Tomato Consumer Behavior in Hino City, Japan: Application of Multiple Correspondence and K-means Cluster Analyses

抄録

Japan is currently facing multiple challenges related to an aging society, including labor shortages in various sectors, especially in agriculture. Despite government support, new farmers struggle to discern and understand market trends, changing consumer behavior, and seasonal changes. This study focuses on tomatoes and aims to assist new farmers and producers in making strategic decisions by utilizing data science techniques to understand local market consumer behavior and trends. A questionnaire survey was used to identify consumer behavior based on demographic characteristics, consumer preferences, seasonal buying and consumption behaviors, spending price per purchase, and purchasing channels. We collected 316 valid data points using a questionnaire survey deployed in face-to-face interactions across multiple locations as well as online collection methods. Data was collected from May 01, 2022, to June 30, 2022. Multiple correspondence analysis and K- means cluster analysis were used to determine six consumer segments - convenient supermarket shoppers, premium salad shoppers, price-conscious tomato enthusiasts, diverse tomato tasters, quality-conscious shoppers, and gourmet tomato shoppers. The analyses revealed the unique characteristics of tomato purchasing and consumption behaviors, including variations in tomato type, consumption type, season, demographic factors, and preferred purchasing channels. This study further explored the factors influencing tomato purchasing decisions within each segment by integrating data-driven decision-making principles. This approach allows for actionable insights facilitated by understanding local consumers while empowering new tomato farmers to make informed decisions.