• Title/Summary/Keyword: Air Passenger Demand

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A Study on Air Demand Forecasting Using Multivariate Time Series Models (다변량 시계열 모형을 이용한 항공 수요 예측 연구)

  • Hur, Nam-Kyun;Jung, Jae-Yoon;Kim, Sahm
    • The Korean Journal of Applied Statistics
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    • v.22 no.5
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    • pp.1007-1017
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    • 2009
  • Forecasting for air demand such as passengers and freight has been one of the main interests for air industries. This research has mainly focus on the comparison the performance between the univariate seasonal ARIMA models and the multivariate time series models. In this paper, we used real data to predict demand on international passenger and freight. And multivariate time series models are better than the univariate models based on the accuracy criteria.

Analysis of Success Factors for Converting Passenger Aircrafts to Freighters Using AHP (AHP 기법을 활용한 여객기의 화물기로의 개조사업 성공요인 분석)

  • Gwang Cho, Cho;Hyun Cheol Lee
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.46 no.3
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    • pp.148-160
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    • 2023
  • The air transport industry is experiencing unprecedented fluctuations in aviation demand through the Covid-19 pandemic, and is more focused than ever on maintaining and generating business profitability. During the pandemic, demand for air cargo has soared, and the conversion business from passenger aircrafts to freighters(P2F) is drawing attention as a new business in the aviation maintenance industry. This study derives important factors to be considered in order to successfully carry out the P2F project through a wide range of cases and related literature, and analyzes the relative importance of each factor using the analytic hierarchy process. Through a survey of 33 aviation maintenance experts with more than 20 years of field experience, the importance of main factors and their sub factors was determined and implications were drawn. As a primary result, in order to succeed in the P2F project, the main factors were identified in the order of skill, finance, and location. The most important sub factors for each main factors were identified in order of securing airframe modification skill, securing infrastructure construction cost, and creating P2F business complex and district. The quantified success factors suggested the critical direction for the successful development of Korea's P2F business, and presented viable and specific business strategies and implementation plans for each factors.

A Study on the Prediction Analysis of Aviation Passenger Demand after Covid-19

  • Jin, Seong Hyun;Jeon, Seung Joon;Kim, Kyoung Eun
    • Journal of the Korean Society for Aviation and Aeronautics
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    • v.28 no.4
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    • pp.147-153
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    • 2020
  • This study analyzed the outlook for aviation demand for the recovery of the aviation industry, focusing on airlines facing difficulties in management due to the Covid-19 crisis. Although the timing of the recovery in aviation demand is uncertain at the moment, this study is based on prior research related to Covid-19 and forecasts by aviation specialists, and analyzed by SWOT technique to a group of aviation experts to derive and suggest implications for the prospects of aviation demand. Looking at the implications based on the analysis results, first, customer trust to prevent infection should be considered a top priority for recovering aviation demand. Second, promote reasonable air price policy. Finally, it seeks to try various research and analysis techniques to predict long-term aviation demand to overcome Covid-19.

A Study on the Temperature Variation Characteristics of Electric Car Depending on Passenger Number (승객 수에 따른 전동차 객실공간의 온도변화 특성 연구)

  • Hahm, Dae-Ju;Park, Duck-Shin;Nam, Seong-Won;Maeng, Hee-Young
    • Proceedings of the KSR Conference
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    • 2008.11b
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    • pp.393-399
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    • 2008
  • A Study has been conducted on the characteristics of temperature variation depending on passenger number that is measured in Bundang Line(From Sunleng To Bojong). As a basic study, the air quality of passenger room for the electric rail car is evaluated. Although ISO7730 recommends that the height of measuring points for the heat environment is to set at 0.1m, 0.6m, 1.1m and 1.7m respectively, temperature are measured at two points at 1.1m and 1.7m because of the difficulty to measure temperature of 0.1m height in rush hour. We compared the results of temperature variations between two stations in rush hour(07:56-08:41). In general, the capacity of a passenger car is designed for 160 persons, but over 280 persons often board on electric rail in rush hour. The temperature of room is adjusted from $22^{\circ}C$ to $24^{\circ}C$, but it is measured from $26^{\circ}C$ to $28^{\circ}C$ on average. Therefore, it shows that there are difference between the set temperature and measured one. This article suggests the ways of the time adjusting and air-conditioning to satisfy customer's demand and the guide line to design the optimum capacity of air-conditioner of the new electric rail car which will be introduced in the near future.

