• Korean Journal of Organic Agriculture
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• v.30 no.3
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• pp.351-374
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• 2022

In recent years, the development of rice industry has been highly valued by the state. In hubei area, due to the development of the modernization and the shortage of labor, traditional way of rice cultivation methods is facing serious challenges, and economic benefits have become the decisive factor for the effective promotion and application of rice cultivation methods. According to the research results, first, in the input-side analysis, in the CCR model, D5, D12, D26, D28, D32, D36 farmers with high efficiency appear. The analysis result shows that among the 60 farmers, the average efficiency is 89%, and there is an inefficiency of 11%. In the BCC model, 14 farmers were identified as high-efficiency farmers, with an average efficiency of 0.9453. Second, in direct seeding cultivation of rice, the average scale efficiency is 0.9227, while the average pure technical efficiency is 0.9644. This shows that the effect of scale efficiency is greater than that of purely technical factors, ignoring the reasons for the low operational efficiency of direct seeding cultivation farmers. It can be predicted that with the further deepening of farmers' understanding of this planting mode, the proportion of rice direct seeding may be further expanded in the future. Relevant agricultural departments should further promote this technology to farmers, study the direct seeding technology using scientific methods, and evaluate the changes of this cultivation mode. The agricultural departments of government should concern about the climate risk assessment of direct seeding rice, the environmental impact assessment caused by the extensive use of herbicides, the application of mechanical technology in the process of direct seeding, the lodging of direct seeding rice, and other related issues.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.91-110
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• 2011

This paper analyzes the cases where the hotels have increased their services and enhanced their work process through IT solutions to cope with computerization globalization. Also the cases have been studies where national hotels use the CRM solution internally to respond effectively to customers requests, increase customer analysis, and build marketing strategies. In particular, this study discusses the introduction of the CRM solutions and CRM sales business and marketing services using a process for utilizing the presumed, CRM by introducing effective DEA(Data Envelopment Analysis). First, the comparison has done regarding the relative efficiency of L Company with the CCR model, then compared L Company's restaurants and facilities' effectiveness through BCC model. L Company reached a conclusion that it is important to precisely create and manage sales data which are the preliminary data for CRM, and for that reason it made it possible to save sales data generated by POS system on each sales performance database. In order to do that, it newly established Oracle POS system and LORIS POS system concerned with restaurants for food and beverage as well as rooms, and made it possible to stably generate and manage sales data and manage. Moreover, it set up a composite database to control comprehensively the results of work processes during a specific period by collecting customer registration information and made it possible to systematically control the information on sales performances. By establishing a system which unifies database and managing it comprehensively, impeccability of data has been greatly enhanced and a problem which generated asymmetric data could be thoroughly solved. Using data accumulated on the comprehensive database, sales data can be analyzed, categorized, classified through data mining engine imbedded in Polaris CRM and the results can be organized on data mart to provide them in the form of CRM application data. By transforming original sales data into forms which are easy to handle and saving them on data mart separately, it enabled acquiring well-organized data with ease when engaging in various marketing operations, holding a morning meeting and working on decision-making. By using summarized data at data mart, it was possible to process marketing operations such as telemarketing, direct mailing, internet marketing service and service product developments for perceived customers; moreover, information on customer perceptions which is one of CRM's end-products could feed back into the comprehensive database. This research was undertaken to find out how effectively CRM has been employed by comparing and analyzing the management performance of each enterprise site and store after introducing CRM to Hotel enterprises using DEA technique. According to the research results, efficiency evaluation for each site was calculated through input and output factors to find out comparative CRM system usage efficiency of L's Company four sites; moreover, with regard to stores, the sizes of workforce and budget application show a huge difference and so does the each store efficiency. Furthermore, by using the DEA technique, it could assess which sites have comparatively high efficiency and which don't by comparing and evaluating hotel enterprises IT project outcomes such as CRM introduction using the CCR model for each site of the related enterprises. By using the BCC model, it could comparatively evaluate the outcome of CRM usage at each store of A site, which is representative of L Company, and as a result, it could figure out which stores maintain high efficiency in using CRM and which don't. It analyzed the cases of CRM introduction at L Company, which is a hotel enterprise, and precisely evaluated them through DEA. L Company analyzed the customer analysis system by introducing CRM and achieved to provide customers identified through client analysis data with one to one tailored services. Moreover, it could come up with a plan to differentiate the service for customers who revisit by assessing customer discernment rate. As tasks to be solved in the future, it is required to do research on the process analysis which can lead to a specific outcome such as increased sales volumes by carrying on test marketing, target marketing using CRM. Furthermore, it is also necessary to do research on efficiency evaluation in accordance with linkages between other IT solutions such as ERP and CRM system.

