비재무정보를 이용한 스포츠서비스산업 기업의 생존에 관한 연구

윤호중(Yoon, Hojung) 한국스포츠산업경영학회 2020 한국스포츠산업경영학회지 Vol.25 No.4

본 연구는 비재무정보를 활용하여 스포츠서비스산업 기업의 생존 요인에 대해 알아보고자 하였다. 산업분류, 기업 규모, 기업 형태, 종업원 수, 계열 여부 등의 비재무적인 요소에 따른 생존율의 차이를 알아보기 위해 카플란-마이어 분석을 수행하였으며, 비재무적 요소들이 생존에 미치는 영향은 콕스비례위험모형을 이용하여 파악하였다. 분석은 2018년을 절단점으로 하여 2000년부터 2012년 사이에 설립된 총 550개 기업을 대상으로 하였다. 생존분석 결과 산업분류 별로는 골프장 운영업, 골프연습장 운영업 업종이 스포츠시설 운영업, 유원지 및 기타 오락관련 서비스업보다 생존율이 높았으며, 기업규모 별로는 대기업, 중기업 등 일정규모 이상의 기업 규모를 가진 기업이 소기업보다 생존율이 높았다. 주식회사 등 관련자가 다수 있는 기업 형태가 개인 기업 형태보다 생존율이 높게 나타났으며, 계열 기업이 비계열 기업보다 생존율이 높으며, 종업원 수가 많은 기업의 생존율이 상대적으로 높음을 확인 할 수 있었다. 골프 관련 기업, 기업 규모가 크고 종업원 수가 많은 기업 등의 생존율이 상대적으로 높은 것으로 나타났다. 콕스비례위험모형으로 생존에 영향을 미치는 요인을 파악한 결과 산업분류, 기업규모, 기업형태, 종업원 수 등의 비재무정보들이 스포츠서비스산업기업의 생존에 영향을 미치는 변수로 나타났다. 이러한 결과는 한국의 스포츠서비스산업 기업은 특정 산업, 대규모, 대자본에 의해 설립된 기업이 소규모 소자본으로 설립된 기업보다 오래 생존함을 보여주는 것으로 향후 우리나라 스포츠산업이 지속적으로 발전하기 위해서는 소기업도 함께 성장 및 발전 할 수 있는 토대를 마련할 필요가 있다. The purpose of this study was to find the survival factors of sports service industry"s firms with non-financial information. Kaplan-meier analysis was conducted to determine the difference in survival rates according to non-financial factors such as industrial classification, size of enterprises, type of enterprises, number of employees, and whether they are affiliated. In addition, the effects of non-financial factors on survival was found using Cox’s proportional hazard regression model. The analysis was conducted on a total of 550 firms established between 2000 and 2012, and we had set 2018 as the cutting point. According to the survival analysis, the golf course operation firms and golf driving range operation firms had a higher survival rate than the sports facility operation firms, amusement parks, and other entertainment related service firms. And firms such as large-sized firms and medium-sized firms, had a higher survival rate than small-sized firms. In addition, it was confirmed that the survival rate of firms with a large number of related persons, such as corporation, was higher than that of individual firms, and the survival rate of affiliates was higher than that of non-affiliated firms, and the survival rate of companies with large number of employees was relatively higher. Golf-related companies, large companies and large employees had relatively high survival rates. With Cox’s proportional hazard regression model found factors affecting survival. It was non-financial information such as industrial classification, size of enterprises, type of enterprises and number of employees were variables affecting the survival of sports service industry companies. These results showed that a company established by a particular industry, large scale, or large capital survives longer than a company established with small scale and small capital. In order for the Korean sports industry to continue to develop in the future, it is necessary to lay the foundation for small businesses to grow and develop together.

