• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.527-538
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• 2021

The purpose of the study is to determine the efficiency, position, and partner selection of securities companies via the negative super-SBM model used in data envelopment analysis (DEA). This model utilizes a variety of inputs, including current assets, non-current assets, fixed assets, liabilities, owner's equity and charter capital, and outputs including net revenue, gross profit, operating profit, and net profit after tax collected from the financial reports (Vietstock, 2020) of 32 securities companies, operating during the period from 2016 to 2019, negative data are collected as well. Empirical results determined both efficient and inefficient terms, and then further determined the position of each securities firm under consideration of every term. The overall score arrived at discovered a large performance change realizing a maximum score able to reach 20.791. In the next stage, alliancing inefficient companies was carried out based on the 2019 scores to seek out optimal partners for the inefficient companies. The tested result indicated that AAS was the best partner selection when its partners received a good result after alliancing, as with FTS (11.04469). The partner selection is deemed as a solution helpful to inefficient securities companies in order to improve their future efficiency scores.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.20 no.6
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• pp.209-220
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• 2010

Evaluating performance in public sector aims to enhance the efficiency of organizations. Evaluating the efficiency which is the ratio between input and output, organizations set directions of improvement. This research applied Data Envelopment Analysis(DEA) useful to evaluating the efficiency of organizations in public sector. Decision Making Units(DMU) of this research are 21 Information Security Organizations of departments/agencies. As the results, the mean of efficiency score of 21 DMUs is a little more than 50%. Means of departments(8 DMUs) and agencies/committees(11 DMUs) are similar to the total efficiency score. For these results, the decision makers of the information security organizations in public sector have to strive to improve the inefficiency.

• The Journal of Economics, Marketing and Management
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• v.9 no.3
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• pp.11-21
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• 2021

Purpose: The purpose of this study is to understand the status quo of production efficiency in private industrial enterprises above designated scale in China's 31 provinces (including municipalities directly under the central government, autonomous regions) (hereinafter referred to as China's 31 provinces). Research design, data and methodology: Find out the factors affecting the development of production efficiency in private industrial enterprises, using DEA, Data Envelopment Analysis and Malmquist index analysis, build the evaluation model of production efficiency in private industrial enterprises, and analyze the data of China's 31 provinces private industrial enterprises in 2015-2019. Results: The research results show that the production efficiency of private industrial enterprises in China is improving on the whole. Although the total factor productivity has decreased slightly, the overall efficiency and pure technical efficiency have increased significantly. Conclusions: The conclusion of this study can provide reference for Chinese private industrial enterprises to improve production efficiency and make development plan. The limitation of this paper lies in the fact that the private industrial enterprises in inefficient provinces have not been given specific improvement plans.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.895-904
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• 2021

This study aims to investigate the impact of innovation on firm efficiency. Panel data of fourteen finance companies and nine technology companies from 2011 to 2019 on the Vietnam Stock Exchange Market is derived from audited financial statements, annual reports, and other crucial reports that are provided by Vietstock; macroeconomic variables are collected from the World Bank Database. A two-stage approach is used. First, use of the Data Envelopment Analysis methodology to measure firm efficiency. Second, use of the Pooled ordinary least squares, the Fixed effects model, and the Random effects model to investigate the impact of innovation on firm efficiency. Furthermore, the Generalized Method of Moments and the Tobit model are used to validate the impact of innovation on firm efficiency, and the t-test is used to confirm the difference in efficiency with and without the impact of innovation between two industries. The results show that there is a significant impact of innovation on efficiency, and innovation plays a more important in increasing the efficiency of the finance industry than the technology industry. Moreover, the relation between age and efficiency is like the U-shaped, and between size and efficiency is like the inverted U-shaped, whereas efficiency is not associated with inflation.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.1
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• pp.741-750
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• 2021

The research aims to analyze the level of efficiency by grouping banks during the period 2017 - 2018 into category 1 and category 2 banks and then dividing them as Regional Development Banks (BPD) and Non-BPD Conventional Commercial Banks (BUK) within each category. The research objects are banks within the categories BPD and BUK comprised 18 BPDs and 35 BUKs. The research methodology uses 3 stages, first, using Data Envelopment Analysis (DEA) we measure the level of bank efficiency; second, using the Tobit regression model we evaluate the effect of financial performance on DEA efficiency, and third, using the Mann-Whitney test we determine whether there is a difference in the efficiency of category 1 and 2 banks. The results showed that there was a decrease in the efficiency of category 1 and 2 banks but on average, the efficiency of category 1 banks is higher than category 2 banks. The estimation results of the Tobit regression model show that only the ROA variable affects the efficiency level of category 1 banks, while category 2 banks are influenced by NPL and ROA variables. In the Mann-Whitney test, it was proven that there were differences in efficiency between BUK and BPD in category 1 and 2 banks.

