Understanding psychosocial determinants of sustainable farming behaviour among local rice farmers in Indonesia

Understanding psychosocial determinants of sustainable farming behaviour among local rice farmers in Indonesia | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Understanding psychosocial determinants of sustainable farming behaviour among local rice farmers in Indonesia Nugroho Hasan, Mohamad Harisudin, Kusnandar Kusnandar, Putriesti Mandasari, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9024162/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 15 You are reading this latest preprint version Abstract Moving from risk perception to concrete farm action remains a central challenge in sustainable agriculture. Farmers may be aware of environmental and health risks, but such awareness does not automatically translate into sustainable practices without supportive beliefs and enabling conditions. To explain this gap, this study applies an extended Health Belief Model (HBM) to analyse sustainable rice farming practices in Indonesia, focusing on Rojolele Srinuk cultivation in Klaten Regency, Central Java. The framework includes perceived susceptibility, severity, benefits, barriers, self-efficacy, and cues to action. It is extended with multidimensional risk perception health, environmental, and socio-ethical risks. Sustainability knowledge is added as a moderating variable to capture cognitive differences among farmers. Data from 420 farmers were collected through stratified random sampling and analysed using Partial Least Squares–Structural Equation Modeling (PLS-SEM). The results show that perceived susceptibility, perceived benefits, self-efficacy, and cues to action significantly encourage sustainable behaviour. Perceived barriers reduce it. Perceived severity has no significant effect, suggesting that long-term risks may be normalized in routine practice. Multidimensional risk perception strengthens self-efficacy and cues to action. Sustainability knowledge shows a limited but meaningful moderating role. These findings provide behavioural insight for designing context-sensitive sustainability policies in developing-country agriculture. Sustainable rice farming Health Belief Model Psychosocial determinants Risk perception Sustainability knowledge Farmer behaviour Figures Figure 1 Figure 2 Figure 3 1. Introduction Indonesia’s rice sector remains central to national food security and continues to show strong production dynamics. Official statistics indicate that 2024 provides the current baseline for harvested area and output, while projections for 2025 suggest further expansion. Milled dry grain (GKG) production is expected to reach approximately 60.34 million tonnes, representing a 13.6% increase compared to 2024. This growth is largely driven by expanded harvested areas and favourable climatic conditions (Indonesia Statistic Agency, 2025 ).At the same time, national agricultural policies increasingly emphasise downstream processing, land expansion, and investment to strengthen food security. These strategies, however, also intensify pressure to balance productivity gains with environmentally sustainable farming practices (Atmajaya et al., 2025 ; Hasan et al., 2025b ; Indonesia Ministry of Agriculture, 2024 ). At the regional level, Central Java remains one of Indonesia’s main rice-producing provinces, although recent performance shows notable fluctuations. In 2024, harvested area declined to about 1.55 million hectares, with production estimated at 8.89 million tonnes of unhusked rice, down from the previous year (Central Java Statistic Agency, 2025 ). A similar pattern occurred in Klaten Regency, where both harvested area and production fell despite ongoing government programs promoting expanded planting, mechanisation, and pest control (Klaten Regency Statistic Agency, 2024 ). Within this setting, Rojolele Srinuk, an aromatic local variety with economic, cultural, and social significance, is strategically important for sustaining local agricultural systems agriculture (Hasan et al., 2025a ; Kristamtini et al., 2021). Nevertheless, sustaining Rojolele Srinuk cultivation is constrained by persistent structural challenges. These include land fragmentation, the dominance of smallholder farming, intensive use of chemical inputs, and limited farmer regeneration (Antriyandarti et al., 2023 ; Pratama et al., 2024 ). Such constraints indicate that technological interventions and policy incentives alone are insufficient. Farmers’ behavioural responses to risk, uncertainty, and evolving production demands play a decisive role in shaping the adoption of sustainability-oriented practices (Fanak et al., 2025 ; May et al., 2019 ; Moridi et al., 2025 ; Uikey et al., 2025 ). Empirical studies increasingly confirm that decision-making in agriculture is influenced by psychosocial considerations, including perceptions of health risks, environmental consequences, and social responsibility toward households and future generations (Ratnayake et al., 2024 ; Salam et al., 2024 ; Sapkota et al., 2025 ; Trezise & Richardson, 2023 ). In this regard, the Health Belief Model (HBM) provides a relevant framework for explaining why farmers adopt or resist sustainability-promoting practices (Nasiri et al., 2024 ). The model is particularly suitable for agricultural contexts, where decisions involve weighing perceived risks, expected benefits, and practical constraints under uncertainty (Karimi & Ataei, 2023 ; Kirscht, 1998 ; Li et al., 2022 ). Although previous studies have applied HBM to agricultural and environmental behaviour, most focus on general adoption outcomes or isolated constructs. Few studies integrate multidimensional risk perception and farmers’ sustainability knowledge into a unified behavioural model (Li et al., 2023 ; Pratama et al., 2024 ; You et al., 2022 ). Accordingly, this study examines how psychosocial factors influence sustainable farming behaviour in Rojolele Srinuk cultivation in Klaten Regency. It applies the HBM, extended to include multidimensional risk perception (covering health, environmental, and socio-ethical risks), and farmers’ sustainability knowledge. The novelty of this research lies in the development of an integrated empirical model that connects risk awareness, cognitive evaluation, and behavioural response within a local rice-farming context. By strengthening behavioural insight in environmental and agricultural research, this study also provides policy-relevant guidance for designing more effective sustainability-oriented extension and intervention strategies. 2. Literature Review 2.1. Demographic characteristic Demographic characteristics are important determinants of farmers’ behaviour and their adoption of sustainable agricultural practices. Variables such as age, education level, household size, farming experience, and landholding size shape decision-making capacity, access to information, labour availability, and resource constraints (Cho & Lee, 2025 ; Creppy et al., 2024 ). Age and farming experience are often associated with technological conservatism, as older farmers or those with long experience tend to maintain conventional practices. In contrast, higher education levels and larger landholdings are generally positively related to innovation adoption, as education enhances information access and analytical ability, while larger farms provide economies of scale and greater capacity to absorb risk (Haile et al., 2025 ; Kyire et al., 2023 ; Salam et al., 2024 ). Household size also influences cultivation decisions by determining the availability of family labour and shaping input-use strategies (Ngwenya & Mukwada, 2024 ; Woodmansee et al., 2025 ).. A larger household may ease labour constraints but may also increase consumption pressure, thereby affecting production choices (Dey et al., 2024 ). In the context of Rojolele Srinuk cultivation, family support, accumulated farming experience, and household structure are likely to influence farmers’ commitment to conservation-oriented and sustainable agricultural practices. 2.2. Multidimensional risk perception Multidimensional risk perception reflects how individuals evaluate potential losses and negative consequences associated with their actions, including social, health, environmental, and ethical dimensions. In agricultural settings, risk perception shapes how farmers respond to innovation, policy change, and sustainability pressures (Datta & Behera, 2022 ; Wolff et al., 2018 ). Farmers do not assess risks purely in technical terms; they also consider social acceptance, community norms, and the broader consequences of their decisions. Previous studies show that perceived risk can either motivate behavioural adjustment or hinder change, depending on how farmers weigh potential benefits against social and economic uncertainties (Ma & Rahut, 2024 ; Zoundji et al., 2024 ). Concerns about community reactions, group expectations, and long-term agronomic impacts often become part of the total risk evaluation when deciding whether to adopt new or sustainable practices (Zheng & Dallimer, 2016 ). In this study, multidimensional risk perception consists of perceived health risk, perceived environmental risk, and perceived socio-ethical risk (Karimi & Ataei, 2023 ). Perceived health risk refers to farmers’ awareness of potential adverse health effects arising from pesticide exposure, wastewater, and other chemical inputs (Aslam et al., 2025 ). Perceived environmental risk concerns the belief that excessive use of fertilizers and pesticides may damage soil quality, water systems, and ecological balance (Kyire et al., 2023 ; Mallick et al., 2022 ; Zhu et al., 2024 ). Perceived socio-ethical risk relates to concerns about social judgement, community norms, and the moral implications of farming practices for future generations (Chen et al., 2025 ; Karimi & Ataei, 2023 ). Together, these dimensions capture the broader risk considerations that may influence farmers’ sustainability-related decisions. 