Exploring Consumer Preferences for Toyota Used Cars Through Machine Learning and Big Data

Abstract

The used car market has grown significantly worldwide, especially in developing countries were affordability and economic constraints shape consumer behavior. This study investigates how external factors, including brand image, corporate image, country image, and perceived risk, influence consumers' attitudes toward purchasing and their purchase intentions for used cars. To achieve each research objective, a dual-method approach was adopted. First, big data analysis and machine learning techniques were used to identify frequently purchased car brands and market trends. Second, a quantitative survey of 501 consumers was conducted to empirically examine the effects of selected external variables on buying behavior. The findings reveal that all five factors significantly influence consumer decisions, with brand image and corporate image having the most substantial direct impact on purchase attitude towards used cars. Moreover, perceived risk was found to moderate the relationship between attitude and purchase intention, suggesting that higher perceived risk weakens the positive influence of favorable attitudes on actual buying intentions. By combining big data analytics with survey-based research, this study offers a comprehensive and evidence-based perspective. The insights are valuable for marketers and importers seeking data-driven strategies in Mongolia's expanding used car sector.