Enhancing Car Purchasing Decisions: A Simple Additive Weighting-Based Decision Support System for Multi-criteria Evaluation - Abyakta, Dimas Eri (International Journal of Enterprise Modelling, 2024)
This research focuses on the development and implementation of a Car Purchasing Decision Support System, employing the Simple Additive Weighting (SAW) method, aimed at aiding consumers in navigating the multifaceted landscape of car purchases. The system utilizes a structured approach to evaluate and rank car models based on multiple criteria, including price, fuel efficiency, safety rating, and design preferences. Through the application of the SAW method, the research delineates a systematic framework for decision-making, offering transparency and clarity in the evaluation process. Findings highlight the effectiveness of the Decision Support System in providing structured guidance to buyers, empowering them with comprehensive information to make informed decisions aligned with their preferences. The study not only presents a hierarchy of suitability among car models but also emphasizes the significance of criteria weights in influencing the rankings. It underscores the system's adaptability, allowing for adjustments in criteria weights to accommodate changing buyer preferences and market dynamics. The implications of this research extend beyond individual decision-making, offering insights for industry stakeholders into consumer preferences and market trends. Recommendations for future improvements advocate for enhanced data integration, user-centric design, and the incorporation of ethical and social factors to further refine these Decision Support Systems.