This study aims to develop a resilient contractor selection model that also considers community concerns in post-disaster reconstruction projects using a “build-back better (BBB)” approach.

At the outset, a comprehensive literature review was conducted to develop the model. During this literature review, a set of contractor selection criteria were identified. Focus group discussion (FGD) sessions were then organized to revise and refine the identified criteria. As a result, a final list of 39 selection criteria was developed. Next, the Bayesian best worst method (BBWM) was conducted to determine the weights of each selection criterion. Finally, the proposed model was validated by conducting a hypothetical case study and fuzzy VlseKriterijuska Optimizacija I Komoromisno Resenje (fuzzy VIKOR) analysis. Moreover, a sensitivity analysis was conducted to examine the effect of the maximum group utility (v) value in the model.

The results emphasized that contractors in post-disaster reconstruction projects cannot be selected merely based on “technical” and “economic” factors. Instead, the other aspects, namely “organizational and managerial,” “environmental sustainability,” “resource management and procurement” and “end-user,” should also be taken into consideration. Second, factors related to financial strength, experience, risk management, energy efficiency, resource availability and assurance were particularly deemed the most significant, needing the detailed attention of the decision-makers. Lastly, the case study revealed that the proposed model has a significant potential to systemize contractor selection processes in post-disaster reconstruction projects.

Disasters, which are increasing in frequency and severity today, devastate the community’s environmental, economic and social conditions. Post-disaster reconstruction projects commence rapidly after a disaster for recovery. However, poor management procedures in these projects trigger time and cost overruns. Unlike traditional construction projects, post-disaster reconstruction projects are distinctive due to the uncertainties caused by the disasters and the prioritization of community concerns. Therefore, contractors should be selected in a way that can meet the specific needs of reconstruction projects. Otherwise, resilience in the built environment and community satisfaction can hardly be enhanced. Accordingly, this study is one of the first attempts to develop a contractor selection model for post-disaster reconstruction projects. It is believed that the developed model will make essential theoretical and practical contributions to the post-disaster reconstruction domain.