• Journal of Korea Port Economic Association
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• v.32 no.2
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• pp.123-135
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• 2016

This study uses Data Envelopment Analysis(DEA) to investigate the management efficiency of Korean shipping companies based on business administration costs such as corporate entertainment, advertisement, and labor costs. We analyze shipping enterprises listed on the Korean stock market of the period of 2010-2014. Corporate entertainment, advertisement and labor costs are used as input variables and sales and net income are used as output variables. We use technical efficiency, pure technical efficiency, scale efficiency and returns to scale to propose a plan to improve the efficiency of inefficiency decision-making units (DMUs). The results of the efficiency analysis show that six of the DMUs in the technical efficiency of CCR model and eight of the DMUs in the pure technical efficiency of BCC model are in efficient state. In terms of return to scale, six of the DMUs(24% of all DMUs) show increasing returns to scale, while 13 DMUs(52% of all DMUs) showdecreasing returns to scale. Because multiple efficient state for DMUs exist in the technical efficiency analysis, we conduct a super efficiency analysis. The results show that the efficient state of the twomost efficient DMUs are 1.314 and 1.243, respectively. This implies that these DMUs could maintain their current levels of the efficiency if they increase the amount spent on advertisements, corporate entertainment and labor costs by 31.4% and 24.3%. respectively. We conclude this study by providing the efficiency states of each DMU and target for improving the inefficiencies in each case.

• Journal of Venture Innovation
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• v.1 no.2
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• pp.35-46
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• 2018

The research on the efficiency analysis of domestic auto parts companies is mostly based on the calculation of the magnitude of the performance creation such as the sales amount compared to the input assets. However, the performance indicators such as sales, operating profit, and net profit are directly related to the cost structure and This cost structure is affected by changes in the firm's asset and capital structure. As a result, it is considered that efficient capital procurement needs to be done at the same time to create efficient management performance through proper investment. This study focuses on this point and attempts to measure the efficiency of procurement capital relative to the sales and other performance indicators generated by the first 33 suppliers who supply parts to Hyundai Kia Motors. Among the methods of evaluating efficiency, the DEA model based on the linear programming method is most widely used as a nonparametric method but The efficient frontier-based DEA model has the limitation that it can not use the variables that have a downward influence on the efficiency. This is inadequate to directly consider variables such as borrowings and total liabilities related to capital procurement. In this study, the efficiency of capital procurement was measured using Worst Practice DEA and the improvement direction of the capital procurement aspect of domestic auto parts companies was suggested

• Korean Journal of Construction Engineering and Management
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• v.13 no.5
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• pp.94-102
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• 2012

Recently, the global financial crisis and the increasing number of unsold houses in Korea are construction companies to assess their efficiency. The most important factor in analyzing the efficiency of a company is the input-output variable. However, systematic stud the core input-output variables, which have a great influence on the efficiency analysis. Thus, to the core input-output variables for efficiency analysis of construction companies, this study propose a model that includes all combinations of input-output variables and to find the core input-output variables using the Data Envelopment Analysis(DEA) model and Principal Component Analysis(PCA). Existing research and theories were studied variables and 21 models were established to measure efficiency. were obtained that the core input and output variable in 2006 the number of employees and sales. For 2008, the core input variable was capital stock and the core output variable was quarterly net profit. For 2010, the core input variable was fixed asset and the core output variable was sales. Through obtaining the variables that greatly affect the efficiency of construction companies, it is considered that individual construction companies will be able to prepare a priority strategy to enhance efficiency.