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Big Data-Based Air Demand Prediction for the Improvement of Airport Terminal Environment in Urban Area (도심권 공항 터미널 환경 개선을 위한 빅 데이터 기반의 항공수요예측)

  • Cho, Him-Chan;Kwag, Dong-gi;Bae, Jeong-hwan
    • Journal of the Korea Convergence Society
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    • v.10 no.8
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    • pp.165-170
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    • 2019
  • According to the statistics of the Ministry of Land Transport and Transportation in 2018, the average annual average number of air traffic users for has increased by 5.07% for domestic flights and 8.84% for international flights. Korea is facing a steady rise in demand from foreign tourists due to the Korean Wave. At the same time, a new lifestyle that values the quality of life of individuals is taking root, along with the emergence of LCC, and Korean tourists' overseas tours are also increasing, so improvement and expansion of domestic airport passenger terminals is urgently needed. it is important to develop a structured airport infrastructure by making efficient and accurate forecasts of aviation demand. in this study, based on the Big Data, long-term domestic and international demand forecasts for urban airports were conducted.. Domestic flights will see a decrease in the number of airport passengers after 2028, and international flights will continue to increase. It is imperative to improve and expand passenger terminals at domestic airports.

A Study of Legal Restrictions on International Air Cargo Services (국제항공화물운송의 법적 규제에 대한 고찰)

  • LEE, Jae-Woon
    • THE INTERNATIONAL COMMERCE & LAW REVIEW
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    • v.69
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    • pp.371-388
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    • 2016
  • International air transport for cargo services is a facilitator for various trade sectors and, by itself, an important service industry. Although international air cargo industry is expected to grow continuously, industry stakeholders complain about legal constraints in the industry and demand more liberalized regime. From its birth at the beginning of the 20th century, the airline industry was tightly regulated by governments with a strong tradition of protectionism. In the past few decades, however, protectionism in the airline industry has steadily declined. Indeed, the airline industry is largely in the process of liberalization. Interestingly, it has been easier to liberalize air cargo service than passenger service. Indeed, states have traditionally shown far more willingness to provide market access for foreign carriers carrying cargo than passengers. Given the impact of air cargo service in a state's wider economy and own characteristics of cargo services (i.e. air cargo traffic is inherently one-way, unlike passenger traffic, which tends to involve round trips), more liberalized approach is necessary for air cargo services. Among three approaches: bilateral, regional (block-based) and multilateral, it is desirable to adopt a multilateral treaty (a new multilateral all-cargo agreement) so as to harmonize and simplify complicated trade regulations on air cargo services.

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A Study on International Passenger and Freight Forecasting Using the Seasonal Multivariate Time Series Models (계절형 다변량 시계열 모형을 이용한 국제항공 여객 및 화물 수요예측에 관한 연구)

  • Yoon, Ji-Seong;Huh, Nam-Kyun;Kim, Sahm-Yong;Hur, Hee-Young
    • Communications for Statistical Applications and Methods
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    • v.17 no.3
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    • pp.473-481
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    • 2010
  • Forecasting for air demand such as international passengers and freight has been one of the main interests for air industries. This research has mainly focus on the comparison of the performances of the multivariate time series models. In this paper, we used real data such as exchange rates, oil prices and export amounts to predict the future demand on international passenger and freight.

