• International Journal of Highway Engineering
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• v.12 no.4
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• pp.93-100
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• 2010

Trip generation is the first step in the conventional four-step model and has great effects on overall demand forecasting, so accuracy really matters at this stage. A linear regression model is widely used as a current trip generation model for such plans as urban transportation and SOC facilities, assuming that the relationship between each socio-economic index and trip generation stays linear. But when rapid urban development or an urban planning structure has changed, socio-economic index data for trip estimation may be lacking to bring many errors in estimated trip. Hence, instead of assuming that a socio-economic index widely used for a general purpose, this study aims to develop a new trip generation model by type based on the market separation for the variables to reflect the characteristics of various zones. The study considered the various characteristics (land use, socio-economic) of zones to enhance the forecasting accuracy of a trip generation model, the first-step in forecasting transportation demands. For a market separation methodology to improve forecasting accuracy, data mining (CART) on the basis of trip generation was used along with a regression analysis. Findings of the study indicated as follows : First, the analysis of zone characteristics using the CART analysis showed that trip production was under the influence of socio-economic factors (men-women relative proportion, age group (22 to 29)), while trip attraction was affected by land use factors (the relative proportion of business facilities) and the socio-economic factor (the relative proportion of third industry workers). Second, model development by type showed as a result that trip generation coefficients revealed 0.977 to 0.987 (trip/person) for "production" 0.692 to 3.256 (trip/person) for "attraction", which brought the necessity for type classifications. Third, a measured verification was conducted, where "production" and "attraction" showed a higher suitability than the existing model. The trip generation model by type developed in this study, therefore, turned out to be superior to the existing one.

• Journal of Intelligence and Information Systems
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• v.27 no.4
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• pp.23-48
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• 2021

The Korean economy has achieved continuous economic growth for the past several decades thanks to the government's export strategy policy. This increase in exports is playing a leading role in driving Korea's economic growth by improving economic efficiency, creating jobs, and promoting technology development. Traditionally, the main factors affecting Korea's exports can be found from two perspectives: economic factors and industrial structural factors. First, economic factors are related to exchange rates and global economic fluctuations. The impact of the exchange rate on Korea's exports depends on the exchange rate level and exchange rate volatility. Global economic fluctuations affect global import demand, which is an absolute factor influencing Korea's exports. Second, industrial structural factors are unique characteristics that occur depending on industries or products, such as slow international division of labor, increased domestic substitution of certain imported goods by China, and changes in overseas production patterns of major export industries. Looking at the most recent studies related to global exchanges, several literatures show the importance of cultural aspects as well as economic and industrial structural factors. Therefore, this study attempted to develop a forecasting model by considering cultural factors along with economic and industrial structural factors in calculating the import volume of each country from Korea. In particular, this study approaches the influence of cultural factors on imports of Korean products from the perspective of PUSH-PULL framework. The PUSH dimension is a perspective that Korea develops and actively promotes its own brand and can be defined as the degree of interest in each country for Korean brands represented by K-POP, K-FOOD, and K-CULTURE. In addition, the PULL dimension is a perspective centered on the cultural and psychological characteristics of the people of each country. This can be defined as how much they are inclined to accept Korean Flow as each country's cultural code represented by the country's governance system, masculinity, risk avoidance, and short-term/long-term orientation. The unique feature of this study is that the proposed final prediction model can be selected based on Design Principles. The design principles we presented are as follows. 1) A model was developed to reflect interest in Korea and cultural characteristics through newly added data sources. 2) It was designed in a practical and convenient way so that the forecast value can be immediately recalled by inputting changes in economic factors, item code and country code. 3) In order to derive theoretically meaningful results, an algorithm was selected that can interpret the relationship between the input and the target variable. This study can suggest meaningful implications from the technical, economic and policy aspects, and is expected to make a meaningful contribution to the export support strategies of small and medium-sized enterprises by using the import forecasting model.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.2
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• pp.549-559
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• 2014

