1. Introduction

Agriculture remains a cornerstone of Iran’s economy, yet rural communities dependent on farming face persistently low incomes and living standards. The sector is increasingly strained by falling commodity prices, rising production costs, environmental degradation, climate volatility, weak governmental support, and erratic market fluctuations. These pressures have eroded smallholders’ profitability, forcing many to abandon their farms and migrate to urban centres in search of alternative livelihoods.

To counteract this trend, policymakers and international bodies, including the United Nations, have promoted agritourism a strategy that combines agricultural production with recreational and educational services for visitors. Agritourism does not replace farming; rather, it diversifies income streams, enhances resilience against external shocks (natural disasters, price swings, input cost volatility), and helps preserve rural cultural heritage. Leading agricultural nations such as China, the United States, Japan, India, and Germany have long integrated tourism with farming and are now advancing towards “smart” agritourism, leveraging digital technologies to optimise operations and visitor experiences.

In contrast, Iran and specifically Kermanshah province, a major agricultural region has been slow to adopt agritourism and related smart technologies. This study therefore investigates the determinants of farmers’ behavioural intention to use smart agritourism technologies, combining the Theory of Planned Behaviour (TPB) and the Technology Acceptance Model (TAM) to capture both socio‑psychological and technological factors.



2. Methodology

This descriptive‑correlational study targeted all farmers in Kermanshah province (N = 164,000), based on records from the Provincial Agricultural Jihad Organisation. Using multi‑stage random sampling stratified by climatic zones, 384 respondents were selected following Krejcie and Morgan’s (1970) table.

A researcher‑developed questionnaire comprised two sections: (i) 16 items on personal characteristics, and (ii) 30 items measuring six model constructs perceived ease of use (5 items), perceived usefulness (5), attitude (5), subjective norm (5), perceived behavioural control (3), and intention to adopt (7). Face and content validity were confirmed by an expert panel from agriculture and tourism. Reliability was assessed via Cronbach’s alpha (acceptable for all sections), composite reliability (CR > 0.7), and rho_A (> 0.7), while convergent validity was supported by average variance extracted (AVE > 0.5 for all constructs, and less than CR). Discriminant validity was confirmed using the HTMT criterion (0.79 < 0.85). Data were analysed using SmartPLS3.



3. Findings

Farmers reported moderate perceived usefulness (mean = 3.18/5), indicating they recognise the benefits of smart technologies, and a generally positive attitude (mean = 3.27/5). However, perceived ease of use scored low (mean = 18.2 on a transformed scale), suggesting that farmers find these technologies difficult to operate. Intention to adopt was at an average level. Subjective norm showed a relatively high mean (3.65/5), reflecting strong social pressure from peers, family, and local leaders to accept technology, whereas perceived behavioural control had a lower average.

Structural equation modelling revealed that subjective norm and attitude directly and positively influenced intention to adopt, while perceived ease of use and perceived usefulness exerted indirect effects through attitude and subjective norm. Perceived behavioural control did not significantly affect intention. The model explained 88% of the variance in farmers’ behavioural intentions.



4. Discussion and Conclusion

The results underscore that the socio‑psychological mechanism governing smart agritourism adoption in Kermanshah follows a “willingness‑before‑capability” logic. Farmers’ intentions are primarily shaped by internal beliefs (positive attitudes towards income diversification) and external social pressures (local norms), rather than by their assessment of objective feasibility (behavioural control). Despite infrastructural deficits water scarcity, economic marginalisation, and limited digital access farmers exhibit a strong mental and psychological readiness to engage with the digital ecosystem. Crucially, perceived usefulness and ease of use act as foundational prerequisites for building positive attitudes and norms. Yet the low ease‑of‑use score signals a critical mismatch: the gap is not one of reluctance, but of practical capacity. Thus, current extension strategies that focus solely on awareness‑raising and persuasion are insufficient. Policymakers and planners must shift from a “farmer encouragement” paradigm to an “environmental facilitation” approach. Concrete investments are needed in digital infrastructure, affordable financial services, technical support, and user‑friendly platforms that translate existing desire into tangible action. For Kermanshah a province dominated by smallholder agriculture and vulnerable to climatic and economic shocks agritourism is perceived not as a luxury, but as a pragmatic resilience tool and a means to safeguard rural identity. This social capital and intrinsic motivation constitute a robust foundation for future interventions. Planning should therefore harness this positive disposition, removing practical barriers so that the proven willingness can materialise into sustained adoption.