Why Vietnamese Coconut Farmers Go Organic: Neighbors and Confidence Beat Policy

In the coconut groves of Vietnam’s Mekong Delta, a quiet struggle is underway between two ways of farming. On one side stands a generation of conventional production built on chemical fertilizers and pesticides; on the other, a fledgling organic movement that promises healthier soils, safer food, and access to premium export markets. A new study of 205 coconut-farming households in Vinh Long province, published in Environmental and Sustainability Indicators, offers one of the most detailed statistical portraits yet of what actually pushes farmers across that divide, and its central finding is striking: the strongest driver of organic adoption is not government policy or even personal conviction about environmental benefits, but the expectations of family, neighbors, cooperatives, and local authorities.

The research team, led by Van Dinh Ha and An Thinh Nguyen, combined a classic psychological framework from behavioral science with modern machine-learning tools. At the heart of the study lies the Theory of Planned Behavior, a model first formalized by Icek Ajzen in 1991, which holds that behavior is proximately driven by intention, and that intention in turn is shaped by three forces: attitude, the farmer’s own evaluation of whether organic farming is worthwhile; subjective norms, the perceived expectations of important others; and perceived behavioral control, the farmer’s sense of having the knowledge, money, and skills to pull it off. Rather than simply bolting extra variables onto this framework, the researchers gave each addition a distinct theoretical role. Descriptive norms, which capture what farmers observe their peers actually doing, were separated from subjective norms, which capture what important others expect. Policy satisfaction was positioned as a measure of the institutional environment, while farm size was treated as an objective resource condition tied to current practice rather than to intention.

The setting matters as much as the theory. The Mekong Delta is Vietnam’s agricultural heartland, but it is also one of the country’s most climate-vulnerable regions, exposed to salinity intrusion and sea-level rise. In 2017, the Vietnamese government issued Resolution 120/NQ-CP, a landmark strategy urging the delta to work with nature rather than against it, shifting away from intensive rice monoculture toward diversified, climate-resilient systems. Coconut cultivation fits this vision unusually well: palms tolerate saline conditions, need relatively few chemical inputs, and slot easily into intercropping and ecological farming systems. National policy has followed through, with Decision No. 431/QD-BNN-TT designating coconut a priority crop for organic-oriented development through 2030. Yet adoption remains stubbornly limited, which is precisely the gap the study set out to explain.

Fieldwork was conducted in November 2025 through face-to-face interviews across 18 communes of the newly enlarged Vinh Long province, formed by the merger of Ben Tre, Tra Vinh, and the former Vinh Long. The sample was stratified into conventional farmers and farmers already transitioning to or practicing organic methods, though certified-organic growers proved so rare, just three households in the entire sample, that they could not be analyzed separately. The demographics tell their own story: 80.5 percent of respondents were male, most were between 31 and 50 years old, and the majority had primary to high school education. Only 32.7 percent were in a registered organic-conversion process, and a remarkable 81.5 percent said they were unaware of organic coconut farming as a model at all. Awareness, clearly, is not the same as adoption, and the study treats the two very differently.

Methodologically, the team ran a two-stage analysis. Partial least squares structural equation modeling, or PLS-SEM, served as the primary engine for testing the theoretically specified relationships, with 5,000 bootstrap resamples to assess statistical significance. An artificial neural network was then applied purely as an exploratory sensitivity check, ranking the relative importance of the significant variables. The researchers were careful about what the cross-sectional design could and could not show: because intention and current behavior were measured in the same survey wave, the resulting coefficients are associations, not evidence of causal or temporal order. This caution proved prescient, as the heterotrait-monotrait ratio between intention and behavior reached 0.875, slightly above the conventional 0.85 threshold, signaling substantial empirical proximity between the two constructs that the authors explicitly flag as a limitation.

The structural results were emphatic. Every hypothesized relationship held. Intention showed by far the strongest association with current organic adoption practices, with a path coefficient of 0.670, and an effect size of 0.789 that qualifies as large by conventional statistical benchmarks. Among the drivers of intention, subjective norms led with a coefficient of 0.396, followed by attitude at 0.354 and perceived behavioral control at 0.337. Descriptive norms and policy satisfaction also reached significance, at 0.136 and 0.167 respectively, but with much smaller effect sizes. Farm size, notably, influenced current practices directly rather than working through intention, with a coefficient of 0.133, consistent with the idea that larger landholdings give farmers the buffer to absorb certification costs, record-keeping burdens, and the temporary production dips of the conversion period. The model explained 52.8 percent of the variance in intention and 59.5 percent in behavior, solid figures for social science field research.

