• International conference on construction engineering and project management
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• 2009.05a
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• pp.425-432
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• 2009

The construction industry has been a main pillar and serves as a regulator of the Hong Kong economy. Subsequently, the fluctuations in the level of construction output can induce significant rippling effects to the economy. The Asian Financial Crisis started in 1997 and the SARS outbreak in 2003 both introduced major challenges and impacts to the Hong Kong economy and consequently the construction sector. Such decline in the importance of construction has suggested a possible structural change in the sector. It is worth investigating the driving forces behind the construction demand and see if they have changed after the heavy impacts in the past decade. The above considerations have, therefore, been the motivation of the present study to model the Hong Kong residential construction demand through multiple regression technique which can identify the significant influencing factors to the residential demand. The residential construction is studied as it constitutes a significant portion of the total construction volume. The residential sector has great influence to the general economy of Hong Kong. It is found that the underlying market structure and the driving factors for Hong Kong residential demand before and after the Asian Economic Crisis and SARS outbreak are different, suggesting that the residential construction sector or even the larger construction industry may have undergone a major structural change as Hong Kong's economy approaches maturity. It is also observed that the past literatures on construction demand are mostly focusing on predicting demand under a stable economic environment. Hence, it is worth examining if it is possible to model during economic hardship when the residential sector fluctuate dramatically under different external impacts, such as the recent global financial tsunami.

• Environmental and Resource Economics Review
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• v.9 no.5
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• pp.925-945
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• 2000

This paper analyses the impact of energy-saving investment on Greenhouse gas emissions using a model of energy demand in Korea. SUR method was employed to estimate the demand equation. The econometric estimates provide information about the energy price divisia index, sector income, and energy saving-investment elasticities of energy demand. Except for energy price divisia, the elasticities of each variable are statistically significant. Also, the price and substitution elasticities of each energy price are similar to the results reported by the previous studies. The energy-saving investment is statistically significant and elasticities of each sector is inelastic. Using the coefficient of energy-saving investment and carbon transmission coefficient, the amount of reduction of energy demand and the reduction of carbon emissions can be estimated. The simulation is performed with the scenario that the energy-saving investment increase by 10~50%, keeping up with Equipment Investment Plan of 30% increase in energy-saving investment by 2000. The results show that the reduction of energy demand measured as 11.2% based upon 1995's level of the energy demand, in industrial sector. Accordingly, the carbon emissions will be reduced by 11.3% based upon 1995's level of the carbon emissions in industrial sector.

• Journal of Korean Society of Transportation
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• v.35 no.2
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• pp.91-104
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• 2017

In this study, we discuss the modeling of domestic transport sector using GCAM(Global Change Assessment Model). The GCAM is one of integrated assessment models widely used in internationally modeling community, and applied for the evaluation of IPCC 5th Report. Nevertheless, it is noted that there are a considerable number of problems in its application to domestic transport sector. First, the base year information of GCAM for detailed transportation service demand is found not consistent with national statistics. Second, the transportation sector simulation results do not properly reflect the past trends of service demand. Thus, the base year service demand is carefully matched with the detailed national statistics. In addition, the existing models were checked and modified so that the simulation results of service demand can accurately reflect past trends of national statistics. As a result, it is reported in detail how the current GCAM simulation results are corrected and how the trend of past transportation sector service demands is properly reflected. This study is expected to be useful as a basic tool for future scenario analysis for transportation policy, technology evaluation and greenhouse gas reduction measures.

• Journal of the Korean Operations Research and Management Science Society
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• v.8 no.2
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• pp.45-56
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• 1983

This paper presents a generalized fuel choice model in which restrictive constraints on cross-price coefficients as Baughman-Joskow-FEA Logit Model need not be imposed, but all demand elasticities are uniquely determined. The model is applied to estimating aggregate energy demand and fuel choices for the residential and commercial sector. The structural equations are estimated by a generalized least squares procedure using national-level EPB, KDI, BK, KRIS, MOER data for 1965 and 1980, and other related reports. The econometric results support the argument that “third-price” and “fourth-price” coefficients should not be constrained in estimating relative market share models. Furthermore, by using this fuel choice model, it has forecasted energy demands by fuel sources in, the residential and commercial sector until 1991. The results are turned out good estimates to compare with existing demands forecasted from other institutes.