2.3. Health belief model The Health Belief Model (HBM) is one of the most established theoretical frameworks for explaining individual decision-making in preventive and protective behaviour. Originally developed in public health research, the model has evolved conceptually and empirically, making it applicable to environmental behaviour, sustainable agriculture, and occupational safety contexts (Ataei et al., 2021 ; Luger, 2013 ; Nasiri et al., 2024 ; Singh et al., 2026 ). HBM explains behaviour through subjective beliefs about vulnerability to risk, the seriousness of consequences, expected benefits, perceived barriers, and confidence in performing protective actions (Baghestani et al., 2025 ; Wang et al., 2021 ). In this study, sustainable Rojolele Srinuk rice farming is positioned as a long-term protective action aimed at safeguarding farmers’ health, preserving environmental quality, and maintaining the economic and social viability of the farm enterprise. The perceived susceptibility construct in the HBM refers to farmers' perception of their vulnerability to risks arising from unsustainable farming practices (Jamshed et al., 2020 ). In the context of rice farming, this vulnerability can manifest as the risk of health problems due to exposure to pesticides and chemical fertilizers, the risk of land degradation, and the risk of decreased productivity and income in the future (Mkonda & He, 2018 ). Farmers feel more vulnerable to these risks tend to have higher psychological readiness to consider behavioral changes toward more sustainable practices (Habiba et al., 2012 ). This perception of vulnerability becomes the starting point for the formation of risk awareness in the farmers' decision-making process (Karimi & Ataei, 2023 ). Perceived benefits refer to farmers’ beliefs that sustainable practices will generate tangible and relevant advantages (Dhar et al., 2020 ; C. Liu et al., 2022 ; Methamontri et al., 2022 ). These benefits may include improved occupational health, better soil and environmental quality, greater yield stability, and enhanced market value of the Rojolele Srinuk variety. Within the HBM framework, perceived benefits function as a rational justification for behavioural change, particularly when expected gains are seen as outweighing potential costs or risks (Abdollahzadeh & Sharif, 2021 ; Karimi & Ataei, 2023 ). Perceived severity refers to the extent to which farmers believe that the consequences of a given risk are serious and potentially disruptive to their lives (Chen et al., 2010 ; Gichohi-Wainaina et al., 2021 ). In the context of Rojolele Srinuk rice cultivation, this perception extends beyond immediate health effects to include environmental degradation, long-term declines in land productivity, and threats to farming as a sustainable source of family income and intergenerational continuity (Mgendi et al., 2022 ; Zenda et al., 2024 ). When risks are perceived as severe, farmers are more likely to critically reassess their current cultivation practices and consider adjustments toward more sustainable approaches ((Kassian et al., 2017 ; Moridi et al., 2025 ). Conversely, perceived barriers represent the obstacles farmers associate with adopting sustainable practices (Brunt et al., 2025 ; Rehman et al., 2023 ). These may include limited capital, uncertainty about yields, lack of technical knowledge, weak institutional support, and prevailing social norms favouring conventional methods (Antwi-Agyei & Stringer, 2021 ; Cramb, 2020 ; Pilato et al., 2018 ). HBM literature consistently identifies perceived barriers as a dominant inhibiting factor; even when risks and benefits are recognised, behavioural change may not occur if obstacles are considered too substantial (Martin et al., 2024 ; Nyantakyi-Frimpong, 2020 ). Self-efficacy, an important extension of the original HBM, refers to farmers’ confidence in their ability to implement sustainable techniques, manage constraints, and make informed farm decisions (Moridi et al., 2025 ; Nasiri et al., 2024 ). Strong self-efficacy not only directly supports behavioural adoption but also reinforces the influence of risk and benefit perceptions on action (Shen et al., 2025 ; Wang et al., 2021 ). Cues to action function as internal or external triggers that prompt behavioural change (Nasiri et al., 2024 ; Xu et al., 2023 ). In the context of Klaten Regency, cues to action may include agricultural extension services, government programs, certification schemes, market demand for high-quality rice, and farmers’ direct experiences with declining land quality or health problems. These triggers activate the psychological readiness shaped by other HBM constructs and facilitate actual behavioural change. Consistent with the classical HBM framework, this study also incorporates modifying factors, namely demographic characteristics and sustainability knowledge. These factors shape perceptions of risk, benefits, barriers, and self-efficacy, thereby indirectly influencing behaviour. Overall, HBM is positioned as a causal framework that explains how psychosocial factors systematically shape farmers’ decisions regarding sustainable Rojolele Srinuk rice cultivation. The theoretical model of this study is presented in Fig. 1 . 2.4. Farmer sustainability knowledge Farmers’ sustainability knowledge refers to their level of understanding and awareness of the principles, practices, and long-term implications of sustainable farming systems ((Liu et al., 2023 ; Shijin, 2021 ). This knowledge includes technical, environmental, economic, and social dimensions, such as soil fertility management, efficient use of inputs, protection of farmer health, and the continuity of farming across generations (Kabir et al., 2017 ). In the sustainable agriculture literature, knowledge is regarded as a fundamental cognitive resource that shapes environmentally responsible and long-term-oriented decision-making (Müller et al., 2019 ). In the context of rice farming, particularly for local varieties such as Rojolele Srinuk, knowledge of sustainability becomes increasingly important given the intensive use of land, water, and chemical inputs. Farmers with stronger sustainability knowledge are generally better able to recognise the health and environmental risks associated with unsustainable practices and to appreciate the long-term benefits of adopting more environmentally sound approaches (Sahara et al., 2025 ). Knowledge therefore functions not only as a source of risk awareness but also as a reinforcing factor that strengthens farmers’ orientation toward the long-term sustainability of their farming enterprises. Within the HBM framework, sustainability knowledge functions as a modifying factor that shapes how farmers interpret risk, benefits, and barriers related to sustainable practices. Farmers with higher levels of knowledge are more likely to perceive risks as concrete and consequential, while also being better able to recognise potential benefits and identify practical solutions to existing constraints (Beltrán-Tolosa et al., 2020 ). In addition, sustainability knowledge can strengthen self-efficacy by enhancing farmers’ confidence in their ability to implement sustainable techniques under real farming conditions. Empirical studies consistently show that sustainability knowledge is positively associated with pro-environmental farming behaviour, although the relationship is often indirect and mediated by psychosocial constructs (Li et al., 2023 ; Qadir et al., 2024 ). Integrating sustainability knowledge into the HBM framework therefore allows for a more comprehensive explanation of behavioural formation. In this study, sustainability knowledge is positioned as a reinforcing variable that strengthens the influence of psychosocial factors on farmers’ commitment to sustaining Rojolele Srinuk rice cultivation in Klaten Regency. 3. Methodology 3.1. Research design and approach This study adopts a quantitative and explanatory design to analyse farmers’ behaviour in supporting the sustainability of Rojolele Srinuk rice farming. It aims to examine the causal relationships between psychosocial factors and sustainability-oriented behaviour based on a strong theoretical foundation (Bagambilana & Rugumamu, 2023 ; Sohrabizadeh et al., 2024 ). Data were collected through surveys, complemented by interviews and field observations. The survey instrument was developed from the Health Belief Model (HBM) indicators (Table 3 ). The study includes eleven variables three exogenous, seven endogenous, and one moderating variable measured using a five-point Likert scale ranging from strongly disagree (1) to strongly agree (5) (Ayu Purnamawati et al., 2023 ; Das & Mishra, 2023 ). All constructs were assessed for validity and reliability using SEM-PLS procedures. 3.2. Study area, data collection and sample This research was conducted in Klaten Regency, which was purposively selected because it serves as a key production area for the local Rojolele Srinuk rice variety (Fig. 2 ). The specific research sites were determined based on their status as production centres characterised by grey regosol soils—derived from volcanic ash and intermediate sand parent materials and supported by established irrigation systems (Table 1 ). Table 1 List of research area and sample Number List of research area (district) Type of irrigation Population (N) Sample (n) Sampling Fraction (n/N) 1 Delanggu, Polanharjo, and Karanganom Technical Irrigation of Spring Water Sources 1,430 231 16.2% 2 Juwiring and Trucuk Technical irrigation for rivers/dams and deep wells 551 89 16.1% 3 Prambanan Rainfed and semi-technical irrigation 619 100 16.2% Total 2,600 420 Source: Klaten Statistic Agency and Agriculture Agency, 2024 The respondents in this study consisted of 420 farmers selected through proportionate stratified random sampling from an estimated population of approximately 2,600 Rojolele Srinuk farmers in Klaten Regency. Stratification was applied because the farmer population is heterogeneous, particularly in terms of agroecological conditions (spring irrigation, dam or river irrigation, and rainfed systems), production intensity and associated farming risks, and access to water resources, all of which may influence behaviour and risk perceptions. By grouping farmers into relatively homogeneous strata while maintaining heterogeneity between strata, this approach enhances sample representativeness and improves the precision of parameter estimation (Raj & Sofi, 2023 ). Within each stratum, respondents were randomly selected based on the criterion that they had cultivated Rojolele Srinuk rice at least once in the past five years. The chosen sample size also satisfies methodological requirements for PLS-SEM analysis. According to the 10-times rule and statistical power considerations, models with moderate effect sizes generally require at least 150–200 observations (considerations (Hair, J. F. et al., 2021; Kimaro et al., 2017 ). With 420 respondents, this study exceeds the recommended threshold, thereby ensuring adequate statistical power and stable parameter estimation. 3.3. Analysis techniques The Partial Least Squares–Structural Equation Modeling (PLS-SEM) approach was employed to analyse the research model. This method is appropriate for examining complex relationships among multiple latent variables and for testing interaction effects within an integrated framework (Azadi et al., 2025 ; Hair et al., 2024 ). Compared to conventional linear regression, PLS-SEM is better suited for models involving simultaneous causal paths and latent constructs. The analysis was conducted using SmartPLS software, which is widely applied in explanatory research and theory development because it focuses on maximizing the variance of endogenous constructs while estimating structural relationships concurrently (Guenther et al., 2023 ; Harisudin et al., 2023 ). In addition, PLS-SEM does not require strict multivariate normality assumptions, making it robust for survey data measured on Likert scales. With 420 respondents, the sample size exceeds recommended thresholds for stable parameter estimation and adequate statistical power (Hair et al., 2022; Sarstedt et al., 2022 ). 