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Journal articles on the topic 'Chinese agriculture; Data envelopment analysis'

Author: Grafiati

Published: 4 June 2021

Last updated: 13 February 2022

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1

Yang, C. H., L. Wu, and H. L. Lin. "Analysis of total-factor cultivated land efficiency in China's agriculture." Agricultural Economics (Zemědělská ekonomika) 56, No. 5 (June 1, 2010): 231–42. http://dx.doi.org/10.17221/37/2009-agricecon.

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Along with the rapid economic growth, there has been a booming demand for agricultural products in China, but the increased land usage for the manufacturing sector has caused a decrease in the total cultivated land. Through the data envelopment analysis (DEA) approach, this study first constructs the index of the total-factor cultivated land efficiency (TFCLE) by taking the ratio of the actual cultivated land input to target the cultivated land input. Next, we examine the determinants of inefficiency on the cultivated land use. Based on a province-level panel data over 1997–2006, the empirical estimates indicate that the TFCLE is moderate and fluctuates during the sample period, ranging from 0.601 to 0.713, suggesting room for efficiency improvement in Chinese farmland use. The coastal regions are found to experience a significantly higher degree of the TFCLE compared with non-coastal regions. Overall, there is no significant competition effect brought on by the WTO entry on promoting TFCLE, though this effect differs between the coastal and non-coastal regions. The second-stage regression results show that the natural and artificial disasters, flood, drought, and pollution are the the main causes of inefficiency. Innovative activity and the FDI are evidenced to have a significantly positive relation with the TFCLE in Chinese agriculture. We also find the positive TFCLE-enhancing the effects of production diversification and import competition.

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Cao, Yangdong, Wang Zhang, and Jinzheng Ren. "Efficiency Analysis of the Input for Water-Saving Agriculture in China." Water 12, no. 1 (January 11, 2020): 207. http://dx.doi.org/10.3390/w12010207.

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To optimize the installation distribution of water-saving techniques and improve the efficiency of water-saving agricultural inputs, we used a three-stage data envelopment analysis (DEA) model and Chinese provincial panel data from 2014 to 2016 to analyze the input efficiency of the water-saving irrigation. This study explores the efficiency derived from the efforts of water-saving initiatives in the agricultural sector in China. We present the impacts of factors such as technology, scale, diminishing marginal revenue, and crop water requirements on the research results. We found overall efficiency of water-saving irrigation is increasing nationally. The efficiency of water-saving irrigation input will significantly increase if management and organization of the input improve. Increasing the investment in areas with increasing marginal revenue would improve the local agricultural water-saving input efficiency in areas such as Hainan, Chongqing, Guizhou, Tibet, and Qinghai; although in areas with large water requirement for major crops, such as Inner Mongolia and Xinjiang, the efficiency of water-saving irrigation is generally high. Shanxi requires a large amount of water as the efficiency of agricultural water-saving input is 0.07, which is relatively lower than the average efficiency of all regions (0.39). The cultivated area index and the GDP per capita had no significant effect on the irrigation input efficiency.

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3

Jiao, Weihua, Zetian Fu, Weisong Mu, Xiaoshuan Zhang, Jianjun Lu, and Mark Xu. "Estimating technical efficiency of Chinese table grape wholesalers." British Food Journal 117, no. 6 (June 8, 2015): 1670–88. http://dx.doi.org/10.1108/bfj-03-2014-0134.

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Purpose – The purpose of this paper is to estimate the technical efficiency of Chinese table grape wholesalers and subsequently to examine the degree to which the calculated efficiency correlates with a set of explanatory variables. Design/methodology/approach – A two-stage procedure is applied in this paper. First, a non-parametric data envelopment analysis (DEA) technique is applied to investigate the degree of technical efficiency for Chinese table grape wholesalers. Second, Tobit regression is used to analyze the factors influencing technical efficiency. Findings – Research results reveal that the mean technical efficiency of the sample is 0.544 and 0.860 under constant returns scale (CRS) and VRS assumptions, respectively, and the scale efficiency (SE) is 0.620. The variables of experiences, number of grape varieties on sale, daily selling volumes and fixed sale ratio have a significant effect on technical efficiency, while the other exogenous variables do not affect the efficiency in any significant way. Research limitations/implications – The findings of this research are specific to table grape wholesalers in China, however, the method used in this study is transferrable and applicable to the study of similar problems in others countries. Originality/value – This research has yielded some interesting and original insights into the efficiency level of Chinese grape wholesalers and the factors that influence the level of efficiency. The findings have practical implications for Chinese agriculture policy makers, and are able to stimulate further research of a similar type in the international agricultural research community.

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Liu, Zhuo-wan, Tomas Balezentis, Yao-yao Song, and Guo-liang Yang. "Estimating Capacity Utilization of Chinese State Farms." Sustainability 11, no. 18 (September 6, 2019): 4894. http://dx.doi.org/10.3390/su11184894.

