• Asia-Pacific Journal of Business
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• 제15권1호
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• pp.239-256
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• 2024

Purpose - The purpose of this study was to examine the main determinants of the gap between housing demand and house affordability. Design/methodology/approach - This study used the micro-level data of 60,043 households from Korea Housing-Finance Corporation by covering the period 2011 to 2022. Findings - First, the trend of general housing demand showed a higher figure in the future demand than in current demand. And such a tendency showed in all types of households, a relative young, low income, and single households. In the case of current housing demand, it has increased by 2022 from the beginning of 2013, while the future demand has rapidly increased from 2020. Second, although the house affordability showed a higher figure in current housing demand by 2019, its trend changed to be higher in future housing demand from 2020 by a rapid decreasing affordbility in current demand. In the case of young householders, the current house affordability was higher than that of future. The figure of low income householders was below 1 point in both periods, and house affordability of single householders showed a similar level in both periods. which showed over 1 point. Third, financial regulation on housing markets induced th widening of the gap between housing demand and house affordability, and such a trend is much atronger in the future(potential) gap of demand and affordability. More specifically, the strengthen financial regulation leaded to the widening of the gap in all types of households, a relative young, low income, and single households. Research implications or Originality - The effect of financial regulation is necessary to consider under the features of each households.

• Journal of Korea Port Economic Association
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• 제37권1호
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• pp.71-85
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• 2021

A variety of methods have been proposed through a number of studies on sophisticated demand forecasting models that can reduce logistics costs. These studies mainly determine the applicable demand forecasting model based on the pattern of demand quantity and try to judge the accuracy of the model through statistical verification. Demand patterns can be broadly divided into regularity and irregularity. A regular pattern means that the order is regular and the order quantity is constant. In this case, predicting demand mainly through regression model or time series model was used. However, this demand is called "intermittent demand" when irregular and fluctuating amount of order quantity is large, and there is a high possibility of error in demand prediction with existing regression model or time series model. For items that show intermittent demand, predicting demand is mainly done using Croston or HOLTS. In this study, we analyze the demand patterns of various items of air cargo with intermittent patterns and apply the most appropriate model to predict and verify the demand. In this process, intermittent optimal demand forecasting model of air cargo is proposed by analyzing the fit of various models of air cargo by item and region.

• Magazine of the Korean Society of Agricultural Engineers
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• 제43권1호
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• pp.53-65
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• 2001

To estimate agricultural water demand, many factors such as weather, crops, soil, cultivation method, crop coefficient and cultivation area, etc. must be considered. But it is not easy to estimate water demand in consideration of these factors, which are variable according to growth stage and regional environment. This study provides estimation system for agricultural water demand(ESAD) in order to estimate water demand easily and accurately, and arranges all factors needed for water demand estimation. This study identifies the application of estimation system for agricultural water demand with the data observed in the other studies, and analyzes nationwide agricultural water demand. The results are as follows. 1) The practice of different rice cultivation in the paddy field resulted in different water demands. Water depth and infiltration ratio in paddy are the most important factors to estimate water demand. The water depths in paddy simulated by ESAD is very similar to the observed ones. 2) Water demand of upland crops varies with the crops, soil, etc.. Effective rainfall estimated by daily routing of soil moisture varies according to the crops, soil, and effective soil zone(root depth). As crop root become grown, effective rainfall and an amount of irrigation water has been increased. 3) The current unit water demand of upland crops applied as 500mm or 550mm to estimate water demand does not reflect the differences caused by the crops, regional surrounding, weather condition, etc. Results from ESAD for the estimation of water demand of upland crops show that ESAD can simulate the actual field conditions reasonably because it simulates the actual irrigation practices with the daily routing of soil moisture.

• 공원문화
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• 통권26호
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• pp.26-32
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• 1984

There have been few researches on the factors affecting forest recreation demand and demand for and value of forest recreation in Korea. This study has three main objectives as follows; First, to introduce the nature of recreation demand, the factors affecting forest recreation demand, and the methods of measuring demand for and benefits from forest recreation by reviewing related literatures. Secondly, to investigate the visitors' characteristics, patterns of recreation activities, and their attitudes for the recreation environments at the Deogyu National Park through interviewing them with the questionaire. Thirdly, to estimate the demand for and benefits of forest recreation at the National Park by Travel Cost Method. The survey was dealt by three trained interviewers at the enterance of the park for 5 days from September 26 to October 10, 1982. The 430 respondents were sampled randomly among 9,391 visitors with 4.6% of sampling rate. As the results, the study revealed that most of visitors to Deogyu National Park were from urban areas and belonged to the intermediate-upper income classes, and that most of them traveled more than 250 km or 4 hours to the site from their origins. And more respondents answered that the recreation environments of the cite were more or less better than other recreation areas. From the date of travel distances and participation rates of 13 cities or counties, the demand schedule of forest recreation at the National Park was established. The estimated equation of total experience demand curve is; Log $VR_i$ 2.6353 – 1.021 Log $D_i$ $R^2=0.9451$ where, $VR_i$ $(%\times1000)$ = Participation rate of the ith origin $D_i$ (km) = Travel distance from the ith origin From the total experience demand curve, the demand curve of recreation resources was built by adding travel cost in distance (km). The regression equation of the recreation resources at the Nation park is; Log V = 4.0304 – 0.8167 Log D $R^2=0.9060$ From the demand schedule of recreation resources, the recreational bendfits of Deogyu National Park was estimated. The estimated bendfits to a visitor from the forest is equivalent to the travel cost of 2,372 km. The study also found out that the demand for recreation resources was less elastic than the demand for the total recreation experience at the Deogyu National Park.

