• The Journal of Information Systems
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• v.26 no.3
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• pp.171-185
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• 2017

Purpose Recently, there has been an increase in attempts to analyze social phenomena, consumption trends, and consumption behavior through a vast amount of customer data such as web search traffic information and social buzz information in various fields such as flu prediction and real estate price prediction. Internet portal service providers such as google and naver are disclosing web search traffic information of online users as services such as google trends and naver trends. Academic and industry are paying attention to research on information search behavior and utilization of online users based on the web search traffic information. Although there are many studies predicting social phenomena, consumption trends, political polls, etc. based on web search traffic information, it is hard to find the research to explain and predict tourism demand and establish tourism policy using it. In this study, we try to use web search traffic information to explain the tourism demand for major cities in Gangwon-do, the representative tourist area in Korea, and to develop a nowcasting model for the demand. Design/methodology/approach In the first step, the literature review on travel demand and web search traffic was conducted in parallel in two directions. In the second stage, we conducted a qualitative research to confirm the information retrieval behavior of the traveler. In the next step, we extracted the representative tourist cities of Gangwon-do and confirmed which keywords were used for the search. In the fourth step, we collected tourist demand data to be used as a dependent variable and collected web search traffic information of each keyword to be used as an independent variable. In the fifth step, we set up a time series benchmark model, and added the web search traffic information to this model to confirm whether the prediction model improved. In the last stage, we analyze the prediction models that are finally selected as optimal and confirm whether the influence of the keywords on the prediction of travel demand. Findings This study has developed a tourism demand forecasting model of Gangwon-do, a representative tourist destination in Korea, by expanding and applying web search traffic information to tourism demand forecasting. We compared the existing time series model with the benchmarking model and confirmed the superiority of the proposed model. In addition, this study also confirms that web search traffic information has a positive correlation with travel demand and precedes it by one or two months, thereby asserting its suitability as a prediction model. Furthermore, by deriving search keywords that have a significant effect on tourism demand forecast for each city, representative characteristics of each region can be selected.

• Journal of Digital Convergence
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• v.18 no.2
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• pp.197-204
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• 2020

The purpose of this paper is to find the direction by analyzing the synchronization phenomenon and the change rate of apartment charter rate in Korea, Seoul, Busan, Daegu, Gwangju and Daejeon. For this purpose, this study used a total of 239 monthly data from January 2000 to November 2019 in Kookmin Bank housing statistics. In the correlation analysis, Korea showed the highest relationship in order of Seoul, Busan, Incheon and Daegu. Seoul showed a low figure of 0.3 without any distinctive features from other cities. On the other hand, Busan, Daejeon and Daegu showed high correlations. As a result of the regression analysis, Korea and 5 major cities were all moving in the same direction with positive(+) values. And Busan and Seoul responded significantly to Korea. In the shock response, Korea is most shocked by the change in Seoul. Daegu is relatively shocked by Busan and Daejeon. Seoul's charter rate has declined most strongly in the last three years. Therefore, it is time to be careful not to incur losses due to gap investment. If we look at the relationship between the charter rate and the sale price in future studies, we can better understand the Korean apartment market.

• Land and Housing Review
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• v.5 no.4
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• pp.259-269
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• 2014

After global financial crisis, the ratio of household debt to GDP was decreasing in other advanced countries such as the U.S., and the U.K. and so on. But, in Korea, household debt (of which residential mortgage loan account for a large part) ratio is still increasing. This paper focuses on the scale and characteristics of households in negative housing equity (those are called House-poors in Korea), and also the socio-economic backgrounds of the formation process. In financial perspective, the problem of negative housing equity depends on financial debt repayment capability. We used DSR (Debt Service Ratio) and LTA (Loan to Asset ratio) as financial indicators to evaluate the debt repayment capability. The critical value of DSR is assumed as 40%, and LTA 100%. The socio-economic backgrounds of the House-poors are as follows : increasing households debt dependency, over lending competition of financial institutions and unreasonable loan in household economy, instability of real estate market, week regulation on mortgage loan. Finally, this paper suggests some implications about the range and the target of public intervention.

