• IE interfaces
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• v.22 no.1
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• pp.44-55
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• 2009

We propose a method for selection of input-output factors in DEA. It is designed to select better combinations of input-output factors that are well suited for evaluating substantial performance of DMUs. Several selected DEA models with different input-output factors combinations are evaluated, and the relationship between the computed efficiency scores and a single performance criterion of DMUs is investigated using decision tree. Based on the results of decision tree analysis, a relatively better DEA model can be chosen, which is expected to well represent the true performance of DMUs. We illustrate the effectiveness of the proposed method by applying it to the efficiency evaluation of 101 listed companies in steel and metal industry.

• Journal of the Korean Operations Research and Management Science Society
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• v.23 no.3
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• pp.75-90
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• 1998

The improper use of input and output factors in DEA has a critical and negative impact on the efficiency measurement and the discernment of decision making units(DMUs) : hence the proper selection Process of the factors should precede the actual applications of DEA. In this paper, we propose a new approach to selecting proper factors based on Tofallis' partial efficiency evaluation method(1996). With the approach, the factors aye clustered by measuring their respective partial efficiencies and analyzing the rank correlations of them. The method and procedure we propose in this paper are then applied to measure the efficiencies of the public libraries in Seoul District area, and the results show that the proposed approach can provide meaningful information to improve discernment of the DMUs while using less number of input factors (and less information). The proposed method can be effectively used in the situation where the number of the DMUs to be considered is relatively small compared to the number of available input and output factors, which usually lessens the power to identify the inefficient units in DEA.

• Journal of Integrative Natural Science
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• v.8 no.4
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• pp.293-304
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• 2015

This study examined the factors which have influence on the welfare facilities for the elderly and analyzes their efficiency. It investigated theoretical studies and preceding studies and divided the efficiency evaluation factors into input and output factors. Input factors included budget, the number of workers and clients and facility area and output factors were operation management, the number of clients, profitability and welfare for the elderly. To sum up the analysis results of evaluation factors of welfare facilities for the elderly, the analysis of relative importance of input showed that budget was most important. As a result of analyzing the relative importance among detailed items, balance sheet and professional manpower were highest. Input factors by facility types showed that the budget for utility facilities and living facilities were highest. In output factors, utility facilities and living facilities were highest in management systematization and welfare for the elderly, respectively. In efficiency evaluation, utility facilities for the elderly showed 100% of efficiency in CCR and BCC models. In welfare facilities for the elderly, while CCR model showed 100% of efficiency in facility types A, C, D, and F, the efficiency was low in facility B (79.89%), E (77.14%), and G (80.72%). In BCC model, facility E was low as 78.69%. In efficiency comparison between utility facilities and living facilities for the elderly welfare, the efficiency of utility facilities for the elderly welfare was higher. Therefore, this study investigated the efficiency of welfare facilities for the elderly as its main purpose and presented policy suggestions based on the research results as the alternative.

• Journal of the Korean Professional Engineers Association
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• v.32 no.6
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• pp.40-43
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• 1999

The R&D productivity has the same meaning as that of general meaning. Its input includes budget, facility, schedule, idea and target, and its output includes patent, paper, technological innovation and revenue increase and technology accumulation influenced by these factors. The choice of R&D item which will have the large effectiveness after customization, resource input of proper level, application of efficient development schema, effective usage of development output, objective appraisal for the R&D output and extension for the future project are the main factors for which is suggested to enhance the R&D productivity. The management's expectation for R&D can be represented as the innovativeness of output and potential influence to outsiders. The speedy output, even if incremental investment more than planning happens, will eventually result in the productivity enhancement of the enterprise, and managers must not encounter the opportunity loss in return for the excessive investment control.

• Journal of Navigation and Port Research
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• v.41 no.5
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• pp.337-344
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• 2017

In the offshore crane system, the requirements on the operating safety are extremely high due to many external factors. Rope extension is one of the factors producing vertical vibration of load. In this study, the load is carried by the motor-winch actuator control and the rope is modeled as a mass-damper-spring system. To control the load position and suppress the vertical vibration of the load, a control system based on input-output linearization method is proposed. By the simulation and experiment results with pilot crane model, the effectiveness of proposed control method is evaluated and verified.

