• Proceedings of the KSR Conference
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• 2008.11b
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• pp.626-637
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• 2008

Although the amount of travel demand is a critical factor in a benefit-cost (B/C) analysis of railway investment, the travel demand changes especially for induced demand have not been considered. Therefore, the basic study of how to estimate travel demand changes after railway investment is worth investigating. This study reviews the methodologies for estimating diverted and induced demand generated after railway investment, and proposes appropriate approaches that will help railway planners to practically apply them in a case study. Further, the research stimulates the needs of consideration of the travel demand changes in the feasibility studies of railway planning.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.4
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• pp.59-66
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• 2020

In this study, we consider the problem of forecasting the number of inbound foreigners visiting Korea. Forecasting tourism demand is an essential decision to plan related facilities and staffs, thus many studies have been carried out, mainly focusing on the number of inbound or outbound tourists. In order to forecast tourism demand, we use a seasonal ARIMA (SARIMA) model, as well as a SARIMAX model which additionally comprises an exogenous variable affecting the dependent variable, i.e., tourism demand. For constructing the forecasting model, we use a search procedure that can be used to determine the values of the orders of the SARIMA and SARIMAX. For the exogenous variable, we introduce factors that could cause the tourism demand reduction, such as the 9/11 attack, the SARS and MERS epidemic, and the deployment of THAAD. In this study, we propose a procedure, called Measuring Impact on Demand (MID), where the impact of each factor on tourism demand is measured and the value of the exogenous variable corresponding to the factor is determined based on the measurement. To show the performance of the proposed forecasting method, an empirical analysis was conducted where the monthly number of foreign visitors in 2019 were forecasted. It was shown that the proposed method can find more accurate forecasts than other benchmarks in terms of the mean absolute percentage error (MAPE).

• Korean Journal of Artificial Intelligence
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• v.10 no.1
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• pp.27-32
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• 2022

As the need for eco-friendly transportation increases due to the deepening climate crisis, many local governments in Korea are introducing shared bicycles. Due to anxiety about public transportation after COVID-19, bicycles have firmly established themselves as the axis of daily transportation. The use of shared bicycles is spread, and the demand for bicycles is increasing by rental offices, but there are operational and management difficulties because the demand is managed under a limited budget. And unfortunately, user behavior results in a spatial imbalance of the bike inventory over time. So, in order to easily operate the maintenance of shared bicycles in Seoul, bicycles should be prepared in large quantities at a time of high demand and withdrawn at a low time. Therefore, in this study, by using machine learning, the linear regression algorithm and MS Azure ML are used to predict and analyze when demand is high. As a result of the analysis, the demand for bicycles in 2018 is on the rise compared to 2017, and the demand is lower in winter than in spring, summer, and fall. It can be judged that this linear regression-based prediction can reduce maintenance and management costs in a shared society and increase user convenience. In a further study, we will focus on shared bike routes by using GPS tracking systems. Through the data found, the route used by most people will be analyzed to derive the optimal route when installing a bicycle-only road.

• The Journal of Fisheries Business Administration
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• v.54 no.2
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• pp.31-44
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• 2023

This study examines the demand system of shrimp imported from top four countries and domestically produced by using AIDS (Almost Ideal Demand System) model. Top four import countries are Vietnam, Ecuador, China, and Malaysia based on the value of imports in 2021. As results of the analysis, the demand system of shrimp turn out to be below. First, the relationship of domestic shrimp and imported shrimp (Ecuadorian and Vietnamese) is identified as complements or substitutes depending on whether the income effect is considered. This result implies that imported shrimp supplements domestic supply against excess demand while homogeneous shrimp products competes with domestic shrimp in fish market. Second, the relationship among imported shrimps turned out to be both substitutes and complements. Especially, the Vietnamese shrimp is complementary with Chinese and Malaysian shrimp, but substitutes of Ecuadorian. It is assumed that adjoining Asian countries shares similar shrimp species and processing system which differentiates from Ecuadorian. Finally, the study included quarter as dummy variable and GDP as instrumental variable of expenditure in the model. The result confirmed that domestic shrimp is highly on demand during the main production season while imported shrimp is mainly demanded during the rest of the season.

• Korean Journal of Organic Agriculture
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• v.31 no.4
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• pp.343-355
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• 2023

Dairy processing experience tourism, that combines production, processing, and services, can be a good alternative to increase added value in Mongolian livestock industry. In addition, in order to successfully pursue this, it is necessary to first identify consumers' potential demand for the experience tourism and the factors affecting demand. Accordingly, this study estimated consumers' potential demand for dairy processing experience tourism using data from 758 people obtained through an online survey targeting Ulaanbaatar residents. As a result of the estimation, it was found that the variables that affect potential demand are the experience fees, average monthly household income, gender, age, arol consumption, and education level. The potential demand for dairy processing experience tourism was measured by multiplying the population of Ulaanbaatar by the estimated probability of accepting the experience tourism, and the total revenue was maximum at 32.303 million Tuk when the experience fee was 50,000 Tuk. The implications based on the analysis results are that, in order to promote participation in the experience tourism, it is necessary to promote it primarily to people with high average monthly household income, high level of education, younger age groups, and male. It can be said that preference is high and sufficient potential demand exists, but it is suggested that appropriate setting of experience fees is important.

