• Korean small business review
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• v.41 no.2
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• pp.51-78
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• 2019

The purpose of this study is to classify unlisted companies' entering method into stock market and to find out a advantageous choice between IPO and SPAC. The research samples are two types(79 IPO companies and 46 SPAC companies) of 125 companies. Which were being listed in the KOSDAQ market from 2010 to 2017. The analysis results are as follows. At first, after analyzing the impact of well known variables such as asset size, company history and number of employees to select listing methods. I found that the variables of asset size and company history have a significant negative (-) effect on the SPAC variable. Secondly, the debt ratio variable has a significant positive (+) effect on the SPAC variable. Third, it was found that the ratio of profitability variables, such as operating income to sales have a systematically positive (+) effect on the SPAC variable. Fourth, I analyzed the impact of the largest stockholder in unlisted companies on the selection of listing methods. I found that the largest stockholder are systematically having a positive (+) effect on SPAC. The result means that unlisted companies that chose SPAC have the larger shareholder shares that are relatively higher than the unlisted companies that chose IPO.

• Journal of Industrial Convergence
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• v.21 no.11
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• pp.13-27
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• 2023

This study aims to contribute to the reduction of the failure rate and social costs resulting from business failures by analyzing factors that affect the insolvency of social enterprises, as the role of social enterprises is increasing in our economy. The data used in this study were classified as normal and insolvent companies among social enterprises (including prospective social enterprises) that were established between 2009 and 2018 and received credit guarantees from credit guarantee institutions as of the end of June 2022. Among the collected data, 439 social enterprises with available financial information were targeted; 406 (92.5%) were normal enterprises, and 33 (7.5%) were insolvent enterprises. Through a literature review, eight non-financial factors commonly used for insolvency prediction were selected. The cross-analysis results showed that four of these factors were significant. Logistic regression analysis revealed that two variables, including corporate credit rating and the personal credit rating of the representative, were significant. Financial factors such as debt ratio, sales operating profit rate, and total asset turnover were used as control variables. The empirical analysis confirmed that the two independent variables maintained their influence even after controlling for financial factors. Given that government-led support and development policies have limitations, there is a need to shift policy direction so that various companies aspiring to create social value can enter the social enterprise sector through private and regional initiatives. This would enable the social economy to create an environment where local residents can collaborate to realize social value, and the government should actively support this.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.3
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• pp.19-31
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• 2022

Currently, the role of public accelerators in the domestic accelerator market is gradually expanding. Accordingly, in order to establish relevant policies properly, it is necessary to check the effect and validity of public accelerators' investment. However, there is no quantitative research conducted on domestic accelerators, using their financial data, as domestic accelerators have a short history and quantitative data on them are not disclosed. Therefore, this study conducted an empirical analysis with financial data of the startups that received equity investments from public accelerators to confirm the effect of public accelerators'investment in startups. A regression analysis was conducted with financial data from 112 startups that acquired investments from public accelerators in the period of 2016~2020. And the findings are as follows: First, it was found that the initial investment of public accelerators had an effect on the growth and profitability of startups. Specifically, it was confirmed that the initial investment of public accelerators had a positive (+) effect on sales growth rates and total asset growth rates, which are growth indicators. Second, it was found that the joint investment of public accelerators had a significant positive (+) effect on profit margin, an indicator of profitability, rather than on growth. Therefore, it is deemed that it will be a great force for growth if investment in the early-stage startups that showed significant investment results in this study is continuously expanded in combination with support projects, which are a strength of public accelerators. Since this study has confirmed the investment effect of public accelerators, it is deemed necessary to actively promote policies that direct public accelerators' projects toward improving the performance of startups through joint investment with the private sector and supplementing private accelerators' deficiencies.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.10B
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• pp.946-961
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• 2008

This study aims to provide guidelines on future policy for restructuring the scheme of aid programs associated with If small and medium-sized enterprises (i.e. SME) in Korea. For this purpose, we investigate an empirical dataset of recent aid programs deployed by Ministry of Information and Communication (i.e. MIC) for the last four years First, it is examined that the programs are practiced in accordance with their own policy objective by comparing matching samples between two groups such as program beneficiary and non-beneficiary companies. Second, positioning transition of programs within a same category is visualized in terms of two business portfolio analysis matrices. Third, an affiliation network matrix of (he programs is newly developed and then we attempt to analyze the programs relationship by the application of multidimensional scaling method to the affiliation network matrix. The empirical dataset is composed of two different kinds of corporate datasets. One is a corporate dataset of 8,994 beneficiary companies that are aided by MIC during the year of '03-'06. The other is also a corporate dataset of 18,354 non-beneficiary companies that have no records of the program supports during the years at all. Particularly, the matching samples of non-beneficiary companies are prepared in order to have comparable corporate age years (i.e. CAY) against beneficiary companies' CAY. Results show that; 1) up-to-date, the programs are properly assigned to IT SME conforming to their own policy objective; 2) however, as the year goes on, the following two distinct positioning transitions are revealed such as (1) both CAY and corporate sales (i.e. SAL) are increased simultaneously, (2) ratio of intangible assets (i.e. RIA) is decreased and ratio of operating gain to revenue (i.e. ROR) is increased. Hence, the role of the programs gets weakened with regard to providing seed money to technology innovation-typed IT SME so that a managerial adjustment of the programs is required consequently; 3) even though the model adequacy is not satisfactory through the analysis of multidimensional scaling method, the relationship of indirect-typed programs can relatively be stronger than that of direct-typed programs.