Strategic Planning Model in Higher Education using Neutrosophic Z Numbers

Abstract

Strategic planning in higher education faces complex challenges due to the imprecise nature of decision-making criteria, the diversity of stakeholders involved, and the changing dynamics of academic environments. This study addresses the problem of how to model institutional planning processes that effectively incorporate the uncertainty, subjective assessments, and incomplete data characteristic of this context. While various approaches to decision-making in education exist, the current literature presents a significant limitation: the lack of methods that simultaneously integrate the vagueness of human perceptions, the inconsistency of institutional preferences, and the quantitative restrictions inherent to the university setting. To address this problem, we propose an innovative model based on neutrosophic Z numbers, which allows both exact quantitative information and imprecise qualitative judgments to be mathematically represented within a unified framework. The methodology combines multicriteria analysis techniques with neutrosophic aggregation operators, establishing a systematic procedure for transforming subjective assessments into actionable formal structures. The approach includes specific steps for collecting strategic criteria, weighting variables using adaptive membership functions, and generating optimized action plans. The contributions of this work are both theoretical and practical. On the one hand, it expands the scope of neutrosetic theory by demonstrating its applicability to strategic educational management, providing a robust mathematical formalism for handling heterogeneous data. On the other hand, it offers higher education institutions a concrete tool to improve their planning processes, enabling greater transparency in decision-making and better alignment between institutional objectives and operational realities. The presented model represents a significant advance over traditional methods, comprehensively capturing the complexity inherent in modern university systems.