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As the most populous country in the world, China has one of the largest agricultural systems in the world, which plays an important role in ensuring China’s food security. The state farms comprise an integral part of China’s agricultural system. However, there have been few studies evaluating the efficiency and capacity utilization of China’s state farms. In this paper, we estimate the efficiency and capacity utilization of state farms across 27 Chinese regions by applying the data envelopment analysis method. Performance of the overall state farm system and its three sub-industries is taken into consideration simultaneously. Over the period of 2013–2017, the technical efficiency fluctuated in between 0.74 and 0.84, whereas the capacity utilization fluctuated around 0.85. The regional differences were observed. The regional differences were also observed.

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5

An, Qingxian, Xuyang Liu, Yongli Li, and Beibei Xiong. "Resource planning of Chinese commercial banking systems using two-stage inverse data envelopment analysis with undesirable outputs." PLOS ONE 14, no. 6 (June 13, 2019): e0218214. http://dx.doi.org/10.1371/journal.pone.0218214.

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6

Li, Nan, Yuqing Jiang, Hailin Mu, and Zhixin Yu. "Efficiency evaluation and improvement potential for the Chinese agricultural sector at the provincial level based on data envelopment analysis (DEA)." Energy 164 (December 2018): 1145–60. http://dx.doi.org/10.1016/j.energy.2018.08.150.

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7

Zhong, Zhangqi, Yiqin Hu, and Lei Jiang. "Impact of Climate Change on Agricultural Total Factor Productivity Based on Spatial Panel Data Model: Evidence from China." Sustainability 11, no. 6 (March 13, 2019): 1516. http://dx.doi.org/10.3390/su11061516.

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To respond to the adverse impact of climate change on agricultural total factor productivity, the question of how to adopt actively appropriate strategies is particularly critical for the stakeholders. However, the previous researchers have paid more attention to investigating the measure methods, regional differences, and determinants of Chinese agricultural total factor productivity, but the possible impact of climate change factors like rainfall, temperature, and evaporation on regional agricultural total factor productivity in China have not yet received the attention that they deserve. Furthermore, more importantly, the study on how to take active measures to reduce and mitigate the negative effects from climate change is relatively small. Therefore, in allusion to the above-mentioned problems, using the data envelopment analysis and building a spatial panel data model embedded with climate change factors, this paper calculated Chinese agricultural total factor productivity and then explored the possible impact of climate change on regional agricultural total factor productivity at a provincial level in China. Results mainly show that the impact of some factors, like annual total precipitation, average temperature in the growing season, and evaporation intensity on regional agricultural total factor productivity, are all very significant and negative, which suggests that the more precipitation, the higher the temperature is, and the higher evaporation intensity would lower agricultural total factor productivity in China. Furthermore, in order to response to mitigate the adverse effects from climate change on agricultural total factor productivity, local governments should continue to increase financial support for the local agricultural economic development, because this action could be beneficial for the related stakeholders in improving agricultural total factor productivity. Summing up, our evidence study would provide an important basic theory basis in terms of increasing agricultural total factor productivity and promoting regional agricultural economic development in China.

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8

Xiaolin, Tang, Wang Jieqiong, Zhang Biao, and Zhang Lingxian. "Application of the DEA on the performance evaluation of the agricultural support policy in China." Agricultural Economics (Zemědělská ekonomika) 63, No. 11 (November 6, 2017): 510–23. http://dx.doi.org/10.17221/120/2016-agricecon.

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The paper utilizes the data envelopment analysis (DEA) method based on the OECD policy classification to evaluate the performance of the agricultural support policy at the provincial and agricultural commodity levels from the respective viewpoints of agricultural input and output. The analysis at the provincial level mainly focuses on the similarities and differences in the performance of the agricultural support policies between the primary grain-producing areas and the secondary grain-producing areas; at the agricultural commodity level, 17 representative Chinese agricultural commodities are selected and their performance compared. The results are then used to proffer suggestions for the future agricultural support policy optimization in China. The paper found that 50% of the provinces were DEA-efficient, in general, during the study period due to the low overall province-level scale efficiency. The performance values of the secondary grain-producing areas were significantly lower than those of the primary grain-producing areas due to the overall low scale and technical efficiency values. These results show that the support policies for agricultural commodities in China altogether require a further improvement, mainly due to the low technical efficiency of agricultural commodities.

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Mu, L., L. Fang, H. Wang, L. Chen, Y. Yang, X. J. Qu, C. Y. Wang, Y. Yuan, S. B. Wang, and Y. N. Wang. "Exploring Northwest China's agricultural water-saving strategy: analysis of water use efficiency based on an SE-DEA model conducted in Xi'an, Shaanxi Province." Water Science and Technology 74, no. 5 (June 17, 2016): 1106–15. http://dx.doi.org/10.2166/wst.2016.286.

