• Journal of Korean Society for Quality Management
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• v.47 no.1
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• pp.33-46
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• 2019

Purpose: This study proposed a DEA (Data Envelopment Analysis)-based stepwise benchmarking target selection for inefficient DMU (Decision Making Unit) to improve its efficiency gradually to reach most efficient frontier considering resource (DEA inputs and outputs) improvement preferences. Methods: The proposed method proceeded in two steps. First step evaluates efficiency of DMUs by using DEA, and an evaluated DMU selects benchmarking targets of HCU (Hypothesis Composit Unit) or RU (Real Unit) considering resource improvement preferences. Second step selects stepwise benchmarking targets of the inefficient DMU. To achieve this, this study developed a new DEA model, which can select a benchmarking target of an inefficient DMU in considering inputs or outputs improvement preference, and suggested an algorithm, which can select stepwise benchmarking targets of the inefficient DMU. Results: The proposed method was applied to 34 international ports for validation. In efficiency evaluation, five ports was evaluated as most efficient port, and the remaining 29 ports was evaluated as relative inefficient port. When port 34 was supposed as evaluated DMU, its can select its four stepwise benchmarking targets in assigning the preference weight to inputs (berth length, total area of pier, CFS, number of loading machine) as (0.82, 1.00, 0.41, 0.00). Conclusion: For the validation of the proposed method, it applied to the 34 major ports around the world and selected stepwise benchmarking targets for an inefficient port to improve its efficiency gradually. We can say that the proposed method enables for inefficient DMU to establish more effective and practical benchmarking strategy than the conventional DEA because it considers the resource (inputs or outputs) improvement preference in selecting benchmarking targets gradually.

• Health Policy and Management
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• v.10 no.4
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• pp.75-98
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• 2000

This study applied Data Envelopment Analysis(DEA) and Ratio Analysis and Regression Analysis to a set of Korean Public Corporation Medical Centers to evaluate their relative human resource efficiencies. The output measure used in this study was based on health insurance system which was used in both in-patient departments and out-patient departments. Inputs included working time of the doctors, nurses, technicians, and managerial department staff. Based on the data provided on the inputs and outputs, the analysis showed 23 of the 34 hospitals to be relatively inefficient. Each hospital with an efficiency rating of less than 1 was considered relatively inefficient. In addition, managerial strategies based on dual variables were constructed to indicate the manner In which inefficient hospitals may be made efficient. A subsequent analysis of t-test revealed that the bed occupancy rate, medical revenue per 100beds, value added revenue per staff, medical revenue per staff were statistically significant. The results of this study suggest the DEA is a promising tool for evaluating relative human resource efficiency in hospitals which have multiple inputs and outputs and where the efficient production function is not specifiable with any precision. But it is considered that efficiency evaluations may be most effective]y accomplished by Incorporating a combination of methodologies such as ratio analysis and regression analysis.

• Journal of Energy Engineering
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• v.28 no.4
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• pp.61-75
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• 2019

This article analyzed the direct impact of resource inputs on business performances of Korean environmental companies conducting R&D, and the mediation effects of product-, process-, organization-, marketing-innovations between resource inputs and business performances. We conducted the mediation analysis using SPSS and Process Macro, based on a survey data from the Korean environmental companies. The article found that ① resource inputs have directly had a positive impact on business performances, and ② innovations have mediated them. ③ But among 4 types of innovations, the only mediation effect of organization-innovation has been verified, and the others have not appeared. Considering the above results, the following policy implications can be suggested. ① It is necessary to reinforce related policies so that companies can improve business performances through innovation. ② The government needs to carry out the prudent supporting policies so that innovations in product, process, and marketing can lead to business performances. This article has the limitation of using the survey data, and needs further researches on the sectoral system of innovation for Korean environmental industry.

• Environmental and Resource Economics Review
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• v.18 no.4
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• pp.745-766
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• 2009

It is not valid to measure the degree of market power based on the markup of price over marginal market cost in an industry for which the market price of some inputs is not available because those inputs are then excluded in estimating the dual total cost function. If the roles of those inputs are ignored, the markup of price over marginal market cost is likely to be positive in the perfectly competitive industry. In order to have accurate market power markups for the environmentally regulated Korean iron and steel industry, in which the market price of raw material and the price of abatement capital are hard to obtain, in this paper, a dual cost function is derived given the optimal quantities of raw material and abatement capital, and then estimated jointly with the supply relation. The annual average degree of market power for the industry is estimated to be 0.49 over the period 1982~2001. Ignoring environmental regulation would overstate the degree of market power by about 8 percent.

• Environmental and Resource Economics Review
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• v.23 no.3
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• pp.453-472
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• 2014

Analyzing the effects of carbon emissions trading, which is scheduled to be introduced in Korea in 2015, requires an accurate assessment of $CO_2$ abatement costs by both industries and firms. Firms faced with regulatory constraints are unlikely to minimize their production costs due to rising production costs caused by allocative inefficiency of inputs. The use of a distance function would results in underestimation of $CO_2$ abatement costs, because it fails to capture the allocative distortion costs. Recognizing the disadvantage of the previous approach, first, this paper tests for allocative efficiency of input for the Korean steel industry over the period 1990-2010, then derives the marginal $CO_2$ abatement costs by applying a cost function approach. The hypothesis of allocative efficiency in inputs is rejected and the steel industry pays an annual average cost of 92,000 won in removing an additional ton of $CO_2$ over the sample period.