• Journal of Distribution Science
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• v.12 no.4
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• pp.23-30
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• 2014

Purpose - The purpose of this study is to analyze the efficiency of retail businesses by dividing domestic retailers into discount stores, super supermarkets (SSMs), and department stores. It suggests retail-business investment strategies by using data environment analysis (DEA) to analyze how input elements such as store area, parking lot area, number of employees, and sales management expenses for the convenience of customers positively affect business performance measurements such as sales and visiting customers per day. Research Design, Data, and Methodology - The DEA model calculates a ratio of the weighted mean of various inputs to the weighted mean of various outputs and measures the efficiency of a specific decision making unit (DMU). The study included 19 companies (five discount store DMUs, ten SSM DMUs, and four department store DMUs). Because the business elements and sizes of retail store DMUs used in this analysis are different, average per-store input and output variables were used. Data were collected from "The Yearbook of Retail Industry in Korea (2012)." DEA analysis was used to determine differences in efficiency among discount stores, SSMs, and department stores in terms of the business elements of each retail business. It was also used to determine what business elements were excessively invested in by comparing and analyzing efficiency by business elements using SPSS software's ANOVA (Analysis of Variance). Results - The CCR and BCC efficiency analysis found that the efficiency of discount stores is low. We believe that the saturation state of discount stores is a major factor. The ANOVA analysis confirms the VRS hypothesis with a statistically significant difference among the three groups, based on an analysis confidence interval of 95%. CRS and SE were not found to be significantly different among the three groups. As for the post hoc test, which concretely shows differences by group, the Scheffe's multiple comparison analysis test found the average differences between group 1 (discount stores) and group 2 (SSM) to be statistically significant. Conclusions - The DEA efficiency analysis implies that investment in input elements, including store area, parking lot area, and sales management expenses, were excessive in the case of discount stores, while SSMs need to invest more in promotion activities such as gifts, events, and coupons for customer management. Department stores have found that small companies invest excessively in input elements. Department stores need to invest in differentiated shopping mall complexes. This study was limited in acquiring statistical data; various input variables which might have shown more secure customer management and promotional expenses could not be applied. As the study was limited in various aspects of the efficiency analyses because financial analyses of the companies and of causal relationships, including satisfaction and loyalty of visiting customers, were not done, these aspects will be examined in the next study.

• Journal of the Korea Society of Computer and Information
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• v.20 no.6
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• pp.141-150
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• 2015

The aim of this study is to analysis the efficiency of the Long-term Care facilities as well as make counterproposals to conduct of efficient management for the Long-term Care facilities. The data of professionals states of Long-term Care facilities and wages state of Long-term Care facilities from regions in 2014. To analyse the data, the number of professionals and facilities are an input variable whereas the size of number and wages are the output variables. The results showed as below. First, according to the CCR test, Kangwon, Gyeonggi, GyeongNam, Deajeon, Seoul, Ulsan, Incheon, Jeju, and Chong Buk showed significance, but Daegu and Busan showed no significance. Second, the BCC result showed that Kangwon, Gyeonggi, GyeongNam, Deajeon, Seoul, Ulsan, Incheon, Jeju, and Chong Buk has efficiency whereas Daegu and Busan has no efficiency. The result of excess efficieincy analysis confirmed 133.5% in Jeju as the highest area, 37.54% of the highest efficiency of the care provider, and 28.61% of imporvable possibility with doctor's number. The realization of increasing numbers, the ensure of the doctor's number, and consolidating of the care provider's the espertise are required for the future.

