• Journal of Korean Society for Quality Management
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• v.35 no.3
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• pp.21-36
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• 2007

This article is to analyze the service efficiency of public sector using Data Envelopment Analysis(DEA). We tried to measure the public service quality and overall satisfaction by using several DEA models, degree of combination and top2box which is a little bit different methodology from traditional ones. We used CCR, Super-efficiency and Slack based measure(SBM) model in DEA to measure public service efficiency of the 16 public institutions(7 City Halls and 9 Provincial offices). Since the traditional method based on the measurement model(CCR, BCC) has the fundamental problems without taking account of the existence of slacks inputs and outputs in several efficient units, we suggest to measure the exact amount of efficiency and inefficiency of the public sector and rank analysis many efficient units exactly through the slacks-based measure model(SBM)

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2001.10a
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• pp.213-217
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• 2001

This paper deals with the estimation of efficiency of Telecommunication Operators(TOs) using DEA (Data Envelopment Analysis). The measure of efficiency using DEA accomplishes next two steps. First, the efficient frontier is derived using the data of input and output. And then the efficiency of the decision making units are measured by the distances from this frontier To measure efficiency, we consider a one-output, three-input production function. We use the tangible assets, investment cost, the number of employees for input data and measure the output by the revenue. After measuring the efficiency, We can compare the domestic TOs with the international TOs and the wire TOs with wireless ones by average efficiency. After accomplishing the analysis of efficiency, the internal/external efficiency is measured simultaneously through correlation between efficiency and profitability, quality level.

• Journal of Technology Innovation
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• v.13 no.2
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• pp.207-222
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• 2005

A prerequisite for making R&D more productive is to able to measure its productivity. Most of the previous studies on this topic have attempted to measure R&D productivity at the firm or industry levels. In this study, however, R&D productivity is measured at the national level to provide R&D policy implications, particularly for Asian countries. Contrary to the previous studies where total factor productivity was adopted, this study employs the data envelopment analysis (DEA) approach to measure R&D productivity. DEA is a multi-factor productivity analysis model for measuring the relative efficiency of each Decision Making Unit (DMU). In addition to the basic DEA model that includes all inputs and outputs, five additional models are constructed by combining single input with all outputs and single output with all inputs in order to measure specialized R&D efficiency. In this study, the twenty-seven countries are classified into four clusters based on the output-specialized R&D efficiency: inventors, merchandisers, academicians, and duds. Then, the characteristics of the Asian countries with respect to R&D efficiency are identified. It is found that Singapore ranks high in total efficiency, and Japan in patent-oriented efficiency. Meanwhile, China, Korea, and Taiwan are found to be relatively inefficient in R&D. We expect that the findings from this study will be able to provide directions for R&D policy-making of the Asian countries.

• Environmental and Resource Economics Review
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• v.9 no.5
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• pp.811-827
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• 2000

Since improved thermal efficiency reduces capacity requirements and energy costs, electricity producers often treat thermal efficiency as a measure of management or economic performance. The conventional measure of the thermal efficiency of a fossil-fuel generation system is the ratio of total electricity generation to the simple sum of energy inputs. As a refined approach, we present a novel thermal efficiency measure using the concept of the Divisia index number. Application of this approach to the Korean power sector shows improvement of thermal efficiency of 1.1% per year during 1970-1998. This is higher than the 0.9% improvement per year given by the conventional method. The difference is attributable to the effect of fuel substitution. In the Divisia decomposition context, we also show the limitations of the popular $T{\ddot{o}}rnqvist$ index formula and the superiority of the Sato-Vartia formula.

• Journal of Korea Trade
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• v.25 no.5
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• pp.93-109
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• 2021

Purpose - The logistics industry is often featured by its location relevance and industrial concentration. Industrial concentration is conducive to the effective transmission of information by reducing transaction costs and improving transaction efficiency, thus promoting the development of trade. The main purpose of this paper is to measure the spatial total factor productivity and location quotient of the logistics industry in Korea, and to study the impact of the logistics industry efficiency and agglomeration effect on import and export trade in Korea. Design/methodology - First, used the spatial stochastic frontier method to measure the spatial total factor productivity of the logistics industry in Korea, this serves as the efficiency index of the logistics industry in various regions of Korea. Second, calculated the location quotient (LQ) of the logistics industry to measure the industry's concentration degree. Third, employed a spatial econometric model to analyze the impacts of factors such as the efficiency and concentration levels of the logistics industry on import and export trade in Korea. Findings - This study's main findings can be summarized as follows: this study found that the overall efficiency of the logistics industry in Korea needs to be improved, even though it showed an upward trend in all regions of the country; Moreover, the agglomeration level of Korea's logistics industry needs to be improved; Finally, the positive spatial correlation and industrial agglomeration effect of Korea's logistics industry had a positive impact on the country's import and export trade. Originality/value - This study is innovative in terms of research perspective and methods. Most of the previous studies have measured the development level of the logistics industry using the logistics performance index (LPI), Fewer studies have assessed through the spatial total factor productivity and location quotient of the logistics industry in Korea to measure the efficiency index of the logistics industry in various regions of Korea and concentration degree, as well as there was almost no study on the impact of logistics industry efficiency and agglomeration effect on import and export trade in Korea. This study addresses this limitation by analyzing the impacts of the efficiency and agglomeration effect of the logistics industry on import and export trade in Korea.