• Land and Housing Review
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• v.11 no.2
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• pp.33-46
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• 2020

As the fastest growing office transaction volume in Korea, there's been a need for development of indicators to accurately diagnose the office capital market. The purpose of this paper is experimentally calculate to the office price index for effective benchmark indices in Seoul. The quantitative methodology used a Case-Shiller Repeat Sales Model (1991), based on actual multiple office transaction dataset with over minimum 1,653 ㎡ from Q3 1999 to 4Q 2019 in the case of 1,536 buildings within Seoul Metropolitan. In addition, the collected historical data and spatial statistical analysis tools were treated with the SAS 9.4 and ArcGIS 10.7 programs. The main empirical results of research are briefly summarized as follows; First, Seoul office price index was estimated to be 344.3 point (2001.1Q=100.0P) at the end of 2019, and has more than tripled over the past two decades. it means that the sales price of office per 3.3 ㎡ has consistently risen more than 12% every year since 2000, which is far above the indices for apartment housing index, announced by the MOLIT (2009). Second, between quarterly and annual office price index for the two-step estimation of the MIT Real Estate Research Center (MIT/CRE), T, L, AL variables have statistically significant coefficient (Beta) all of the mode l (p<0.01). Third, it was possible to produce a more stable office price index against the basic index by using the Moore-Penrose's pseoudo inverse technique at low transaction frequency. Fourth, as an lagging indicators, the office price index is closely related to key macroeconomic indicators, such as GDP(+), KOSPI(+), interest rates (5-year KTB, -). This facts indicate that long-term office investment tends to outperform other financial assets owing to high return and low risk pattern. In conclusion, these findings are practically meaningful to presenting an new office price index that increases accuracy and then attempting to preliminary applications for the case of Seoul. Moreover, it can provide sincerely useful benchmark about investing an office and predicting changes of the sales price among market participants (e.g. policy maker, investor, landlord, tenant, user) in the future.

• Journal of Cadastre & Land InformatiX
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• v.49 no.2
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• pp.23-38
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• 2019

The National Land Census Project aims to survey the national land regularly to resolve the land category disagreement and reflect the actual land use. The objective of this study is to investigate whether not only the National Land Census Project but also related land and housing surveys bring about the improvement of social welfare in light of the invested budget, and to measure the project feasibility. The potential benefit after the National Land Census Project is not traded in the market. To determine the economic value of this potential benefit, the Contingent Valuation Method was used. This study utilized the single-bounded and double-bounded dichotomous choice models simultaneously to estimate the project feasibility of the cadastral system improvement. According to this study, cost-benefit ratio of the project was estimated larger than 1, which means that social benefits are larger than social costs.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.6
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• pp.651-659
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• 2014

With the popularization of big data environment, big data have been highlighted as a key information strategy to establish national spatial data infrastructure for a scientific land policy and the extension of the creative economy. Especially interesting from our point of view is the cadastral information is a core national information source that forms the basis of spatial information that leads to people's daily life including the production and consumption of information related to real estate. The purpose of our paper is to suggest the scheme of big data analytics with respect to the articles of cadastral resurvey project in order to approach cadastral information in terms of spatial data integration. As specific research method, the TM (Text Mining) package from R was used to read various formats of news reports as texts, and nouns were extracted by using the KoNLP package. That is, we searched the main keywords regarding cadastral resurvey, performing extraction of compound noun and data mining analysis. And visualization of the results was presented. In addition, new reports related to cadastral resurvey between 2012 and 2014 were searched in newspapers, and nouns were extracted from the searched data for the data mining analysis of cadastral information. Furthermore, the approval rating, reliability, and improvement of rules were presented through correlation analyses among the extracted compound nouns. As a result of the correlation analysis among the most frequently used ones of the extracted nouns, five groups of data consisting of 133 keywords were generated. The most frequently appeared words were "cadastral resurvey," "civil complaint," "dispute," "cadastral survey," "lawsuit," "settlement," "mediation," "discrepant land," and "parcel." In Conclusions, the cadastral resurvey performed in some local governments has been proceeding smoothly as positive results. On the other hands, disputes from owner of land have been provoking a stream of complaints from parcel surveying for the cadastral resurvey. Through such keyword analysis, various public opinion and the types of civil complaints related to the cadastral resurvey project can be identified to prevent them through pre-emptive responses for direct call centre on the cadastral surveying, Electronic civil service and customer counseling, and high quality services about cadastral information can be provided. This study, therefore, provides a stepping stones for developing an account of big data analytics which is able to comprehensively examine and visualize a variety of news report and opinions in cadastral resurvey project promotion. Henceforth, this will contribute to establish the foundation for a framework of the information utilization, enabling scientific decision making with speediness and correctness.

