Promoting agricultural sustainable development by a novel integrated pythagorean neutrosophic and WINGS-BWM model

This paper identifies nine factors affecting agricultural sustainable development by reading extensive literature and invites five experts to assess these factors using the pythagorean neutrosophic linguistic variable. Some of these factors can directly reduce the environmental footprint of agriculture, improve soil health, and promote biodiversity, while others can indirectly integrate to support the adoption of sustainable practices, further mitigating environmental degradation. Collectively, these factors reinforce ecological balance and play a critical role in advancing agricultural sustainable development. To unravel the complex relationships among these factors, a novel decision theory model is proposed, integrating pythagorean neutrosophic set (PNS) with Weighted Influence Nonlinear Specification System (WINGS) and Best-Worst Method (BWM). In addition, we not only categorized all factors into cause-and-effect factors, but also constructed a network relationship diagram based on them. The study shows that agricultural modernization (Y6) is the most important factor and land remediation (Y2) is the most influential factor. This integrated approach can more effectively address the common challenges of uncertainty and linguistic ambiguity in decision-making scenarios. Combining PNS with WINGS helps make the interactions and importance of factors more apparent, which is particularly suitable for analyzing key factors that promote agricultural sustainability. The incorporation of BWM further ensures the model's accuracy and objectivity. This method provides a more comprehensive and accurate reflection of decision-makers' opinions and judgments, improving decision-making efficiency, and can be widely applied not only in agriculture but also to other decision-making problems.