Digital Literacy and Farmers' Income Level: A Difference Analysis Based on K-prototypes Clustering

The enhancement of Farmers' Digital Literacy (FDL) can facilitate their rapid integration into digital society and plays a positive role in the wealth accumulation of farming households. To effectively measure the farmers' proficiency in digital technology, 16 measurement indicators were designed, which were condensed into 5 factors through factor analysis, constructing a digital literacy index system from 5 dimensions. For mixed-type data including categories such as farmers' income levels and the average values of 5 factors, the k-prototypes algorithm was adopted for clustering and to portray the farmer's portrait. Taking 3 administrative villages in three districts of Taizhou City, Zhejiang Province as the experimental subjects, the experimental results show that the scale data has good reliability and validity. After the factor analysis rotation, there is a strong correlation between the 16 indicators and the 5 factors, which is in line with the expected corresponding relationship. After clustering, the farmer groups are divided into "high," "medium," and "low" levels of digital literacy. The higher the level of digital literacy, the more likely the farming household is to be at a higher income level. Subsequent strategies can be developed for targeted groups to systematically enhance the digital literacy of low-income groups.