• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.4
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• pp.1-20
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• 2023

This study attempted to identify the relationship between the investment determinants of accelerators and investment performance through empirical analysis. Through literature review, four dimensions and 12 measurement items were extracted for investment determinants, which are independent variables, and investment performance was adjusted to the cumulative amount of subsequent investment based on previous studies. Performance data from 594 companies selected by TIPS from 2017 to 2019, which are relatively reliable and easy to secure data, were collected, and the subsequent investment cumulative attraction amount, which is a dependent variable, was hypothesized through multiple regression analysis three years after the investment. As a result of the study, 'industrial experience years' in the characteristics of founders, 'market size', 'market growth', 'competitive strength', and 'number of patents' in the characteristics of products and services had a significant positive (+) effect. The impact of independent variables on dependent variables was most influenced by the competitive strength of market characteristics, followed by the number of years of industrial experience, the number of patents, the size of the market, and market growth. This was different from the results of previous studies conducted mainly on qualitative research methods, and in most previous studies, the characteristics of founders were the most important, but the empirical analysis results were market characteristics. As a sub-factor, the intensity of competition, which was the subordinate to the importance of previous studies, had the greatest influence in empirical analysis. The academic significance of this study is that it presented a specific methodology to collect and build 594 empirical samples in the absence of empirical research on accelerator investment determinants, and created an opportunity to expand the theoretical discussion of investment determinants through causal research. In practice, the information asymmetry and uncertainty of startups that accelerators have can help them make effective investment decisions by establishing a systematic model of experience-dependent investment determinants.

• The Korean Journal of Financial Management
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• v.25 no.4
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• pp.25-51
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• 2008

In this paper, we analyse empirically the fixed asset investment smoothing of working capital of firms listed on Korea Securities Market. The main results of this study can be summarized as follows. Firms will seek to lower long-term cost by smoothing fixed asset investment and maintaining stationary investment with working capital. Working capital is not only an important use of fund, but also a source of liquidity that should be used to smooth fixed asset investment relative to cash flow shocks if firms face financial constraints. Working capital investment is more sensitive than fixed asset investment to cash flow fluctuations. If firms face financial constraints, working capital investment will compete with fixed asset investment for the limited pool of available cash flows. So, fixed asset investment will have negative relationship with working capital investment. However, criticism that the positive correlation between cash flows and fixed asset investment could arise simply because cash flows is proxy variable for investment demand. Finally, controlling for the fixed asset investment smoothing effects of working capital results in a much larger estimate of the long run impact of financial constraints. Financial constraints is measured by dividend payout ratio and market access level. Fazzari et al. (1988), Fazzari and Petersen (1993), and Faulkender et al. (2008) emphasize that low dividend firms or market unaccessible firms are more likely to face financial constraints, and rarely make use of new equity issuing. The results from empirical analysis show that financial constraints can be better explained using 'adjustment cost' concept. Specifically, the results show that financial constraints exist and that in order to measure financial constraint effects more succinctly, fixed asset investment smoothing effects with working capital should be considered.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.95-118
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• 2017

Recent centrally the downtown area, the transaction between the row housing and multiplex housing is activated and platform services such as Zigbang and Dabang are growing. The row housing and multiplex housing is a blind spot for real estate information. Because there is a social problem, due to the change in market size and information asymmetry due to changes in demand. Also, the 5 or 25 districts used by the Seoul Metropolitan Government or the Korean Appraisal Board(hereafter, KAB) were established within the administrative boundaries and used in existing real estate studies. This is not a district classification for real estate researches because it is zoned urban planning. Based on the existing study, this study found that the city needs to reset the Seoul Metropolitan Government's spatial structure in estimating future housing prices. So, This study attempted to classify the area without spatial heterogeneity by the reflected the property price characteristics of row housing and Multiplex housing. In other words, There has been a problem that an inefficient side has arisen due to the simple division by the existing administrative district. Therefore, this study aims to cluster Seoul as a new area for more efficient real estate analysis. This study was applied to the hedonic model based on the real transactions price data of row housing and multiplex housing. And the K-Means Clustering algorithm was used to cluster the spatial structure of Seoul. In this study, data onto real transactions price of the Seoul Row housing and Multiplex Housing from January 2014 to December 2016, and the official land value of 2016 was used and it provided by Ministry of Land, Infrastructure and Transport(hereafter, MOLIT). Data preprocessing was followed by the following processing procedures: Removal of underground transaction, Price standardization per area, Removal of Real transaction case(above 5 and below -5). In this study, we analyzed data from 132,707 cases to 126,759 data through data preprocessing. The data analysis tool used the R program. After data preprocessing, data model was constructed. Priority, the K-means Clustering was performed. In addition, a regression analysis was conducted using Hedonic model and it was conducted a cosine similarity analysis. Based on the constructed data model, we clustered on the basis of the longitude and latitude of Seoul and conducted comparative analysis of existing area. The results of this study indicated that the goodness of fit of the model was above 75 % and the variables used for the Hedonic model were significant. In other words, 5 or 25 districts that is the area of the existing administrative area are divided into 16 districts. So, this study derived a clustering method of row housing and multiplex housing in Seoul using K-Means Clustering algorithm and hedonic model by the reflected the property price characteristics. Moreover, they presented academic and practical implications and presented the limitations of this study and the direction of future research. Academic implication has clustered by reflecting the property price characteristics in order to improve the problems of the areas used in the Seoul Metropolitan Government, KAB, and Existing Real Estate Research. Another academic implications are that apartments were the main study of existing real estate research, and has proposed a method of classifying area in Seoul using public information(i.e., real-data of MOLIT) of government 3.0. Practical implication is that it can be used as a basic data for real estate related research on row housing and multiplex housing. Another practical implications are that is expected the activation of row housing and multiplex housing research and, that is expected to increase the accuracy of the model of the actual transaction. The future research direction of this study involves conducting various analyses to overcome the limitations of the threshold and indicates the need for deeper research.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.45 no.4
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• pp.9-21
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• 2008

In this paper, we propose a GNSS-based RF receiver, A high precision localization architecture, and a high sensitivity localization architecture in order to solve the satellite navigation system's problem mentioned above. The GNSS-based RF receiver model should have the structure to simultaneously receive both the conventional GPS and navigation information data of future-usable Galileo. As a result, it is constructed as the multi-band which can receive at the same time Ll band (1575.42MHz) of GPS and El band (1575.42MHz), E5A band (1207.1MHz), and E4B band (1176.45MHz) of Galileo This high precision localization architecture proposes a delay lock loop with the structure of Early_early code, Early_late code, Prompt code, Late_early code, and Late_late code other than Early code, Prompt code, and Late code which a previous delay lock loop structure has. As we suggest the delay lock loop structure of 1/4chips spacing, we successfully deal with the synchronization problem with the C/A code derived from inaccuracy of the signal received from the satellite navigation system. The synchronization problem with the C/A code causes an acquisition delay time problem of the vehicle navigation system and leads to performance reduction of the receiver. In addition, as this high sensitivity localization architecture is designed as an asymmetry structure using 20 correlators, maximizes reception amplification factor, and minimizes noise, it improves a reception rate. Satellite navigation system repeatedly transmits the same C/A code 20 times. Consequently, we propose a structure which can use all of the same C/A code. Since this has an adaptive structure and can limit(offer) the number of the correlator according to the nearby environment, it can reduce unnecessary delay time of the system. With the use of this structure, we can lower the acquisition delay time and guarantee the continuity of tracking.