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Worldwide, water scarcity threatens delivery of water to urban centers. Increasing water use efficiency (WUE) is often recommended to reduce water demand, especially in water-scarce areas. In this paper, agricultural water use efficiency (AWUE) is examined using the super-efficient data envelopment analysis (DEA) approach in Xi'an in Northwest China at a temporal and spatial level. The grey systems analysis technique was then adopted to identify the factors that influenced the efficiency differentials under the shortage of water resources. From the perspective of temporal scales, the AWUE increased year by year during 2004–2012, and the highest (2.05) was obtained in 2009. Additionally, the AWUE was the best in the urban area at the spatial scale. Moreover, the key influencing factors of the AWUE are the financial situations and agricultural water-saving technology. Finally, we identified several knowledge gaps and proposed water-saving strategies for increasing AWUE and reducing its water demand by: (1) improving irrigation practices (timing and amounts) based on compatible water-saving techniques; (2) maximizing regional WUE by managing water resources and allocation at regional scales as well as enhancing coordination among Chinese water governance institutes.

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10

Tan, Xianhua, Sanggyun Na, Lei Guo, Jing Chen, and Zhihua Ruan. "External Financing Efficiency of Rural Revitalization Listed Companies in China—Based on Two-Stage DEA and Grey Relational Analysis." Sustainability 11, no. 16 (August 15, 2019): 4413. http://dx.doi.org/10.3390/su11164413.

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Rural revitalization is an important strategy to promote sustainable development of rural areas in China. Rural revitalization listed companies play an important role in implementing the rural revitalization strategy and developing the agricultural industry. However, the financing problem has always been a bottleneck problem with Chinese listed companies. This study used a two-stage DEA (data envelopment analysis) method to evaluate the funds raising efficiency, funds using efficiency, and overall financing efficiency of 34 rural revitalization listed companies in 2018. The results show that the financing efficiencies of 34 sample companies were low, only six companies have overall efficient financing, and there was much room for improvement. Financing efficiency varied greatly depending on the nature of the company, the industry, and the listing board. The efficiency of funds using of state-owned enterprises was much lower than that of private companies. The average efficiency value of agricultural company funds raising was lower than that of manufacturing. The efficiency of small and middle-size enterprises (SMEs) was lower than that of main board companies, but the growth enterprise market (GEM) companies achieved higher efficiency in the funds using. Further, by using the grey relational analysis (GRA) method, we found that the key factors affecting the financing efficiency of sample companies included capital structure, debt-paying ability, governance structure, company age, and operating ability. To improve financing efficiency, the companies should not only optimize their capital structure and governance structure but also improve their management and innovation capabilities. At the same time, the state also needs to give different policies support according to the characteristics of the companies.

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11

Gao, You Min, and Xiao Wen Wang. "Efficiency Comparison in Chinese Construction Industry Based on Data Envelopment Analysis and Super Efficiency Data Envelopment Analysis." Applied Mechanics and Materials 275-277 (January 2013): 2788–92. http://dx.doi.org/10.4028/www.scientific.net/amm.275-277.2788.

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Construction industry is a main industry in national economy, Chinese construction industry has made huge achievement, but the developments between different provinces in China are imbalanced. To compare the different efficiencies between them, data envelopment analysis and an important extended means of DEA were introduced, compared and applied in empirical analysis of Chinese construction industry efficiency between different provinces based on statistical data. Then some conclusions and advices were reached in the end.

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12

CHEN, YAO. "ON PREFERENCE STRUCTURE IN DATA ENVELOPMENT ANALYSIS." International Journal of Information Technology & Decision Making 04, no. 03 (September 2005): 411–31. http://dx.doi.org/10.1142/s0219622005001647.

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The paper studies the result of Zhu21 and establishes a relationship between the efficiency in data envelopment analysis (DEA) and the pareto optimality under multiple objective linear programming (MOLP). It is shown that the DEA/preference structure models in Zhu21 can be derived by traditional MOLP techniques. Incorporation of tradeoffs or value judgments is a direct result of using MOLP techniques. New uses of DEA are developed and described. The approach is applied to a set of Chinese cities.

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13

Li, Zhiyong, Jonathan Crook, and Galina Andreeva. "Chinese companies distress prediction: an application of data envelopment analysis." Journal of the Operational Research Society 65, no. 3 (March 2014): 466–79. http://dx.doi.org/10.1057/jors.2013.67.

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14

Yougbaré, Jacob Wendpanga. "Analysis of Agricultural Performance in Burkina Faso Using Data Envelopment Analysis." European Journal of Pure and Applied Mathematics 14, no. 2 (May 18, 2021): 366–79. http://dx.doi.org/10.29020/nybg.ejpam.v14i2.3888.

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In this paper, we used the DEA method, to apply to the agriculture sector in BurkinaFaso. We applied the method with forty-one (41) agricultural farmers with data taking into account cultivated area, manual (human) labour, the liquidity fund of the working household, the number of crops (products) and the expected farm incomes. The results highlight the seven (7) technical efficiencies. Taking into account the variable scale yields, fourteen (14) efficient farms are obtained. These results show how non-efficient farms in the DEA sense are indexed to efficient farms that can serve as benchmarks or benchmarks in terms of performance improvement. This study shows that efficiency does not depend on the category of operator but on overall performance (efficiency and productivity).