스포츠용품 제조업의 생산성분석: 한국의 우수체육용구생산업체를 중심으로

윤호중(Yoon, Hojung) 한국스포츠산업경영학회 2021 한국스포츠산업경영학회지 Vol.26 No.2

한국에서는 스포츠용품의 생산을 장려하고 품질 향상을 유도하기 위한 스포츠산업 보호 육성 정책으로 우수체육용구생산업체를 지정하여 다양한 혜택을 부여하고 있다. 본 연구에서는 우수체육용구생산업체로 지정된 업체가 산업 보호 육성정책의 혜택을 받아 생산성이 향상되었는지를 알아보기 위해 Malmquist 생산성 지수를 이용해 생산성변화를 추정하고 추정된 생산성변화가 종업원 수와 R&D 투자 여부에 따라 차이가 있는지를 분석하고자 하였다. 2016~2019년을 분석기간으로 하여 생산성변화를 살펴본 결과 생산성은 약간 증가하는 것으로 나타났지만 기업규모나 R&D 투자 여부에 따른 생산성 차이는 보이고 있지 않은 것으로 나타났다. 우수체육용구생산업체 지정의 취지를 살리기 위해서는 우수용구업체 선정 시에 생산성 향상과 관련한 지표를 선정 지표에 반영하여 장기적으로 생산성 향상으로 이어질 수 있도록 제도를 개선할 필요가 있으며, 지정업체에 대한 철저한 사후평가가 이루어질 필요가 있다. In Korea, excellent sports goods manufacturer designated as part of the sports industry protection and promotion policy to encourage the production of sports goods and induce quality improvement. And they were provided various benefits. In this study, the Malmquist productivity index was used to estimate the productivity change to find out whether a company designated as an excellent sports goods manufacturer had benefited from the industrial protection and promotion policy. And we tried to analyze whether the estimated productivity change is different depending on the number of employees or whether to invest R&D. As a result of looking at the change in productivity using 2016-2019 as the analysis period, it was found that the productivity increased slightly, but there was no difference in productivity depending on the number of employees or whether to invest R&D. In order to make use of the purpose of designating excellent sports goods manufacturer, it is necessary to improve the system so that it can lead to productivity improvement in the long term by reflecting the indicators related to productivity improvement in the selection index when selecting excellent sports goods manufacturer. And it is necessary to conduct a thorough ex post evaluation of the designated company.

동시 사용자수를 고려한 패키지 소프트웨어 구매에 관한 경제성 분석

윤호중(HoJung Yoon),안재경(Jaekyoung Ahn) 한국IT서비스학회 2011 한국IT서비스학회지 Vol.10 No.4

When your company buys packaged software, the company needs to determine how many software licenses must be purchased. If the quantity is too small, it will be not enough for the users to access the programs at anytime within the company. Conversely, if the quantity is too large, they will waste a lot of money. In this paper, we surveyed several number of researchers of K institute and derived the using pattern of a specific packaged software. We estimated a proper number of packaged software licenses by Erlang Loss Function, the Engset Model, and simulation model. With the results of the three methodologies, we were able to empirically verify economic benefits of packaged software purchase by comparing NPV (Net Present Value) between user licenses and network licenses. Consequently, TCO of user licenses is much higher than that of network licenses. We had probabilistically calculated proper number of licenses based on the using pattern of users. Hence, this paper will be useful for decision makers who are going to determine package software's type and quantity from an economic perspective.

머신러닝을 이용한 한국 스포츠산업 기업의 부실 예측에 관한 연구

윤호중 ( Yoon Hojung ) 한국체육학회 2019 한국체육학회지 Vol.58 No.6

The purpose of this study is to predict the insolvency of sports industry companies by machine learning. In order to predict corporate insolvency, we defined a company with a negative interest payment ratio for three years as a insolvency company and vice versa as a healthy company. We selected the variables that satisfy the equal variance among the financial indicators that can be analyzed for the insolvent and healthy companies, and then conducted a T-test to select the financial variables that showed significant differences between the two groups. Using the selected financial indicators, machine learning was performed using logistic regression and discriminant analysis methods. The five financial indicators, such as Total assets growth, Financial expenses / total liabilities, NWC to total assets, Total CF to total liabilities, NWC turnover, were used as input variables to predict corporate insolvency. The training was conducted using the training data, and the results of the training were verified using the validation data. As a result, the prediction accuracy of the logistic regression analysis was 88.5%, which is higher than the 80.3% of the discriminant analysis. Apply the results of this study to identify companies that may be insolvent. By providing a way to prevent the insolvency will be, directly or indirectly, reduce the damage caused by the company insolvent.

