Fundamentally, the Theory of Planned Behavior links behavioral intentions to three intrinsic determinants: attitude, subjective norm, and perceived behavioral control. Attitude reflects the individual’s evaluation of the expected outcomes, subjective norm represents perceived social influences, and perceived behavioral control signifies the sense of agency over performing a given behavior. This classical model has seen widespread use in predicting farmer behavior, yet for conservation agriculture practices that carry unique socioeconomic and technical profiles, it benefits from augmentation with further explanatory variables.

The study explores several external factors—perceived benefit, environmental benefit, prior knowledge, coping appraisal, risk perception, and perceived ease of adoption—and their relationship with farmers’ intentions to engage in DSR and ZT-maize farming. These variables enrich the model, considering that adopting CA involves not only internal motivation but also external conditions and knowledge levels. The nuanced findings offer a layered understanding of how these factors collectively mediate intentions, shedding crucial insights into sustainable agricultural transitions.

Attitude emerges as a powerful predictor of intention for both DSR and ZT-maize, reinforcing that farmers who view these practices as advantageous and valuable are more mentally prepared to embrace them. Interestingly, this positive relationship holds stronger for ZT-maize than for DSR, a variance attributed to the relative complexity in managing DSR, particularly due to weed control challenges absent in ZT-maize. Farmers perceive ZT-maize as more straightforward, reinforcing a higher confidence level in adopting this technology.

The social dimension, encapsulated by subjective norm, also plays a vital role. Farmers are heavily influenced by social pressures and the expectations of significant referents, a phenomenon especially pronounced in collectivist farming communities. The pressure to conform to normative behaviors can serve as a potent motivator. For ZT-maize, the social reinforcement is stronger, linked to perceptions of ease and tangible benefits such as improved soil health and reduced loss risks. Conversely, the challenges in managing DSR create a more cautious social attitude, tempering this influence somewhat.

Perceived behavioral control notably correlates with farmers’ intentions, emphasizing the importance of self-efficacy in adopting new agricultural techniques. When farmers feel confident and capable of managing the agronomic intricacies of DSR and ZT-maize, particularly with guidance from extension agents and targeted training, their willingness to adopt rises significantly. However, where support and knowledge are lacking, perceived behavioral control weakens, potentially stalling adoption due to feelings of incompetence or uncertainty.

An intriguing interplay exists between subjective norm and perceived behavioral control, wherein positive social endorsement boosts farmers’ confidence to manage CA practices effectively. This synergy indicates that communal encouragement not only influences social approval but also enhances individual agency, creating a reinforcing feedback loop conducive to adoption.

Beyond core TPB constructs, perceived benefit and environmental benefit significantly shape attitudes and intentions. When farmers recognize that CA reduces cultivation costs, boosts yields, and enhances income, their attitudes toward adoption become favorable. Simultaneously, an ecological awareness—appreciating the reduction in greenhouse gas emissions, improved soil health, and lowered water use associated with these practices—further catalyzes positive attitudes. These dual benefits create a compelling rationale for adoption.

Prior knowledge stands as a key antecedent to perceived behavioral control rather than directly influencing intention. Experience and familiarity with CA principles empower farmers to better judge the ease or difficulty of adoption, fostering confidence. Nevertheless, prior knowledge alone does not suffice to drive intention without translating into perceived control, underscoring the necessity of practical support and training. Barriers such as psychological resistance to change and economic concerns highlight why cognitive awareness must be paired with tangibly accessible resources and social networks to promote behavior change.

The role of coping appraisal, particularly response efficacy, reinforces this dynamic. Farmers who believe that CA adoption can effectively reduce costs and enhance productivity develop positive attitudes, even amidst acknowledged risks. This optimism drives stronger intentions, reflecting a calculated weighing of benefits versus potential losses. Positive attitudes partially mediate this relationship, underscoring their pivotal role in behavioral determination.

Self-efficacy related to perceived ease of adoption is another critical factor. If farmers view CA practices as straightforward, with adequate access to machinery, training, and timely support, this perception fuels adoption intention. The differing experiences between DSR and ZT-maize shine through here; ZT-maize’s relative ease builds confidence, whereas DSR’s challenges, particularly in weed and pest management, generate apprehensions that need to be addressed to unlock adoption potential.

