• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.16 no.12
• /
• pp.8719-8727
• /
• 2015

The purpose of this study is to examine the production efficiency of Rose farm and to explain the factors of the inefficiency. To analysis the production efficiency, SFA(Stochastic Frontier Analysis) and DEA(Data Envelopment Analysis) methods are measured, and then, Tobit regression model is used to analysis the influential factors on the production efficiency. As a result, first, the production efficiency by SFA is 88.4%, and by DEA, results are 78.5% and 85.2% in the CRS and VRS model, respectively. In particular, the production efficiency of the measurement results of the two methods are complementary, it is described in the same order of efficiency of each management body. Second, the results of tobit model shows that 6 input-factors are significant, and seed/nursery and material costs, which have the largest regression coefficient value and positive effect on production efficiency, are the most influential factors. Therefore, the results of this study indicates Rose farm can enhance their management efficiency by increasing amount of the seed/nursery and material costs.

• Journal of Korea Port Economic Association
• /
• v.31 no.1
• /
• pp.85-110
• /
• 2015

The purpose of this paper is to show the clustering trend and the empirical comparison and to choose the clustering ports for 3 Korean ports(Busan, Incheon and Gwangyang Ports) by using the Fuzzy(Average Index Transformation) DEA and Cross-efficiency models for 38 Asian ports during 11 years(2001-2011) with 4 input variables(birth length, depth, total area, and number of crane) and 1 output variable(container TEU). The main empirical results of this paper are as follows. First, clustering results by using Fuzzy(AIT)DEA show that 3 Korean ports[Busan(56.29%), Incheon(57.96%), and Gwangyang(66.80%) each]can increase the efficiency. Second, according to Cross-efficiency model, Busan(Hongkong, Kobe, Manila, Singapore, and Kaosiung etc.), Incheon(Aquaba, Dammam, Karachi, Mohammad Byin Oasim and Davao), and Gwangyang(Damman, Yokohama, Nogoya, Keelong, Kaosiung, and Bangkok) should be clustered with those ports in parentheses. Third, when both Fuzzy(AIT)DEA and Cross-efficiency models are mixed, the empirical result shows that 3 Korean ports[Busan(71.38%), Incheon(103.89%), and Gwangyang(168.55%) each]can increase the efficiency. The efficiency ranking comparison among the three models by using Wilcoxon Signed-rank Test was matched with the average level of 66%-67%. The policy implication of this paper is that Korean port policy planner should introduce the Fuzzy(AIT)DEA, and Cross-efficiency models with the mixed two models when clustering is needed among the Asian ports for enhancing the efficiency of inputs and outputs. Also, the results of SWOT analysis among the clustering ports should be considered.

• Environmental and Resource Economics Review
• /
• v.30 no.1
• /
• pp.79-105
• /
• 2021

In the circumstance of standing out the climate change issue, the purpose of this study is to compare the efficiency of offshore and coastal fisheries according to whether or not greenhouse gas (GHG) emissions are considered, and then to present policy alternatives based on the analysis results. For analysis, the traditional data envelopment analysis (DEA), the slacks-based measure (SBM) and the SBM-undesirable models were used, and robust analysis of variance (ANOVA) and Wilcoxon Signed-rank tests were performed. As a result, the study showed that the average efficiency of fisheries decreased as the traditional DEA extended to the SBM model considering the slack and the SBM-undesirable model including the GHG emissions. Specifically, the average efficiency of the traditional DEA model, SBM model, and SBM-undesirable model was analyzed as 0.7350, 0.5820 and 0.4976 respectively. In addition, the results of the robust ANOVA and Wilcoxon Signed-rank tests all showed that there are statistically significant differences in efficiency between offshore and coastal fisheries as well as among traditional DEA, SBM and SBM-undesirable models. As a policy alternative to the analysis, it was suggested that to improve the efficiency of coastal and offshore fisheries, it is necessary to actively implement the new fishing vessel project and develop smart and electric hybrid fishing vessels.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2007.05a
• /
• pp.183-187
• /
• 2007