• Journal of the Korean Home Economics Association
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• v.48 no.1
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• pp.83-96
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• 2010

This study was conducted to derive useful predictive variations for the qualitative supply of homes to provide information to real estate venture businesses and other business owners in neighborhood amenities and significant basic information to housing suppliers and policy makers. For this purpose, a number of apartment dwellers in Seoul were surveyed to examine their housing satisfaction, difference in housing satisfaction according to variables, and any relevant correlations. In detail, 500 apartment dwellers in Seoul were surveyed from September 1, 2009 to September 20, 2009 to gather resources that were processed through SPSS 14.0 to find percentage of frequency, mean, standard deviations, t-test, ANOVA, and Duncan Multiple Ranger's Test. The following were the findings of this study: First, housing satisfaction of apartment dwellers in Seoul was above average with the highest satisfaction with neighborhood environment. Second, satisfaction with amenities was significantly affected by dweller-related variables. Gangnam dwellers were more satisfied with housing environment and community environment than Gangbuk dwellers. By age, people in 20s and 30s showed high satisfaction with housing environment. Satisfaction with community environment was high among 20s, 30s and 40s. Satisfaction with management conditions was high among 20s. Also, satisfaction was high when housing period was between 1 and 10 years. By size, dwellers in 40py or larger homes showed high satisfaction with housing environment and management conditions. Dwellers in 30py and 40py or larger homes were satisfied with community environment. By ownership, dwellers with ownership of their homes showed high satisfaction. Third, there was a significant difference in satisfaction with neighborhood and social environments according to dweller-related variables. By region, dwellers of Gangnam area showed high satisfaction with neighborhood environment. By age, people in 20s, 30s and 40s showed high satisfaction with neighborhood environment. Also, satisfaction with neighborhood environment was high when housing period was around 10 years. By size, dwellers in 30py and 40py or larger homes were satisfied with neighborhood and social environments. Fourth, there was a close correlation between satisfaction with housing environment and satisfaction with community environment, and between satisfaction with community environment and satisfaction with management conditions. Thus, most dwellers that were satisfied with one variable of housing environment showed high satisfaction with other variables.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.6
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• pp.710-719
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• 2017

This study conducted a survey on the time serial change in the aging ratio and population structure in new towns and their housing complex of Korea and Japan, and revealed the differences in the factors that affect the aging ratio in new towns of Korea and Japan through a comparison of the housing provision of housing complex with a high aging ratio. Rapid aging is underway around the housing complexes that were developed in the beginning of Tama new town in Japan. Agingtends to increase in proportion to the opening time of the housing complex. Rental housing residents of early migration households showed rapid aging because they had generation separation early due to narrow housing. On the other hand, Bundang new town maintains a lower aging ratio and speed than Seoul and Seoul metropolitan area due to the constant influx of student population. On the other hand, aging is more likely to increase in large houses due to the depression of the real estate market.

• Journal of Cadastre & Land InformatiX
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• v.49 no.1
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• pp.123-144
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• 2019

The purpose of this study is to grasp factors the increasing population growth rate of the region through the regional and housing market characteristics. This paper has used multiple regression as the dependent variable (average of the population growth rate of 85cities during the last five years) and the independent variables analyzed the regional and housing market characteristics on the average. The results of the analysis, The regional and housing market variables that have had a significant impact on the regional population growth rate over the last five years are birth rate, employment rate, production available population growth rate, apartment rate, resale rights rate, and apartment turnover rate and the number of businesses per thousand and has decreased. In other words, The regions where the population increased by region for the last five years were the ones with the transfer of public institutions (innovation cities) and land development among the Seoul metropolitan area and non-Seoul metropolitan area excluding Seoul and metropolitan cities. The results of this study is intentional to suggest Policy point of view for the balanced regional development presented at the government level for other the metropolitan area, such as the small and medium cities that are undergoing population decline.

• Journal of the Korea Convergence Society
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• v.10 no.8
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• pp.181-193
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• 2019

The regional economy growth of Jeju has seen higher than national growth since 2011 by the establishment of Jeju Special Self-Governing Province and the increase of incoming population, but its economic growth has slowed after 2016. This study conducted the dynamic shift-share analysis using the production and employees of each industry from 2010 to 2016, targeting Jeju with many factors of regional economic change. In the results of empirical analysis, the regional economy of Jeju was not the industrial structure depending on the national growth, but the industrial structure by the competitiveness and industrial structure of Jeju region. The industries having positive(+) effects of industrial mix effect and competitive effect on the production and the number of employees were the electricity/gas/heavy equipments & waterworks, construction, accommodation & restaurants, and service industry. These industries have positive effects on the regional industry of Jeju. The above-mentioned industries are not only more likely to grow than other regions, but also to drive the local economy of Jeju. In order for these industries to continuously contribute to the regional economy of Jeju, it would be necessary to have the policy/institutional support in the long-term perspective.