4. Results 4.1. Demographic characteristic Table 2 indicates that the majority of Rojolele Srinuk farmers are male, accounting for 84.3% of the total respondents. The age distribution is dominated by farmers between 50 and 69 years, suggesting limited generational renewal in rice farming within Klaten Regency. This ageing farmer structure highlights the need for targeted interventions to encourage younger participation in local rice cultivation. Despite this demographic pattern, farmers remain committed to cultivating Rojolele Srinuk because of its established market demand and strong customer base. In terms of education, 57.1% of respondents have completed senior high school, indicating a relatively adequate level of formal education that may support the adoption of improved and sustainability-oriented practices. Table 2 Respondent demographics Features of population Total Percentage Distribution of farmers Delanggu 96 22.9% Polanharjo 100 23.8% Karanganom 35 8.3% Juwiring 14 3.3% Trucuk 75 17.9% Prambanan 100 23.8% Gender Male 354 84.3% Female 66 15.7% Age (years) 20–29 1 0.2% 30–39 7 1.7% 40–49 73 17.4% 50–59 162 38.6% 60–69 127 30.2% 70 + 50 11.9% Family numbers (people) 1–3 242 57.6% 4–6 173 41.2% 7–9 5 1.2% Educational Background Bachelor's degree or equivalent 22 5.2% Diploma or equivalent 6 1.4% High school or equivalent 240 57.1% Junior high school or equivalent 73 17.4% Elementary school or equivalent 77 18.3% No formal education 2 0.48% Another job Has another job 261 62.1% Does not have another job 159 37.9% Farming experiences (years) 1–9 46 11% 10–19 134 31.9% 20–29 108 25.7% 30–39 74 17.6% 40–49 39 9.3% 50+ 19 4.5% Land area (meter squares) 10000 19 4.5% Land ownership status Owned 273 65% Rented 67 16% Profit-sharing 80 19% Farmer's income each planting season 50,000,000 16 3.8% A substantial proportion of farmers in Klaten Regency engage in off-farm employment. Approximately 62.1% of respondents report having secondary occupations, including trading, construction work, village administration, and civil service, while only 37.9% depend solely on agriculture as their primary source of income. This pattern reflects the limited economic capacity of small-scale rice farming to fully support household needs. Most farmers cultivate relatively small landholdings, typically between 0.1 and 0.5 hectares, generating gross revenues of around Rp 10–20 million per planting season (approximately four months). However, this amount does not represent net income, as production costs average about Rp 2 million per 0.1 hectare. Although seasonal earnings may exceed the regional minimum wage of Rp 2,389,873 (Klaten Department of Industry and Manpower, 2026), household expenditures and farming costs remain substantial. Income constraints are further intensified for farmers who rent land or operate under sharecropping arrangements, which reduce their final returns. 4.2. Measurement model assessment 4.2.1. Measurement model evaluation In this study, construct consistency was evaluated using Average Variance Extracted (AVE), Composite Reliability (CR), and Cronbach’s alpha. The results indicate that all constructs meet the recommended thresholds, with AVE values ≥ 0.50, CR ≥ 0.70, and Cronbach’s alpha ≥ 0.70, confirming adequate convergent validity and internal reliability (Hair et al., 2021 ; Hasan et al., 2025b ). Indicator performance was further assessed through outer loadings and collinearity statistics (VIF) (Hair et al., 2021 ). Although the ideal loading threshold is above 0.70 (Kusnandar et al., 2023; Sutrisno et al., 2024 ), several indicators in this study show loadings between 0.480 and 0.680. Following established guidelines, indicators within the 0.40–0.70 range were retained because the corresponding constructs continued to satisfy overall reliability and validity criteria (Hair et al., 2021 ). Table 3 Construct validity and reliability Latent Variable Indicators Loading Factor VIF AVE CR Cronbach Alpha Cues To Action (CTA) CTA 1: I participate in agricultural extension programs because they encourage me to implement sustainable Rojolele Srinuk rice cultivation practices. 0.888 3.205 0.713 0.925 0.898 CTA 2: Information from extension workers, farmer groups, or social media motivates me to implement environmentally friendly practices in my farming. 0.888 3.676 CTA 3: Examples of sustainable practices from other farmers motivate me to emulate them. 0.895 3.223 CTA 4: Government support (subsidies, regulations, and assistance with production facilities) encourages me to cultivate Rojolele Srinuk rice sustainably. 0.816 2.283 CTA 5: Suggestions or requests from buyers/consumers trigger changes in my practices. 0.721 1.871 Environmental Risk (ER) ER 1: I believe the overuse of pesticides is reducing biodiversity. 0.835 2.301 0.620 0.907 0.878 ER 2: I am concerned that climate change is exacerbating the risk of crop failure. 0.724 2.021 ER 3: I believe environmental sustainability is crucial to the future of agriculture. 0.786 2.046 ER 4: I believe soil erosion and land degradation are serious threats to farmers. 0.778 2.259 ER 5: I believe organic practices can reduce the risk of environmental damage. 0.823 2.236 ER 6: I believe the sustainability of farming depends on environmental sustainability. 0.774 2.035 Farmer Behavior (FB) FB 1: I have reduced my use of chemical fertilizers compared to the previous year. 0.783 2.158 0.559 0.896 0.865 FB 2: I regularly apply organic fertilizers or manure to some of my land. 0.831 2.423 FB 3: I implement integrated pest management (a balance between biological/botanical and chemical pesticides) depending on the pests that attack me. 0.791 2.217 FB 4: I implement more efficient water management practices on my land. 0.481 1.574 FB 5: I have participated in training/mentoring on sustainable agricultural techniques in the past 12 months. 0.772 1.982 FB 6: I market my crops with an emphasis on quality/sustainability (e.g., local/premium labels). 0.665 1.849 FB 7: I actively engage other farmers and share my experiences to improve sustainable practices. 0.844 2.865 Farmer Sustainability Knowledge (FSK) FSK 1: I understand the basic concepts of sustainable agriculture. 0.658 1.452 0.535 0.888 0.850 FSK 2: I understand the effects of chemical fertilizer use on soil fertility. 0.710 2.257 FSK 3: I understand the benefits of organic fertilizer and how to make it. 0.811 2.743 FSK 4: I know integrated pest management (IPM) techniques suitable for rice. 0.772 2.070 FSK 5: I know harvesting and post-harvest practices that maintain rice quality. 0.743 1.940 FSK 6: I understand how to access markets or certification for sustainable products. 0.545 1.310 FSK 7: I am aware of the relationship between sustainable practices and long-term health/economy. 0.838 2.365 Health Risk (HR) HR 1: I am concerned about the impact of pesticide use on my health. 0.898 3.498 0.670 0.924 0.900 HR 2: I believe the use of chemicals in agriculture can cause disease. 0.806 2.202 HR 3: I feel the quality of the air and water around the rice fields affects my family's health 0.805 2.387 HR 4: I feel their quality of life is declining due to exposure to hazardous materials. 0.693 1.843 HR 5: I feel it is important to reduce my exposure to chemicals for my health. 0.869 3.238 HR 6: I believe that protecting the health of farmers is as important as protecting the harvest. 0.823 2.734 Perceived Barriers (PBAR) PBAR 1: Additional costs (e.g., using organic fertilizers) make me hesitate to fully implement sustainable farming. 0,810 1.316 0.503 0.797 0.722 PBAR 2: Labor shortages make implementing sustainable practices difficult. 0,839 1.379 PBAR 3: Changing farming habits feels difficult and reduces my desire to change. 0.597 1.944 PBAR 4: Short-term economic risks hold me back from implementing sustainable practices. 0.545 1.869 Perceived Benefit (PB) PB 1: I believe that implementing sustainable agriculture improves the quality of Rojolele Srinuk rice. 0.811 2.267 0.615 0.905 0.875 PB 2: Environmentally friendly practices can reduce production costs in the long term. 0.771 2.065 PB 3: I believe sustainable practices can increase income through the premium specialty rice market. 0.787 2.056 PB 4: I believe that sustainable cultivation maintains the health of the soil, water, and the surrounding environment. 0.725 1.672 PB 5: I believe that adopting conservation techniques increases production resilience to climate change. 0.831 2.276 PB 6: I believe that sustainability helps maintain Rojolele Srinuk production for future generations. 0.776 2.033 Perceived Severity (PSVR) PSVR 1: I believe that excessive pesticide use will negatively impact my health and that of my family. 0.819 2.074 0.596 0.852 0.766 PSVR 2: I believe that soil degradation due to excessive chemical fertilization will reduce future farming productivity. 0.900 2.532 PSVR 3: I believe that if sustainable practices are not implemented, the sustainability of Rojolele Srinuk rice will be threatened. 0.580 1.217 PSVR 4: I believe that sustainable farming is crucial to ensuring the well-being of future generations. 0.753 1.476 Perceived Susceptibility (PSCP) PSCP 1: I feel the sustainability of my farming business depends on implementing sustainable farming practices. 0.636 1.472 0.522 0.843 0.766 PSCP 2: I believe the market is demanding more environmentally friendly products. 0.652 1.528 PSCP 3: I am concerned that my farming business is threatened by climate change. 0.761 1.855 PSCP 4: I believe smallholder farmers are more vulnerable to the risk of crop failure. 0.690 1.985 PSCP 5: I believe the risk of losses will increase if farming practices remain unchanged. 0.850 2.087 Self Efficacy (SE) SE 1: I am confident in my ability to implement sustainable Rojolele Srinuk rice cultivation techniques. 0.834 2.464 0.662 0.907 0.872 SE 2: I believe that training and mentoring will help my farming business become independent. 0.803 1.834 SE 3: I feel capable of overcoming technical challenges in implementing sustainable farming. 0.854 2.570 SE 4: I am confident in my ability to maintain the sustainability of my farming business and ensure its profitability. 0.736 1.734 SE 5: I am confident in my ability to overcome community/peer resistance in implementing new practices. 0.834 2.183 Socio Ethical Risk (SR) SR 1: I believe environmentally friendly practices are more in line with society's moral values. 0.836 2.043 0.604 0.882 0.830 SR 2: I feel social pressure is pushing me to farm more sustainably. 0.553 1.208 SR 3: I believe consumers prefer environmentally friendly products. 0.823 1.947 SR 4: I believe ethical farming is important for maintaining social relationships among farmers. 0.757 1.699 SR 5: I believe agricultural sustainability is a moral obligation for farmers. 0.874 2.479 Collinearity was assessed using the Variance Inflation Factor (VIF). In PLS-SEM, a VIF value below 5 indicates the absence of serious multicollinearity and is the most commonly accepted threshold (Hair et al., 2021 ). A stricter criterion of VIF < 3.3 suggests very low collinearity and is often applied in models that require higher sensitivity to multicollinearity issues. In contrast, VIF values above 5 indicate potential collinearity concerns, while values exceeding 10 signal serious multicollinearity problems that require indicator removal or model revision. In this study, most indicators exhibit VIF values below 3.3, and only two indicators show VIF values slightly above 3.3 but still below 5. These results indicate that collinearity is well within acceptable limits and that the structural model can be considered statistically sound. 