Construction material supply for post-Cyclone Gabrielle transport infrastructure recovery in New Zealand: Challenges and strategies
Kenan Liu et al.
Abstract
A shortage of local construction materials and inefficient supply chains can severely impede post-disaster reconstruction and recovery. Yet, the extant literature offers limited insights into the material supply processes in relation to transport infrastructure recovery and extreme weather events. To address the gap, this paper adopted a case study approach, including literature reviews, semi-structured interviews and on-site observations, to examine the key challenges impeding material supply for the rapid recovery of transport networks following the 2023 Cyclone Gabrielle in New Zealand. Intervention measures and their effectiveness were also evaluated. The findings revealed that high-specification aggregates (e.g., sealing chips), asphalt concrete and rock armour experienced various supply issues, such as shortages, high haulage costs, delivery delays, and substandard quality. These problems primarily stemmed from six critical challenges, which fall into four domains: 1) geo-conditions, 2) resource management and allocation prioritisation, 3) supply chain planning and development, and 4) project governance and procurement management. The challenges interacted to create systematic complexity in material supply systems. While the intervention measures demonstrated promise in addressing these issues, the persistence of adverse outcomes underscores the necessity for future efforts to shift the focus upstream toward prevention and drive broader systemic transformation. Accordingly, a strategic framework was proposed to enhance construction material supply for rapid and effective transport infrastructure recovery after future extreme weather events.
1 citation
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.16 × 0.4 = 0.06 |
| M · momentum | 0.53 × 0.15 = 0.08 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.