유역에서 토사유실로 인한 고농도 탁수의 발생은 현장조사와 수치모형 해석으로 평가될 수 있다. 하지만 현장조사로는 토사유실을 정량화하기에는 제한적이므로 수치모형의 적용이 요구된다. 토사유사예측을 위한 모형 적용 시, 시공간 분석을 위해서 물리적 기반 분포형 혹은 준 분포형 모형이 선호된다. 본 연구에서는 임하 안동 유역의 유출 및 토사유실 분석을 위하여 SWAT 모형 및 HSPF 모형을 적용하였다. 두 모델의 유량 검 보정은 유역 내에 수위 관측 자료(1999년${\sim}$2006년)를 이용하였으며 유사농도는 2006년 하절기 현장 조사를 통해 보정되었다. SWAT 모형의 일별 유출량 변화에 대한 Nash-Sutcliffe 효율계수는 $0.43{\sim}0.76$의 범위로 전반적으로 측정 유량을 잘 모의 하는 것으로 나타났다. HSPF 모형은 SWAT 모형과 마찬가지로 높은 효율의 일별 유출량 예측성을 보였다. 그러나 두 모델은 첨두 유량을 과소산정 하였다. 두 모형의 그래픽 분석결과 측정 유사 농도를 잘 모의하였고, 특히 HSPF 모형은 강우사상에 따른 시간별 실측값의 경향을 잘 예측하였다. 두 모형의 예측성 비교 시, 유출량은 SWAT 모형이 HSPF 모형이 비해 더 잘 모의하였으며 유사 농도는 HSPF 모형이 더 높은 정확성을 보였다. 본 연구의 결과는 향후 각 소유역별로 탁수를 유발하는 토사 유실량 평가, 유역의 토사유실 저감대책 효과분석 및 저수지 모형과의 연계를 통한 유입된 탁수의 효율적인 관리대책 수립에 이용될 것으로 사료된다.

• Korean Journal of Construction Engineering and Management
• /
• v.15 no.5
• /
• pp.103-114
• /
• 2014

Data envelopment analysis (DEA) measures the relative efficiency of decision making units (DMUs) with multiple performance factors that are grouped into outputs and inputs. DEA has proven to be superior to simple aggregation of performance measures, and is also useful for evaluating the performance of construction companies for comparison with competitor performance. The purpose of this study was to survey literatures on the application of DEA methodology and to propose a methodological scheme to measure the performance of construction organizations. Articles on previous studies were surveyed and examined as part of a comprehensive review. The survey revealed that the application of DEA in the construction industry was li mited. Further, the survey indicated that there is a need for the development of a methodological framework on the special goals and subjects of performance measurement, methods of data structure and collection, selection of appropriate DEA models, analysis of results, and post-test. Based on the survey, this study identified and discussed the types of major issues and topics for future studies from a methodological perspective, which could be helpful to researchers interested in using DEA to study performance issues in construction organizations.

• Korean Business Review
• /
• v.23 no.2
• /
• pp.53-75
• /
• 2010

Gangwon-do has evaluated the result of technical support business and marketing support business separately as a part of enterprise support business, and the evaluation, targeting enterprises, has been restricted to the investigation of satisfaction only. The study develops the model that assesses the efficiency of the enterprises using DEA, the econometric model which is approved the utility in efficiency evaluation, and evaluates it through the model. As a result, the model can be developed to the appropriate variable of the enterprise support business using the elements of input and output in the business. And by using the model of DEA, it is suggested the efficiency measurement of each enterprises' and improvement that inefficient enterprises must have. Especially, it is important to assess the efficiency of supporting enterprises primary.

• Journal of Digital Convergence
• /
• v.10 no.9
• /
• pp.159-164
• /
• 2012

Although the display industry plays an important role in the entire Korean economy, few empirical research has analyzed the efficiency of display companies. The purpose of this paper is to measure and analyze efficiency of korean listed display firms using DEA(Data Envelopment Analysis) models. We evaluate the CCR and BCC efficiency in DEA models and the return to scale of the Korean listed display companies. The benchmarking companies and efficiency value for the display companies with inefficiency are also provided to improve their efficiency. We analyzed the 44 listed companies consisted of 7 listed on KOSPI and 37 listed on KOSDAQ at the end of 2010. The analysis results show six companies whose values of CCR are 1, and fourteen firms whose values of BCC efficiency are 1. In additions, the six companies have the scalability efficiency. Eventually the efficiency analysis can provide the valuable information for inefficient companies to find benchmarking companies and to improve their efficiency.

