Vietnam's dragon fruit sector supports export earnings and rural livelihoods but remains exposed to climate stress, resource-intensive production, market volatility, and demanding market requirements. This study provides a systems-informed documentary synthesis of sustainability transition pathways in Bình Thuận, Long An, and Tiền Giang. Drawing on 24 government, scholarly, programme, technical, and sector documents, it examines how technological innovation, livelihood capacity, value-chain governance, and institutional coordination interact to shape smallholder resilience. The synthesis identifies two provisional mechanisms. Resource-efficient technologies may reduce selected inputs and operating costs, potentially strengthening reinvestment capacity. Conversely, climatic and market shocks may reduce income, constrain adaptation investment, and increase subsequent vulnerability. Value-chain governance mediates these pathways by distributing information, compliance costs, risks, and market benefits among farmers, cooperatives, intermediaries, exporters, and buyers. Four connected leverage areas emerge: context-appropriate technology, accessible finance and extension, effective cooperative coordination, and equitable governance of standards and traceability. Programme-reported efficiency gains remain pilot-specific and do not establish sector-wide effectiveness. The study integrates sustainable-livelihood, climate-smart agriculture, Global Value Chain, and systems perspectives. It conceptualises environmental performance, livelihood resilience, and market inclusion as related but distinct outcomes whose alignment depends on complementary technical, financial, organisational, and governance mechanisms. By connecting local sustainability dynamics with cross-border market integration, the study contributes to globalization debates concerning how value-chain governance and institutional conditions may shape the distribution of sustainability costs, risks, and benefits among smallholder producers. The proposed framework offers testable propositions for future empirical validation rather than a definitive model of sector performance.
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Le et al. (2026) studied this question.
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