• Proceedings of the Society of Korea Industrial and System Engineering Conference
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• 2002.05a
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• pp.177-187
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• 2002

In this paper, we consider a multi-factor, multi-cause decision making problem of supply chain. And we show how to measure the operational efficiency of the components in supply chain and also how to improve the efficiency of each component and whole supply chain. As a methodology, the data envelopment analysis (DEA) is adopted to measure the efficiency by considering weight factors such as flexibility, information sharing, logistics level, etc. The proposed algorithm allows whole supply chain to have the improved efficiency rate.

• Journal of Korean Society for Quality Management
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• v.32 no.2
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• pp.77-92
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• 2004

It is difficult but very necessary to measure the productivity of container terminals as logistics service provider. It is meaningful to find the appropriate inputs and outputs of the logistics service delivery systems and to measure the relationship between these inputs and outputs. This study proposes a model of evaluating the efficiency of container terminals. The evaluation consists of three phases. First, DEA(Data Envelopment Analysis) phase, determines the efficiency score and weights of DMUs(Decision Making Unit). This phase performs through four steps : selection of DMU, selection of DEA model, determination of input and output factors, calculation of efficiency score and weights for each DMU. Secondly, CEM (Cross Evaluation Model) phase, is to calculate the cross-efficiency scores of DMUs. This phase performs through three steps: selection of CEM, determination of cross-efficiency score for each DMU and development of cross-efficiency matrix. Finally, average cross-efficiency analysis phase is to compute the average cross-efficiency score. The proposed model discriminates among DMUs and ranks DMUs, whether they are efficient or inefficient.

• Journal of Korea Port Economic Association
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• v.18 no.1
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• pp.3-26
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• 2002

The purpose of this paper is to Investigate the productive efficiency and competitive strength of world container ports using the DEA, Super-efficiency, and FDH methods with the raw data from previous research by Jun et al.(1993). The super-efficiency measure examines the maximal radial change In input, outputs for an observation to remain efficient. Therefore, it provides a means of distinguishing between efficient observations, which would otherwise seem identical. FDH provides a good test mechanism for examining the practical implications of the choice available among alternative efficiency measures and orientations, because of the lack of convexity of its production possibility set. Both methods are complementary to DEA. This paper follows the traditional productivity analysis method overcoming the limitation of previous studies by using the DEA, FDH and Super-efficiency methods, and proposing in measure the relative competitive strength of worldwide container ports. The main empirical results of this paper are as follows: Firstly the ports of Singapore, Hongkong, Kilrung, Busan, Tokyo. and Longbeach were found to be efficient In the CCR model. The ports of Felixstowe, Bangkok, Singapore, Hongkong, Kilung, Busan, Tokyo, and Longbeach were found to be efficient in the BCC model. Secondly, super. efficiency rankings under CRS and input-oriented model are as follows: Longbeach, Keelung, Singapore, Busan, Tokyo, and Honkong. However, it was difficult In differenciate the rankings under the VRS and input-oriented model. due to major difficulties posed by the ports of Singapore, Hongkong, and Longbeach. Thirdly, the FDH method shows that the inefficient ports are Bremerhaven, Antwerp, Le Havre, Kobe, Seattle, New York The policy Implications of this study are as follows: Firstly, when port authorities want to measure the international competitive strength of container ports and enhance their productive efficiency, they should consider the traditional method as well as introducing the Super-efficiency and FDH methods. Secondly, according to the analysis results of the super-efficiency and FDH methods, poll authorities should recommend benchmarks ports and dominated ports as reference ports in order to enhance the productive efficiency of their container ports that have an efficiency rating of less than 1. Efficient ports whose efficiency ratings are over 1 in the Input-oriented Super-efficiency model should also consider the usage of input and output elements used by more efficient ports.

• Journal of Korean Society for Quality Management
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• v.36 no.4
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• pp.102-116
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• 2008

The most widely used models to study the quality of service are the SERVQUAL and SERVPERF models that measure service mechanisms. This paper is to estimate service efficiency and consistency for Retail Industry. We tried to measure the service quality and overall satisfaction by using DEA and PCI, degree of combination and top2box which is a little bit different methodology from traditional ones. Rather than using the usual method of converting the service quality index by mean value, the Service Efficiency Index(SEI) and Service Quality Consistency Index(SQCI) are used to measure the efficiency and consistency level, which in turn can be used as the new service quality indices. The result of SEI and SQCI show the efficiency frontier in retail industry that 6 DMUs are analyzed relative efficient DMUs, 12DMUs are inefficient DMUs and retail Industry consistency level appeared low(0.35-0.47) Also, there is a significant difference in terms of efficiency and consistency in the each retail industry. Finally, we showed the summarized result as the Effi-Con Matrix.

• Journal of the Korean Data and Information Science Society
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• v.17 no.3
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• pp.805-809
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• 2006

In this paper a shrinkage estimator for the measure of dispersion of the inverse Gaussian distribution with known mean is proposed. Also we compare the relative bias and relative efficiency of the proposed estimator with respect to minimum variance unbiased estimator.