Thailand's agricultural sector is the lowest-paying sector. Research on digital process innovation is needed in Thailand, where specific contexts are critical in filling the literature gap. This study investigates how digital process innovations can enhance farmers’ welfare. The research method is a multiple-case study with three cases. A multiple-case study can answer how and why questions and provide analytic generalizations. Case 1 was a GIS decision support system. Cases 2 and 3 were IoT-based farming systems. The Thai government supported all the cases. These cases utilized IT to facilitate digital process innovations as farm management concepts, such as agricultural safety, crop suitability, demand-driven agriculture, farmer networks, multi-cropping, smart farming, and precision agriculture. These cases were investigated independently and then integrated into a synthesized data model. The study collected data from 32 participants, including developers who invented the cases, mid-tier employees and local government officers who facilitated the use of the cases, user farmers who used the cases, and non-user farmers who grew the same crop but did not use the cases and served as the control group for each case. The data model demonstrates how advancements in digital process innovations impact farmers’ welfare. Additionally, this study makes theoretical and practical recommendations.
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