• The Korean Journal of Air & Space Law and Policy
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• v.35 no.3
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• pp.39-63
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• 2020

This paper reviews the Interpretative Guidelines on EU passenger rights regulations in the context of the developing situation with COVID-19 of EU commission. To enlighten the obscurity and to mitigate the economic impacts of the COVID-19, European Commission has published "Interpretative Guidelines on EU passenger rights regulations in the context of the developing situation with Covid-19" on March 18, 2020. The Guideline essentially aims to create a coherent system of rules to assist the passengers, industry and national authorities overall under the unprecedented circumstances across the European Union. To do so, the Guideline is drafted to cover the rights of passengers travelling by air, rail, ship or bus/coach, maritime and inland waterways, as well as the corresponding obligations for carriers. From an aviation industry focused perspective, by referencing the Regulation (EC) numbered 261/2004, the Guideline specifically applies to cancellation and delay in flights which are seen as the dark spots for the air carriers concerning potential burdens.

• Journal of the Korean Society for Railway
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• v.7 no.1
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• pp.9-13
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• 2004

Railway passenger demand forecasts may be used directly, or as inputs to other optimization models use them to produce estimates of other activities. The optimization models require demand forecasts at the most detailed level. In this environment exponential smoothing forecasting methods such as Holt-Winters are appropriate because it is simple and inexpensive in terms of computation. There are several initialization methods for Holt-Winters Model. The purpose of this paper is to compare the initialization methods for Holt-Winters model.

• Journal of Korean Society of Transportation
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• v.31 no.3
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• pp.3-18
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• 2013

This study develops a forecasting method to estimate air cargo demand from ICN(Incheon International Airport) to all airports in EU with Seasonal Autoregressive Integrated Moving Average (SARIMA) Model using volumes from the first quarter of 2000 to the fourth quarter of 2009. This paper shows the superiority of SARIMA Model by comparing the forecasting accuracy of SARIMA with that of other ARIMA (Autoregressive Integrated Moving Average) models. Given that very few papers and researches focuses on air route, this paper will be helpful to researchers concerned with air cargo.

• Journal of Korean Society of Transportation
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• v.23 no.7 s.85
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• pp.181-190
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• 2005

The time required for airport process is considered more important as the airports are becoming bigger. International Civil Aviation Organization mattes this international standards and recommends not to exceed it. The passenger forecasting model is developed to predict the number of passengers at the check-in counter, and the area of formalities for departure and entry. In case of forecasting the number of outbound-passengers. the patterns of show-up lead time(SLT) at the check-in counter and lag time from check-in counter to the area of departure formalities are modeled in terms of time. On the other hand, the matter of the choice of check-in counters and areas of departure formalities are modeled in terms of space. In case of forecasting the number of inbound-passengers and transfer passengers, the time of airplane movement from arrival to block on at the gate and the time of passengers required from gate to the area of formalities for entry are modeled in terms of time. While the matter of the choice of gates and the areas of formalities for entry are modeled in terms of space. The average error of forecasting outbound-passengers and inbound-passengers is respectively 15% and 10%, which are considered excellent with the 5% error of passenger reservation information as input data. Through the development of passenger forecasting models, we assure we could provide passengers with valuable service because we allocate resource such as employees and equipments according to the degree of concentration of passengers.

• Journal of Korean Society of Transportation
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• v.26 no.1
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• pp.51-63
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• 2008

Jeju-Mainland demand for air passenger is variated by the season because most of the demands stem from the leisure travel. This research is to estimate the econometrics demand models(A simple time series model and the partial adjustment model) and elasticities of each models for the Jeju-Mainland domestic routes air travel market using the time series aggregate data between the year 1996 and 2005. As the result of estimating, income elasticity was evaluated to be elastic(1.55) and fare elasticity was inelastic(-0.49${\sim}$-0.59) for A simple time series models. In the partial adjustment model's case, income elasticity was evaluated to be inelastic(0.51) in short-run whereas it was evaluated to be elastic(1.88) in long-run. Fare elasticity was evaluated to be inelastic in short-run(high-demand season: -0.13, slack season: -0.20) and long-run(high-demand season: -0.48, slack season: -0.72).

• Journal of Korean Society of Transportation
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• v.18 no.1
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• pp.27-34
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• 2000

This study analyzes the price elasticities of airline Passenger demand through the 'Stated Preference' technique which uses survey data. Because the domestic airfare has been regulated by the government. it is not easy to derive Price elasticity through the usual regression analysis with aggregate data and thus a special methodology is required for elasticity estimation. Therefore, in this study we estimated the Price elasticities of domestic air passenger demand and the modal share change rates to the alternative modes with logit model and sample enumeration method, by analyzing the survey data on air Passengers' demand behavior about the mode choice between air-rail. air-bus, and air-car. As the results, the estimated price elasticities are in the range of -0.6~-0.9, and rail is mainly chosen as an alternative mode. bus is chosen Partly, and car is barely used.

• 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.

• Journal of Korea Port Economic Association
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• v.33 no.1
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• pp.31-46
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• 2017

With an increases in income levels and the establishment of a five-day workweek, the number of passengers using international passenger terminals around the world continues to grow every year. However, previous researches on port sector have focused on cargo, and neglected the study on the passenger attraction strategy of the international passenger terminal. Maximizing passenger attraction strategy of the international passenger terminal requires establishing and operating the port marketing strategy, which reflects port characteristics and the tourism marketing strategy, which reflects the hinterland characteristics in an integrated approach. Therefore, the study presents a marketing mix strategy for Daesan International Passenger Terminal based on existing literatures, and a tourism marketing strategy for Seosan city based on the "6A" factor. Recommendations for the Daesan Port include the grand image improvement strategy of Seosan city, utilization of marine tourism resources and development of various tourism products linked to the neighboring areas.

• Journal of Korean Society of Transportation
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• v.22 no.1 s.72
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• pp.19-30
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• 2004

Once baggage demand of passengers is forecast, BHS requirements must be analyzed, i.e., the number of originating/transferring/terminating bags to be handled, the number of conveyor lines to be installed, the number of containers for baggage make-up, the number of claim devices for baggage claim, and so on. Therefore, the determination of the baggage traffic volume is one of the most important analysis components for the airport design. Accordingly, this research proposes time-based distribution table models in order to accurately estimate BHS requirements to obtain design criteria in airport design phase. As the BHS requirements are ascertained, related requirements of the facilities can be determined by applying actual specifications of devices, i.e., throughput. This research found that the proposed mathematical model gives a good reflection of IIA (Incheon International Airport)'s operational condition. That means the model provides apparent reliability and feasibility. Furthermore, the specifications of devices are the newest figures. This fact supports that the research provides more effcient and reliable results.

• 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.