Sustainable Performance Index for Assessing the Green Technologies in Urban Infrastructure Projects

Woosik Jang, Sang Ku Lee, Seung Heon Han

Research output: Contribution to journalArticlepeer-review

22 Citations (Scopus)


To mitigate the environmental problems caused by global warming and climate change, many countries agree that reduction in greenhouse gas (GHG) emissions is mandatory. Against this backdrop, the construction industry has continuously attempted to reduce or mitigate the GHG emissions from construction projects. However, most green technology (GT) applications remain more focused on building projects and are largely limited to the operation and maintenance phases. Addressing this issue, this research proposes a sustainable performance index (SPI) for assessments of GTs related to urban infrastructures from the early stages of a project lifecycle. First, 31 infrastructure-related GTs are presented from a literature review. Second, the SPI, including environmental, economic, and social categories and 12 subfactors, is established using the fuzzy-analytic hierarchy process (fuzzy-AHP) method that functions well in eliminating the ambiguity and uncertainty in the weighting of the SPI factors. The illustrative case application shows that the SPI is expected to support decision-making processes for selecting the proper GTs and to provide a balanced view that accounts for economic and social impacts on the early planning stages of urban infrastructure projects.

Original languageEnglish
Article number4017056
JournalJournal of Management in Engineering
Issue number2
Publication statusPublished - 2018 Mar 1

Bibliographical note

Funding Information:
This work was supported by a Korea Science and Engineering Foundation (KOSEF) grant funded by the Korean government (MOST) (NRF-2015R1A2A1A09007327).

Publisher Copyright:
© 2017 American Society of Civil Engineers.

All Science Journal Classification (ASJC) codes

  • Industrial relations
  • Engineering(all)
  • Strategy and Management
  • Management Science and Operations Research


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