Assessing the impacts of preferential procurement on low-carbon building. (20th January 2016)

• Record Type: Journal Article
• Authors: Liu, Xiaoyu; Cui, Qingbin
• Is Part Of: Journal of cleaner production. Volume 112:Part 1(2016:Jan.)
• Page Start: 863
• Page End: 871
• Publication Date: 2016-01-20
• Subjects: Greenhouse gas emissions -- Building construction -- Bid preference -- Project procurement; Factory and trade waste -- Management -- Periodicals; Manufactures -- Environmental aspects -- Periodicals; Déchets industriels -- Gestion -- Périodiques; Usines -- Aspect de l'environnement -- Périodiques; 628.5
• DOI: 10.1016/j.jclepro.2015.06.015
• Languages: English
• ISSNs: 0959-6526

Abstract

Abstract: The significance of global warming is shaping building procurement, with much of the effort aimed at reducing greenhouse gas emissions through a preferential bidding mechanism. However, only a limited number of studies have quantitatively estimated the potential impact of bid preference on the emission reduction from building construction. The aim of this paper is to improve our understanding of how bid discounts change owners' procurement costs and the magnitudes of emission mitigation. A two-stage optimization model is designed to help the owner determine the discount rate that would automatically control the emission of the awarded contract within a desired level. The goal is for bidders to regard emission reduction efforts as an investment, with returns coming in the form of an increased chance of winning the bid. Our results imply that for the building retrofit project studied herein, a discount rate of 0.6 is suggested for every percentage of emission reduction. This discount level reduces greenhouse gas emissions by 28.2% while raising procurement costs by 3.7% relative to a non-preference mechanism. The increased procurement costs can be partially compensated under existing cap-and-trade scheme. The results show that the choice of discount significantly alters bidders' efforts on emission mitigation, and emission control cost can be minimized with the proposed optimization algorithm. Highlights: A model is developed for owners to determine bid discount to reduce project emission. The case study suggests a 0.6 discount for every percentage of emission reduction. The 0.6 discount reduces emissions by 28.2% while raising procurement costs by 3.7%. The choice of bid discount significantly alters bidders' emission reduction efforts.