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15

Sueyoshi, Toshiyuki. "Measuring the industrial performance of Chinese cities by data envelopment analysis." Socio-Economic Planning Sciences 26, no. 2 (April 1992): 75–88. http://dx.doi.org/10.1016/0038-0121(92)90015-w.

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16

Lilienfeld, Amy, and Mette Asmild. "Estimation of excess water use in irrigated agriculture: A Data Envelopment Analysis approach." Agricultural Water Management 94, no. 1-3 (December 2007): 73–82. http://dx.doi.org/10.1016/j.agwat.2007.08.005.

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17

Hidayah, Qori Halimatul, Mustafid, and Kusworo Adi. "System of Performance Evaluation of Rice Paddy Production with Data Envelopment Analysis." E3S Web of Conferences 125 (2019): 22006. http://dx.doi.org/10.1051/e3sconf/201912522006.

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Agriculture is one of the important factors in the development of the economy in Indonesia as an agricultural country because most of Indonesia's population has work in the field of agriculture or planting. Concepts and elements to understand and apply the performance calculations of evaluation of rice production using Data Envelopment Analysis. In this article convey and receive the evaluation of paddy production performance to know the value of efficiency and support in the process of paddy production in 2 planting seasons to find out the optimization of paddy production through performance evaluation Production to improve quality and be able to enrich the people. Input and output processes that have significance to improve the optimization of rice production and level to efficiency in rice production. This article will discuss the performance analysis of rice production and the results that will be given to know the efficiency in production and to help agricultural officers and farmers to produce an optimal and efficient product. Decision Making Unit (DMU) which has an efficiency value of fewer than 1 means inefficient whereas Decision Making Unit (DMU) whose value is 1 means efficient.

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18

YE Qian. "Measuring Efficiency of Chinese Commercial Listed Banks Based on Data Envelopment Analysis." INTERNATIONAL JOURNAL ON Advances in Information Sciences and Service Sciences 4, no. 16 (September 15, 2012): 204–13. http://dx.doi.org/10.4156/aiss.vol4.issue16.24.

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19

Guo, Zisheng, Jianqi Zhang, and Heng Liu. "Opportunity recognition efficiency of small Chinese firms: findings from data envelopment analysis." Chinese Management Studies 13, no. 4 (November 4, 2019): 760–77. http://dx.doi.org/10.1108/cms-05-2018-0546.

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Purpose Small firms in China anticipate entrepreneurial opportunities for continual growth. However, they may fail to recognize opportunities because of their inefficiency in managing their knowledge. Design/methodology/approach In this explorative paper, the authors assess the opportunity recognition efficiency of 168 small Chinese firms using data envelopment analysis (DEA). Supplementary Tobit regressions were conducted for further exploring the factors that influence the firms’ efficiency in opportunity recognition. Findings Results from the DEA suggest that most respondents recognize significantly fewer opportunities than those with equivalent knowledge stock. Moreover, many firms have low levels of pure technical efficiency but high levels of scale efficiency, indicating insufficient use of knowledge as a major reason for inefficiency in opportunity recognition. The Tobit regressions show that sales and research and development intensity are relevant to a firm’s opportunity recognition efficiency. Research limitations/implications This study calls for the investigation of efficiency issues in opportunity recognition and suggests that managers guard against unwarranted loss of opportunities owing to inefficient use of existing knowledge elements. Originality/value First, the authors introduce the concept of opportunity recognition efficiency within the entrepreneurial process. Second, they manifest the role of knowledge management in opportunity recognition. Third, they introduce DEA to investigate the relationship between knowledge stock and opportunity recognition. Fourth, this study reveals that inefficient use of knowledge is a disadvantage of small Chinese firms in terms of opportunity recognition.

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Qiang Chen, Yong, Huanqing Lu, Wenxue Lu, and Ning Zhang. "Analysis of project delivery systems in Chinese construction industry with data envelopment analysis (DEA)." Engineering, Construction and Architectural Management 17, no. 6 (November 9, 2010): 598–614. http://dx.doi.org/10.1108/09699981011090215.

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21

Monchuk, Daniel C., Zhuo Chen, and Yosef Bonaparte. "Explaining production inefficiency in China's agriculture using data envelopment analysis and semi-parametric bootstrapping." China Economic Review 21, no. 2 (June 2010): 346–54. http://dx.doi.org/10.1016/j.chieco.2010.02.004.

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22

Dong, Siping, Yuling Zuo, Shuyan Guo, Meng Li, Xinliang Liu, and Hao Li. "Data Envelopment Analysis for Relative Efficiency Measurement of Chinese Hospitals: A Systematic Review." Research in Health Science 2, no. 2 (March 27, 2017): 79. http://dx.doi.org/10.22158/rhs.v2n2p79.

