Data-driven zero-carbon transition analysis in the industrial and manufacturing sectors: a world-regional perspective

Tat Dat Bui, Viqi Ardaniah, Qinghua Zhu, Mohammad Iranmanesh, Ming Lang Tseng

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

This study contributes to concerning data-driven zero-carbon transition in the industrial and manufacturing sectors. Zero-carbon transition ensures that regions meet energy system provisions, are resilient to climate change, and adopt transition assessments toward the goal of low or zero carbon. Prior studies have failed to (1) generate these attributes from databases and confirm the validity of prominent attributes, (2) build a hierarchical model with an interrelationship from the world-regional perspective, and (3) determine the vital attributes representing knowledge gaps for zero-carbon transition. The proposed hybrid method is employed to obtain attributes from a database and is based on the literature. The results indicate that energy system provisions, low-carbon transition assessment and resilience in terms of climate change adaptation are significant in directing zero-carbon transition studies and challenges. This study shows that Asia and Oceania, Latin America and the Caribbean need to improve their zero-carbon transition performance.

Original languageEnglish
JournalInternational Journal of Logistics Research and Applications
DOIs
Publication statusAccepted/In press - 2023

Keywords

  • Zero-carbon transition
  • data-driven analysis
  • entropy weight method
  • fuzzy Delphi method
  • fuzzy decision-making trial and evaluation laboratory
  • industrial and manufacturing sectors

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