• Journal of the Korea Convergence Society
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• v.12 no.7
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• pp.273-282
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• 2021

Nursing home plays a role in providing elderly care in the context of China's rapid population aging, but little understanding of the efficiency of the nursing homes. In this paper, we investigated the efficiency in nursing homes using Data Envelopment Analysis (DEA) and Malmquist index (MPI) for the modeling of the number of nursing home beds, fixed assets, and medical personnel as input variables, and the number of elderly people of self-care, the number of elderly people of partial self-care, the number of bed-ridden elderly people and the income of nursing homes as output variables. Stratification analysis showed that the top two provinces in the DEA-CCR yield were Beijing and Shanghai in the five-year survey period. Four provinces (Beijing, Jiangsu, Shandong, and Shanghai) scored 1.00 in terms of DEA-BCC yield. The MPI analysis showed that Hainan ranked the highest five-year average in the included provinces. In terms of resource utilization, internal management, operation scale, and other aspects, the nursing homes in the provinces with high-efficiency evaluation results show high efficiency and technological progress, whereas the areas with low-efficiency evaluation showed a feature of the improving technical efficiency.

• Journal of Distribution Science
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• v.11 no.8
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• pp.5-14
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• 2013

Purpose - We live in a world of constant change and competition. Many airports have specific competitiveness goals and strategies for achieving and maintaining them. The global economic recession, financial crises, and rising oil prices have resulted in an increasingly important role for facility investment and renewal and the implementation of appropriate policies in ensuring the competitive advantage for airports. It is thus important to analyze the factors that enhance efficiency and productivity for an airport. This study aims to determine the efficiency levels of 20 major airports in East Asia, Europe, and North America. Further, this study also suggests suitable policies and strategies for their development. Research design, data, and methodology - This paper employs the DEA-CCR, DEA-BCC, and DEA-Malmquist production index analysis models to determine airport efficiency. The study uses data on the efficiency and productivity of the world's leading airports between 2006 and 2010. The input variables include the airport size, the number of runways, the size of passenger terminals, and the size of cargo terminals. The output variables include the annual number of passengers and the annual cargo volume. The study uses basic data from the 2010 World Airport Traffic Report (ACI). The world's top 20 airports (as rated by the ACI report) are investigated. The study uses the expanded DEA Model and the Super Efficiency Model to identify the most effective airports among the top 20. The Malmquist productivity index analysis is used to measure airport effectiveness. Results - This study analyzes longitudinal and cross-sectional data on the world's top 20 airports covering 2006 to 2010. A CCR analysis shows that the most efficient airports in 2010 were Gatwick Airport (LGW), Zurich Airport (ZRH), Vienna Airport (VIE), Leonardo da Vinci Fiumicino Airport (FCO), Los Angeles International Airport (LAX), Seattle-Tacoma Airport (SEA), San Francisco Airport (SFO), HongKong Airport (HKG), Beijing Capital International Airport (PEK), and Shanghai Pudong Airport (PVG). We find that changes in airport productivity are affected more by technical factors than by airport efficiency. Conclusions - Based on the study results, we offer four airport development proposals. First, a benchmark airport needs to be identified. Second, inefficiency must be reduced and high-cost factors need to be managed. Third, airport operations should be enhanced through technical innovation. Finally, scientific demand forecasting and facility preparation must become the focus of attention. This paper has some limitations. Because the Malmquist productivity index is based on the hypothesis of the, the identified production change could be over- or under-estimated. Further, as DEA estimates the relative efficiency. It also cannot generalize to include all airport conditions because the variables are limited. To measure airport productivity more accurately, other input variables and environmental variables such as financial and policy factors should be included.