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<p><em>The purpose was to explore the gap between China and the international world in efficiency measurement of hospitals with Data Envelopment Analysis, and to improve the standardization of healthcare efficiency measurement in China. A systematic review was conducted using appropriate search strategies. Studies were included containing DEA approaches regarding general hospital efficiency, published in international literature and in both Chinese and English about Chinese hospitals from January 2004 to October 2014. The results showed </em>that<em> statistical significances were found in indicators such as number of DMUs, percentage of allocative efficiency studies, ratio of studies with multiple years, number of studies with monetary indicators in input and output sets, etc. The statistical insignificance in some indicators such as the number of input and output indicators were also found among China, Europe, USA and others. Some problems were found in current DEA-based hospital efficiency studies in China, such as inappropriate selection of input-output indicators, no bias-correction on efficiency scores, etc. The standardization of DEA methods applied in China’s hospital efficiency research needs to be improved. Chinese researchers should pay more attention to latest international research findings, so as to keep pace with the cutting edge hospital efficiency research.</em><em></em></p>

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23

Ka-Yiu Fung, Michael, and Ken Kai-Hong Wan. "Ownership and efficiency differentials in chinese industry: further evidence from data envelopment analysis." Applied Economics Letters 3, no. 7 (July 1996): 475–82. http://dx.doi.org/10.1080/758540810.

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JOHNES, Jill, and Li YU. "Measuring the research performance of Chinese higher education institutions using data envelopment analysis." China Economic Review 19, no. 4 (December 2008): 679–96. http://dx.doi.org/10.1016/j.chieco.2008.08.004.

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Jiang, Jiali, Soo Kyoung Lee, and Min-Joo Rah. "Assessing the research efficiency of Chinese higher education institutions by data envelopment analysis." Asia Pacific Education Review 21, no. 3 (July 15, 2020): 423–40. http://dx.doi.org/10.1007/s12564-020-09634-0.

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ERDOĞAN AKTAN, Hande, and Pınar KAYA SAMUT. "Analysis of the Efficiency Determinants of Turkey s Agriculture Sector by Two-Stage Data Envelopment Analysis (DEA)." Ege Akademik Bakis (Ege Academic Review) 13, no. 1 (January 1, 2013): 21. http://dx.doi.org/10.21121/eab.2013119497.

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Li, Liu-Liu, Young-Joon Seo, and Min-Ho Ha. "The efficiency of major container terminals in China: super-efficiency data envelopment analysis approach." Maritime Business Review 6, no. 2 (January 11, 2021): 173–87. http://dx.doi.org/10.1108/mabr-08-2020-0051.

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Purpose Seaports are a signifier for the world economy and international trade. Notwithstanding the considerable role of Chinese ports in global trade, only few studies have explored the efficiency of Chinese container terminals. Furthermore, studies on Chinese port efficiency has typically centered on port-level analysis, not terminal level. Therefore, this study aims to examine the operation efficiency of Chinese container terminals. Design/methodology/approach This study uses super-efficiency data envelopment analysis (SE-DEA) approach. SE-DEA is superior than basic DEA model because it is feasible for categorizing and ranking the efficiency of container terminals more accurately and comprehensively. In the basic model, if the several decision-making units (DMUs) are efficient, the efficiency value of them is “1.” However, in the SE-DEA model, the most efficient DMU is over “1.” Based on the level of container throughput in 2018, the top 20 Chinese container terminal companies were selected. Various production quotas were selected as inputs, while the container throughput was considered output. Findings The findings show that Terminal Shanghai Mingdong Container Terminal Co., Ltd. was ranked 1, followed by Shanghai Shengdong International Container Terminal Co., Ltd., Shanghai International Port (Group) Co., Ltd. and Yidong Container Terminal Branch. Originality/value This study contributes to providing some insights into Chinese container terminal industry to augment the efficiency. This study also provides practical and policy implications (e.g. better terminal operations) for container terminals.

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Liu, Rui Jie, and Zhi Hui Zhang. "Green-Efficiency Assessment of Chinese Industry Based on Principal Component Analysis and Super-Efficiency Data Envelopment Analysis." Advanced Materials Research 490-495 (March 2012): 2264–68. http://dx.doi.org/10.4028/www.scientific.net/amr.490-495.2264.

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Industry is playing an important role in national economy, the efficiency and developing trend of which is widely being paid attention to. However, severe environmental problems always emerge along with rapid industrial development at the same time. Based on the method integrating Principal Component Analysis and Super-efficiency Data Envelopment Analysis, this article introduces environmental factors into the system to evaluate Chinese industrial green-efficiency of year 2000~2008, indicating the current major problems which hinder coordinated economic-environmental development of Chinese industry, and putting forward the improving direction.

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Fernandez-Cornejo, Jorge. "Nonradial Technical Efficiency and Chemical Input Use in Agriculture." Agricultural and Resource Economics Review 23, no. 1 (April 1994): 11–21. http://dx.doi.org/10.1017/s1068280500000368.

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Radial and nonradial measures of technical efficiency are calculated empirically for Florida vegetable farms using DEA (data envelopment analysis) techniques. Use of the nonradial measures to calculate overuse of chemical inputs by inefficient farmers is demonstrated and the potential for reduced environmental loading of pesticides and fertilizers by improving efficiency is evaluated.

