industry Based on System Dynamics Theory

Lin

Zhu

et al. 2022

Sustainability

View full text Add to dashboard Cite

The Boeing 737 MAX crisis and COVID-19 pandemic have seriously influenced the development of China’s aircraft leasing industry in the past two years. This paper applies system dynamics theory to explore the sustainable development of China’s aircraft leasing industry. It analyses the dynamic mechanism and constructs a system dynamics model. Based on China’s macroeconomic data and historical data from the financial, aviation, and leasing industries, it aims to stimulate the development of China’s aircraft leasing industry in the next five years. Through sensitivity analysis, this research finds that changes in GDP growth have the most obvious impact on the sustainable development of China’s aircraft leasing industry. Reducing the average financing cost and the income tax rate of aircraft leasing companies, increasing their investment in talent, and controlling risk will increase the market share of China’s aircraft leasing companies and promote the development of the industry. However, increasing the number of aircraft leasing companies has little effect on market share. On this basis, this paper proposes policy recommendations to promote the sustainable development of China’s aircraft leasing industry.

show abstract

“…Jin et al (2020) proposes a hybrid approach for air passenger demand forecasting, which consists of variational mode decomposition (VMD), autoregressive moving average model (ARMA) and kernel extreme learning machine (KELM). Tascon and Olariaga (2021) seeks to evaluate the impact of demand forecasts on the management of runway capacity, taking Bogotá-El Dorado International Airport in Bogota, Colombia as a case study. The situation described was faced with the use of simulation under the system dynamics approach, to research the management of air transport.…”

Section: Background On Air Passenger Demand Forecastingmentioning

confidence: 99%

The chaos on U.S. domestic airline passenger demand forecasting caused by COVID-19

Jafari¹

2022

IJBFMI

View full text Add to dashboard Cite

Commercial aviation is a major contributor to the US economy, directly or indirectly generating approximately US$680 billion, or 4% of GDP, and supporting millions of jobs. Approximately 965 million passengers flew to US destinations in 2017 (https://rosap.ntl.bts.gov/view/dot/37861). Given the importance of the industry, accurate forecasting of air passenger demand is valuable, and the most sophisticated forecasting technologies can be applied to this endeavour. The ongoing COVID-19 crisis has had an unprecedented impact on air traffic. Effective forecast of passenger demand would benefit airlines to develop adequate recovery plans and prevent (or minimise) any catastrophe in handling passengers during and post pandemic. The purpose of this study is to investigate COVID-19's impact on the US domestic air passengers demand, identify the most influential features on air passenger demand, and design more accurate forecast models. In addition, we address a computational challenge in developing forecasting models due to the volatility of the recent data as a result of the COVID-19 crisis. We use both traditional and artificial intelligence methods and discuss their capabilities to handle the challenge.

show abstract

Air traffic forecast and its impact on runway capacity. A System Dynamics approach

Cited by 25 publications

References 61 publications

System Dynamic Model for Simulating Aviation Demand: Baghdad International Airport as a Case Study

System Dynamic Model for Simulating Aviation Demand: Baghdad International Airport as a Case Study

Research on the Sustainable Development and Dynamic Capabilities of China’s Aircraft Leasing Industry Based on System Dynamics Theory

The chaos on U.S. domestic airline passenger demand forecasting caused by COVID-19

Contact Info

Product

Resources

About