@article {bnh-7443, title = {A new model for effective post-disaster housing reconstruction: Lessons from Gujarat and Bihar in India}, journal = {International Journal of Project Management}, volume = {35}, year = {2017}, month = {07/2017}, abstract = {

This paper critiques the traditional project management (PM) approach for post-disaster reconstruction work in relation to long-term effectiveness at strengthening disaster resilience of communities. While assessments of post-disaster reconstruction projects normally occurs within a few years of the disaster this paper is based on a study of four {\textquoteleft}good practice{\textquoteright} reconstruction projects, 15years after the earthquake and seven years after the flooding disaster from the Indian states of Gujarat and Bihar respectively. This extended timeframe enabled the examination of long-term outcomes related to disaster resilience of communities. The comparison of the four case study projects through extended timeframe enabled authors to articulate critical success factors contributing to project{\textquoteright}s effectiveness. The research found that the best long-term outcomes were achieved when the agencies implementing post-disaster housing reconstruction projects: 1) adopted an {\textquoteleft}agile{\textquoteright} approach to project planning and implementation; 2) allocated\ ample time\ for gaining and maintaining community trust; iii) provided multiple materials, technologies and skilled labour choices to ensure hazard-safety of housing, and (iv) continued community capacity building beyond the completion of the reconstruction work. These imperatives have prompted the development of a progressive, spiral model for effective post-disaster housing reconstruction project management which is presented in this paper.

}, keywords = {Community capacity, Housing reconstruction, India, Post-disaster project management, Project life-cycle, resilience}, doi = {10.1016/j.ijproman.2017.02.002}, url = {https://www.sciencedirect.com/science/article/abs/pii/S0263786317301618}, author = {Mittul Vahanvati and Martin Mulligan} }