4.2.2. Structural model evaluation The results of the inner model evaluation, presented in Table 4 , show the explanatory power of the structural model through R² values. In PLS-SEM, R² values are generally interpreted as follows: above 0.67 indicates a strong model, above 0.33 indicates a moderate model, and above 0.19 indicates a weak model (Hair et al., 2024 ; Solimun et al., 2022). The R² statistic reflects the extent to which endogenous constructs are explained by their corresponding exogenous predictors, with higher values indicating greater predictive capability (Hassan et al., 2025 ). In this study, strong R² values are observed for farmer behaviour, perceived susceptibility, and perceived severity. Moderate explanatory power is found for cues to action, perceived benefits, and self-efficacy. In contrast, perceived barriers exhibit a relatively weak R² value, indicating that this construct is explained to a lesser extent by the predictors included in the model. 4.3. Relationship between variables This study examines the structural relationships among multidimensional risk perception, HBM constructs, and farmers’ sustainable behaviour. The results indicate that perceived health risk, perceived environmental risk, and perceived socio-ethical risk are significantly associated with several HBM components, which in turn influence farmer behaviour. In addition, perceived benefits affect farmer behaviour with sustainability knowledge acting as a moderating variable. Using a 5% significance level, the analysis shows that perceived susceptibility, perceived benefits, perceived barriers, self-efficacy, and cues to action have significant relationships with farmer behaviour in supporting the sustainability of Rojolele Srinuk rice farming (p < 0.05). Perceived barriers exhibit a negative relationship, while the others show positive effects. In contrast, perceived severity does not have a significant direct relationship with farmer behaviour (p > 0.05). Regarding the antecedents of HBM constructs, perceived health risk, perceived environmental risk, and perceived socio-ethical risk each have significant positive relationships with perceived susceptibility and perceived severity (p < 0.05). Perceived health risk and perceived socio-ethical risk significantly influence perceived benefits, whereas perceived environmental risk does not. For perceived barriers, only socio-ethical risk shows a significant relationship, while health and environmental risks do not. All three dimensions of risk perception demonstrate positive and significant relationships with self-efficacy and cues to action (p < 0.05) (Table 4 ). Table 4 Relationship between variables Relationship between the variables coefficient t value sig R 2 Q 2 decision Perceived health risk → Perceived susceptibility 0.445 6.960 0.000 0.695 0.905 Supported Perceived environmental risk 0.200 2.457 0.014 Supported Perceived socio ethical risk 0.251 4.366 0.000 Supported Perceived health risk → Perceived severity 0.419 8.976 0.000 0.720 0.921 Supported Perceived environmental risk 0.331 6.183 0.000 Supported Perceived socio ethical risk 0.157 3.060 0.002 Supported Perceived health risk → Perceived benefits 0.200 2.533 0.011 0.412 0.649 Supported Perceived environmental risk 0.130 1.320 0.187 Not Supported Perceived socio ethical risk 0.361 4.207 0.000 Supported Perceived health risk → Perceived barriers -0.126 1.549 0.121 0.308 0.515 Not Supported Perceived environmental risk 0.178 1.812 0.070 Not Supported Perceived socio ethical risk -0.597 8.057 0.000 Supported Perceived health risk → Perceived self - efficacy 0.146 2.132 0.033 0.496 0.742 Supported Perceived environmental risk 0.265 3.004 0.003 Supported Perceived socio ethical risk 0.345 4.406 0.000 Supported Perceived health risk → Cues to action 0.257 3.538 0.000 0.509 0.755 Supported Perceived environmental risk 0.263 5.433 0.000 Supported Perceived socio ethical risk 0.406 5.978 0.000 Supported Perceived susceptibility → Farmer behavior 0.154 3.438 0.001 0.742 0.929 Supported Perceived severity 0.031 0.604 0.546 Not Supported Perceived benefits 0.120 2.341 0.019 Supported Perceived barriers -0.092 2.677 0.007 Supported Perceived self - efficacy 0.110 2.229 0.026 Supported Cues to action 0.263 5.433 0.000 Supported Farmer sustainability knowledge x Perceived susceptibility → Farmer behavior -0.036 0.776 0.438 0.742 0.929 Not supported Farmer sustainability knowledge x Perceived severity 0.018 0.332 0.740 Not supported Farmer sustainability knowledge x Perceived benefits 0.067 1.655 0.098 Supported in alpha 0.100 Farmer sustainability knowledge x Perceived barriers 0.027 0.793 0.428 Not supported Farmer sustainability knowledge x Perceived self – efficacy -0.046 1.000 0.317 Not supported Farmer sustainability knowledges x Cues to action -0.038 0.923 0.356 Not supported This study also identifies a moderating effect of farmers’ sustainability knowledge on sustainable behaviour. The results indicate that sustainability knowledge strengthens the positive relationship between perceived benefits and farmer behaviour, with significance at the 10% level (p = 0.098 < 0.10). This finding suggests that farmers with higher sustainability knowledge are more likely to translate perceived benefits into concrete sustainable farming actions. The coefficient of determination (R²) values indicate the explanatory power of the structural model for each endogenous construct. Strong R² values are observed for perceived susceptibility (0.695), perceived severity (0.720), and farmer behaviour (0.742), suggesting that these variables are well explained by their respective predictors. Moderate explanatory power is found for perceived benefits (0.412), self-efficacy (0.496), and cues to action (0.509). In contrast, perceived barriers show a relatively weak R² value (0.308). The R² statistic reflects the extent to which endogenous variables can be explained by exogenous variables within the research model, with higher values indicating stronger predictive capacity (Thi Nguyen & Dang, 2022 ). Beside that, the model also validated with Q 2 value for evaluate the model predictive ability. Table 4 show that Q 2 value are strong predictive relevance with score more than 0.00 (Hair et al., 2021 ). 5. Discussions The integration of the Health Belief Model (HBM) with multidimensional risk perception and sustainability knowledge provides a comprehensive explanation of farmers’ behaviour in sustaining Rojolele Srinuk rice cultivation in Klaten Regency. The findings indicate that behavioural change emerges from an interconnected psychosocial process in which perceived risks shape core HBM constructs, which subsequently influence behavioural outcomes. This confirms the relevance of HBM in agricultural sustainability contexts characterised by uncertainty, health concerns, and social responsibility. Health, environmental, and socio-ethical risk perceptions consistently function as antecedents that influence farmers’ cognitive and motivational evaluations. Their positive association with perceived susceptibility suggests that farmers internalise both personal and collective consequences of conventional practices, including health exposure, land degradation, and moral responsibility toward consumers and the community (Abrams et al., 2021 ; Mathew & Tholath, 2024 ; Omi et al., 2025 ; Tenchini et al., 2025 ). Rather than acting independently, these risk dimensions collectively construct a sense of vulnerability that forms the psychological basis for behavioural assessment. Risk perception also extends beyond vulnerability and influences perceived severity, benefits, barriers, self-efficacy, and cues to action, although with varying intensity. The strong relationship between risk perception and perceived severity indicates that farmers recognise the seriousness of declining land productivity, household health risks, and social consequences of unsustainable farming (Li et al., 2022 ; Nguena & Bindoumou, 2024 ; Simarmata et al., 2020 ; Sodhi et al., 2023 ). However, the absence of a direct effect of perceived severity on behaviour suggests that recognising seriousness alone does not guarantee action. Long-term or familiar risks may become normalised within routine agricultural practice, reducing their motivational force (Bagambilana & Rugumamu, 2023 ; Kyire et al., 2023 ). The analysis of perceived benefits and barriers reveals a more pragmatic decision-making pattern. Perceived benefits are significantly shaped by health and socio-ethical risks, indicating that farmers respond more strongly to tangible and socially meaningful outcomes, such as protecting family health and maintaining community reputation (Dey et al., 2024 ; Negi et al., 2025 ; Pratama et al., 2024 ). In contrast, environmental risk perception does not significantly enhance perceived benefits, suggesting a cognitive separation between environmental awareness and personal gain. Environmental risks may be viewed as collective and long-term, whereas benefits are evaluated through immediate and economically salient considerations (Byfuglien et al., 2025 ). This asymmetry explains why environmental awareness alone often fails to drive benefit-based behavioural change without concrete incentives. Perceived barriers further illustrate the differentiated role of risk dimensions. Health and environmental risk perceptions do not significantly reduce perceived barriers, indicating that awareness of risk is insufficient to overcome structural constraints such as limited capital, labour requirements, or access to inputs. In contrast, socio-ethical risk perception significantly reduces perceived barriers, highlighting the influence of social norms and moral responsibility in lowering psychological resistance to change (Karimi & Ataei, 2023 ). Collective expectations appear more effective than individual risk awareness in facilitating behavioural adjustment. Self-efficacy and cues to action emerge as critical mechanisms translating awareness into action. The positive effects of all three risk dimensions on self-efficacy suggest that risk awareness, particularly when framed within social and ethical contexts, strengthens farmers’ confidence in implementing sustainable practices ((Truelove et al., 2015 ; Yanakittkul & Aungvaravong, 2020 ). Similarly, risk perceptions stimulate cues to action through extension programs, policy initiatives, peer influence, and direct farming experiences (Hochman et al., 2017 ; Nelson et al., 2022 ). These findings indicate that risk perception acts primarily as a catalyst activating multiple HBM pathways rather than directly driving behaviour. At the behavioural level, perceived susceptibility, perceived benefits, self-efficacy, perceived barriers, and cues to action jointly explain farmers’ adoption of sustainable practices. The positive effect of perceived susceptibility confirms that farmers who feel personally vulnerable are more inclined to act (Li et al., 2013 ). The strong influence of perceived benefits and self-efficacy, together with the negative