摘要
环境复杂性是汽车制造产业网络复杂性的主要诱因。利用指标波动程度测度复杂性的思想,建立表征汽车制造产业网络外部环境的指标体系,构建指标变动程度的模糊信度结构模型,运用模糊证据推理算法结合熵值理论对多指标进行信息融合,并利用灰色关联分析方法评估复杂性测度结果。通过2002~2012年汽车行业数据的实证研究,结果表明:经济环境与国际环境的波动是导致汽车制造产业网络复杂性的最主要因素,技术环境和市场环境次之;近10年来我国汽车制造产业网络外部环境经历了两次较大波动,总体复杂性呈现增长趋势。本研究可为汽车产业环境复杂性测度及应对提供思路参考。
The complexity of the environmental is the main cause of the complexity of automobile manufacturing industry network. With the thought to measure the complexity through the environmental index volatility, the indicator system of the automobile manufacturing industry network environment and the fuzzy belief structure model for measuring the volatility degree are established, the multiple indexes of environment complexity are transformed into fuzzy belief structures using the fuzzy evidential reasoning algorithm combining the entropy value theory, and then the results of environment complexity of automobile manufacturing industry network are evalua- ted by grey relational analysis method. Through the empirical research on the data of 2002 -2012 in the automo- tive industry, the results show that the fluctuations of economic environment and international environment are the main factors leading to the complexity of automobile manufacturing industry network, followed by the technical environment and market environment. Over the past 10 years of China＇ s automobile manufacturing industry, net- work environment has experienced two large fluctuations, and overall complexity presents a growth trend. This study can provide a reference for complexity measure and control of automotive industry environment.
作者
何喜军
魏国丹
武玉英
HE Xi-jun WEI Guo-dan WU Yu-ying(College of Economic and Management, Beijing University of Technology, Beijing 100124, China)
出处
《运筹与管理》
CSSCI
CSCD
北大核心
2017年第2期173-182,共10页
Operations Research and Management Science
基金
国家自然科学基金资助项目(71371018)
国家社会科学青年基金资助项目(13CGL002)
北京社会科学面上基金资助项目(15JGB124)
关键词
模糊证据推理
汽车制造产业网络
复杂性
熵值法
fuzzy evidential reasoning
automobile manufacturing industry network
complexity
entropy evalua-tion method
