Prioritization of strategic initiatives in the context of natural disaster prevention
DOI:
https://doi.org/10.14488/BJOPM.2019.v16.n3.a10Keywords:
Disaster prevention, Early warning system, Value-Focused Thinking, Multicriteria decision analysisAbstract
Goal: The purpose of this paper is to build the structure of a multicriteria decision model that supports definition and prioritization of strategic initiatives by an institution performing in the prevention of natural disasters.
Design/Methodology/Approach: The Multicriteria Decision Analysis (MCDA) methodological process is adopted to build a multicriteria evaluation model. A two-phase process is followed, employing a top-down approach, based on Value-Focused Thinking (VFT), in combination with the Multi Attribute Value Theory (MAVT) method. The participants of the MCDA process were experts of the control room in the case study institution.
Results: The proposed methodology not only helped decision makers to enumerate a number of strategic initiatives to accomplish the organizational objective, but also helped them to establish a structured procedure to prioritize these initiatives.
Limitations: Absence of a criterion related to the organization budget in the model; limited scope of participation in the process; absence of quantitative criteria.
Practical implications: The major practical contributions are as follows: an structured model that supports the strategic planning process; a better allocation of resources (human, financial, and materials) in projects that are truly aligned with the strategic objective of the organization; the organizational learning coming from the exercise of reflection on values, objectives and preferences; and the legitimacy of decisions as a result of the participative character of the construction process of the model.
Originality/Value: In this study, a multicriteria evaluation model is structured and applied as support for strategic decision making in the context of a natural disaster early warning system. The model has a significant application potential, since it encourages the adoption of structured decision support methods rather than traditional empirical decision making. Thus, the value of the study lies in the contribution that the proposed model can offer to more effective disaster prevention.
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