While sustainable construction practices effectively reduce environmental impact, their exclusive focus on environmental, economic, and social goals limits their ability to actively foster positive transformation and ecosystem restoration. Addressing the growing challenges in the built environment necessitates a shift to regenerative practices within the construction industry. Unlike sustainability, regenerative practices go beyond the concept of merely sustaining the status quo; they are geared towards actively enhancing and restoring the built environment over time. However, implementing these practices is less prominent in the construction industry due to the absence of a suitable tool for evaluating their expected performance outcomes. This study bridges this gap by introducing a novel performance evaluation framework for implementing regenerative construction practices, establishing a benchmark for implementation. Through an extensive literature review and data collection from a committee of regenerative outcome leads, we employ the Fuzzy Analytical Hierarchical Process (FAHP) to establish interconnections among key regenerative performance criteria. Results highlight the dominant significance of “Healthy, more resilient, and connected communities,” surpassing other criteria like “Thriving and prosperous natural systems,” “Prosperous and resilient local economies,” and “Net-positive environmental development.” The proposed evaluation framework offers theoretical and practical implications, fostering a new theoretical approach that exceeds sustainability standards and provides tangible guidance for construction decision-makers.
Funding
Expansion and Validation of Regenerative Decision Support System to improve Resilient Construction | Funder: Te Herenga Waka-Victoria University of Wellington
History
Preferred citation
Oyefusi, O. N., Enegbuma, W. I., Brown, A. & Olanrewaju, O. I. (2024). Development of a novel performance evaluation framework for implementing regenerative practices in construction. Environmental Impact Assessment Review, 107, 107549-107549. https://doi.org/10.1016/j.eiar.2024.107549