The neural network told a partly convergent story. For the intention model, subjective norms again ranked first, with a normalized importance of 100 percent, followed by perceived behavioral control at 79.4 percent and attitude at 74.5 percent; descriptive norms and policy satisfaction trailed at roughly half that weight. For the behavior model, the two methods agreed perfectly: intention dominated at 100 percent, farm size came second at 23.1 percent, and perceived behavioral control third at 17.8 percent. The authors interpret this convergence, especially in the behavior model, as evidence that the intention-behavior linkage is robust, while the formation of intention appears to involve more complex, possibly nonlinear interactions among social, psychological, and institutional factors. Two conceptual mechanisms, switching costs and risk aversion, were invoked as theoretical boundary conditions rather than measured variables, framing why favorable intentions can stall when transition burdens loom large.

One of the study’s most useful contributions is its multigroup analysis comparing conventional and transitioning farmers. Within-group patterns hinted at differences: descriptive norms were significant only among conventional farmers, while policy satisfaction was significant only among those already converting. But the formal between-group comparisons found no statistically significant differences on any path, and the authors are refreshingly disciplined about what that means. The extended framework, they conclude, is broadly stable across adoption status; the within-group quirks are descriptive observations, not evidence that different psychological machinery operates in different farmer types. This matters for policy, because it suggests a single well-designed intervention strategy can serve both constituencies rather than requiring fragmented, group-specific programs.

The practical implications reach well beyond Vietnamese coconut groves. First, because intention is the dominant pathway to behavior, extension programs should do more than distribute technical manuals; they should build conviction and confidence by demonstrating long-term economic, soil-health, and market benefits. Second, since subjective norms outweigh everything else, cooperatives, farmer groups, and trusted local institutions are the natural delivery channels, a finding consistent with Vietnam’s Decree 98/2018 on agricultural cooperation and linkage. Third, perceived behavioral control can be raised directly through targeted support for certification costs, credit access, composting, biological pest control, and record keeping, easing the switching costs that keep willing farmers on the sidelines. The study also notes a governance subtlety: because Vinh Long was only recently merged from three provinces, farmers’ policy perceptions may still reflect legacy institutional arrangements, and authorities should harmonize training, credit, and market-linkage services across former administrative boundaries.

The limitations are honestly catalogued. The non-probability sample of 205 households in a single province limits generalizability; the cross-sectional design cannot establish that intention precedes behavior; household income, land tenure, and certification costs were not modeled; and the neural-network validation relied on internal cross-validation rather than an independent test set. The authors call for longitudinal designs with at least two measurement waves, larger probability-based multi-province samples, and explicit measurement of switching costs and risk preferences. Even so, the study’s core message travels far. In the global push toward organic agriculture, which by 2022 spanned 188 countries and 4.5 million farmers, the transition is often framed as an economic calculation. This research suggests something more fundamentally social is at work: farmers change not merely when the numbers add up, but when the people who matter to them expect it, when they can watch their successful neighbors do it first, and when they feel capable of surviving the switch. Any policy that ignores that social fabric is likely to wither in the field.

Subject of Research: Drivers of smallholder farmers' adoption of organic coconut farming in the Mekong Delta of Vietnam

Article Title: Drivers of farmers' adoption of organic coconut farming in the Mekong Delta of Vietnam: PLS-SEM with an ANN-based sensitivity analysis

Article References: Ha, V. D., Nguyen, A. T., Nguyen, Q. D., Nguyen, B. H., Ngo, N. D., Do, T. M. L., Nguyen, K. L., Nguyen, H. T. L., Nguyen, K. H., Nguyen, T. T. H., Nguyen, T. L. C., & Bui, T. M. A. (2026). Drivers of farmers' adoption of organic coconut farming in the Mekong Delta of Vietnam: PLS-SEM with an ANN-based sensitivity analysis. Environmental and Sustainability Indicators, 32, Article 101568. https://doi.org/10.1016/j.indic.2026.101568

Image Credits: AI Generated

DOI: 10.1016/j.indic.2026.101568

Keywords: organic farming, Mekong Delta, Vietnam, coconut, Theory of Planned Behavior, PLS-SEM, artificial neural network, farmer adoption, subjective norms, sustainable agriculture, smallholders, policy satisfaction