Development of a Prediction Model and Correlation Analysis of Weather-induced Flight Delay at Jeju International Airport Using Machine Learning Techniques (머신러닝(Machine Learning) 기법을 활용한 제주국제공항의 운항 지연과의 상관관계 분석 및 지연 여부 예측모형 개발 - 기상을 중심으로 -)

  • Lee, Choongsub;Paing, Zin Min;Yeo, Hyemin;Kim, Dongsin;Baik, Hojong
    • Journal of the Korean Society for Aviation and Aeronautics
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    • v.29 no.4
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    • pp.1-20
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    • 2021
  • 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.

Analyzing the Impact of Pandemics on Air Passenger and Cargo Demands in South Korea

  • Jungtae Song;Irena Yosephine;Sungchan Jun;Chulung Lee
    • Journal of the Korean Society for Aviation and Aeronautics
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    • v.31 no.1
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    • pp.99-106
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    • 2023
  • 글로벌 팬데믹 사태는 항공 수요에 부정적인 영향을 끼치는 요소 중 하나다. 글로벌 팬데믹으로 인해 한국은 2020년과 2021년의 항공 승객 수가 2019년 대비 각각 68.1%와 47% 감소했다. 본 연구는 지난 20여년 동안 발생한 4대 팬데믹 특성을 분석, 전염병의 영향을 연구하는 것을 목표로 한다. SARS, H1N1, MERS 및 COVID-19의 발생기간 동안 한국의 항공 여객 및 화물 수요에 대한 실증 데이터를 활용하여 영향력을 분석한다. 또한 머신러닝 회귀 모델을 구축하여 향후 발생할 다른 전염병 대한 항공 수요를 예측하고자 한다. 연구 결과, 전염병이 항공 운항편수와 승객에 부정적인 영향을 미친다는 사실을 발견하였다. 반면화물 수송에는 긍정적인 영향을 미친다는 분석 결과를 도출하였다. 본 분석에 활용되는 회귀 모델은 팬데믹 기간 동안 항공수요를 예측하는 데 평균 86.8%의 기능을 보였다. 또한 본 연구는 특정 국가의 팬데믹 상황보다 전 세계적인 팬데믹 상황이 항공 운송 수요에 더 많은 영향을 미친다는 것을 보여준다.

Algorithm Development for Extract O/D of Air Passenger via Mobile Telecommunication Bigdata (모바일 통신 빅데이터 기반 항공교통이용자 O/D 추출 알고리즘 연구)

  • Bumchul Cho;Kihun Kwon
    • The Journal of Bigdata
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    • v.8 no.2
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    • pp.1-13
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    • 2023
  • Current analysis of air passengers mainly relies on statistical methods, but there are limitations in analyzing detailed aspects such as travel routes, number of regional passengers and airport access times. However, with the advancement of big data technology and revised three data acts, big data-based transportation analysis has become more active. Mobile communication data, which can precisely track the location of mobile phone terminals, can serve as valuable analytical data for transportation analysis. In this paper, we propose a air passenger Origin/Destination (O/D) extraction algorithm based on mobile communication data that overcomes the limitations of existing air transportation user analysis methods. The algorithm involves setting airport signal detection zones at each airport and extracting air passenger based on their base station connection history within these zones. By analyzing the base station connection data along the passenger's origin-destination paths, we estimate the entire travel route. For this paper, we extracted O/D information for both domestic and international air passengers at all domestic airports from January 2019 to December 2020. To compensate for errors caused by mobile communication service provider market shares, we applied a adjustment to correct the travel volume at a nationwide citizen level. Furthermore correlation analysis was performed on O/D data and aviation statistics data for air traffic users based on mobile communication data to verify the extracted data. Through this, there is a difference in the total amount (4.1 for domestic and 4.6 for international), but the correlation is high at 0.99, which is judged to be useful. The proposed algorithm in this paper enables a comprehensive and detailed analysis of air transportation users' travel behavior, regional/age group ratios, and can be utilized in various fields such as formulating airport-related policies and conducting regional market analysis.