Risk perception introduces a countervailing force. Farmers’ apprehensions regarding potential yield loss and increased management pressures can dampen attitudes and reduce intentions to adopt CA. These perceptions often stem from uncertainty in managing complex agronomic conditions inherent to DSR and residual management issues in ZT-maize. Notably, risk perception does not seem to shape subjective norms, suggesting that while farmers are individually concerned about risks, these concerns do not translate into communal pressures for or against adoption. Instead, positive social networks and shared experiences overwhelmingly guide normative influences.

The study’s nuanced exploration of perceived ease of adoption reveals differential mediation effects. For ZT-maize, perceived ease influences intentions both directly and indirectly through attitudes and perceived behavioral control. In contrast, the more complex management demands of DSR mute this mediation, reflecting farmer skepticism about yield reliability and operational difficulties. This highlights the need for tailored extension approaches that address specific technical challenges to bridge gaps in perceived ease and foster positive attitudes.

Overall, this research articulates a compelling, integrative framework that captures the interplay of psychological, social, and technical factors underlying farmers’ adoption intentions of conservation agriculture practices. By extending the TPB and incorporating relevant external factors, it provides actionable insights for policymakers, extension services, and development agencies seeking to enhance CA uptake. Central to success are approaches that build farmer confidence through knowledge dissemination, social support, risk mitigation, and practical facilitation, attuned to the distinct characteristics of different CA practices.

The findings emphasize the dual importance of framing CA as both economically and environmentally beneficial, alongside reducing perceived technical barriers and managing risks. Such a holistic strategy fosters positive attitudes, leverages social capital, and strengthens behavioral control, creating fertile ground for widespread adoption. As the global agricultural sector grapples with climate challenges and sustainability imperatives, insights like these pave the way for transformative change rooted in an understanding of farmer psychology and community dynamics.

In conclusion, the study offers a robust model for forecasting and enhancing farmer willingness to embrace innovative, sustainable farming methods. By recognizing the complex motivators and inhibitors that shape behavior, stakeholders can craft nuanced interventions that resonate with farmers’ lived realities and aspirations—thereby accelerating the transition toward resilient, conservation-oriented agriculture on a global scale.

Subject of Research:
Farmers’ willingness to adopt conservation agricultural practices, specifically direct seeded rice (DSR) and zero-till maize (ZT-maize), analyzed through an extended Theory of Planned Behavior model integrating psychological and external factors affecting adoption intention.

Article Title:
Assessing farmers’ willingness to adopt conservation agricultural practices through an extended theory of planned behavior.

Article References:
Dey, S., Abbhishek, K., Saraswathibatla, S. et al. Assessing farmers’ willingness to adopt conservation agricultural practices through an extended theory of planned behavior. Humanit Soc Sci Commun 12, 1899 (2025). https://doi.org/10.1057/s41599-025-06173-0

Image Credits:
AI Generated

DOI:
https://doi.org/10.1057/s41599-025-06173-0

Beekeeping, traditionally practiced in many cultures, offers multifaceted benefits including income generation, biodiversity enhancement, and pollination services critical to agricultural productivity. However, its promotion as a sustainable business venture among economically marginalized groups requires an understanding beyond simple economic incentives. The study reveals that the intersection of environmental consciousness, entrepreneurial mindset, and available startup resources forms a complex behavioral tapestry that ultimately determines the intention and realization of beekeeping practices in these communities.

Central to this investigation is the conceptual framework deploying the Theory of Planned Behavior (TPB), integrated with environmental concern (EC) and environmental literacy (EL), to predict and analyze attitude toward the environment (ATE), subjective norms (SUN), perceived behavioral control (PBC), beekeeping intention (BKI), and finally, beekeeping startup behavior (BSB). The research confirmed that EC and EL profoundly influence ATE among low-income households, establishing positive environmental attitudes as a cornerstone for the pursuit of green entrepreneurship.

Environmental concern, representing the degree of awareness and worry about ecological degradation, is instrumental in shaping attitudes that favor sustainable practices. Complementing this, environmental literacy encompasses knowledge and understanding of environmental issues and solutions, empowering individuals with the intellectual tools to make informed decisions. The synergy between these two factors fosters an attitudinal environment conducive to embracing beekeeping—an activity inherently aligned with conservation and sustainability goals.