• The Transactions of the Korean Institute of Electrical Engineers A
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• 제55권4호
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• pp.172-178
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• 2006

In this paper, an advanced demand clustering algorithm which can explore the planned maintenance outage of generators in changed electricity industry is proposed. The major contribution of this paper can be captured in the development of the long-term estimates for the generation availability considering planned maintenance outage. Two conflicting viewpoints, one of which is reliability-focused and the other is economy-focused, are incorporated in the development of estimates of maintenance outage based on the advanced demand clustering algorithm. Based on the advanced clustering algorithm, in each demand cluster, conventional effective outage of generators which conceptually capture maintenance and forced outage of generators, are newly defined in order to properly address the characteristic of the planned maintenance outage in changed electricity markets. First, initial market demand is classified into multiple demand clusters, which are defined by the effective outage rates of generators and by the inherent characteristic of the initial demand. Then, based on the advanced demand clustering algorithm, the planned maintenance outages and corresponding effective outages of generators are reevaluated. Finally, the conventional demand clusters are newly classified in order to reflect the improved effective outages of generation markets. We have found that the revision of the demand clusters can change the number of the initial demand clusters, which cannot be captured in the conventional demand clustering process. Therefore, it can be seen that electricity market situations, which can also be classified into several groups which show similar patterns, can be more accurately clustered. From this the fundamental characteristics of power systems can be more efficiently analyzed, for this advanced classification can be widely applicable to other technical problems in power systems such as generation scheduling, power flow analysis, price forecasts, and so on.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• 제21권6호
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• pp.70-86
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• 2022

An autonomous demand-responsive bus with mobility-on-demand service is an innovative transport compensating for the disadvantages of an autonomous bus and a demand-responsive bus with mobility-on-demand service. However, less attention has been paid to the quantitative impact assessment of the autonomous demand-responsive bus due to the technological complexity of the autonomous demand-responsive bus. This study simulates autonomous demand-responsive bus trips by reinforcement learning on a microscopic traffic simulation to quantify the impact of the autonomous demand-responsive bus. The Chungju campus of the Korea National University of Transportation is selected as a testbed. Simulation results show that the introduction of the autonomous demand-responsive bus can reduce the wait time of passengers, average control delay, and increase the traffic speed compared to the results with fixed route bus service. This study contributes to the quantitative evaluation of the autonomous demand-responsive bus.

• The Transactions of The Korean Institute of Electrical Engineers
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• 제57권1호
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• pp.25-33
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• 2008

This paper presents a new approach of a evaluation of location marginal prices(LMPs) considering demand response resources in the competitive electricity market. The stabilization of the electric power supply and demand balance has been one of the major important activities in electric power industry. Recently, much attention is paid to the demand-side resources which are responsive to incentives or time-varying prices and existing power system planning and operation activities are incorporated with the so-called demand response resources. In this paper, we first present an analytical method for calculation of LMPs considering demand response resources and then break down the LMPs into three components. In this study, we assume that Korean power system consists of two major regions, one which is the metropolitan and the other is non-metropolitan region. In the case study, we have considered several LMPs cases with different use of locational demand response resource and we can obtain a locational signal to demand response resources. Also, the economics of demand response resources are evaluated, compared with the increase of transmission line capacity and of generation capacity.

• Journal of Electrical Engineering and Technology
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• 제12권4호
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• pp.1427-1434
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• 2017

Since the late 2000s, there has been growing preparation in South Korea for a sudden reunification of South and North Korea. Particularly in the power industry field, thorough preparations for the construction of a power infrastructure after reunification are necessary. The first step is to estimate the peak load demand. In this paper, we suggest a new peak demand estimation methodology by integrating existing correlation analysis methods between economic indicators and power generation quantities with a power supply interruption model in consideration of power consumption patterns. Through this, the potential peak demand and actual peak demand of the Nation, which experiences power supply interruption can be estimated. For case studies on North Korea after reunification, the potential peak demand in 2015 was estimated at 5,189 MW, while the actual peak demand within the same year was recorded as 2,461 MW. The estimated potential peak demand can be utilized as an important factor when planning the construction of power system facilities in preparation for reunification.

• Environmental and Resource Economics Review
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• 제16권4호
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• pp.781-802
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• 2007

This study estimates a demand function for municipal water in Seoul area using a Stone-Geary functional form. The Stone-Geary model offers more precise estimates for price elasticity of water demand since it explicitly separates 'basic demand' which is not influenced by the price from 'economic demand' which depends on the price. Our results show that about 84% of the total water demand is the basic demand. The results suggest that the minimum consumption range m stepwise price system should be lowered from $30m^3$ to $15m^3$ per month.

• The Transactions of The Korean Institute of Electrical Engineers
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• 제63권11호
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• pp.1503-1510
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• 2014

This study organizes scenarios on the power supply plans and electricity load forecasts considering their uncertainties and estimates natural gas quantity for electricity generation, total electricity supply cost and air pollutant emission of each scenario. Also the analysis is performed to check the properness of government's natural gas demand forecast and the possibility of achieving the government's CO2 emission target with the current plan and other scenarios. In result, no scenario satisfies the government's CO2 emission target and the natural gas demand could be doubled to the government's forecast. As under-forecast of natural gas demand has caused the increased natural gas procurement cost, it is required to consider uncertainties of power plant construction plan and electricity demand forecast in forecasting the natural gas demand. In addition, it is found that CO2 emission target could be achieved by enlarging natural gas use and demand-side management without big increase of total costs.