• Korea Trade Review
• /
• v.41 no.3
• /
• pp.27-42
• /
• 2016

This study is to investigate seaport clustering by using meta-frontier and cross-efficiency models. Data covers the 13 Asian ports during 2009, 2010 and 2013 with 3 inputs(depth, total area, and number of cranes) and 1 output(TEU). Correlations coefficient from cross-efficiency matrix are used for measuring clustering dendrogram. After that, meta-frontier analysis for investigating whether the clustering using cross-efficiency method increases the meta-efficiency. Empirical main results are as follows: First, group efficiencies of Busan, Incheon, and Gwangyang ports are increased. Second, meta and group efficiencies of China ports are greater than those of Korean ports. Third, distortion of technology gap of Gwangyang is lower than that of Busan and Incheon. Fourth, Gwangyang, clustering with Ningbo, Chingtao, Tokyo and Caosung ports in 2009 and with Dubai port in 2013 can increase the efficiency. Fifth, to enhance the efficiency, Busan port should be clustered to group 2 in 2010 and group 1 in 2013, and Incheon port clustered to group 2 in 2010 and 2013. Fifth, it is empirically investigated that Busan, Incheon and Gwangyang ports can increase the efficiency by using Cross-efficiency and Meta-frontier models. Port policy planner should promote the clustering policy for Busan with Hong Kong, Shanghai, and Singapore, Incheon and Gwangyang with Chingtao, Nagoya, Ningbo, Tokyo, and Kaoshung ports.

• The Korean Journal of Financial Management
• /
• v.7 no.1
• /
• pp.1-20
• /
• 1990

In most of studies on market efficiency, the stability of risk measures and the normality of residuals unexplained by the pricing model are presumed. This paper re-examines stock splits, taking the possible violation of two assumptions into accounts. The results does not change the previous studies. But, the size of excess returns during the 2-week period before announcements decreases by 43%. The results also support that betas change around announcements and the serial autocorrelation of residuals is caused by events. Based on the results, the existing excess returns are most likely explained as a compensation to old shareholders for unwanted risk increases in their portfolio, or by uses of incorrect betas in testing models. In addition, the model suggested in the paper provides a measure for the speed of adjustment of the market to the new information arrival and the intensity of information contents.

• Journal of Korea Port Economic Association
• /
• v.25 no.3
• /
• pp.139-164
• /
• 2009

The purpose of this paper is to investigate the value chain efficiency of Korean port investment by using the newly developed multi-year and multi-stage value chain efficiency model of DEA(Data Envelopment Analysis). Inputs[port investment amount, cargo handling capacity, and berthing capacity], and outputs[cargo handling amount, number of ship calls, revenue, and score of customer service satisfaction] are used during 14 years(1994-2007) for 20 Korean seaports by using two kinds of DEA models. Empirical main results are as follows: First, Model 1 shows that the ranking order of multi-stage value chain efficiency is Stage 2, Stage 3-1, Stage 1, and Stage 3-2. And according to the value chain average efficiency scores, ranking order is stages 2, 1, 3-1, and 3-2. In Model 2, 3(Incheon, Mogpo, and Jeju) out of 9 ports show the ranking order of Stages 2, 3-2, 3-1, and 1. And value chain average efficiency scores rank in order of Stages 2, 3-2, 3-1, and 1. Second, the difference among the value chain efficiency scores of each stage comes from the efficiency deterioration of all ports except Stages 2 and 1 in Model 1. In Model 2, value chain efficiency scores among the Stages 3-1, 3-2 compared to Stage 1 were deteriorated. The main policy implication based on the findings of this study is that the manager of port investment and management of Ministry of Land, Transport and Maritime Affairs in Korea should introduce the multi-year, multi-stage value chain efficiency method for deciding the port investment amount and evaluating the effect of port investment after considering the empirical results of this paper carefully.