Analysis of Rent-Free Determinants : Evidence from Seoul Office Market (오피스 렌트프리 결정요인 분석 : 서울시를 중심으로)
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- Journal of Cadastre & Land InformatiX
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- v.49 no.1
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- pp.5-15
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- 2019
This study is to review methodological limitations of previous studies, propose Tobit Model as an analysis model. We model used annual rent-free as dependent variable and considering to contract characteristics and building characteristics as independent variable. We model was consisted to the three model as follow: Basic model, Time control model, Quadratic model. As a result of the analysis, existing variables revealed through previous studies such as contract period, contract area, total floor area, and building age were all statistically significant. These results were robust when considering time effects. Also, floor area and annual rent-free was quadratic relationship by inverse U shape. This result provide to methodological contribution for related research. Also, provide to more accurate information for participants in seoul office market.
In the rapid technological development of artificial intelligence (AI), electric vehicles, and robots based the fourth industrial revolution, semiconductors determine the core performance, and semiconductor competitiveness is directly related to national competitiveness. However, the Korean semiconductor industry has continuously weakened its competitiveness in the system semiconductor field, excluding memory semiconductors, so in this study, a new smart contract basedblockchain business model to engage the global market, which is the most urgent need for the growth of Korean fabless system semiconductor industry in recession. F-SBM (Fabless-Smart contract based Blockchain Model) proposed. In this study, through the new F-SBM, it was verified how to engage new customers for fabless firms through smart contract based consortium blockchain regarding technology, economy, and reliability items of fabless. This model has great significance in improving the high entry barriers to engaging new customers for the long-cherished desire of the Korean fabless system semiconductor industry and deriving new growth solutions.
LL (Leased Line service) is a facility-based service as a traditional business data service, but new competition services, such as FR (Frame Relay), VPN (Virtual Private Network), and ATM (Asynchronous Transfer Mode), are value-added services. Because of different service classifications, it is hard to gather necessary data for the service providers to plan their market strategies and regulations and policies are also applied asymmetrically to each service provider. Therefore an appropriate market classification is required for the business data services. After various methods of market classification are reviewed, the Hendry model is selected in this paper to analyze substitution-degree among brands or among services. Since the structure of virtual competitions is required for the Hendry model to be applied to data service market, the market is analyzed first by the well-known Porter's model. By the analysis of Porter's model, two virtual competition structures are set up - one is for the competitions among leased line service providers, and the other is for the competitions among business data services such as LL, FR, VPN and ATM. After the Hendry model is applied to each competition structure, it is confirmed that 7 LL service providers do not compete directly, but 2 sub-markets exist for the LL service provisions. However, it is shown that 4 business data services compete directly. Using the Switching Probability Matrix from Hendry model, future market shares of LL service providers and market shares of business data services are forecasted. These empirical results are helpful for service providers to set competitive strategies with the minimization of cannibalization effect and they can easily and efficiently predict their market demands.
This study empirically examines the impact of SSM market entry on changes in market shares among retailing types. The data is monthly time-series data spanning over the period from January 2000 to December 2010, and the effect of SSM market entry on market shares of retailing types is analyzed by utilizing several key factors such as the number of new SSM monthly entrants, total number of SSMs, the proportion of new SSM entrant that is smaller than