A dynamic model for costing disaster mitigation policies

Abstract

The optimal level of investment in mitigation strategies is usually difficult to ascertain in the context of disaster planning. This research develops a model to provide such direction by relying on cost of quality literature. This paper begins by introducing a static approach inspired by Joseph M. Juran's cost of quality management model (Juran, 1951) to demonstrate the non-linear trade-offs in disaster management expenditure. Next it presents a dynamic model that includes the impact of dynamic interactions of the changing level of risk, the cost of living, and the learning/investments that may alter over time. It illustrates that there is an optimal point that minimises the total cost of disaster management, and that this optimal point moves as governments learn from experience or as states get richer. It is hoped that the propositions contained herein will help policymakers to plan, evaluate, and justify voluntary disaster mitigation expenditures.

Building disaster‐resilient micro enterprises in the developing world

“…Given the minimal investment in disaster mitigation and preparedness in developing countries, it is likely that the proposed model actually will reduce the total cost of recovery (Altay et al, 2013). Such an approach potentially could be a more productive use of scare resources than traditional, top-down 'ex-post' interventions, especially for the informal sector.…”

Country logistics performance and disaster impact

“…Therefore, when humanitarian organisations do arrive on location, they rely heavily on the resources in-country (Tatham et al, 2012), one of them being the logistics network. The importance of the timing window for the response means that planning and preparing for disasters is generally considered to be more cost-effective than post-disaster initiatives such as disaster relief and recovery (Altay et al, 2013;Christoplos et al, 2001;Skoufias, 2003). Logistics activities during the response often require planning and preparing for (Beresford and Pettit, 2009;Kovács and Spens, 2007;McEntire, 2002;Perry, 2007;van Wassenhove, 2006) since activities such as supplier selection, procurement and customs clearance are time-consuming processes.…”

Estimating the mitigation effect of Tokai earthquake measures on housing damage: a counterfactual approach

“…Altay, Prasad, and Tata (2013) developed a model with which to determine the optimal level of disaster mitigation investment using a methodology from the literature on the cost of quality, and discovered that the optimal level moves as governments learn more from experience and states become richer. De Hoop and Ruben (2010) used a simulation-based model to evaluate consumption losses after earthquakes under different governmental intervention scenarios.…”

“…This approach allowed us to produce data for earthquake-proof and non-earthquake-proof houses at the municipality level, categorised by construction year and by structure. 5 For an application of counterfactual analysis to an estimation of disaster damage, see de Hoop and Ruben (2010) and Altay, Prasad and Tata (2013). The variable of procurement price of the house per unit area of floor space was attained from MLIT (2003b).…”