• Environmental and Resource Economics Review
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• v.23 no.1
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• pp.43-65
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• 2014

In this paper, we test for allocative efficiency of productive inputs including electricity and measure the divergence between the actual and optimal level of electricity for the chemical products, which is a relatively highly electricity-intensive sector in Korean manufacturing industries, by estimating a shadow cost function. Supposing cost minimization subject to market prices was achieved, we derive the price elasticities of demand for each input and simulate the impact of a 10% increase in power rate on its demand and supply price by estimating jointly a cost function with an inverse supply relation. The null hypothesis of allocative efficiency of inputs is rejected over the period 1982-2006. On average, electricity is used more than optimal level by 98% per year. The demand for electricity decreases by 11.4%, and supply price, on average, falls by 0.08%, other things being equal.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1149-1151
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• 1996

In the last several years, considerable attention has been focused on the problem of designing observers for linear systems with unknown inputs. Since UIO(unknown inputs observer) has the derivative of the outputs, it is very sensitive to measurement noises. Therefore this note propose an algebraic approach to UIO design to alleviate the prescribed problems. Since the proposed method has simple form to estimate state and unknown input and robustness to sensor noise, we believe that it is very attractive in practice.

• Journal of Korean Society of Forest Science
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• v.94 no.5 s.162
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• pp.302-306
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• 2005

Litterfall and nutrient inputs were measured in even-aged coniferous plantations (a 31-year-old Pinus rigida and a 31-year-old Larix leptolepis) on a similar site condition in the Forest Practice Research Center, Gyeonggi Province. Litterfall was collected monthly from circular littertraps (collecting area: $0.50m^2$) for three years between April 1997 and February 2000. Average total annual litterfall was significantly higher for pine (5,802 kg/ha/yr) than for larch (4,562 kg/ha/yr) plantations. Needle litter in both plantations accounted for about 63% of total litterfall. Litterfall in the larch was distributed as follows: needle > other leaf > branch > miscellaneous > bark, while it was needle > miscellaneous > other leaf > branch > bark in the pine plantation. There was no temporal variation in needle litter, other leaf and bark during the 3 year study period. The concentrations of all nutrients (N, P, K, Ca, Mg) in needle litter were significantly higher in the larch than in the pine plantations. The annual nutrient concentration of needle litter in the larch varied among the years, whereas no year variation of needle litter was in the pine except for phosphorus (P). Nitrogen (N) and P inputs by needle litter were significantly higher for larch than for pine plantations established on a similar soil. The differences in N and P inputs were attributed to lower nutrient concentration in pine needle litter compared with larch needle litter, not to total needle litter mass. Annual inputs of nutrient in both plantations were not significantly different among years except for K of the larch although there was yearly different in needlefall mass and nutrient concentration during the 3-year observed period. The results indicate that the mechanisms of litterfall and nutrient inputs vary considerably between pine and larch plantations established on a similar site condition.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.2
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• pp.65-73
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• 2018

The dynamic capabilities of sensing market signals, creating new opportunities and reconfiguring resources and capabilities to new opportunities in a rapidly changing economic environment determines the competitiveness of the enterprise to create added value and survival. This study conceptualized a two-stage performance measurement framework based on the casual model of resource (input)-process-performance (output). We have developed a 'Process capability index' that reflect the dynamic capabilities factors as a key intermediary product linking resource inputs and performance outputs in enterprise performance measurement. The process capability index consists of four elements : manpower (level of human resource), operation productivity, structure and risk management. The DEA (Data Envelopment Analysis) model was applied to the developed performance indicators to analyze the branch office performance of a telecom company. Process capability efficiency (stage 1) uses resource inputs to reach a certain level of process capabilities. In performance result efficiency (stage 2), the process capabilities are used to generate sales revenues and subscribers. The two-stage DEA model derives intermediate output values that optimize the individual stages simultaneously. Some branch offices in the telecom company have focused on process capability efficiency or some other branch offices focused on performance result efficiency. Positioning map using two-stage efficiency decomposition and benchmarking can help identify the sources of inefficiencies and visualize strategic directions for performance optimization. Applications of two-stage DEA in conjunction with the case study that are meaningfully used in performance measurement areas have been scarce. In particular, this paper has the contribution to present a new performance measurement model considering the organization theory, the dynamic capabilities.

• Environmental and Resource Economics Review
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• v.9 no.2
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• pp.349-371
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• 2000

Data Envelopment Analysis model is a linear programming based technique for measuring the relative performance of organizational units where the presence of multiple inputs and outputs makes comparison difficult. A common measure for relative efficiency is weighted sum of outputs divided by weighted sum of inputs. DEA model allows each unit to adopt a set of weight that shows it in the most favorable light in comparison to the other unit. In this paper, we present the mathematical background and characteristics of DEA model, and give a short case study where we apply the DEA model to evaluate the relative efficiencies of 51 global electricity companies. The technical efficiency and scale efficiency are also to be investigated. Generating capacity and the number of employees are used for input data, and revenue, net profit and electricity sales are used for output data. We find that the companies with 100% relative efficiency are only 9 among 51 electricity companies. And the technical and scale efficiency of KEPCO is 98.7% and 78.89%, respectively. This means that the inefficiency of KEPCO is caused by the scale inefficiency. The analysis shows that the employees should be decreased by 15% at minimum to get the 100% efficiency. The result suggests that KEPCO needs the structural reform to improve the efficiency.