Evaluating blockchain technology for contract farming in Tanzania: A task-technology fit analysis

Abstract

This study employs Task-Technology Fit (TTF) theory to evaluate the alignment between blockchain technology capabilities and contract farming tasks in Tanzania’s Singida District, examining technological suitability and implementation requirements for improving agricultural operations. The study utilizes a mixed-methods approach, combining quantitative and qualitative data from 100 stakeholders (60 farmers, 20 agricultural officers, 15 agribusiness representatives, and 5 government officials). Data collection involved structured surveys, in-depth interviews, and focus group discussions, analyzed through the TTF framework to assess technology-task alignment and implementation factors. Results reveal strong technology-task fit in contract creation (9/10), payment processing (9/10) and record-keeping (9/10), with blockchain’s smart contracts and immutable ledger capabilities effectively addressing current operational inefficiencies. However, significant implementation challenges exist, including infrastructure gaps (45%) and varying readiness levels between urban (7.8/10) and rural (5.2/10) areas. Stakeholder acceptance ranges from 92% (farmers) to 78% (government officials), indicating the need for targeted implementation strategies. This research presents the first comprehensive TTF analysis of blockchain technology in Tanzania’s agricultural context, integrating technical alignment assessment with implementation readiness evaluation. The findings provide evidence-based guidance for policymakers and stakeholders considering blockchain adoption in developing agricultural economies.