Farmer Typologies and Quality of Life: A Cluster Analysis of Farmers in Nakhon Si Thammarat, Thailand

บทคัดย่อ

     This study aimed to identify farmer typologies based on demographic, socioeconomic, agricultural, family, and digital characteristics using the K-prototypes clustering algorithm, compare multidimensional quality of life (QoL) among the identified farmer typologies, and characterize the identified typologies and discuss their implications for targeted rural development and QoL improvement strategies. A cross-sectional study was conducted among 311 farmers randomly selected from 1,395 farming households in Na San Subdistrict, Phra Phrom District, Nakhon Si Thammarat Province, Thailand. Farmer typologies were identified using the K-prototypes clustering algorithm based on demographic, socioeconomic, agricultural, household, and digital characteristics. The optimal clustering solution was determined using the average silhouette coefficient, Davies–Bouldin index, cluster interpretability, and bootstrap stability analysis. Differences in QoL among the identified typologies were examined using one-way analysis of variance (ANOVA), followed by Tukey's honestly significant difference (HSD) post hoc test. Three distinct farmer typologies were identified: Traditional Farmers with Limited Digital Inclusion (32.48%), Intermediate Farmers with Moderate Digital Inclusion (41.80%), and Digitally Connected Progressive Farmers (25.72%). Significant differences in QoL were observed across all domains and the overall QoL score (all p < .001), with Digitally Connected Progressive Farmers consistently reporting the highest QoL and Traditional Farmers with Limited Digital Inclusion reporting the lowest. These findings indicate that farmer typologies characterized by multidimensional demographic, socioeconomic, agricultural, household, and digital characteristics are associated with variations in QoL. The study extends current knowledge by demonstrating the value of multidimensional farmer typologies for understanding heterogeneity among farmers and providing evidence to inform typology-based strategies that support digital inclusion and promote inclusive rural development. Because this study employed a cross-sectional design, the observed associations should not be interpreted as evidence of causal relationships.