DECISION-MAKING UNDER COMPLEXITY: APPLYING ELECTRE TO CHANGE MANAGEMENT STRATEGY

Abstract

This study applies the ELECTRE methodology to evaluate four change management strategies: Change Facilitation, Strategic Evolution, Adaptation Strategy, and Process Improvement Management. The evaluation considers parameters such as uncertainty, potential disputes, safety hazards, past experiences, reputation impact, and side costs from failure. Findings aim to guide organizations in selecting the most effective change management approach. Research Significance: This research is significant as it provides a structured approach to evaluating change management strategies in organizations. By applying the ELECTRE methodology, it offers insights into how factors like uncertainty, potential disputes, safety risks, and reputation impact influence the accomplishment of change projects. The results help people make better decisions in dynamic business environments. Methodology: The ELECTRE A multi-criteria decision analysis technique called the (Elimination and Choice Expressing Reality) methodology is used to rank options according to a number of criteria. In this study, ELECTRE is applied to assess change management strategies, considering factors like uncertainty, safety hazards, reputation impact, and potential costs, providing a robust framework for decision-making. Alternative: M1 Change Facilitation, M2 Strategic Evolution, M3 Adaptation Strategy, M4 Process Improvement Management Evolution parameter: Uncertainty about final consequences (C1), Possible disputes in future (C2), Safety hazards (C3), Related experiences in the past (C4), The effect on the business's image (C5), incidentals because of the likelihood of failure (C6), Result: The findings of this investigation show that the most appropriate change management strategy varies depending on the specific evaluation parameters. Alternatives such as Change Facilitation and Process Improvement Management offer distinct advantages in reducing risks, uncertainty, and safety concerns, while also considering past experiences and reputation impact for optimal decision-making.