Understanding Consumer Buying Intention of E-Commerce Airfares Based on Multivariate Demographic Segmentation: A Multigroup Structural Equation Modeling Approach

The Behavioral Intention to Adopt Circular Economy-Based Digital Technology for Agricultural Waste Valorization

Thailand generates considerable amounts of agricultural food waste. This research focuses on the manufacturing and retail agricultural food system in the northeastern region of Thailand. Our study aimed to investigate the user segments and factors that influence users' behavioral intentions to utilize mobile technology for agricultural waste valorization. This study is based on the Unified Theory of the Adoption and Utilization of Technology (UTAUT2). In order to classify these segments, we performed a cluster analysis using demographic variables: gender, age, and income. In addition, the researchers employed a method known as multigroup structural equation modeling to determine and contrast the users' behavioral intentions. The results showed two types of users: (1) older users with various income ranges, and (2) younger users with a low-income range. Explicitly, age and income were the significant variables for the demographic segmentation, but gender was not. The results also revealed that social influence, price value, and trust highly affected the behavioral intentions of older and various-income users, but did not influence younger and low-income users. However, privacy strongly affected the behavioral intentions in the younger segment, but not those in the older one. Lastly, habit or regularity influenced the behavioral intentions of users in both segments. This study highlights implications for how developers and practitioners might adapt their platform strategies using a circular agricultural platform and user behaviors.