An interdisciplinary system dynamics model for post-disaster housing recovery

Abstract

Many previous disasters have demonstrated the need for extensive personal, public, and governmental expenditures for housing recovery highlighting the importance of studying housing recovery. Yet, much research is still needed to fully understand the multi-faceted and complex nature of housing recovery. The goal of this paper is to present a holistic model to further the understanding of the dynamic processes and interdependencies of housing recovery. The impetus for this work is that inequalities in housing recovery could be addressed more effectively if we better understood interconnected factors and dynamic processes that slow down recovery for some. Currently, there is a lack of understanding about such factors and processes. Literature from engineering and social sciences was reviewed to develop an integrated system dynamics model for post-disaster housing recovery. While it is beyond current capabilities to quantify such complexities, the presented model takes a major stride toward articulating the complex phenomenon that is housing recovery.

Keywords:

• Post-disaster housing recovery
• system dynamics
• social vulnerability
• causal factors
• indicators

Acknowledgments

The authors would like to acknowledge the Risk-Based Community Resilience Planning Center of Excellence funded by the National Institute of Standards and Technology for facilitating this interdisciplinary collaboration, and providing a platform for this interdisciplinary thinking and research on housing recovery. The Center for Risk-Based Community Resilience Planning is a NIST-funded Center of Excellence; the Center is funded through a cooperative agreement between the U.S. National Institute of Standards and Technology and Colorado State University (Grant Number 70NANB15H044). The views expressed are those of the author(s), and may not represent the official position of the National Institute of Standards and Technology or the U.S. Department of Commerce.

Notes

1. Nejat & Ghosh, 2016; Olshansky, Hopkins, & Johnson, 2012; Rubin & Barbee, 1985; Sapat & Esnard, 2017.

2. For an extensive and in-depth review of the literature on housing recovery, the interested reader is referred to Hamideh and Sutley (forthcoming).

3. This statement is based on a recent field study conducted by the authors.

4. Ireton, Ahmed, & Charlesworth, 2014; Mitchell, Esnard, & Sapat, 2012; Rathfon, Davidson, Bevington, Vicini, & Hill, 2013; Siembieda, Johnson, & Franco, 2012.

5. Green & Olshansky, 2012; Green et al., 2007; Hwang, 2011; Kamel, 2012; Peacock et al., 2014; Rathfon et al., 2013; Spader & Turnham, 2014; Stevenson, Emrich, Mitchell, & Cutter, 2010; Weber & Lichtenstein, 2015.

6. Brown et al., 2012; Hwang, 2011; Khazai & Hausler, 2005; Liel et al., 2013; Paul & Che, 2011; Rossetto et al., 2014.

7. Bevington et al., 2011; Brown et al., 2012; Green et al., 2007; Hill et al., 2011; Hirayama, 2000; Hoshi, Murao, Yoshino, Yamazaki, & Estrada, 2014; Kamel, 2012; Khazai & Hausler, 2005; Kikitsu & Sarkar, 2014; Kumar et al., 2015; Liel et al., 2013; Rathfon et al., 2013; Rossetto et al., 2014; Siembieda et al., 2012; Spader & Turnham, 2014; Tafti & Tomlinson, 2015.

8. Cheng, Ganapati, & Ganapati, 2015; Green et al., 2007; Lester, Perry, & Moynihan, 2014; Stevenson et al., 2010; Weber & Lichtenstein, 2015.

9. Chang, 2010; Lu & Xu, 2014; Lui & Plyer, 2008.

10. Chang, 2010; Elliott, Hite, & Devine, 2009; Lu & Xu, 2014.

11. Green & Olshansky, 2012; Masozera, Bailey, & Kerchner, 2007; Mukherji, 2010; Spader & Turnham, 2014.

12. Chang, Wilkinson, Potangaroa, & Seville, 2010; Hwang, 2011.