effect of perceived barriers, indicates that decisions are grounded in a rational evaluation of expected gains, implementation feasibility, and personal capability (Methamontri et al., 2022 ; Sharna et al., 2025 ). Cues to action reinforce the importance of institutional support and social engagement in converting intention into practice. The moderating role of sustainability knowledge adds important nuance to these relationships. Knowledge does not uniformly strengthen all behavioural pathways. The non-significant or negative moderation of vulnerability suggests that more informed farmers rely less on emotional risk perception and more on deliberate planning (Ahmad et al., 2022 ; Khai et al., 2023 ). Conversely, the positive moderation of perceived benefits (significant at the 10% level) indicates that knowledge enhances farmers’ ability to translate recognised advantages into concrete action. The absence of significant moderation for barriers, self-efficacy, and cues to action suggests that knowledge alone cannot eliminate structural constraints or substitute for institutional support (Krisnawati et al., 2025; Son et al., 2021 ). Overall, this study advances sustainability behaviour research by demonstrating that multidimensional risk perception operates as an integrated psychosocial catalyst within the HBM framework, while sustainability knowledge functions as a selective enhancer of benefit-oriented reasoning. These findings challenge the assumption that increasing knowledge alone will automatically promote sustainable behaviour. Instead, effective sustainability strategies must align knowledge dissemination with tangible benefits, supportive social norms, and enabling institutional structures. 6. Conclusion 6.1. General conclusion and implication This study demonstrates that sustainable farming behaviour among Rojolele Srinuk rice farmers is primarily shaped by perceived susceptibility, perceived benefits, self-efficacy, and cues to action, whereas perceived severity plays a limited direct role due to the normalization of risk in routine agricultural practice. By integrating multidimensional risk perception and sustainability knowledge into the HBM framework, this research extends HBM-based sustainability studies beyond simple direct-effect explanations. Sustainability knowledge does not uniformly strengthen all behavioural pathways; instead, it selectively reinforces benefit-oriented reasoning, refining the theoretical application of HBM in agricultural contexts. These findings contribute to broader development goals, particularly SDG 2 (Zero Hunger) through sustainable food production, SDG 3 (Good Health and Well-being) through reduced exposure to chemical risks, and SDG 12 (Responsible Consumption and Production) through environmentally responsible farming. In the Indonesian context, the results provide empirical support for policies aimed at building a resilient and sustainability-oriented agricultural transformation. Policy implications emerge clearly from the identified behavioural mechanisms. Extension strategies should move beyond fear-based risk communication and emphasise tangible economic, health, and social benefits of sustainable practices. Strengthening farmers’ self-efficacy through participatory training, demonstration plots, and peer learning is essential to translate awareness into action. Social and ethical norms should be leveraged to reduce perceived barriers by reinforcing collective responsibility and local identity. Finally, supportive market and institutional mechanisms (including improved market access, price incentives, and targeted input support) are necessary to ensure that perceived benefits outweigh structural constraints and enable the long-term sustainability of local rice farming systems. 6.2. Limitations and further research This study has several limitations that should be acknowledged. First, the cross-sectional design limits the ability to capture dynamic changes in farmers’ perceptions and behaviour over time, particularly given that sustainability adoption is gradual and iterative. Second, the analysis relies on self-reported survey data, which may be affected by social desirability and recall bias, especially in contexts where sustainable agriculture is normatively promoted. Third, the geographic focus on Rojolele Srinuk farmers in Klaten Regency limits the generalisability of the findings to other agroecological and institutional settings. Finally, although sustainability knowledge is modelled as a moderating variable, broader structural factors (such as market incentives, policy enforcement, and institutional capacity) are not explicitly incorporated into the interaction framework. Future research should adopt longitudinal or quasi-experimental designs to better examine how psychosocial factors and sustainability knowledge evolve over time and to strengthen causal inference. The HBM framework could be expanded by incorporating institutional support, policy incentives, and market access as moderating or contextual variables to assess how structural conditions shape behavioural responses. Comparative studies across different regions, rice varieties, or farming systems would help test the robustness of the selective moderation effect identified in this study. Additionally, integrating behavioural SEM models with biophysical or sustainability performance indicators such as soil health metrics, input efficiency, or multidimensional sustainability indices would strengthen the link between farmer behaviour and measurable environmental outcomes. Declarations Acknowledgement The author acknowledges to the research funding specifically Indonesia Ministry of Higher Education, Science, and Technology with PMDSU Postgraduate Research Scheme under contract number 105/C3/DT.05.00/PL/2025 and National Taiwan University for supporting in publication funding. Funding This research was funded by Indonesia Ministry of Higher Education, Science, and Technology with PMDSU Postgraduate Research Scheme under contract number 105/C3/DT.05.00/PL/2025 Data availability The datasets produced and/or analysed in the current work are available from the corresponding author upon reasonable request. Ethics approval This study has obtained ethical approval from the Research Ethics Committee of the Faculty of Medicine, Universitas Sebelas Maret (Approval Number: 39/UN27.06.11/KEP/EC/2026). All research procedures were conducted in accordance with the ethical guidelines and regulations of Universitas Sebelas Maret, Indonesia. Consent to participate Research participants, particularly male and female farmers aged above 20 years, were provided with an explanation by the researcher through informed consent, which was approved by the research ethics committee, and participants consented to participate in this study voluntarily and without coercion. Consent to publication Not applicable Conflict of interest The author declares that there is no conflict of interest, either financial or related, with the reviewer or publisher in the publication of this article. Clinical Trial Not applicable Author Contribution Nugroho Hasan: Writing original draft, methodology, conceptualization, and data analysis. Mohamad Harisudin: Writing – review, editing, and supervision. Kusnandar: Review and supervision. Putriesti Mandasari: Writing – review, editing, supervision, investigation. Li – Fen Lei: Review and supervision References Abdollahzadeh G, Sharif M. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9024162","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":619271295,"identity":"e6f34283-07a5-417f-b1e9-49b389df00cc","order_by":0,"name":"Nugroho Hasan","email":"","orcid":"","institution":"Universitas Sebelas Maret","correspondingAuthor":false,"prefix":"","firstName":"Nugroho","middleName":"","lastName":"Hasan","suffix":""},{"id":619271296,"identity":"018b3b48-a54d-43a5-8c40-1497701162c1","order_by":1,"name":"Mohamad Harisudin","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABA0lEQVRIiWNgGAWjYFACHhDBzGDA3gCkbeSQxA8Q0sJzgLGBIc2YFC0SCahaGHBp0W3vPfjpRo01g7nk8+cPfiQYMBjcbn/A8KOGQYYPhxazM+eSpXOOpTNYzs4xbOwBablzxoCx5xgDjyQuLTdyDKRz2A4DDc9hbOD98YfB4EYOAwNvAwOPAW4txr9z/gG13Dz+sPEPyJYb6Q8Y/+LXYiad2wbUcoPBsJkHrCXBgBmvLWfOmFnn9qUzGJzJMZwtk2DAIwl06mGZYxK4/XK8x/h2zjdrBoPjxx98fJNgIMd3I/3hwzc1Nva4QgwG6hugDHA0ARVL4Fc/CkbBKBgFowAvAABXZV2CgnQomgAAAABJRU5ErkJggg==","orcid":"","institution":"Universitas Sebelas Maret","correspondingAuthor":true,"prefix":"","firstName":"Mohamad","middleName":"","lastName":"Harisudin","suffix":""},{"id":619271297,"identity":"ecd5756b-d8d7-4878-bafc-22832cc17810","order_by":2,"name":"Kusnandar Kusnandar","email":"","orcid":"","institution":"Universitas Sebelas Maret","correspondingAuthor":false,"prefix":"","firstName":"Kusnandar","middleName":"","lastName":"Kusnandar","suffix":""},{"id":619271298,"identity":"3766178d-fa8a-4afd-9a96-1c209bbfaab1","order_by":3,"name":"Putriesti Mandasari","email":"","orcid":"","institution":"Universitas Sebelas Maret","correspondingAuthor":false,"prefix":"","firstName":"Putriesti","middleName":"","lastName":"Mandasari","suffix":""},{"id":619271299,"identity":"2ee7beba-3a32-46e9-b2c7-66c91b563629","order_by":4,"name":"Li-Fen Lei","email":"","orcid":"","institution":"National Taiwan University","correspondingAuthor":false,"prefix":"","firstName":"Li-Fen","middleName":"","lastName":"Lei","suffix":""}],"badges":[],"createdAt":"2026-03-03 23:23:21","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9024162/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9024162/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":106726792,"identity":"8145d43e-6fa2-4f72-95c9-02444fc7628b","added_by":"auto","created_at":"2026-04-12 18:37:16","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":211512,"visible":true,"origin":"","legend":"\u003cp\u003eTheoritical framework of this study\u003c/p\u003e","description":"","filename":"Picture1.png","url":"https://assets-eu.researchsquare.com/files/rs-9024162/v1/1bbdfa07e4c91db99b92f0ba.png"},{"id":106638388,"identity":"751d8799-c38f-4db3-9c58-d14ad338eb6c","added_by":"auto","created_at":"2026-04-10 17:19:29","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":206476,"visible":true,"origin":"","legend":"\u003cp\u003eMap of Research Location\u003c/p\u003e","description":"","filename":"Picture2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9024162/v1/49141d7379db46cb8ac5872a.jpg"},{"id":106638389,"identity":"663a9430-a690-4b67-9c7a-5c586d7daceb","added_by":"auto","created_at":"2026-04-10 17:19:30","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":710760,"visible":true,"origin":"","legend":"\u003cp\u003eMeasurement model from bootstrapping\u003c/p\u003e","description":"","filename":"F3.png","url":"https://assets-eu.researchsquare.com/files/rs-9024162/v1/6eb99436775ae5435cb8886b.png"},{"id":106727804,"identity":"79c79672-7969-492f-b1dc-a0b8f9a00c6d","added_by":"auto","created_at":"2026-04-12 18:40:56","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2815646,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9024162/v1/14b18fde-823f-439b-8d72-e191c3d5dc78.