The rapid expansion of cities led to the shortage of housing in urban areas. The government compensated for this shortage through large scale residential developments that increased the housing supply. The supply of condominium apartments remains above 83% of the entire housing supply, and the proportion of apartments are at a steady increase, at about 50%. Due to the increase, illegally parked cars resulting from the shortage of parking spaces within the apartment complex have become increasingly problematic as they block the transit of emergency vehicles, and heighten the tension among neighboring residents in obtaining a parking space. Especially, the future residents are considered to plan the parking based on the estimated demand for parking. However, the parking unit method utilized to estimate the parking demand accounts for the exclusive use of space, which is believed to be far from the parking demands in reality. The reason for this discrepancy is that, as the number of households decrease, and area of exclusive space is expanded, the planned parking increases. On the other hand, when the number of households increase, and the area of exclusive space is reduced, the planned parking decreases, thus methods to recalculate the parking units based on estimated parking demand is an urgent concern. To estimate the parking units based on condominium apartments, this study first examined the existing research literature, and appointed the field of investigation to collect the necessary data. In addition, field study data and surveys collected and analyzed, in order to identify the problems underlying parking units, and problems regarding the current traffic impact assessment parking unit calculation method were deduced. Through identifying the influential factors on parking demand estimates, and performing a factorial analysis based on the collected data, the variables were selected in relation to the parking demand estimates, to develop the parking unit estimate model. Finally, through comparing and verifying the existing traffic impact assessment parking unit estimate against the newly developed model using collected data, a far more realistic parking unite estimate was suggested, reflecting the characteristics of the residents. The parking unit estimate model developed in this study is anticipated to serve as the guidelines for future parking lot legislature, as wel as the basis to provide a more realistic estimate of parking demands based on the resident characteristics of an apartment complex.

• Economic and Environmental Geology
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• v.42 no.2
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• pp.143-152
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• 2009

Recent raw material prices fluctuation has been unexpectedly high and that made Korean economic activities to be depressed. Because most raw material supply in Korea depends upon oversea imports, unexpected raw material price fluctuation affects Korean industrial economies through macroeconomic variables. So Korean government enforces some political measures such as demand management and the supply-security assurance as long-range policies, and reservation and general early warning system as short-range policies. In short-range policies, it is necessary to be expected short term fluctuation. Up to recently, there have been many researches and most of those researches use parametric methods or time series analyses. Because those methods and analyses often generate inadequate relations among variables, it is possible that some consistent variables are left out or the results are misunderstood. This study, therefore, is aim to mitigate those methodological problems and find the relatively appropriate model for economic explanation. So that, in this paper, by using non-parametric signal approach method mitigating some shortages of previous researches and forecasting properly short-range prices fluctuation of non-ferrous materials are presented empirically.

• Informatization Policy
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• v.21 no.2
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• pp.89-110
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• 2014

As a travel demand management and environmental policy, the government actively promotes alternative work arrangements such as telecommuting. Against this backdrop, several empirical studies, which aim to verify the benefits of telecommuting, have been recently conducted. Little consensus, however, exists with respect to the defining, measuring, and forecasting telecommuting, although these are fundamental basis of policy evaluation and academic research. As a fundamental research for analyzing telecommuting impacts, this paper reviews various definitions regarding telecommuting, examines telecommuting penetration and level of telecommuting through review of available survey data in Korea, and forecasts future penetration. The result suggests that current home-based telecommuting penetration and level of telecommuting is approximately 0.5 to 1.1% and 0.2 to 0.5%, respectively, and is approximately 0.2% and 0.1%, respectively, for the center-based telecommuting. In addition, shift-share analysis shows that home-based telecommuting penetration in the Seoul Metropolitan Area in 2020 will be 1.3%, not much different with the current value. Consequently, current telecommuting penetration is much lower than the value that is fed to us by the media (10~20%), and the future prospect is also much lower than the goal of government (30~45%); thus, we can conclude that government's goal of telecommuting promotion is difficult to meet if active encouragement policy will not be introduced.

• Journal of Korean Society of Transportation
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• v.26 no.4
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• pp.185-194
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• 2008

When forecasting demand for a new road, a select link analysis is usually used to understand the OD pairs that send trips along paths that use the selected link (i.e., the new road). These OD pairs and their associated volumes are listed in a select link analysis. However, there is no research about other methods to obtain these results, so experts are almost always dependent on select link analysis results to obtain these results. The purpose of this study is to propose a model with a different approach from select link analysis to obtain the previously mentioned results. Time and spatial characteristics of networks are used in this new approach. Select link analysis results are used as a comparison index for the results by the proposed model. Also, two case studies (interzonal trips and intracity trips) are performed to validate the significance of the model. Consequently, a correlation coefficient between the results by the proposed model and the comparison index shows high significance: 0.82.