• The Korean Journal of Franchise Management
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• v.5 no.1
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• pp.85-108
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• 2014

This study provides the information about size, financial structure, profitability and growth of franchisors using financial data(asset, liability, equity, sales volume, operating income and net income) in uniform franchise offering circular of fair trade commission. The data were collected from 1,050 franchisors in various business fields: fast food, family restaurant, bakery, agriculture & fishery and liquor shop in the uniform franchise offering circular in 2012 and 2011. Results of this study are as follows: For company size, median of total assets was KRW 675 million and the accumulated median assets rate was 0.48%, but the accumulated median company numbers were 49.9%, which showed small size. For financial structure, 525 companies were below 200% debt ratio, while 314 (29.9%) companies were in over 200% debt, and 211 (20.1%) companies were impaired in capital. These also showed financial structure was vulunerable. For profitability, median of ROA for total companies were only 4.72%, which showed low profitability. For growth, median of growth rate for sales were 7.57% per year, which showed mature industry. In overall, the results showed franchisors should improve their financial status.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.2 no.4
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• pp.103-133
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• 2007

The purpose of this study is to investigate whether customer satisfaction is affected by the expenditure for the customer satisfaction such as advertising, promotion, and training. This study also investigate whether the financial performance of the firm is affected by the customer satisfaction. The major findings are summarized as following. First, the customer satisfaction is affected by the expenditure for the customer satisfaction such as promotion, training. But customer satisfaction is not affected by advertising cost. Second, considering the time-lag and incremental valiables, the relationship between customer satisfaction and expenditure for the customer satisfaction is not founded. Third, the customer satisfaction affects positively on the corporate financial performance, such as ratio of operating income to sales, ratio of net income to sales, return on total assets, and return on equity. Finally, considering the time-lag the relationship between customer satisfaction and financial performance is not founded. Considering the incremental valiables, the relationship between customer satisfaction and financial performance is founded when ratio of operating income to sales and return on total assets are used financial performance. These findings imply that the expenditure for promotiom and training is needed to increase the customer satisfaction. Also improvement customer satisfaction is needed to increase the financial performance. The limitations of this study are as following. First, this study could not consider the other variables that would affect on the relationship among expenditure for customer satisfaction, level of customer satisfaction, and financial performance. Second, the results of this study are difficult to generalize because this study is focused on the service industry.

• Journal of Digital Convergence
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• v.19 no.12
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• pp.321-329
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• 2021

A measure of managerial ability was derived using DEA, a measure of management efficiency, and the correlation coefficient between discretionary accrual and non-discretionary accrual, net income and operating cash flow standard deviation was used as a proxy for income smoothing. verified. In addition, the manager's compensation was used by taking the natural logarithm of the cash compensation per manager. The analysis results are summarized as follows. The analysis period for hypothesis testing is from 2004 to 2017, as a result of the hypothesis analysis of the correlation with the level of manager's compensation, it was suggested that the income smoothing behavior decreased the performance-based compensation and increased the performance-controlled compensation. This can be said to be the result of indirectly confirming that additional compensation is differentially paid for income smoothing. This study has a contribution to the study by empirically analyzing whether income smoothing affects the relationship between managerial ability and managerial compensation. However, although a number of previous studies empirically analyzed that there are upper and lower bounds for manager compensation, there is limitations that could not be analyzed for asymmetric compensation due to income smoothing is expected to expand.

• Journal of Korean Society of Transportation
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• v.25 no.3
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• pp.55-63
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• 2007

This paper analyzes the relative efficiency of Korea's logistics industry with the DEA-ANP model from 2003 to 2005. To measure the efficiency, this paper used the numbers of employees, fixed assets. total capital. and operating costs as input factors and sales amounts and net incomes as output factors. The average efficiency score of the entire logistics industry is 0.175, so most logistics companies in Korea should improve their current inefficiencies. The industry with the highest efficiency score is marine transportation. with an average three-year efficiency score of 0.3692. In terms of sales and high efficiency. most of the highest-ranked companies belong to the marine transportation industry, so marine transportation has the most influence on raising the efficiency score of Korea's logistics industry. To improve the inefficiency of inputs that exists overall in the logistics industry it is necessary to control excessive numbers of employees. To improve the amount of sales, it is necessary to make a policy of satisfying various logistics demands, continuous investments, and attracting foreign logistics demand: such things will help strengthen the international competitiveness of Korea's logistics industry.