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Understanding psychosocial determinants of sustainable farming behaviour among local rice farmers in Indonesia","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eIndonesia\u0026rsquo;s rice sector remains central to national food security and continues to show strong production dynamics. Official statistics indicate that 2024 provides the current baseline for harvested area and output, while projections for 2025 suggest further expansion. Milled dry grain (GKG) production is expected to reach approximately 60.34\u0026nbsp;million tonnes, representing a 13.6% increase compared to 2024. This growth is largely driven by expanded harvested areas and favourable climatic conditions (Indonesia Statistic Agency, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).At the same time, national agricultural policies increasingly emphasise downstream processing, land expansion, and investment to strengthen food security. These strategies, however, also intensify pressure to balance productivity gains with environmentally sustainable farming practices (Atmajaya et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Hasan et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2025b\u003c/span\u003e; Indonesia Ministry of Agriculture, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAt the regional level, Central Java remains one of Indonesia\u0026rsquo;s main rice-producing provinces, although recent performance shows notable fluctuations. In 2024, harvested area declined to about 1.55\u0026nbsp;million hectares, with production estimated at 8.89\u0026nbsp;million tonnes of unhusked rice, down from the previous year (Central Java Statistic Agency, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). A similar pattern occurred in Klaten Regency, where both harvested area and production fell despite ongoing government programs promoting expanded planting, mechanisation, and pest control (Klaten Regency Statistic Agency, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Within this setting, Rojolele Srinuk, an aromatic local variety with economic, cultural, and social significance, is strategically important for sustaining local agricultural systems agriculture (Hasan et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2025a\u003c/span\u003e; Kristamtini et al., 2021).\u003c/p\u003e \u003cp\u003eNevertheless, sustaining Rojolele Srinuk cultivation is constrained by persistent structural challenges. These include land fragmentation, the dominance of smallholder farming, intensive use of chemical inputs, and limited farmer regeneration (Antriyandarti et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Pratama et al., \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Such constraints indicate that technological interventions and policy incentives alone are insufficient. Farmers\u0026rsquo; behavioural responses to risk, uncertainty, and evolving production demands play a decisive role in shaping the adoption of sustainability-oriented practices (Fanak et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; May et al., \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Moridi et al., \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Uikey et al., \u003cspan citationid=\"CR102\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Empirical studies increasingly confirm that decision-making in agriculture is influenced by psychosocial considerations, including perceptions of health risks, environmental consequences, and social responsibility toward households and future generations (Ratnayake et al., \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Salam et al., \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Sapkota et al., \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Trezise \u0026amp; Richardson, \u003cspan citationid=\"CR100\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn this regard, the Health Belief Model (HBM) provides a relevant framework for explaining why farmers adopt or resist sustainability-promoting practices (Nasiri et al., \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The model is particularly suitable for agricultural contexts, where decisions involve weighing perceived risks, expected benefits, and practical constraints under uncertainty (Karimi \u0026amp; Ataei, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Kirscht, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e1998\u003c/span\u003e; Li et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Although previous studies have applied HBM to agricultural and environmental behaviour, most focus on general adoption outcomes or isolated constructs. Few studies integrate multidimensional risk perception and farmers\u0026rsquo; sustainability knowledge into a unified behavioural model (Li et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Pratama et al., \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; You et al., \u003cspan citationid=\"CR108\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e Accordingly, this study examines how psychosocial factors influence sustainable farming behaviour in Rojolele Srinuk cultivation in Klaten Regency. It applies the HBM, extended to include multidimensional risk perception (covering health, environmental, and socio-ethical risks), and farmers\u0026rsquo; sustainability knowledge. The novelty of this research lies in the development of an integrated empirical model that connects risk awareness, cognitive evaluation, and behavioural response within a local rice-farming context. By strengthening behavioural insight in environmental and agricultural research, this study also provides policy-relevant guidance for designing more effective sustainability-oriented extension and intervention strategies.\u003c/p\u003e"},{"header":"2. Literature Review","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Demographic characteristic\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eDemographic characteristics are important determinants of farmers\u0026rsquo; behaviour and their adoption of sustainable agricultural practices. Variables such as age, education level, household size, farming experience, and landholding size shape decision-making capacity, access to information, labour availability, and resource constraints (Cho \u0026amp; Lee, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Creppy et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Age and farming experience are often associated with technological conservatism, as older farmers or those with long experience tend to maintain conventional practices. In contrast, higher education levels and larger landholdings are generally positively related to innovation adoption, as education enhances information access and analytical ability, while larger farms provide economies of scale and greater capacity to absorb risk (Haile et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Kyire et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Salam et al., \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Household size also influences cultivation decisions by determining the availability of family labour and shaping input-use strategies (Ngwenya \u0026amp; Mukwada, \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Woodmansee et al., \u003cspan citationid=\"CR105\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).. A larger household may ease labour constraints but may also increase consumption pressure, thereby affecting production choices (Dey et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). In the context of Rojolele Srinuk cultivation, family support, accumulated farming experience, and household structure are likely to influence farmers\u0026rsquo; commitment to conservation-oriented and sustainable agricultural practices.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Multidimensional risk perception\u003c/h2\u003e \u003cp\u003eMultidimensional risk perception reflects how individuals evaluate potential losses and negative consequences associated with their actions, including social, health, environmental, and ethical dimensions. In agricultural settings, risk perception shapes how farmers respond to innovation, policy change, and sustainability pressures (Datta \u0026amp; Behera, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Wolff et al., \u003cspan citationid=\"CR104\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Farmers do not assess risks purely in technical terms; they also consider social acceptance, community norms, and the broader consequences of their decisions. Previous studies show that perceived risk can either motivate behavioural adjustment or hinder change, depending on how farmers weigh potential benefits against social and economic uncertainties (Ma \u0026amp; Rahut, \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Zoundji et al., \u003cspan citationid=\"CR112\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Concerns about community reactions, group expectations, and long-term agronomic impacts often become part of the total risk evaluation when deciding whether to adopt new or sustainable practices (Zheng \u0026amp; Dallimer, \u003cspan citationid=\"CR110\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn this study, multidimensional risk perception consists of perceived health risk, perceived environmental risk, and perceived socio-ethical risk (Karimi \u0026amp; Ataei, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Perceived health risk refers to farmers\u0026rsquo; awareness of potential adverse health effects arising from pesticide exposure, wastewater, and other chemical inputs (Aslam et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Perceived environmental risk concerns the belief that excessive use of fertilizers and pesticides may damage soil quality, water systems, and ecological balance (Kyire et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Mallick et al., \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Zhu et al., \u003cspan citationid=\"CR111\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Perceived socio-ethical risk relates to concerns about social judgement, community norms, and the moral implications of farming practices for future generations (Chen et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Karimi \u0026amp; Ataei, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Together, these dimensions capture the broader risk considerations that may influence farmers\u0026rsquo; sustainability-related decisions.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Health belief model\u003c/h2\u003e \u003cp\u003eThe Health Belief Model (HBM) is one of the most established theoretical frameworks for explaining individual decision-making in preventive and protective behaviour. Originally developed in public health research, the model has evolved conceptually and empirically, making it applicable to environmental behaviour, sustainable agriculture, and occupational safety contexts (Ataei et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Luger, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Nasiri et al., \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Singh et al., \u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e2026\u003c/span\u003e). HBM explains behaviour through subjective beliefs about vulnerability to risk, the seriousness of consequences, expected benefits, perceived barriers, and confidence in performing protective actions (Baghestani et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Wang et al., \u003cspan citationid=\"CR103\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). In this study, sustainable Rojolele Srinuk rice farming is positioned as a long-term protective action aimed at safeguarding farmers\u0026rsquo; health, preserving environmental quality, and maintaining the economic and social viability of the farm enterprise.