• The Journal of Bigdata
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• v.6 no.1
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• pp.91-113
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• 2021

Despite the influence of real estate in the Korean asset market, it is not easy to predict market trends, and among them, apartments are not easy to predict because they are both residential spaces and contain investment properties. Factors affecting apartment prices vary and regional characteristics should also be considered. This study was conducted to compare the factors and characteristics that affect apartment prices in Seoul as a whole, 3 Gangnam districts, Nowon, Dobong, Gangbuk, Geumcheon, Gwanak and Guro districts and to understand the possibility of price prediction based on this. The analysis used machine learning algorithms such as neural networks, CHAID, linear regression, and random forests. The most important factor affecting the average selling price of all apartments in Seoul was the government's policy element, and easing policies such as easing transaction regulations and easing financial regulations were highly influential. In the case of the three Gangnam districts, the policy influence was low, and in the case of Gangnam-gu District, housing supply was the most important factor. On the other hand, 6 mid-lower-level districts saw government policies act as important variables and were commonly influenced by financial regulatory policies.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.2
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• pp.273-282
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• 2021

This study investigates for skills mismatching of the IT service sector in the flows of fast technology changes. It was conducted through an in-depth interview method for professional groups. There were differences in demand for skilled labor by business organizations and educators as providers of skilled labor. A five-point Likert scale was used. The degree of importance of 3.7 average point and the degree of satisfaction of 3.4 average point were responded for the set items in case of matching. In addition, the degree of importance of 3.79 average point and the satisfaction of 3.12 were responded in case of non-majored education students for IT. The skills desired from business organizations included multi-dimensional competencies and soft-skill items. For the reason of skills mismatching, business organizations presented ineffective specifications or divisions of the industrial manpower structure, and educational institutions selected the mismatching of time. Professional groups forecasted that the mismatching gap would expand in the future. To solve the gap, the participated professionals selected an industry-university institute collaboration course and gave an opinion to seek a method to foster manpower in the long-term perspective.

• Journal of the Korean earth science society
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• v.45 no.1
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• pp.19-36
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• 2024

The global seasonal forecasting system version 6 (GloSea6) operated by the Korea Meteorological Administration for 1- and 3-month prediction products does not include complex atmospheric chemistry-aerosol physical processes (UKCA). In this study, low-resolution GloSea6 and GloSea6 coupled with UKCA (GloSea6-UKCA) were installed in a CentOS-based Linux cluster system, and preliminary prediction results for the spring of 2000 were examined. Low-resolution versions of GloSea6 and GloSea6-UKCA are highly needed to examine the effects of atmospheric chemistry-aerosol owing to the huge computational demand of the current high resolution GloSea6. The spatial distributions of the surface temperature and daily precipitation for April 2000 (obtained from the two model runs for the next 75 days, starting from March 1, 2000, 00Z) were compared with the ERA5 reanalysis data. The GloSea6-UKCA results were more similar to the ERA5 reanalysis data than the GloSea6 results. The surface air temperature and daily precipitation prediction results of GloSea6-UKCA for spring, particularly over East Asia, were improved by the inclusion of UKCA. Furthermore, compared with GloSea6, GloSea6-UKCA simulated improved temporal variations in the temperature and precipitation intensity during the model integration period that were more similar to the reanalysis data. This indicates that the coupling of atmospheric chemistry-aerosol processes in GloSea6 is crucial for improving the spring predictions over East Asia.

• Journal of Korean Society of Forest Science
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• v.81 no.3
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• pp.255-262
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• 1992

Urguay Round(UR) has lots of implication in the forest product market as well as the other sectors of the economy. Chestnut, one of the major forest product in Korea, would be affected by free trade resulting from the agreement on UR. To establish effective policy measures dealing with negative effects of free trade, if any, the effect of UR on producers should be figured out. In this contest, the purposes of this study are (1) estimating the demand, supply and its price functions of this market and (2) forecasting the effect of UR on growers. Using econometric method, demand, supply and price function of this market are estimated. The total amount of yearly money loss of growers due to free trade from 1992 to 2001 are estimated for four different scenarios. In each scenario, it is assumed that the tariffication reduction is 30%, 40%, 50% and 90%. Yearly money loss of chestnut growers at the year 2001 are forecasted such as 14 billion won, 18 billion won, 24 billion won and 25 billion won for the rate of tariffication reduction of 30%, 40%, 50%, and 90%, respectively.