• IE interfaces
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• v.12 no.4
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• pp.551-556
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• 1999

In this paper, we compare the performance of three data mining classification algorithms(neural network, decision tree, logistic regression) in consideration of various characteristics of categorical input and output data. $2^{4-1}$. 3 fractional factorial design is used to simulate the comparison situation where factors used are (1) the categorical ratio of input variables, (2) the complexity of functional relationship between the output and input variables, (3) the size of randomness in the relationship, (4) the categorical ratio of an output variable, and (5) the classification algorithm. Experimental study results indicate the following: decision tree performs better than the others when the relationship between output and input variables is simple while logistic regression is better when the other way is around; and neural network appears a better choice than the others when the randomness in the relationship is relatively large. We also use Taguchi design to improve the practicality of our study results by letting the relationship between the output and input variables as a noise factor. As a result, the classification accuracy of neural network and decision tree turns out to be higher than that of logistic regression, when the categorical proportion of the output variable is even.

• East Asian Journal of Business Economics (EAJBE)
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• v.9 no.1
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• pp.41-51
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• 2021

Purpose - The purpose of this study is to propose strategies of improving efficiency of 20 listed port companies in China based on analysis of their input-output indexes from 2014 to 2018. Research design, data, and methodology - In this paper, the relevant input-output indicators of 20 listed port companies in China from 2014 to 2018 were adopted. Data derived from the company annual reports announced by Shanghai stock exchange and Shenzhen stock exchange. Comprehensive efficiency and pure technical efficiency were measured from output perspective by DEA and Malmquist index, and efficiency changes and regional efficiency were analyzed. Result - The results showed that the efficiency value of 20 listed port companies in China fluctuated and increased during 2014-2018, regional efficiency was unbalanced, and change of MPI was influenced by internal factors and external factors. Listed port companies affected by internal and external factors needed to make appropriate response to internal and external factors. Conclusion - The research conclusion can provide important reference information about management and planning for port companies in China and related areas. However, this paper is limited to the availability of data. So the improvement scheme for listed companies in inefficient regional ports needs further study, such as using AHP method.

• Economic Analysis
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• v.26 no.4
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• pp.65-97
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• 2020

The purpose of this paper is to analyze the effects of exports on Korea's employment and to decompose driving factors of change in Korea's employment embodied in exports (EEX). This study uses a multi-regional input-output (MRIO) and structural decomposition analysis (SDA) for empirical analysis, and uses a dataset of World Input-Output Tables (WIOTs) and Socio-Economic Accounts (SEAs) from the World Input-Output Database (WIOD). The main findings of the empirical results are summarized as follows. First, Korea's EEX continues to increase and Korea's share of EEX compared to total employment shows an upward trend. However, Korea's employment inducement coefficient of value-added exports showed a downward trend during the 2000-2014 period. Second, final demand from three countries (China, the United States, and the Rest of the World (RoW)) has affected a significant portion of Korea's EEX. Finally, from the results of the SDA, the effect of changes in final demand was the most important driving factor for the increase in Korea's EEX. Based on the results of this empirical analysis, this study discusses useful policy implications that could increase domestic employment in Korea.

• Journal of Information Technology Services
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• v.10 no.2
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• pp.177-188
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• 2011

This paper proposes a DEA model for the performance evaluation of each brand of coking coals in an integrated steel mill. The performance is defined as the efficiency which is the ratio of two linear combinations of the output factors to the input factors. There is only one input factor considered in the model : unit price of each brand based on CIF. Five output factors are chosen in consideration of their impact to the quality of cokes such as Ash, VM, LMF, TD, and Rm. Some of the output factors are treated as undesirable in DEA model because the quality criteria are given by the range. The CCR and BCC efficiencies are derived by the DEA model, and the scale efficiency is calculated, too. Each brand of coking coal is classified into four categories according to the CCR and BCC efficiencies, and the most inferior brands are identified as a result. The impact of the input and output factors to the efficiency is analyzed using a multiple regression, then the unit price is revealed as the most critical among them. Also, ANOVA results show that there exist efficiency differences among the coal types and the countries imported, respectively. Finally, the quantitative projection for the inefficient brands is performed if they are to be efficient. The result could be utilized in selecting the good or bad brands of coking coal based on the efficiency in an integrated steel mill. Also, this model will be used to assess the relative efficiency of a new brand of coking coal if it is a candidate to be imported.

• Journal of Digital Contents Society
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• v.6 no.4
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• pp.235-242
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• 2005

This Study examines influencing factors such as input, process, and output variables on1 student's satisfaction in cyber-education. That is to study on the effectiveness of input, process, and output variables for cyber-education and how does student's interaction moderate influencing factors and student satisfaction. The study was carried out through literature and empirical study. Questionnaire was used to varify the hypothesis based on which the input-process-output with system models were established. The result of hypothesis verification in this study is as follows : First, learning hour and grade showed a positive influence on the students' satisfaction in learning factors. Second reliant of professor, recognized teaming participate, and contents showed a positive influence on the students' satisfaction in system factors. Third, an interesting findings emerged throughout the analysis, showed that process variables were rather meaning factor than input variables.