\u003c/p\u003e \u003cp\u003eThe perceived susceptibility construct in the HBM refers to farmers' perception of their vulnerability to risks arising from unsustainable farming practices (Jamshed et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). In the context of rice farming, this vulnerability can manifest as the risk of health problems due to exposure to pesticides and chemical fertilizers, the risk of land degradation, and the risk of decreased productivity and income in the future (Mkonda \u0026amp; He, \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Farmers feel more vulnerable to these risks tend to have higher psychological readiness to consider behavioral changes toward more sustainable practices (Habiba et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). This perception of vulnerability becomes the starting point for the formation of risk awareness in the farmers' decision-making process (Karimi \u0026amp; Ataei, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePerceived benefits refer to farmers\u0026rsquo; beliefs that sustainable practices will generate tangible and relevant advantages (Dhar et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; C. Liu et al., \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Methamontri et al., \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). These benefits may include improved occupational health, better soil and environmental quality, greater yield stability, and enhanced market value of the Rojolele Srinuk variety. Within the HBM framework, perceived benefits function as a rational justification for behavioural change, particularly when expected gains are seen as outweighing potential costs or risks (Abdollahzadeh \u0026amp; Sharif, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Karimi \u0026amp; Ataei, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePerceived severity refers to the extent to which farmers believe that the consequences of a given risk are serious and potentially disruptive to their lives (Chen et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Gichohi-Wainaina et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). In the context of Rojolele Srinuk rice cultivation, this perception extends beyond immediate health effects to include environmental degradation, long-term declines in land productivity, and threats to farming as a sustainable source of family income and intergenerational continuity (Mgendi et al., \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Zenda et al., \u003cspan citationid=\"CR109\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). When risks are perceived as severe, farmers are more likely to critically reassess their current cultivation practices and consider adjustments toward more sustainable approaches ((Kassian et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Moridi et al., \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eConversely, perceived barriers represent the obstacles farmers associate with adopting sustainable practices (Brunt et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Rehman et al., \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). These may include limited capital, uncertainty about yields, lack of technical knowledge, weak institutional support, and prevailing social norms favouring conventional methods (Antwi-Agyei \u0026amp; Stringer, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Cramb, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Pilato et al., \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). HBM literature consistently identifies perceived barriers as a dominant inhibiting factor; even when risks and benefits are recognised, behavioural change may not occur if obstacles are considered too substantial (Martin et al., \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Nyantakyi-Frimpong, \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Self-efficacy, an important extension of the original HBM, refers to farmers\u0026rsquo; confidence in their ability to implement sustainable techniques, manage constraints, and make informed farm decisions (Moridi et al., \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Nasiri et al., \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Strong self-efficacy not only directly supports behavioural adoption but also reinforces the influence of risk and benefit perceptions on action (Shen et al., \u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Wang et al., \u003cspan citationid=\"CR103\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Cues to action function as internal or external triggers that prompt behavioural change (Nasiri et al., \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Xu et al., \u003cspan citationid=\"CR106\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn the context of Klaten Regency, cues to action may include agricultural extension services, government programs, certification schemes, market demand for high-quality rice, and farmers\u0026rsquo; direct experiences with declining land quality or health problems. These triggers activate the psychological readiness shaped by other HBM constructs and facilitate actual behavioural change. Consistent with the classical HBM framework, this study also incorporates modifying factors, namely demographic characteristics and sustainability knowledge. These factors shape perceptions of risk, benefits, barriers, and self-efficacy, thereby indirectly influencing behaviour. Overall, HBM is positioned as a causal framework that explains how psychosocial factors systematically shape farmers\u0026rsquo; decisions regarding sustainable Rojolele Srinuk rice cultivation. The theoretical model of this study is presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Farmer sustainability knowledge\u003c/h2\u003e \u003cp\u003eFarmers\u0026rsquo; sustainability knowledge refers to their level of understanding and awareness of the principles, practices, and long-term implications of sustainable farming systems ((Liu et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Shijin, \u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). This knowledge includes technical, environmental, economic, and social dimensions, such as soil fertility management, efficient use of inputs, protection of farmer health, and the continuity of farming across generations (Kabir et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). In the sustainable agriculture literature, knowledge is regarded as a fundamental cognitive resource that shapes environmentally responsible and long-term-oriented decision-making (M\u0026uuml;ller et al., \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn the context of rice farming, particularly for local varieties such as Rojolele Srinuk, knowledge of sustainability becomes increasingly important given the intensive use of land, water, and chemical inputs. Farmers with stronger sustainability knowledge are generally better able to recognise the health and environmental risks associated with unsustainable practices and to appreciate the long-term benefits of adopting more environmentally sound approaches (Sahara et al., \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Knowledge therefore functions not only as a source of risk awareness but also as a reinforcing factor that strengthens farmers\u0026rsquo; orientation toward the long-term sustainability of their farming enterprises.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eWithin the HBM framework, sustainability knowledge functions as a modifying factor that shapes how farmers interpret risk, benefits, and barriers related to sustainable practices. Farmers with higher levels of knowledge are more likely to perceive risks as concrete and consequential, while also being better able to recognise potential benefits and identify practical solutions to existing constraints (Beltr\u0026aacute;n-Tolosa et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). In addition, sustainability knowledge can strengthen self-efficacy by enhancing farmers\u0026rsquo; confidence in their ability to implement sustainable techniques under real farming conditions. Empirical studies consistently show that sustainability knowledge is positively associated with pro-environmental farming behaviour, although the relationship is often indirect and mediated by psychosocial constructs (Li et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Qadir et al., \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Integrating sustainability knowledge into the HBM framework therefore allows for a more comprehensive explanation of behavioural formation. In this study, sustainability knowledge is positioned as a reinforcing variable that strengthens the influence of psychosocial factors on farmers\u0026rsquo; commitment to sustaining Rojolele Srinuk rice cultivation in Klaten Regency.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Methodology","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Research design and approach\u003c/h2\u003e \u003cp\u003eThis study adopts a quantitative and explanatory design to analyse farmers\u0026rsquo; behaviour in supporting the sustainability of Rojolele Srinuk rice farming. It aims to examine the causal relationships between psychosocial factors and sustainability-oriented behaviour based on a strong theoretical foundation (Bagambilana \u0026amp; Rugumamu, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Sohrabizadeh et al., \u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Data were collected through surveys, complemented by interviews and field observations. The survey instrument was developed from the Health Belief Model (HBM) indicators (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The study includes eleven variables three exogenous, seven endogenous, and one moderating variable measured using a five-point Likert scale ranging from strongly disagree (1) to strongly agree (5) (Ayu Purnamawati et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Das \u0026amp; Mishra, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). All constructs were assessed for validity and reliability using SEM-PLS procedures.