The outer loading assessment confirms that all indicators adequately represent their respective latent constructs, with values exceeding the 0.60 threshold and most surpassing the ideal 0.70 benchmark (Hair et al., 2022). These results indicate strong convergent validity and empirical robustness, validating that the measurement model is well-specified and suitable for subsequent discriminant validity testing and structural model evaluation.

Figure 2. Result of the structure models - Outer Loading

Table 2. AVE, Cronbach's alpha, and Composite Reliability Analysis

The convergent validity assessment shows that all constructs: Perceived Benefit, Perceived Ease of Use, Subjective Norms, Government Support, and Green Product Purchase Intention, achieved Average Variance Extracted (AVE) values above the 0.50 threshold, all meeting the minimum requirement (Hair et al., 2022). Eliability was established through Cronbach’s Alpha (0.794–0.869) and Composite Reliability (0.856–0.902), both exceeding the 0.70 benchmark, indicating strong internal consistency. These results confirm that the measurement model is both valid and reliable, providing a solid basis for subsequent structural model analysis (Hair et al., 2022).

The HTMT assessment results indicate that all inter-construct correlation ratios are below the conservative threshold of 0.85, ranging from 0.674 to 0.834, thereby confirming discriminant validity in line with the recommendations of Henseler et al. (2015) and Hair et al. (2022). These values suggest that each latent variable is empirically distinct, ensuring that the constructs measure unique conceptual domains without redundancy. This reinforces the robustness of the measurement model and supports the theoretical distinctiveness of perceived benefit, perceived ease of use, subjective norms, government support, and green product purchase intention. As complementary evidence, the Fornell–Larcker criterion also confirms that the square root of each construct’s AVE exceeds its correlations with other constructs, further validating discriminant validity.

Table 4. Inner Model Analysis

The inner model results show substantial explanatory power, with R² for Green Product Purchase Intention (GPPI) at 0.652, indicating that 65.2% of variance is explained by the predictors. Predictive relevance (Q²) was 0.626, confirming the model’s predictive capability.

The structural model results show that perceived benefit, perceived ease of use, and subjective norms each significantly enhance green product purchase intention. Government support strengthens the perceived benefit–intention link, negatively moderates the perceived ease of use–intention relationship, and insignificantly affects the subjective norms–intention path These findings illustrate the nuanced role of institutional support, where positive policy interventions can amplify value perceptions but may inadvertently reduce perceived autonomy in technology application.

The findings reveal that perceived benefit exerts a positive and significant influence on green product purchase intention, supporting the Technology Acceptance Model’s (TAM) premise that perceived usefulness is a primary driver of technology adoption (Davis & Granic, 2024; Venkatesh & Bala, 2008). Farmers in this study, predominantly aged 35–50 with over a decade of experience, were more likely to adopt pheromone mating disruption (PMD) when its tangible advantages, such as reduced pest infestation, environmental safety, and long-term cost efficiency, were evident. These results align with Dai & Cheng (2022), who identified perceived benefit as the strongest predictor of eco-friendly agricultural technology adoption in China, and with Zhuang et al. (2021), whose meta-analysis found it to have the highest effect among green purchase intention determinants. Similar conclusions were reported by Maziriri et al. (2024) and Jijue et al. (2024), both emphasizing that measurable, productivity-linked benefits accelerate adoption.

From a practical standpoint, these insights underscore the importance of benefit-centered communication strategies. Highlighting field trial results, farmer testimonials, and measurable cost savings can strengthen the perceived value proposition, particularly in risk-averse farming communities. This is consistent with Akbar & Nurmahdi, (2019) and Winata & Permana, (2020), who noted that direct experience of tangible benefits significantly enhances acceptance of green innovations. By combining rational appeals (demonstrable economic and ecological gains) with social proof (endorsements from peers and community leaders), PMD providers can reinforce perceived benefit as both the initial driver of purchase intention and the foundation for long-term loyalty toward sustainable agricultural technologies.

The results confirm that perceived ease of use has a positive and significant influence on green product purchase intention, indicating that the simpler an eco- friendly product is to operate, the greater the likelihood of its adoption. For pheromone mating disruption (PMD), ease of installation, minimal technical requirements, and clear instructions emerged as key adoption enablers. This finding aligns with the Technology Acceptance Model (Davis & Granic, 2024), which posits that perceived ease of use enhances perceived benefit and subsequently drives behavioral intention. Empirical support comes from Dai & Cheng (2022) and Zhuang et al. (2021), who found that ease of use is a significant predictor of adoption in both agricultural and global green product contexts, as well as from Akbar & Nurmahdi (2019) and Utama et al. (2024), who highlight that simplified application processes lead to higher acceptance rates in rural farming systems. Demographically, most respondents were experienced farmers aged 30–50, preferring solutions that integrate seamlessly into existing routines, a trend also noted by Rezaei et al. (2020) in sustainable pest management adoption. These insights suggest that simplifying product design and providing practical, hands-on training can accelerate the adoption of sustainable agricultural technologies like PMD.