재무제표를 이용한 한국 스포츠산업 기업의 경영분석

윤호중 ( Hojung Yoon ),김예기 ( Yae Gi Kim ) 한국스포츠과학원 2016 체육과학연구 Vol.27 No.1

In this paper, we analyzed financial ratio of Sports Industry Enterprises in Korea from 2011 until 2014. We use Kis-Value data and extract 195 enterprise from it. And we compared the results with other industries which data were analyzed from the Bank of Korea. The results of the analysis are that the financial ratios of the sports industry is higher than other industries. This shows that the management conditions in sports industry are better than the other industries. In particular, among the sports industries, the management condition in sports service industry shows better states than other sports industries and other industries. This indicates that the sports service industry is a high value-added industry and growth rate of this industry is much faster than other industries. Growth rate of sales of Sports industry in 2014 was 0.1% whereas growth rate of sales of all industries was -1.5%. Also, growth rate of total assets of Sports industry in 2014 was 3.5% while growth rate of sales of all industries was 3.0%. So, growth ratio of the sports industry was higher than all industries. On the other hand, growth rate of tangible asset which represents the investment in fixed assets was 1.9%, which was lower than that of all industries 2.5%. Through operating income to sales, we can know the profitability of company from operating activities. Operating income to sales of sports industry in 2014 was 9.5% whereas operating income to sales of all industries was 4.3%. Especially sports service industry increased 24.6% in 2014. Income before income taxes to sales was 10.1%, which was higher than all industries 3.9%. In particular sports service industry was 28.3%. It shows that the sports service companies have issued a profit through strong corporate activities. Debt ratio of the sports industry in 2014 was 80.9% while it was 91.9% for all industries. Debt ratio of sports facilities industry was 166.9% that is higher than the average of all industries. But the debt ratio of the sports service industry was 29.9%, it can be seen considerably lower than the average of all industries. Total borrowings and bonds payable ratio of the sports industry was 19.8%, it can be seen lower than the 25.3 percent for all industries. Cash flow coverage ratio which represents the ability to afford the interest and debt to cash income. Sports industry rate was 25.4%. It was lower than the all industry``s 62.7% and it indicates sports industry is financially not good. So, we know that sports service industry was financially not healthy. Business analysis results of sports industry of Korea appeared better than other industries. But business conditions are getting worse and, like any other industry. Thus, through the business analysis, we should prepare substantiality of management. And we should plan productivity improvement and business strategies for the changing business environment.

운동 및 경기용품 제조업의 R&D 투자와 기업성과간의 관계에 대한 연구

윤호중 ( Yoon Hojung ) 한국스포츠과학원 2017 체육과학연구 Vol.28 No.3

[Purpose] In recent years, competition among companies has become more and more important to maximize the competitiveness of companies by improving their productivity through technological innovation. Increasing competitiveness through technological innovation is becoming an essential requirement for survival of companies. In order for companies to innovate, it is necessary to spend R&D investment and the government is strengthening various policy supports to do this. Athletic equipment industry classified as manufacturing industry in sports industry. In this study, considering the fact that manufacturing industry occupies a large part of Korea's R&D investment, we compared R&D intensities with athletic equipment industry and other industries. We also examined whether R&D investment has affected firm performance. [Methods] The data used in the analysis were extracted from KIS-DATA with KSIC codes of companies classified as sports and athletic goods manufacturing industry in the 9th Korean Standard Industrial Classification of National Statistical Office. The analysis period is five years from 2011 to 2015 to look at the current status. Looking at the number of companies extracted by year, it was 42 in 2011, 45 in 2012, 46 in 2013, 48 in 2014, and 39 in 2015. [Results] Research showed that the intensity of R&D of athletic equipment industry was 1.22% in 2011, 1.63% in 2012, 1.51% in 2013, 1.53% in 2014 and 1.30% in 2015. This was lower than the manufacturing industry, which was a category of athletic equipment industry, and lower than that of similar small and medium sized enterprises. The correlation between R&D intensities and the sales growth rate of firms showed a positive correlation in 2011 and 2015, but the correlation is not strong. [Conclusion] R&D investment in athletic equipment industry was not actively taking place, and R&D investment did not have a significant effect on the performance of the company.