Construction Supply Chain Management for Circular Economy Performance: Procurement Economics and Configuration Evidence from New Zealand

Abstract

Supply chain management (SCM) optimisation is a critical but under-examined pathway for delivering circular economy outcomes in the construction sector, particularly in geographically remote and small- and medium-sized enterprise-dominated markets such as New Zealand (NZ). This study investigates how SCM practices, such as digital tools, early contractor involvement, strategic partnerships, and reverse logistics, can be optimised to improve circular performance in NZ-built environment projects. A pragmatist, abductive mixed-methods design combined 75 case studies, a 28-case quantitative subset, 15 elite semi-structured interviews and documentary evidence. Reflexive Thematic Analysis was integrated with descriptive statistics, cross-tabulation, non-parametric testing, and configuration archetype analysis. Coordination and partnerships are the most frequently observed SCM lever, appearing in 46.7% of the 75 cases and in all four cases in the highest waste-diversion band, while digital tools are seldom deployed as the primary lever. Two operational metrics summarise these configurations: a Waste Hierarchy Index (WHI) of 77.6%, calculated across the 66 cases with an assignable waste hierarchy position, and a Digital SCM Adoption Rate (DSAR) of 15.1%, calculated across the 73 cases with a stated primary lever. Together they indicate an upstream but digitally uneven pattern of optimisation. The study contributes a configuration-based method for comparing SCM levers in circular construction, together with the first NZ evidence base of this kind, and finds that procurement reform rather than digital investment is the key constraint on circular performance. Practical implications include embedding early contractor involvement and integrated design in public procurement, funding sector-wide digital interoperability rather than firm-level tools, and extending site waste management plan reporting. Priority future research is longitudinal, scale-stratified testing of the configuration archetypes identified in this paper.