A new short paper has been published in the International Journal of Disaster Risk Science by a research group at the Institute for Risk and Disaster Reduction at University College London, in collaboration with the Universidad Nacional Autónoma de México. Entitled ‘A Likert Scale-Based Model for Benchmarking Operational Capacity, Organizational Resilience, and Disaster Risk Reduction’, the main goal of the paper is to introduce a simple and replicable scale that might be helpful for benchmarking gaps analyses and resilience assessments, as well as operational research.
Likert scales are a common methodological tool for data collection used in quantitative or mixed-method approaches in multiple domains. They are often employed in surveys or questionnaires, for benchmarking answers in the fields of disaster risk reduction, business continuity management, and organizational resilience. However, both scholars and practitioners may lack a simple scale of reference to assure consistency across disciplinary fields.
This article introduces a simple-to-use rating tool that can be used for benchmarking responses in questionnaires, for example, for assessing disaster risk reduction, gaps in operational capacity, and organizational resilience. We aim, in particular, to support applications in contexts in which the target groups, due to cultural, social, or political reasons, may be unsuitable for in-depth analyses that use, for example, scales from 1 to 7 or from 1 to 10.
This methodology is derived from the needs emerged in our recent fieldwork on interdisciplinary projects and from dialogue with the stakeholders involved. The output is a replicable scale from 0 to 3 presented in a table that includes category labels with qualitative attributes and descriptive equivalents to be used in the formulation of model answers. These include examples of levels of resilience, capacity, and gaps. They are connected to other tools that could be used for in-depth analysis. The advantage of our Likert scale-based response model is that it can be applied in a wide variety of disciplines, from social science to engineering.
Read the paper (PDF).