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Bojnec, Štefan, Imre Fertő, Attila Jámbor, and József Tóth. "Determinants of technical efficiency in agriculture in new EU member states from Central and Eastern Europe." Acta Oeconomica 64, no. 2 (June 1, 2014): 197–217. http://dx.doi.org/10.1556/aoecon.64.2014.2.4.

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Technical efficiency in agriculture of 10 new EU member states is analysed by Data Envelopment Analysis and econometric panel data analysis. Technical efficiency in agriculture is significantly positively associated with agricultural factor endowments, average farm size, farm specialisation, small-scale farms, and technological change. Foreign direct investments have an ambiguous effect. Reform and institutional developments, large-scale privatisation and price liberalisation, and urban- rural income gap are associated with technical efficiency in agriculture positively. An increase in technical efficiency in agriculture and the development of the rural economy are seen as a strategy to boost the level of living standards in agriculture and in rural areas.

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Du, Kai, Andrew C. Worthington, and Valentin Zelenyuk. "Data envelopment analysis, truncated regression and double-bootstrap for panel data with application to Chinese banking." European Journal of Operational Research 265, no. 2 (March 2018): 748–64. http://dx.doi.org/10.1016/j.ejor.2017.08.005.

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Ghiyasi, Mojtaba, and Ning Zhu. "An inverse semi-oriented radial data envelopment analysis measure for dealing with negative data." IMA Journal of Management Mathematics 31, no. 4 (April 29, 2020): 505–16. http://dx.doi.org/10.1093/imaman/dpaa007.

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Abstract The conventional inverse data envelopment analysis (DEA) model is only applicable to positive data, while negative data are commonly present in most real-world applications. This paper proposes a novel inverse DEA model that can handle negative data. The conventional inverse DEA model is a special case of our model as our model is more general in terms of returns-to-scale properties. The proposed model is used to evaluate the efficiency of the Chinese commercial banks after the global financial crisis, where negative outputs existed. We show that our model is feasible in the presence of negative data and generates empirical findings that are consistent with reality.

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Zhu, Joe. "Data envelopment analysis vs. principal component analysis: An illustrative study of economic performance of Chinese cities." European Journal of Operational Research 111, no. 1 (November 1998): 50–61. http://dx.doi.org/10.1016/s0377-2217(97)00321-4.

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Jiang, Ling, Yunyu Jiang, Zhijun Wu, Dongsheng Liao, and Runfa Xu. "The Measurement of Innovation Efficiency of Chinese High-tech Industry Using Data Envelopment Analysis." Acta Oeconomica 65, s2 (December 2015): 101–13. http://dx.doi.org/10.1556/032.65.2015.s2.8.

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In the era of knowledge economy, a country’s economic competitiveness depends largely on the development level of high-tech industry. This paper evaluates the efficiency of China’s high-tech industry in 31 provinces in 2012 with data envelopment analysis. The empirical results are summarized as following. Firstly, when the effects of exogenous environmental variables are not controlled, the comprehensive technical efficiency of 31 provinces will be overestimated, the pure technical efficiency will be underestimated, and the scale efficiency value will be overestimated. Secondly, after eliminating the environmental impact, the comprehensive technical efficiency of 31 provinces with the average of 0.395 is rather low, due to the low scale efficiency.

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See, Kok Fong, and Yong He. "Determinants of Technical Efficiency in Chinese Banking: A Double Bootstrap Data Envelopment Analysis Approach." Global Economic Review 44, no. 3 (June 10, 2015): 286–307. http://dx.doi.org/10.1080/1226508x.2015.1014392.

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Feng, Qiyuan, Quanyi Qiu, Yuan Quan, and Lina Tang. "Sustainability efficiency of Chinese cities involving coal-fired power plants with data envelopment analysis." International Journal of Sustainable Development & World Ecology 24, no. 5 (December 26, 2016): 395–400. http://dx.doi.org/10.1080/13504509.2016.1273272.

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Charnes, Abraham, William W. Cooper, and Shanling Li. "Using data envelopment analysis to evaluate efficiency in the economic performance of Chinese cities." Socio-Economic Planning Sciences 23, no. 6 (January 1989): 325–44. http://dx.doi.org/10.1016/0038-0121(89)90001-3.

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Zhou, Gengui, Hokey Min, Chao Xu, and Zhenyu Cao. "Evaluating the comparative efficiency of Chinese third‐party logistics providers using data envelopment analysis." International Journal of Physical Distribution & Logistics Management 38, no. 4 (May 16, 2008): 262–79. http://dx.doi.org/10.1108/09600030810875373.

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Korotchenya, V. "Technical efficiency of the Russian agriculture." Voprosy Ekonomiki, no. 4 (April 20, 2016): 144–55. http://dx.doi.org/10.32609/0042-8736-2016-4-144-155.

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Based on the data envelopment analysis methodology applied in the cross-country context with a metafrontier approach and window analysis, the article provides a technical efficiency estimate of the Russian agriculture. The group of countries included in the study comprises the CIS, BRIC, EU, and OECD members. The time interval is 1992-2007. The research has revealed low efficiency of the Russian agriculture among the CIS members and a relatively large technology gap with respect to advanced economies, but which tends to decline. The estimates also indicate growth of the Russian agricultural sector efficiency within the CIS beyond the time interval of the research.

