Risks Associated with Green Building Projects in a Developing Country: An Empirically Derived Taxonomy for Lagos State, Nigeria

This study develops an empirically derived, context-specific taxonomy of risks associated with green building projects in Lagos State, Nigeria, and explains how these risks are structurally organised in an institutionally underdeveloped market. A quantitative cross-sectional survey yielded 152 valid responses from registered architects, quantity surveyors, builders, engineers and project managers (72.4% response rate). Twenty-five risk variables identified through a systematic literature review were rated on a five-point scale and analysed using descriptive statistics and principal component analysis (PCA) with varimax rotation, applied as a dimension-reduction procedure, with the number of components to retain determined by Horn’s parallel analysis. Findings were interpreted using the Technology-Organisation-Environment (TOE) framework and systems theory. Financial risk attracted the strongest agreement as a relevant risk (M = 4.14), followed by design and construction risks (M = 3.80). Parallel analysis supported retaining three components, which together explain 65.37% of the total variance: operational, performance and lifecycle risks; technical and external interface risks; and design, regulatory, market and financial delivery risks. Although financial risk attracted the strongest agreement of any single item, it did not constitute a distinct risk dimension; it was subsumed within the broader front-end delivery component, whereas operational and lifecycle risks accounted for the largest share of common variance. The taxonomy therefore reveals a divergence between the strength of agreement a risk attracts and the share of common variance it accounts for. Findings support lifecycle costing, incentive-based regulation, post-occupancy performance management, and green building risk management within continuing professional development. Convenience sampling, a Lagos-only sampling frame and an early-career respondent bias limit generalisability. This study presents an empirically derived parallel-analysis-verified taxonomy of green building risks, advancing TOE- and systems theory-based understanding of green building risk in developing economies.