| 基于Malmquist-PNN的油田企业技术创新效率评价与智能诊断研究 |
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| 引用本文： | 张惠琴,尚甜甜,邵云飞.基于Malmquist-PNN的油田企业技术创新效率评价与智能诊断研究[J].科研管理,2016,37(12):10-18. |
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| 作者姓名： | 张惠琴 尚甜甜 邵云飞 |
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| 作者单位： | 1电子科技大学经济与管理学院，四川 成都610054；;
2成都理工大学管理科学学院，四川 成都610059；;
3西北工业大学管理学院，陕西 西安710072 |
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| 基金项目： | 国家自然科学基金，教育部人文社会科学研究规划基金，四川省哲学社会科学规划基金，四川省教育厅人文社科重点项目 |
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| 摘 要： | 采用DEA-Malmquist指数分析法对13家上市油田企业2005-2012年间的技术创新效率进行了测量和动态评价,运用概率神经网络PNN实现了对技术创新效率评价结果的智能诊断。研究表明:13家油田企业2005-2012年的全要素生产率未达到效率前沿面,技术创新效率总体上表现的退步趋势主要是由规模效率较低引起的;智能诊断能使决策者快速有效的判断出技术无效的决策单元和决策单元的效率模式,并根据不同的效率模式提出针对性的改善策略。
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| 关 键 词： | 油田企业 全要素生产率 概率神经网络 智能诊断 |
| 收稿时间： | 2015-05-12 |
Efficiency evaluation and intelligent diagnosis to the technological innovation of oilfield enterprises based on Malmquist-PNN |
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| Zhang Huiqin,Shang Tiantian,Shao Yunfei.Efficiency evaluation and intelligent diagnosis to the technological innovation of oilfield enterprises based on Malmquist-PNN[J].Science Research Management,2016,37(12):10-18. |
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| Authors: | Zhang Huiqin Shang Tiantian Shao Yunfei |
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| Institution: | 1. School of Management and Economic, University of Electronic Science and ;
Technology of China, Chengdu 610054, Sichuan, China；;
2. College of Management Science, Chengdu University of Technology, Chengdu 610059,Sichuan, China;
3. School of Management, Northwestern Polytechnical University, Xi’an 710072, Shaanxi, China |
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| Abstract: | The technological innovation efficiency of 13 listed oil field enterprises from 2005 to 2012 has been evaluated integrally and dynamically by using the DEA-Malmquist index analysis method. And an intelligent diagnosis has been conducted to analyze the results of the technological innovation efficiency by using the probabilistic neural network (PNN). The results show that the Malmquist productivity efficiency of the 13 listed oil field enterprises from 2005 to 2012 could not meet the efficient frontier boundary. And the recession performance of technological innovation efficiency is mainly caused by the low scale efficiency. Intelligent diagnosis could help decision makers to estimate technical invalid decision-making units and the efficiency model of the decision-making units quickly and efficiently, and put forward strategies for targeted improvement according to different efficiency models. |
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| Keywords: | oilfield enterprises total factor productivity probabilistic neural network (PNN) intelligent diagnosis |
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