• Korean Journal of Organic Agriculture
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• v.29 no.1
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• pp.41-50
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• 2021

This paper analyzes the efficiency of social enterprises by analyzing bootstrapping data envelopment analysis. Unlike the definitive DEA model, we analyze the confidence intervals of efficiency estimates through the DEA model, which takes into account stochastic factors. Major analysis results are summarized as follows: First, the results of the bootstrapping DEA analysis of social enterprises estimated that the technical efficiency was 0.459 and the 95% confidence interval was 0.389 to 0.601. Second, the number of inefficient social enterprises with efficiency values of less than 0.5 was found to be 15 (55.56%) in technical efficiency, 5 (18.52%) in pure technical efficiency, and 8 (29.63%) in scale efficiency. It can be seen that a significant number of social enterprises are operating in an inefficient state. Third, looking at the returns of scale of social enterprises, 25 (67.57%) are currently in the increasing returns of scale, 10 (27.02%) are in the constant returns of scale, and 2 (5.41%) are in decreasing returns of scale. In other words, it can be seen that social enterprises are under-invested in terms of input factors.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.3
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• pp.355-364
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• 2022

The effect of technological innovation on the high-quality development of the producer services industry depends on whether or not technical innovation efficiency plays a key role. This study looks at the impact of technological innovation and financial technology (fintech) on the development of high-quality producer services in Fujian Province from 2010 to 2019. The efficiency of technological innovation is measured using Data Envelopment Analysis (DEA) and the Malmquist productivity index. The mean overall innovation efficiency score is 0.639, meaning that Fujian accounts for 36.1% of resource utilization inefficiencies and that there are significant differences in technological innovation efficiency between cities. The findings show that high-quality producer services industries benefited from innovation efficiency, but that the influence of technological innovation efficiency is insignificant. This demonstrates that financial innovation has not been able to completely enhance the development level of the producer services industry. This may be due to the unreasonable output structure of technological innovation and the low industrial transformation rate of technological achievements. This study advocates that the R&D fund allocation structure be optimized. That technological innovation can improve the high-quality development of the producer services industry is a consensus within the academic community.

• Korean Journal of Organic Agriculture
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• v.31 no.4
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• pp.357-380
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• 2023

This study analyzed the management efficiency of jujube, bitter persimmon, and chestnut farms using data envelopment analysis (DEA). And this study analyzed causes affecting management inefficiency of those farms using the two-step method. The main findings are as follows. First, as self and employment labor costs are increased, it is important to reduce labor costs which account for 60~70% of the total production cost. Second, efforts to improve management efficiency are needed as overall efficiency of farms were decreased. Third, a pesticide cost per 10a representing a level of pesticide had a negative effect or did not have a statistically significant effect on the management efficiency. This implies that expanding environment-friendly production by reducing pesticides is effective for improving the management efficiency. Fourth, as leading farms were more efficient than general farms, technology dissemination and education through leading farms are important for improving efficiency, and efforts are needed to promote exchange between leading and general farms.

• International Journal of Advanced Culture Technology
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• v.12 no.2
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• pp.167-179
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• 2024

This study addresses the challenge of objectively evaluating the performance of early-stage startups amidst limited information and uncertainty. Focusing on companies selected by TIPS, a leading private sector-driven startup support policy in Korea, the research develops a new indicator to assess technological efficiency. By analyzing various input and output variables collected from Crunchbase and KIND (Korea Investor's Network for Disclosure System) databases, including technology use metrics, patents, and Crunchbase rankings, the study derives technological efficiency for TIPS-selected startups. A prediction model is then developed utilizing machine learning techniques such as Random Forest and boosting (XGBoost) to classify startups into efficiency percentiles (10th, 30th, and 50th). The results indicate that prediction accuracy improves with higher percentiles based on the technical efficiency index, providing valuable insights for evaluating and predicting startup performance in early markets characterized by information scarcity and uncertainty. Future research directions should focus on assessing growth potential and sustainability using the developed classification and prediction models, aiding investors in making data-driven investment decisions and contributing to the development of the early startup ecosystem.

• Korean Journal of Occupational Health Nursing
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• v.11 no.2
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• pp.108-120
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• 2002

This study analyzed the managerial efficiency of 11 organizations, the branch centers of a occupational health service organization in Korea, using the Data Envelopment Analysis (DEA) method. The DEA is a good method for evaluating health services since it can handle multiple inputs and outputs simultaneously, and also identify the sources and amount of inefficiency. The author approached this study using two efficient models: the monetary value model and the real value model. The DEA method based on the monetary value model included cost factors, while the real value model excluded cost factors. The input variables used were manpower of physicians, medical technicians, nurses, industrial hygienists and administrators; labor, maintenance, and material expenses. The output variables used were the number of medical examinations, workplace evaluations, group health management services and income from each service. The major results were as follows: First, in the monetary value model, 6 out of 11 organizations (54.6%) showed an efficiency score of 1.0, which means that they have been operating in very efficient ways. However, 5 organizations (46.4%) showed themselves to be relatively inefficient. Second, in the real value model, 7 out of 11 organizations (63.4%) showed an efficiency score of 1.0, which means they have been operating efficiently, while 4 organizations (46.4%) showed themselves to be relatively inefficient. Third, the reliability of DEA method were analyzed by comparing the results of the monetary value model and real value model. The results of 8 out of 11 organizations were same in terms of being efficient or not. Thus, the DEA could be a valid application method for occupational health service organizations. Fourth, the organizations that displayed common inefficiency in both the monetary value model and in the real value model 3, 9, and 10, were also considered to be managed inefficiency from expertise opinion. In summary, this study evaluated the efficiency of occupational health service organizations applying the DEA method with different variables, and found that the results of analysis could be valid in terms of both modeling and expert sense. In the future, the DEA method will be used as a useful tool to identify and evaluate the efficiency of occupational health service organizations through more applications and refinements.