Abstract
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.
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
3. Adetunji I, Price ADF, and Fleming P (2008), Achieving sustainability in the construction supply chain. In Proceedings of the institution of civil engineers-engineering sustainability (Vol. 161, No. 3, pp. 161–172). Thomas Telford Ltd.
4. Ahmed SM, Azhar S, Ahmad I (2002) Supply chain management in construction: scope, benefits and barriers. Delhi Business Rev 3(1):1–6
5. Badi S, Murtagh N (2019) Green supply chain management in construction: a systematic literature review and future research agenda. J Clean Prod 223:312–322
6. Badri H, Bashiri M, Hejazi TH (2013) Integrated strategic and tactical planning in a supply chain network design with a heuristic solution method. Comput Oper Res 40(4):1143–1154
7. Balasubramanian S, and Shukla V (2017), Green supply chain management: an empirical investigation on the construction sector. Supply Chain Manag: An Int
8. Behera P, Mohanty RP, Prakash A (2015) Understanding construction supply chain management. Prod Plan Control 26(16):1332–1350
9. Bertsimas D, Sim M (2004) The price of robustness. Oper Res 52(1):35–53
10. Bolpagni M, Gavina R, Ribeiro D, and Arnal IP (2022), Shaping the future of construction professionals. Industry 4.0 for the Built Environ: Methodol, Technol Skills, 1–26.
11. Chen CL, Yuan TW, Lee WC (2007) Multi-criteria fuzzy optimization for locating warehouses and distribution centers in a supply chain network. J Chin Inst Chem Eng, 38(5–6):393–407
12. Chen Z, Ming X, Zhou T, Chang Y (2020) Sustainable supplier selection for smart supply chain considering internal and external uncertainty: an integrated rough-fuzzy approach. Appl Soft Comput 87:106004
13. Chen JH, and Ma SH (2008), A dynamic reputation incentive model in construction supply chain. In 2008 International conference on management science and engineering 15th annual conference proceedings (pp. 385–392). IEEE.
14. Cheng JC, Law KH, Bjornsson H, Jones A, Sriram R (2010) A service oriented framework for construction supply chain integration. Autom Constr 19(2):245–260
15. Chibeles-Martins N, Pinto-Varela T, Barbosa-Póvoa AP, Novais AQ (2016) A multi-objective meta-heuristic approach for the design and planning of green supply chains-MBSA. Expert Syst Appl 47:71–84
16. Dantzig GB (1955) Linear programming under uncertainty. Manage Sci 1(3–4):197–206
17. El-Sayed M, Afia N, El-Kharbotly A (2010) A stochastic model for forward–reverse logistics network design under risk. Comput Ind Eng 58(3):423–431
18. Eriksson PE (2010), Improving construction supply chain collaboration and performance: a lean construction pilot project. Supply Chain Manag: An Int J.
19. Fahimnia B, Davarzani H, Eshragh A (2018) Planning of complex supply chains: A performance comparison of three meta-heuristic algorithms. Comput Oper Res 89:241–252
20. Fathollahi-Fard AM, Hajiaghaei-Keshteli M, and Tavakkoli-Moghaddam R (2020), Red deer algorithm (RDA): a new nature-inspired meta-heuristic. Soft Comput, 1–29.
21. Fattahi M, Mahootchi M, Govindan K, Husseini SMM (2015) Dynamic supply chain network design with capacity planning and multi-period pricing. Transp Res Part E: Logist Transp Rev 81:169–202
22. Ghahremani-Nahr J, Kian R, Sabet E (2019) A robust fuzzy mathematical programming model for the closed-loop supply chain network design and a whale optimization solution algorithm. Expert Syst Appl 116:454–471
23. Gholizadeh H, Fazlollahtabar H (2020) Robust optimization and modified genetic algorithm for a closed loop green supply chain under uncertainty: case study in melting industry. Comput Ind Eng 147:106653
24. Gholizadeh H, Fazlollahtabar H, Khalilzadeh M (2020) A robust fuzzy stochastic programming for sustainable procurement and logistics under hybrid uncertainty using big data. J Clean Prod 258:120640
25. Gholizadeh H, Jahani H, Abareshi A, Goh M (2021) Sustainable closed-loop supply chain for dairy industry with robust and heuristic optimization. Comput Ind Eng 157:107324
26. 16.Gao, Y., Tsai, S.-B., Xue, X., Ren, T., Du, X., Chen, Q., and Wang, J. (2023). An Empirical Study on Green Innovation Efficiency in the Green Institutional Environment. Sustainability, 10(3), 13. https://doi.org/10.3390/su
27. Игамова, Ш. З. (2023). ОСОБЕННОСТИ БУХАРСКИЙ ОБЛАСТИ C ПОЗИЦИЙ ИННОВAЦИОННОГО РAЗВИТИЯ ЭКОНОМИКИ. Gospodarka i Innowacje., 42, 170-174.
28. Igamova, S. (2021). PROCESS ANALYSIS OF ESTABLISHMENT WITH EQUIPMENT. ЦЕНТР НАУЧНЫХ ПУБЛИКАЦИЙ (buxdu. uz), 7(7).
29. Irizarry J, Karan EP, Jalaei F (2013) Integrating BIM and GIS to improve the visual monitoring of construction supply chain management. Autom Constr 31:241–254

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