Disaster and Recovery: Processes Compressed in Time

The study of postdisaster recovery is in its infancy, and there is as yet no body of theory to guide researchers (Alesch 2005; Smith and Wenger 2007; Olshansky and Chang 2009). Few researchers have conducted in-depth research of recovery processes following more than one disaster (e.g., Haas et al. 1977; Rubin 1985; Comerio 1998; Phillips 2009; Alesch et al. 2009; Olshansky et al. 2006; Olshansky and Johnson 2010), which has further impeded the development of theory for postdisaster recovery phenomena. This is an important issue, for very practical reasons. In recent years, the world has experienced numerous disastrous events, each of which has displaced hundreds of thousands of families from their homes and killed tens of thousands of people. The most recent of these are the earthquake and tsunami in Japan in March 2011, the devastating earthquake in Haiti in January 2010, and the floods that overwhelmed Pakistan in the summer of 2010. Each such disaster devastates households and communities, requires contributions of billions of dollars from around the world, and requires a strategy for rebuilding homes, livelihoods, and urban systems. A more organized framework for studying—and learning from—recovery processes following such disasters would help to guide local, national, and international agencies in more effectively organizing for and implementing long-term recovery. Recovery involves residents rebuilding homes or seeking new accommodations, businesses repairing and surviving lean times, utilities and public agencies repairing infrastructure and facilities, and households learning to cope with new stresses. These multiple layers of recovery processes provide fruitful research opportunities for urban planners, engineers, political scientists, public administration scholars, sociologists, economists, architects, and others, all relying on theories grounded in their own disciplines. The question is, other than the causative circumstances, is there anything fundamentally different about urban redevelopment, public finance, organization of public institutions, and social and economic problems when the subject of study is in a postdisaster environment? We posit that the key characteristic that distinguishes postdisaster conditions from normal times is time compression. Stated simply, the postdisaster environment consists of a compression of urban development activities in time and in a limited space, a phenomenon that we refer to as time compression. Furthermore, time compression affects different aspects of recovery processes in different ways, thereby changing their relationships compared to normal times. For example, processes of physical construction, financial transactions, social capital formation, and institution building compress unequally in time. The place of disaster thus becomes different from other places in new ways. Researchers describe numerous characteristics of postdisaster recovery, with time compression being one of them (e.g., Haas et al. 1977; Quarantelli 1999; Olshansky and Chang 2009). We argue, however, that time compression is an important overarching characteristic, and that it provides a key to understanding recovery. Time compression explains most of what we know that distinguishes postdisaster recovery processes from similar processes in normal times. This paper offers a conceptual framework to help scholars and recovery professionals of all disciplines think more clearly about how the recovery environment distorts their normal disciplinary lenses. We first explain how time compression works, using examples from the field of urban development and planning. Next we describe how differential compression helps to explain some of the more challenging aspects of urban reconstruction following disasters. Next, several examples illustrate how well-known recovery phenomena can be explained as symptoms of time compression. Finally, we suggest how the concept of time compression can be used to improve planning processes and institutional design following disasters. In the conclusion, we suggest how scholars and practitioners in disciplines other than our own might also find the time-compression concept to be useful.