Nevertheless, attitudes alone do not dictate behavior. The study underscores the importance of subjective norms—social pressures and expectations that influence individual decision-making—and perceived behavioral control, which encapsulates the confidence individuals possess regarding their capacity to execute a behavior. In this context, startup resources (SR) such as technical know-how, financial capital, and pertinent skills are critical control beliefs that determine self-efficacy about beekeeping adoption.

Pragmatically, the availability of startup resources and expertise is a significant barrier to entry for many low-income families. Without access to adequate training and financial support, positive environmental attitudes may not translate into actionable beekeeping ventures. The researchers advocate for developmental organizations to bridge this gap by offering comprehensive training programs and easing financial constraints, thereby reducing perceived control barriers and facilitating the establishment of beekeeping enterprises.

The study’s methodological rigor is notable, employing structural equation modeling to parse relationships between latent behavioral constructs and adopting artificial neural network analysis to capture complex nonlinear interactions. This dual analytical approach enhances the robustness of findings, revealing not only direct influences but also intricate interdependencies among variables driving beekeeping adoption.

Importantly, the model derived indicates that ATE, SUN, and PBC collectively foster strong beekeeping intentions, which in turn significantly predict actual beekeeping startup behaviors. This sequential relationship confirms the TPB’s applicability in the environmental entrepreneurship context, providing empirical support for theoretical constructs traditionally used in social psychology.

Beyond academic insights, the study’s implications bear weighty practical significance. By framing beekeeping as a green business model, it highlights a pathway for simultaneous socioeconomic upliftment and ecological stewardship. Policymakers and practitioners engaged in poverty alleviation and environmental management are thus encouraged to consider beekeeping promotion strategies as part of inclusive development frameworks.

Yet, the research does not shy away from acknowledging its limitations. The focus on a single income group within a specific geographical context limits the generalizability of its conclusions. The cross-sectional and quantitative methodology, while powerful, is subject to common method biases and temporal constraints, which future longitudinal and mixed-methods studies could address to provide deeper causal inferences.

The authors propose expanding research designs with larger and more diverse samples to validate and extend the applicability of findings across different sociocultural and economic landscapes. Incorporating longitudinal data would also allow for tracking changes over time, revealing evolving behavioral patterns and the long-term sustainability of beekeeping ventures in low-income communities.

From a policy perspective, the study advocates for inclusive strategies that target the most marginalized populations, ensuring that green practices like beekeeping do not remain confined to economically privileged groups but become accessible tools in poverty eradication and environmental protection efforts.

In summary, this study robustly supports the notion that beekeeping represents a viable green entrepreneurial practice capable of addressing dual goals: economic advancement for low-income families and ecological conservation. The foundational role of environmental attitudes intertwined with practical resource availability forms a blueprint for effective interventions and policies oriented towards sustainable community development.

Ultimately, the successful integration of environmental concern, literacy, positive social norms, and perceived control into behavioral intention models provides a valuable roadmap for fostering green business adoption. By strategically enhancing knowledge, skills, and resource accessibility, stakeholders can significantly improve the adoption rates of environmentally friendly enterprises such as beekeeping, transforming them into powerful agents of change in the global agenda for sustainable development.

The intersection of ecological stewardship and economic empowerment through beekeeping elucidated in this research underscores a transformative approach that resonates beyond Peninsular Malaysia. Its principles may inspire analogous applications in diversified contexts worldwide, particularly where environmental challenges disproportionately affect impoverished populations.

This endeavor sets the stage for a broader cultural shift where sustainability becomes entwined with livelihoods, inspiring communities to champion green innovation organically. As the world confronts escalating climate threats, such hybrid solutions bridging ecology and economy are paramount, positioning beekeeping as a microcosm of hope and progress for generations to come.

Subject of Research: Evaluation of beekeeping practices through structural equation modeling and artificial neural network analysis among low-income households in Peninsular Malaysia.

Article Title: Evaluating beekeeping practices through structural equation modeling and artificial neural network analysis.

Article References:
Al Mamun, A., Hayat, N., Yang, Q. et al. Evaluating beekeeping practices through structural equation modeling and artificial neural network analysis. Humanit Soc Sci Commun 12, 1875 (2025). https://doi.org/10.1057/s41599-025-06144-5

Image Credits: AI Generated

DOI: https://doi.org/10.1057/s41599-025-06144-5