Joint analysis of eco-efficiency and eco-innovation with common weights in two-stage network DEA: A big data approach

被引：131

作者：

Mavi, Reza Kiani ^{[1
]}

Saen, Reza Farzipoor ^{[2
]}

Goh, Mark ^{[3
]}

机构：

[1] Edith Cowan Univ, Sch Business & Law, Ctr Innovat Practice, Joondalup, WA 6027, Australia

[2] Islamic Azad Univ, Karaj Branch, Dept Ind Management, POB 31485-313, Karaj, Iran

[3] Natl Univ Singapore, NUS Business Sch, 15 Kent Ridge Dr, Singapore 119245, Singapore

来源：

TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE | 2019年 / 144卷

关键词：

Eco-efficiency; Eco-innovation; Two-stage network DEA; Goal programming; Big data; OECD; DATA ENVELOPMENT ANALYSIS; MODELING UNDESIRABLE FACTORS; SUPPLY CHAIN; POWER-PLANTS; WATER; MANAGEMENT; ENERGY; RESOURCE; RANKING; PERFORMANCE;

D O I：

10.1016/j.techfore.2018.01.035

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

The joint investigation of economic growth and environmental impact has led research to develop evaluation models on environmental and economic changes, especially on eco-innovation and eco-efficient products. In this paper, a novel approach is proposed to find the common set of weights in a two-stage network data envelopment analysis based on goal programming to analyze the joint effects of eco-efficiency and eco-innovation, considering the undesirable inputs, intermediate products, and the outputs in the context of big data. Applying the model to the countries in the OECD and ranking the results show that Switzerland is highest in eco-efficiency and Estonia is highest in eco-innovation.

引用

页码：553 / 562

页数：10

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