Case study design for short-term predictable disasters

Abstract

Purpose

The purpose of this work is the development of a structured case study design process for developing case studies in humanitarian logistics, in particular for short-term predictable disaster situations like floods and hurricanes. Moreover, useful public sources are presented in order to enable researchers to find relevant data for their case studies more easily.

Design/methodology/approach

A structured framework for case study design is set up, splitting the process into different steps and phases.

Findings

The framework is applied to an illustrative example, where case studies with different numbers and levels of detail of scenarios are designed based on the three-day forecast for hurricane Harvey in 2017. The corresponding solutions demonstrate the relevance of using as much forecast information as possible in case study building, and in particular in scenario design, in order to get useful and appropriate results.

Research limitations/implications

The case study design process is mostly suitable for short-term predictable disasters, but can also be adapted to other types of disasters. The process has been applied to one specific hurricane here which serves as an example.

Practical implications

Also for practitioners, the results of this work are highly relevant, as constructing realistic cases using real data will lead to more useful results. Moreover, it is taken into account in the case study design process that relief agencies are regularly confronted with disasters in certain areas and hence need to define the basic planning situation and parameters “once and for all” and on a long-term basis, whereas disaster specific data from forecasts are only available within a short time frame.

Originality/value

The new design process can be applied by researchers as well as practitioners, and the publicly available data sources will be useful to the community.

Citation

Grass, E. and Fischer, K. (2020), "Case study design for short-term predictable disasters", Journal of Humanitarian Logistics and Supply Chain Management, Vol. 10 No. 3, pp. 391-419. https://doi.org/10.1108/JHLSCM-11-2019-0077