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Tóth, Orsolya, and István Takács. "Farm Structure And Efficiency In The Hungarian Agriculture." Visegrad Journal on Bioeconomy and Sustainable Development 4, no. 2 (October 1, 2015): 51–56. http://dx.doi.org/10.1515/vjbsd-2015-0012.

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Abstract It has long been the subject of empirical researches to examine the technical efficiency on farm (micro) level. Two main methods are most often used in the empirical literature: the non-parametric Data Envelopment Analysis (DEA) based on linear programming, and the Stochastic Frontier Analysis (SFA) introduced by Aigner, Lovell and Schmidt (1977). The present study aimed to investigate the technical efficiency of farms involved in agricultural activities in Hungary using the DEA-method and the data from the Hungarian FADN database. The technical efficiency was examined based on legal forms, farm size categories and the type of farming between 2001 and 2013.

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Dong, Yizhe, Robert Hamilton, and Mark Tippett. "Cost efficiency of the Chinese banking sector: A comparison of stochastic frontier analysis and data envelopment analysis." Economic Modelling 36 (January 2014): 298–308. http://dx.doi.org/10.1016/j.econmod.2013.09.042.

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Laurinavičius, Eligijus, and Daiva Rimkuvienė. "The Comparative Efficiency Analysis of EU Members Agriculture Sectors." Rural Sustainability Research 37, no. 332 (July 1, 2017): 10–19. http://dx.doi.org/10.1515/plua-2017-0002.

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Abstract Production economics forms a very important part of an enormous range of economic theory. Agricultural production is no exception. When evaluating the competitiveness of the multifunctional agriculture, it is necessary to use the measure of efficiency instead of productivity. The conception of the efficiency is explained and the methods for measurement are provided. The authors discuss the methods of Stochastic Frontier Approach (SFA), Free Disposal Hull (FDH) and Data Envelopment Analysis (DEA) that are particularly useful for multi-criterial evaluation of multifunctional processes. Those methods assign an efficiency score to each Decision Making Unit (DMU) based on how well it transforms a given set of inputs into outputs. Most studies have only focused on application of DEA method for assesment of the efficiency of agriculture farms. There is still a need on applications for sectors. This paper provides an examination of the applicability of DEA method to agriculture sectors efficiency measurement. By applying mathematical models, which are based on the DEA, the efficiency of agriculture in each EU country was evaluated.

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Zhou, Zongqing, Yinghua Huang, and Maxwell K. Hsu. "Using Data Envelopment Analysis to Evaluate Efficiency: An Exploratory Study of the Chinese Hotel Industry." Journal of Quality Assurance in Hospitality & Tourism 9, no. 3 (October 2008): 240–56. http://dx.doi.org/10.1080/15280080802412719.

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Chu Ng, Ying, and Sung Ko Li. "Measuring the Research Performance of Chinese Higher Education Institutions: An Application of Data Envelopment Analysis." Education Economics 8, no. 2 (August 1, 2000): 139–56. http://dx.doi.org/10.1080/096452900410712.

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Li, Feng, Lunwen Wu, Qingyuan Zhu, Yanling Yu, Gang Kou, and Yi Liao. "An Eco-Inefficiency Dominance Probability Approach for Chinese Banking Operations Based on Data Envelopment Analysis." Complexity 2020 (May 4, 2020): 1–14. http://dx.doi.org/10.1155/2020/3780232.

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Data envelopment analysis (DEA) has proven to be a powerful technique for assessing the relative performance of a set of homogeneous decision-making units (DMUs). A critical feature of conventional DEA approaches is that only one or several sets of optimal virtual weights (or multipliers) are used to aggregate the ratio performance efficiencies, and thus, the efficiency scores might be too extreme or even unrealistic. Alternatively, this paper aims at developing a new performance dominance probability approach and applying it to analyze the banking operations in China. Towards that purpose, we first propose an extended eco-inefficiency model based on the DEA methodology to address banking activities and their possible relative performances. Since the eco-inefficiency will be obtained using a set of optimal weights, we further build a performance dominance structure by considering all sets of feasible weights from a data-driven perspective. Then, we develop two pairwise eco-inefficiency dominance concepts and propose the inefficiency dominance probability model. Finally, we illustrate the eco-inefficiency dominance probability approach with 32 Chinese listed banks from 2014 to 2018 to demonstrate the usefulness and efficacy of the proposed method.

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Constantin, Paulo Dutra, Diogenes Leiva Martin, and Edward Bernard Bastiaan de Rivera Y Rivera. "Cobb-Douglas, Translog Stochastic Production Function and Data Envelopment Analysis in Total Factor Productivity in Brazilian Agribusiness." Journal of Operations and Supply Chain Management 2, no. 2 (December 28, 2009): 20. http://dx.doi.org/10.12660/joscmv2n2p20-33.

