Published May 4, 2025 | Version v1

Understanding the Impact of Environmental Regulations on Green Technology Innovation Efficiency in the Construction Industry

  • 1. Associate professor ,PhD Bukhara State University

Description

Green Supply Chain Management (GSCM) has become an important approach in the construction industry to promote environmental sustainability throughout construction projects. However, even with its widespread use, the construction industry still causes many harmful environmental effects, such as high greenhouse gas emissions, resource depletion, excessive waste, and damage to natural habitats, all of which contribute to climate change. To combat these issues, a shift towards regenerative thinking is needed, which goes beyond reducing negative impacts and focuses on actively restoring ecosystems, replenishing resources, and repairing damaged habitats.This study builds on existing GSCM practices and highlights their limitations in achieving true sustainability. In response, it introduces a new framework called Regenerative Supply Chain Management (RSCM), which includes key regenerative principles: Focus on Place, Harmony with Place, and Co-evolution. This framework offers a more thorough approach and supports the transition toward regenerative practices. Ultimately, this framework provides valuable insights into advancing sustainable practices in construction and suggests practical steps for the industry. By adopting regenerative methods, the construction sector can help restore and renew the built environment, leading to a more resilient and sustainable future.

Files

185-195 Igamova.pdf

Files (319.8 kB)

Name Size
md5:03cb64118b094fcc0e8b3f3586a28a86
319.8 kB Preview Download

Additional details

References

  • 1. Abdel-Basset M, Mohamed R, Sallam K, Elhoseny M (2020) A novel decision-making model for sustainable supply chain finance under uncertainty environment. J Clean Prod 269:122324
  • 2. Abdolazimi O, Ma J, Shishebori D, Ardakani MA, Masaeli SE (2023) A Multi-Layer blood supply chain configuration and optimization under uncertainty in COVID-19 pandemic. Comput Ind Eng 182:109441