The results indicate that subjective norms have a positive and significant effect on green product purchase intention, reinforcing the Theory of Planned Behavior’s assertion that social expectations are a key determinant of behavioral intention (Ajzen, 2020). In the context of sustainable agriculture, social influence from family members, fellow farmers, extension agents, and community leaders plays a decisive role in legitimizing the adoption of eco-friendly technologies such as pheromone mating disruption. This finding is consistent with Widiantari & Rachmawati, (2023), who reported a significant positive relationship between subjective norms and green purchase intention in Indonesia, and with Mai (2019), who found similar effects in Vietnam and Taiwan. It also aligns with Masengu et al. (2025), showing that sustainable farming practices are strongly influenced by local community norms, and with Savari & Gharechaee (2020), who demonstrated that social norms significantly shape farmers’ decisions to adopt safer agricultural inputs. The demographic analysis further reveals that younger farmers and those with higher education levels tend to be more responsive to social influence, likely due to their greater engagement in social networks and digital platforms where sustainability information circulates. Collectively, these results underscore that strengthening peer endorsement and community-driven campaigns could be an effective strategy to accelerate green technology adoption in agriculture.

The analysis demonstrates a multifaceted role of government support in moderating the relationships between key antecedents and green product purchase intention. First, government support significantly strengthens the effect of perceived benefit on purchase intention, acting as a leverage that amplifies farmers’ valuation of pheromone mating disruption (PMD). Institutional backing in the form of subsidies, training, and protective regulations reinforces farmers’ belief in the economic, ecological, and social benefits of PMD, consistent with findings by Dai & Cheng, (2022); Iqbal et al. (2024); Tan & Huang (2023); Yang et al. (2023), who emphasized the role of policy interventions in converting perceived value into adoption behavior.

From a socio-economic perspective, government support acts as a catalyst that transforms perceived value into concrete behavioral action. When farmers recognize tangible benefits, such as reduced pest damage, lower pesticide costs, and improved ecological outcomes, these perceptions are reinforced by accessible pricing policies, protective regulations, and hands-on technical assistance. The effect is particularly pronounced among experienced farmers who have previously engaged in sustainable agriculture programs, reinforcing trust in both the technology and the supporting institutions. In this way, government involvement is not merely supplementary but serves as a critical leverage point that magnifies the perceived advantages of green technologies, embedding them into farmers’ purchasing decisions and fostering long-term adoption.

In contrast, the moderating effect on perceived ease of use is significant but negative, suggesting that high levels of institutional facilitation can diminish the influence of usability on purchase intention. Under low government support, ease of use remains a strong adoption driver; however, when extensive external assistance is provided, its role becomes less critical. This counterintuitive pattern aligns with Liu & Tsaur (2020); Tan & Huang, (2023). who noted that excessive facilitation may substitute internal cognitive motivation, shifting reliance from product simplicity to structured external support.

From a theoretical standpoint, these results challenge the traditional Technology Acceptance Model (Davis & Granic, 2024), which posits that perceived ease of use should consistently foster adoption intention. In this case, high government involvement may shift farmers’ decision-making from internal evaluation of usability toward reliance on external structures. Dai & Cheng (2022) note that policy incentives can accelerate adoption, but our findings suggest that overreliance on external support may dilute the impact of usability perceptions. This dynamic calls for a balanced approach where government assistance facilitates adoption while simultaneously nurturing farmers’ confidence and autonomy in operating green technologies. For producers and distributors, enhancing the clarity, accessibility, and operational simplicity of pheromone mating disruption products remains critical to ensuring that ease of use retains its motivational power even in contexts of strong institutional support.

Finally, government support does not significantly moderate the relationship between subjective norms and purchase intention, indicating that social influence operates independently of institutional interventions. In cohesive farming communities, subjective norms are shaped more by peer-to-peer interactions, local leaders, and trusted networks than by formal programs. Farmers tend to be influenced more by family, local leaders, and fellow farmers than by formal government programs, a pattern consistent with the Theory of Planned Behavior (Ajzen, 2020), where subjective norms operate as independent determinants of behavioral intention. This aligns with Masengu et al. (2025) and Witek & Kuźniar (2023), who found that informal peer influence outweighs policy campaigns in shaping sustainable purchase behavior, particularly in tightly knit agricultural communities.

The parallel slopes observed in the simple slope analysis for both high and low government support conditions further confirm the absence of moderation, implying that strong social expectations can drive adoption intentions regardless of policy incentives. Similar insights are reported by García et al. (2020) and Maziriri et al. (2024), highlighting that community-based endorsements and shared success stories create higher legitimacy and adoption likelihood compared to bureaucratic directives. In this study, subjective norms measured through peer, family, community leader influence, and farmer group recommendations proved more decisive than government-provided training, subsidies, or regulations. This suggests that strategies to promote green agricultural technologies, such as pheromone mating disruption, should prioritize strengthening horizontal social networks and leveraging respected local influencers, ensuring that adoption motivation stems from authentic community endorsement rather than institutional pressure.

Collectively, these findings suggest that while government support can be a powerful enabler in some contexts, its design and delivery must be carefully balanced. Over-facilitation may undermine intrinsic adoption drivers such as perceived ease of use, whereas peer-driven influence remains largely unaffected by institutional intervention. For policy and industry stakeholders, this underscores the need to complement formal support mechanisms with community-based diffusion strategies to maximize adoption impact.