• Journal of Korean Society of Water and Wastewater
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• v.22 no.1
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• pp.23-29
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• 2008

Throughout the analysis of field data from water distribution system, valid parameters were determined that can be included in the water service and design plan. This study investigates water consumption patterns to understand the variation of water-demand structures utilizing the pattern analysis of domestic purpose water. Water use data were collected by a public water resources management firm in Korea, Kwater, for 140 houses monitored during three years. Flow meters were installed at the faucet for drinking water, the shower booth, the laundry machine, bathroom sink, toilet, and garden faucet. Data was filtered using multiple physically meaningful criteria to improve analysis credibility. Mann Kendall and Spearman's Rho tests were used to carry out the analysis. Distinct factors of water consumption patterns can be determined for both increasing and decreasing trends of water use. Throughout the data analysis, the characterization of terms was classified and analyzed by the condition of the location of water-demand. Analysis of this data provide a physical basis for the parameter configuration of a reasonable design for a domestic water demand prediction model.

• Journal of Families and Better Life
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• v.27 no.3
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• pp.79-91
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• 2009

The purpose of this study is to understand the reduction of energy consumption and demand level for education relating to the reduction of energy consumption by middle school students. First, the perception of the reduction of energy consumption had a significant relationship with sex and grade. Second, the demand level for education relating to the reduction of energy consumption showed a significant relationship with only sex. Third, regression analysis on the influence of perception of the reduction of energy consumption showed a correlation between theperception of a reduction of energy consumption and the demand level for education relating to a reduction of energy consumption. The research suggests that students want an education that reduces energy consumption at school implemented during experience-centered and activity-centered discretionary activities, rather than duringtheory-centered curricular activities. It also suggests that overcoming limitations of space, that is, implementation of such education at various places besides school, and the application of teaching and teaming methods which use the internet and image media are more effective for education for the reduction of energy consumption.

• Journal of the Korean Institute of Rural Architecture
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• v.16 no.3
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• pp.9-18
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• 2014

Small and medium-sized local airports have suffered from chronic operating deficits due to many factors except for large airports in Incheon, Gimpo, Jeju and Gimhae. These small and medium-sized local airports have currently been degraded to inefficient airports handling the significantly lower airline demand than their carrying capacities. In this context, this study conducted a survey on the actual conditions of the airline demand in small and medium-sized local airports for the last 10 years after the opening of the Korea Train eXpress and investigated the causes and actual conditions of an increase and a decrease in the airline demand. In addition, it analyzed the functionality, convenience and economic feasibility, competition elements in comparison with other means of transportation, and the actual competitive conditions of local airports. It investigated facility improvements through a field visit for local airports and analyzed the performance rate of passenger demands and the use rate of terminal facilities according to a change in the airline demand. This study aimed to provide basic data in the architectural planning field, needed to establish a plan for the airport revitalization of local airports with the results of an analysis on the actual conditions of small and medium-sized local airports.

• Environmental Engineering Research
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• v.15 no.3
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• pp.135-140
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• 2010

With the various urban characteristics of each city, the existing water demand prediction, which uses average liter per capita day, cannot be used to achieve an accurate prediction as it fails to consider several variables. Thus, this study considered social and industrial factors of 164 local cities, in addition to population and other directly influential factors, and used main substance and cluster analyses to develop a more efficient water demand prediction model that considers unique localities of each city. After clustering, a multiple regression model was developed that proved that the $R^2$ value of the inclusive multiple regression model was 0.59; whereas, those of Clusters A and B were 0.62 and 0.74, respectively. Thus, the multiple regression model was considered more reasonable and valid than the inclusive multiple regression model. In summary, the water demand prediction model using principal component and cluster analyses as the standards to classify localities has a better modification coefficient than that of the inclusive multiple regression model, which does not consider localities.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.05a
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• pp.1116-1123
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• 2006

The methodological framework proposed in this paper addresses the strength of the applied Bass model by Mahajan and Muller(1996) that it reflects the substitution of next generations among products. Also this paper is to estimate and analyze the forecast of demand for products that do not exist in the marketplace. We forecast the sales of digital TV using estimated market share and data obtained by the face to face Interview. In this research, we use two methods to analyze the demand for Digital TV that are the forecasting the Demand for the Substitution and binary logit analysis. The logit analysis is to estimate the decisive factor of purchasing digital TV. The decisive factors are composed of purchasing plan, region, gender, TV price, contents, coverage, income, age, and TV program. We apply the model to South Korea's market for digital TV. The results show that (1) Income, region and TV price play a prominent part which is the decisive factor of purchasing digital TV. (2) We forecaste the demand of digital TV that will be demanded about 18 millions TVs in 2015