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The objective of this paper is to apply a Cobb-Douglas, Translog Stochastic Production Function and Data Envelopment Analysis in order to estimate inefficiencies over time as well as respective TFP (Total Factor Productivity) sources for main Brazilian grain crops - namely, rice, beans, maize, soybeans and wheat - throughout the most recent data available comprising the period 2001-2006. The results indicate that, although positive changes exist in TFP for the sample analyzed, a decline in the use of technology has been evidenced for all grain crops in which it is observed a historical downfall in the use of inputs in Brazilian agriculture

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Suzigan, Luis H., Carlos Rosano Peña, and Patricia Guarnieri. "Eco-efficiency Assessment in Agriculture: A Literature Review Focused on Methods and Indicators." Journal of Agricultural Science 12, no. 7 (June 15, 2020): 118. http://dx.doi.org/10.5539/jas.v12n7p118.

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Combining economic performance with environmental and social concern has been a developing topic in recent decades. Eco-efficiency analysis is a widely applied tool to assess the efficiency of agricultural systems, while increasingly considering their environmental and social impact. The main objective of this article is to accomplish a literature review on the application of eco-efficiency analysis in agricultural systems, focusing on methods and indicators that are most regarded for the quantitative assessment of agricultural eco-efficiency. The literature review found two main methods most widely applied to assess eco-efficiency: Life Cycle Assessment (LCA) and Data Envelopment Analysis (DEA), which are often combined. LCA is generally focused on the assessment of the environmental impacts of products and practices. DEA is mostly used to measure the eco-efficiency of decision-making units, such as farms, regions, or countries, and has no subjective focus on neither technical nor environmental performance. Both methods share a wide range of economic and environmental indicators but fail to incorporate the social dimension of sustainability into the eco-efficiency analysis. A simple framework, based on Data Envelopment Analysis, is offered to assess the eco-efficiency of the Brazilian agriculture, aiming at identifying the benefits and limitations of the analysis.

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Salama, Sri Cahyaning Umi. "EFFICIENCY ANALYSIS OF STATE BUDGET ON AGRICULTURAL DEVELOPMENT IN INDONESIA 2012-2016." Journal of Developing Economies 3, no. 1 (July 31, 2018): 33. http://dx.doi.org/10.20473/jde.v3i1.8596.

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Indonesia is still far behind compared to other Asian countries in agriculture. The technology and the availability of pre-facilities are still inadequate because of the many obstacles that hamper agricultural development. Agricultural development is a major component of rural development. One way to help the process of agricultural development is with the ease of access to finance.The State through the Ministry of Agriculture continues to make efforts in encouraging the development of domestic agriculture. Funds distributed are not small so it is necessary to calculate the efficient use of state budget funds in agricultural development in Indonesia. This study aims to measure the level of efficiency of the state budget for the agricultural sector. The data used are secondary data derived from the Ministry of Agriculture's financial report from 2012 to 2016.The method used is Data Envelopment Analysis (DEA) with input oriented and output oriented with Variable Returns to Scale (VRS). The input variable used is the realization of State Budget (APBN) for agriculture sector, while the output variables used are Farmer's Exchange Rate (NTP), Gross Domestic Product, and Farmer Productivity. The results show that the year 2015 becomes a very inefficient year both in terms of input oriented and output oriented. The increase in the realization of state expenditures for agriculture is not balanced by significant results, even in 2016 where the relatively small increase in the realization of the agriculture sector budget has had a comparable impact.Keywords: Efficiency, realization Budget expenditure, agricultural development

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Jian-yao, Zhao, Shuai Li-na, Guo Fang, and Chen Li. "Analysis of Service Efficiency of Traditional Chinese Medicine (TCM) Hospitals in China Based on Data Envelopment Analysis (DEA)." E3S Web of Conferences 251 (2021): 01032. http://dx.doi.org/10.1051/e3sconf/202125101032.

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In order to optimize the allocation of health resources and promote the development of traditional Chinese medicine (TCM), this research employs the China Health Statistics Yearbook 2018 to collect relevant data on TCM hospitals in 2017, and the DEA method is used to construct a BCC model for the evaluation of service efficiency of these hospitals in 30 provinces (including autonomous regions and municipalities directly under the central government) across the country. It is found that TCM hospitals in non-effective DEA provinces are not operating efficiently, with excessive investment in institutions, beds, and health staff, and insufficient output of visits, bed utilization, and the average length of stay. Given this, attention to promoting the service capacity and efficiency of TCM hospitals should be paid on the following aspects: scientific allocation of health resource, strengthened external policy control, improved internal management of hospitals, optimized characteristic services and establishment of scientific evaluation system.

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Yang, Wei, Jinfeng Shi, Han Qiao, Yanmin Shao, and Shouyang Wang. "Regional technical efficiency of Chinese Iron and steel industry based on bootstrap network data envelopment analysis." Socio-Economic Planning Sciences 57 (March 2017): 14–24. http://dx.doi.org/10.1016/j.seps.2016.07.003.

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