• Journal of Korea Technology Innovation Society
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• v.19 no.4
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• pp.711-735
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• 2016

Drug Development is very important for promoting public health and pharmaceutical industry. There has been many studies on the efficiency of drug development, but there are few studies on the drug development R&D performed by government. Since CCR model assumes unidirectional influence of input and output, it is not appropriate to analyze the efficiency of R&D due to the time-lag and spill-over effect. Also, BBC model which assumes variable returns to scale has difficulty in deriving priorities between decision making units. Recently, Range Adjusted Measure (RAM) model has been suggested in R&D efficiency analysis. RAM model measures the efficincy by eliminating inefficiencies under variable returns to scale assumption, and its strong monotonicity enables to provide clear priorities between decision making units. In this study, we analyzed the efficiency of national R&D programs for drug development using the two-step approach, including RAM model and Tobit regression analysis, and discussed major policy implications.

• Korea Journal of Hospital Management
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• v.16 no.4
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• pp.35-66
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• 2011

This study analyzed efficiency by utilizing DEA analytical technique centering on materials for 2009 of 20 major university hospitals in capital area. Input variables were utilized professor & full-time doctor, resident, nurse & number of bed hospitals. Output variables were analyzed by dividing number of annual outpatients & number of annual inpatients, and annually total outpatient profit & inpatient profit into a model of the standard for number of patients and the standard for medical profit. DEA analysis was elicited efficiency score by applying CCR, BCC, BFG, scale profit, and SE model. Through t-test after eliciting efficiency score, the implications were suggested by comparing efficiency between DMU in Seoul and DMU in capital area, by comparing between high-class general hospitals and general hospitals, and by comparing between high-class general hospitals in Seoul and 5 big hospitals. As a result of analysis, the major university hospitals in capital area showed high efficiency as a whole close to "1," but indicated low efficiency relatively in CCR field. Thus, the expansion in scale within capital area was indicated to reach the limit. Second, in a model of analyzing the standard for number of patients, the medical institutions, which are being operated efficiently, were indicated to be 10 DMUs. In the standard for medical profit, 12 DMUs were analyzed to be operated efficiently. Third, the efficiency in general hospital was higher than high-class general hospital. Thus, the efficiency of operation was indicated to be more important than scale. Also, large high-class hospitals(big 5) where are located in downtown Seoul showed the higher efficiency than other general high-class general hospitals, but were indicating very low efficiency in some DMUs. Fourth, as a result of generalizing and evaluating the number of patients and the medical profit, the efficient DMU was indicated to be more when analyzing on the basis of medical profit than the standard for number of patients. Thus, major university hospitals in capital area were indicated to make more effort for section in medical profit. Based on the analytical results of efficiency, a strategy for reinforcing efficiency in inefficient DMU was indicated to be needed a strategy of creating customers for promoting number of patients and a strategy for making operation efficient for increasing profitability.

• Journal of Korean Society of Forest Science
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• v.105 no.2
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• pp.247-252
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• 2016

This study was conducted to evaluate the technical efficiency of Annual Chestnut production in South Korea. In this study, technical efficiency is the maximum possible production for which a certain amount of costs is inputted. For analysis on the technical efficiency we used output-oriented BCC Model, and then we analyzed correlation among input costs, production, gross income, net income, and market price per unit in order to determine the cause of variation in the technical efficiency. As study materials, we used statistics for the forestry production costs for 7 years from 2008 to 2014. The study results showed that the maximum possible production and actual production in 2008, 2009, and 2010 were 1,568 kg, 1,745 kg, and 1,534 kg by hectares in the order which were the same values. Consequently, the technical efficiency of those was all evaluated as 1.00. On the other hand, actual production from 2011 to 2014 was 1,270 kg 1,047 kg, 1,258 kg, and 1,488 kg by hectares in the order and the maximum possible production was 1,524 kg, 1,467 kg, 1,635 kg, and 1,637 kg by hectares in the analysis. From those values, the technical efficiency was evaluated in the following order:0.83, 0.71, 0.75, 0.91. The lowest value of the technical efficiency was 0.71 in 2012, and the values of this increased gradually since 2013. It is indicated that the cause of variation in the technical efficiency was related to the relationship between production and market price, and there was a negative correlation with r = -0.821 (p<0.05). The level of maximum available production per unit area was between 1,488kg in lower limit and 1,745 kg in upper limit, and the average was turned out as 1,548 kg.