Joint analysis of eco-efficiency and eco-innovation with common weights in two-stage network DEA: A big data approach
Document Type
Journal Article
Publication Title
Technological Forecasting and Social Change
Publisher
Elsevier Ltd
School
School of Business and Law
RAS ID
26602
Abstract
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.
DOI
10.1016/j.techfore.2018.01.035
Access Rights
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Comments
Mavi, R. K., Saen, R. F., & Goh, M. (2018). Joint analysis of eco-efficiency and eco-innovation with common weights in two-stage network DEA: A big data approach. Technological Forecasting and Social Change, 144, 553 - 562. Available here