Analysis of Indicator Dynamics in Agricultural Sustainability using Neutrosophic Cognitive Maps

Abstract

Agricultural sustainability is a complex system influenced by interconnected environmental, economic, and sociocultural factors, whose relationships are often marked by uncertainty. This study addresses the interdependence of these factors using Neutrosophic Cognitive Maps (NCMs), a methodology capable of modeling causality in complex systems by incorporating degrees of truth, falsity, and indeterminacy. Twelve key indicators across the three dimensions of sustainability were selected, and an NCM was constructed based on expert criteria to visualize and analyze their dynamic interactions. Centrality analysis, following a de-neutrosophication process, revealed that sociocultural indicators, specifically the well-being of the agricultural community (X12) and the preservation of traditional knowledge (X11), along with economic resilience to shocks (X8), possess the greatest influence within the system. Findings underscore the strong interconnection between dimensions, highlighting, for example, the positive influence of traditional knowledge on biodiversity (X1) and the tension between productivity (X5) and natural resources (X2, X3) if not managed sustainably. The research demonstrates the utility of NCMs for capturing the complexity and uncertainty inherent in agricultural sustainability and offers a basis for developing more integrated and adaptive strategies and policies, recognizing the fundamental role of sociocultural dynamics and economic resilience.