• Journal of the Korea Institute of Building Construction
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• v.11 no.1
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• pp.35-44
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• 2011

Business performance measurement is used as an important tool to evaluate management performance, control human resources, and implement strategies. It can be measured simply in terms of finance including net profit, return on investment, and return on equity, but this is not sufficient because the performance outside of finance such as internal business process and informatization cannot be examined. Therefore this study defined a KPI(Key Performance Indicators) applicable to local construction companies ranked in the top 30 in construction capability, and also introduced differentiated results from the earlier studies by reflecting more realistic corporate management based on the existing studies and interviews with business experts.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.1
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• pp.229-249
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• 2022

This paper investigates machine learning models for predicting the designation of administrative issues in the KOSDAQ market through various techniques. When a company in the Korean stock market is designated as administrative issue, the market recognizes the event itself as negative information, causing losses to the company and investors. The purpose of this study is to evaluate alternative methods for developing a artificial intelligence service to examine a possibility to the designation of administrative issues early through the financial ratio of companies and to help investors manage portfolio risks. In this study, the independent variables used 21 financial ratios representing profitability, stability, activity, and growth. From 2011 to 2020, when K-IFRS was applied, financial data of companies in administrative issues and non-administrative issues stocks are sampled. Logistic regression analysis, decision tree, support vector machine, random forest, and LightGBM are used to predict the designation of administrative issues. According to the results of analysis, LightGBM with 82.73% classification accuracy is the best prediction model, and the prediction model with the lowest classification accuracy is a decision tree with 71.94% accuracy. As a result of checking the top three variables of the importance of variables in the decision tree-based learning model, the financial variables common in each model are ROE(Net profit) and Capital stock turnover ratio, which are relatively important variables in designating administrative issues. In general, it is confirmed that the learning model using the ensemble had higher predictive performance than the single learning model.

• Journal of Preventive Medicine and Public Health
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• v.31 no.3 s.62
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• pp.490-502
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• 1998

This study purports to find the predictor of hospital bankruptcy in Korea and to examine the predictive power of the discriminant function model of hospital bankruptcy. Data on 17 financial and 4 non-financial indicators of 31 bankrupt and 31 profitable hospitals of 1, 2, and 3 years before bankruptcy were obtained from the hospital performance databank of Korea Institute of Health Services Management. Significant variables were identified through mean comparison of each indicator between bankrupt and profitable hospitals, and the discriminant function model of hospital bankruptcy was developed. The major findings are as follows 1. As for profitability indicators, net worth to total assets, operating profit to total capital, operating profit ratio to gross revenues, normal profit to total assets, normal profit to gross revenues, net profit to total assets were significantly different in mean comparison test in 1, 2, and 3 years before hospital bankruptcy. With regard to liquidity indicators, current ratio and quick ratio were significant in 1 year before bankruptcy. For activity indicators, patients receivable turnover was significant in 2 and 3 years before bankruptcy and added value per adjusted inpatient days was significant in 3 years before bankruptcy. 2. The discriminant function in 1, 2, and 3 years before bankruptcy were; $Z=-0.0166{\times}quick$ ratio-$0.1356{\times}normal$ profit to total assets-$1.545{\times}total$ assets turnrounds in 1 year before bankruptcy, $Z=-0.0119{\times}quick$ ratio-$0.1433{\times}operating$ profit to total assets-$0.0227{\times}value$ added to total assets in 2 years before bankruptcy, and $Z=-0.3533{\times}net$ profit to total assets-$0.1336{\times}patients$ receivables turn-rounds-$0.04301{\times}added$ value per adjusted $patient+0.00119{\times}average$ daily inpatient census in 3 years before bankruptcy. 3. The discriminant function's discriminant power in 1, 2, and 3 years before bankruptcy was 77.42, 79.03, 82.25% respectively.