KJC Korea
Journal Central

One of the efforts for sustainable development is activate transit use in transportation sector. The importance of public transit has grown gradually and many policies have been established. However, most of policies were implemented uniformly, so the effects of the policies did not meet the expectations. To accomplish of this study, we selected assessment indexes, city characteristics, and grouped using factor analysis, principal component method. Then we have 6 clusters by cluster analysis and analyzed the relationship between city characteristics and transit modal share through multiple regression analysis. The result demonstrates that public transit share tends to increase in a city has higher self-reliance ratio of local finance, paved roadway occupancy, tax revenue, population density, and car supply ratio. However, parking place occupancy and urban-rural consolidation policy have negative effect on the public transit share.

This paper aims to analyze the spatial and temporal change of land use and density in Seoul from 1980 to 2007. After reviewing previous study and obtaining related data, this study examines geographical patterns of the total floor area of residential, commercial, office, and industrial land use with diverse methods such as density, continuity, residential-non residential ratio, land use mix, and hot spot analysis. Further, this study attempts to classify the spatial clusters by land use and density based on the output from hot spot analysis. This study confirms that residential land use is more dispersed than that of non-residential. Further, the density and mix of land use have risen due to the increasing supply of physical space for population and economic activity. While non-residential land use tends to appear in localized clusters, residential areas scattered over Seoul city. The outputs of this study provide the insightful implication that policy for linking between socioeconomic features and local contexts of land use and density matters for effective and efficient master plan in Seoul.

The purpose of this study is to consider the way of applying the real options analysis to the economic feasibility study of the road project. It is said that the real options analysis can supplement the traditional NPV(net present value)'s weakness that can't consider the future's uncertainty. This study reviewed the definition of the real options firstly, and investigated the theories of option valuation models, risk-neutral approach, four-step option valuation process etc. And then three kinds of options(option to contract/abandon/defer) were applied to a road project that the pre-feasibility study had been undertaken on it, and the value of options were estimated. The results showed that NPV of the road project increased when the options were applied. And the value of options increased as the volatility of the underlying asset and the life of option increase. These results shows that the theories about real options can be realized well in the case of the feasibility study of the road projects. But the greatest limit of this study is that the value of time - instead of the traffic volume - was used to estimate the volatility of the underlying asset. This limit was caused by difficulty in the acquisition of the relevant transportation analysis software file. So in the future study, it is necessary to resolve this difficulty and to consider the traffic volume in estimating the volatility of the underlying asset.

The natural vacancy rate is one of the key elements to understand the rent adjustment process, the study on the issue, however, has not been so active in Seoul office market because of the lack of time series data. This study establishes three models, 1) fixed value, 2) moving average and 3) optimal inventory, and analyzes rent adjustment process by office size using quarterly data from 2003 on Seoul office market. The empirical results suggest that the natural vacancy rate mechanism works differently by office size. In the large-sized office group fixed value model is more significant amid both fixed value and optimal inventory models are working. In the middle-sized office group all the three models work and are significant. In the small-sized office group, on the contrary, any model is not significant. That means the rent of large-sized office regresses to fixed target vacancy rate, the rent of middle-sized office moves actively clearing the excess vacancy rate between current vacancy rate and natural vacancy rate which is responding sensitively to the change of market variables, and the rent of small-sized office is not explained through the three models above.

The global financial crisis caused by a collaboration real estate with capital markets and has expanded all over the world. This situation in the real estate finance market is an opportunity to highlight the importance of risk. Increased risk in commercial real estate, because the relationship between macroeconomic. Particularly since the financial crisis caused by the expansion of capital markets, the impact was an increase in risk. Risk factor analysis to quantify risk based on the Monte Carlo Simulation was carried out. Depending on the Loan to Value have risen along with return and risk and fluctuations of the up-phase the yield rising risk decreased down-phase the yield decreases and the risk increases. In Scenario analysis by investors, Our results show that the difference between return and risk is a more business cycle than characteristics real estate and the investor. Thus Business Cycle risk than the individual risks are much more influential in real estate investing. We can calculate the probability of Possibility of investment and loss of principal. Thus we can do Building of risk assessment models were available.

Recently, an explosive growth in electronic commerce, telemarketing, and TV home shopping industries has brought an increase of consumer's need of direct shipment of purchased goods by parcel service. Although there exist a countless number of different starting points and destinations in the parcel service, to build an efficient hub network is important in aspects of not only speedy pickup and delivery but also operational cost. However, most of all companies made decision on the optimum number of distribution centers, their locations and sizes, and network strategy without any detailed analysis procedures. They made decisions by using traditional experiences. The purposes of this study are to build a mathematical model that could reflect the characteristics of cargo transportation and transportation economies of scale and to apply the model to the domestic express parcel service industry. It is assumed that parcel delivery service used less than two hub terminals as its analysis target and the hub network designed to make a single allocation. In addition, this study applied the model to the LINGO, an optimization package, after using the Heuristic method, which is to simplify a network by grouping into sub-terminals.

This study aims at identifying a parcel based land price estimation model, considered spatial dependency and heterogeneity, focused on the farmland which is the main target of land policy as a future urbanized land. In addition to ordinary least square estimation like hedonic price model, spatial econometrics approaches such as spatial auto regression model, spatial error model and geographically weighted regression model were used to estimate the farmland price at the urban fringe in Seoul Metropolitan Area and compared. The empirical results showed that GWR model weighted tricube adaptive kernel has about 30% lower RMSE than OLS model. In the future, it is strongly suggested to apply transaction price based GWR models for public purpose land price estimation such as landbanking and public land disposal, both indirect and long-term land policy, especially when calibrating other price factors.

Overestimation of local population growth may be contributed to the noncompliance to the government planning guidelines. Most municipalities in Gyeongbuk have been reluctant to firstly test its assumption of trend extrapolation; secondly to compare between the results of survival analysis and local population growth; and fianlly to review the relevant case studies of migration patterns. However, the study found that the most critical problem in the population forecast is that the level of compliance does not correspond to the level of accuracy. Given the past population change, this study suggested a couple of the alternative guideline in the population forecast. First, the planners should take account of a historically accepted range of population change and its natural and social changes as a baseline of population analysis. Second, the planners make sure that there is a strongly positive correlation found between natural change and social change in population. Third, population growth, therefore, should be estimated by entailing both natural increase “and” social increase of population. Finally, it is also recommended that the municipalities with population size of 200 thousand or less should prepare a high risk of population decrease.

The purpose of this study is to develop indicators and index of healthy cities, to apply them in Seoul Metropolitan Area(SMA), and to utilize them as monitering systems of healthy city policies. The analyses are dune at the cities, counties, and communities levels on 2009, and covered SMA. It collected appropriate healthy cities indicators after reviewing literatures and interviewing experts in public health and planning fields. An analytic hierarchy process(AHP) was used to find the parameters among the indicators and produced index of healthy cities. For the result of expert survey, citizen's health condition(32.8%) was the first priority, and environment(28.4%) was second important one from the components of healthy cities. The following were healthcare service(2.5%) and socioeconomic factor(16.3%). As an index of healthy cities in SMA, Gangnam-gu(1.227), Seocho-gu(1.080), and Gwacheon-si(0.826) were top three regions. the regions of top 20% of healthy cities indices were clustered in southeast and downtown of Seoul, and southern part of Gyeonggi while the areas with bottom 20% located in islands in Inchoen and northeast Gyeonggi. This study contributes to provide indicators and index of healthy cities in Korea. It further provides useful insights into planners in monitering current systems and building appropriate policies.