• Environmental and Resource Economics Review
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• v.15 no.2
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• pp.297-318
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• 2006

Imported natural gas has been consumed by urban gas use and generation sector in Korea. The share of generating sector in total demand for natural gas is only 33% at 2000. This paper examines the potential of natural gas use in generation sector in the future. We build some hypothetical but realistic scenarios reflecting rapidly changing economic environment. We used standard programs for plant mix decision under those scenarios. We found that it is very likely to have high gas demand in the future, if we remove the cross-subsidizing price structure.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.6
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• pp.946-954
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• 2016

Energy industry is undergoing a paradigm shift in customer participation in the smartgrid. Customers traditionally consume electrical power. But nowadays not only do they generate electricity from private distributed generations, they can participate in demand response programs with their negawatt power which means a theoretical unit of power representing an amount of energy saved. Therefore development of decision-making criteria for electric load aggregation becomes a greater consideration as an amount of energy saved from demand response resources increases. This paper proposes load aggregators' decision-making criteria in the industrial sector where it made up the largest portion in demand response portfolio in order to assure reliability performance for demand response resources.

• Knowledge Management Research
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• v.6 no.2
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• pp.23-47
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• 2005

This study is performed the multinomial logistic regression with the officials needs level about a component of knowledge administration for drawing a demand estimation model in the knowledge administration activities. This study is not that an activity and domain of knowledge administration is to apply and to operate uniformly it in public sector, one is suggested an application with a demand diagnose of knowledge administration in order to saw a course of the knowledge administration programs to suit a function and role of public administration. A result of this study is that an activity and domain of the knowledge administration is different from a component of it namely, knowledge creating, knowledge organizing, knowledge sharing and distribution, knowledge utility, and knowledge store. And the officials individual characteristics, administration agency, a kind of business, and a function and role of work are different from demand of knowledge administration. Also, the practical use of KMS (knowledge management system) is not so high in public sector. Accordingly, the tools of knowledge administration will deliberate on a consolidation with the existing system in the device.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.5
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• pp.531-537
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• 1999

This paper presents the evaluaton procedures and the estimation model for DSM potential on commercial sector in Korea. In general, the evaluation process of the potential savings for DSM measures or programs consists of baseline electricity consumption forecast and potential evaluation such as technical potential(TP), economic potnetial(EP), and achievable potential(AP). A library of energy conservation measures applicable to each end-use or apparatus is developed, and energy savings and other factors are applied to the baseline demand estimates of consumption to produce potential savings estimates. The purpose of this paper is to establish the evaluation process of those DSM potential for commercial sector. In case study, we applied it to commercial sector for horizon years by end-use.

• Korean System Dynamics Review
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• v.3 no.1
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• pp.79-104
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• 2002

A system dynamics project is going on for forecasting automobile market in Korea. The project is made up of three stages, and the first stage has been wrapped up. As the first attempt, most efforts have been focused on the sound foundation rather than the exact forecast. The model consists of three sectors; the supply sector, the demand sector, and the population sector. The supply sector is a simple stock and flow diagrams representing the supply capacities of all automobile types. The major effort is made on the demand sector and the population sector. The demands are divided into three categories; replacement demands, new demands, and additional demands. The model applies “one car per person" concept, and assumes there will be no additional demands for a while. The replacement demands are calculated based on a simple stock and flow diagram. The new demands are calculated via Bass models; each bass model represents a diffusion for each age group. The population is divided into 101 age groups (age 0 to age 100). The model has been calibrated with past 10 year data (1990 - 1999), and tested for the next two years (2000-2001). The results ware acceptable, although a fine tuning is required. Now the second stage is going on, and most of efforts are made how to incorporate the economic and cultural factors.

• Environmental and Resource Economics Review
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• v.31 no.4
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• pp.849-864
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• 2022

In case of a specific sector being divided into sub-sectors, this study presents a process for estimating an input-output table, which is frequently used as basic data in fields of energy and environment economics. RAS method, which is universally used for this case, requires information on production, intermediate input sum, and intermediate demand sum for each sector in the new table. But in many cases, it is difficult to secure information on intermediate demand sum by sector. This study suggests a process for estimating a new input-output table without using information of intermediate demand sum in the case of sector separation, under the assumption that information of production value and intermediate input sum by sector are available. The key idea is that the values of many elements in the input-output table after disaggregation are the same as those in the table before disaggregation and that the sum of the elements after disaggregation, equals the values of the elements before disaggregation. The process of estimating the intemediate transaction matrix or the input coefficient matrix is presented by using these information instead of intermediate demand sum information. A small-scale simulation shows that the average error rate of the process proposed in this study is about 11.23% in estimating input coefficients, which is smaller than the 11.30% estimation error of RAS using the information of intermediate demand sum. However, since it is known in the literature that using additional information does not always improve estimation performance compared to not using it, additional research on various simulations is needed to apply the method of this study to reality.