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

Reza Kiani Mavi, Reza Farzipoor Saen*, Mark Goh

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

94 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)553-562
Number of pages10
JournalTechnological Forecasting and Social Change
Volume144
DOIs
Publication statusPublished - Jul 2019

Keywords

  • Big data
  • Eco-efficiency
  • Eco-innovation
  • Goal programming
  • OECD
  • Two-stage network DEA

ASJC Scopus subject areas

  • Business and International Management
  • Applied Psychology
  • Management of Technology and Innovation

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