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Study area, data collection and sample\u003c/h2\u003e \u003cp\u003eThis research was conducted in Klaten Regency, which was purposively selected because it serves as a key production area for the local Rojolele Srinuk rice variety (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The specific research sites were determined based on their status as production centres characterised by grey regosol soils\u0026mdash;derived from volcanic ash and intermediate sand parent materials and supported by established irrigation systems (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eList of research area and sample\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eList of research area (district)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eType of irrigation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePopulation (N)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSample (n)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSampling Fraction (n/N)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDelanggu, Polanharjo, and Karanganom\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTechnical Irrigation of Spring Water Sources\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1,430\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e231\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e16.2%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJuwiring and Trucuk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTechnical irrigation for rivers/dams and deep wells\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e551\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e16.1%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrambanan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRainfed and semi-technical irrigation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e619\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e16.2%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e2,600\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e420\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eSource: Klaten Statistic Agency and Agriculture Agency, 2024\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe respondents in this study consisted of 420 farmers selected through proportionate stratified random sampling from an estimated population of approximately 2,600 Rojolele Srinuk farmers in Klaten Regency. Stratification was applied because the farmer population is heterogeneous, particularly in terms of agroecological conditions (spring irrigation, dam or river irrigation, and rainfed systems), production intensity and associated farming risks, and access to water resources, all of which may influence behaviour and risk perceptions. By grouping farmers into relatively homogeneous strata while maintaining heterogeneity between strata, this approach enhances sample representativeness and improves the precision of parameter estimation (Raj \u0026amp; Sofi, \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Within each stratum, respondents were randomly selected based on the criterion that they had cultivated Rojolele Srinuk rice at least once in the past five years.\u003c/p\u003e \u003cp\u003eThe chosen sample size also satisfies methodological requirements for PLS-SEM analysis. According to the 10-times rule and statistical power considerations, models with moderate effect sizes generally require at least 150\u0026ndash;200 observations (considerations (Hair, J. F. et al., 2021; Kimaro et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). With 420 respondents, this study exceeds the recommended threshold, thereby ensuring adequate statistical power and stable parameter estimation.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.3. Analysis techniques\u003c/h2\u003e \u003cp\u003eThe Partial Least Squares\u0026ndash;Structural Equation Modeling (PLS-SEM) approach was employed to analyse the research model. This method is appropriate for examining complex relationships among multiple latent variables and for testing interaction effects within an integrated framework (Azadi et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Hair et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Compared to conventional linear regression, PLS-SEM is better suited for models involving simultaneous causal paths and latent constructs. The analysis was conducted using SmartPLS software, which is widely applied in explanatory research and theory development because it focuses on maximizing the variance of endogenous constructs while estimating structural relationships concurrently (Guenther et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Harisudin et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). In addition, PLS-SEM does not require strict multivariate normality assumptions, making it robust for survey data measured on Likert scales. With 420 respondents, the sample size exceeds recommended thresholds for stable parameter estimation and adequate statistical power (Hair et al., 2022; Sarstedt et al., \u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Results","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n \u003ch2\u003e4.1. Demographic characteristic\u003c/h2\u003e\n \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e indicates that the majority of Rojolele Srinuk farmers are male, accounting for 84.3% of the total respondents. The age distribution is dominated by farmers between 50 and 69 years, suggesting limited generational renewal in rice farming within Klaten Regency. This ageing farmer structure highlights the need for targeted interventions to encourage younger participation in local rice cultivation. Despite this demographic pattern, farmers remain committed to cultivating Rojolele Srinuk because of its established market demand and strong customer base. In terms of education, 57.1% of respondents have completed senior high school, indicating a relatively adequate level of formal education that may support the adoption of improved and sustainability-oriented practices.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eRespondent demographics\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"3\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eFeatures of population\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003ePercentage\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eDistribution of farmers\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eDelanggu\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e22.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003ePolanharjo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e23.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eKaranganom\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e8.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eJuwiring\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e3.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eTrucuk\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e17.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003ePrambanan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e23.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e354\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e84.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e15.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge (years)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e20\u0026ndash;29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e30\u0026ndash;39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e1.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e40\u0026ndash;49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e17.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e50\u0026ndash;59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e162\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e38.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e60\u0026ndash;69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e127\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e30.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e70 +\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e11.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eFamily numbers (people)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e1\u0026ndash;3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e242\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e57.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e4\u0026ndash;6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e173\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e41.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e7\u0026ndash;9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e1.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducational Background\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eBachelor\u0026apos;s degree or equivalent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e5.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eDiploma or equivalent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e1.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eHigh school or equivalent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e240\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e57.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eJunior high school or equivalent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e17.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eElementary school or equivalent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e18.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eNo formal education\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.48%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eAnother job\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eHas another job\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e261\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e62.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eDoes not have another job\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e159\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e37.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eFarming experiences (years)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e1\u0026ndash;9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e11%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e10\u0026ndash;19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e134\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e31.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e20\u0026ndash;29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e108\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e25.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e30\u0026ndash;39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e17.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e40\u0026ndash;49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e9.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e50+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e4.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eLand area (meter squares)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;1000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e1.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e1000\u0026ndash;2999\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e168\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e40%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e3000\u0026ndash;5999\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e135\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e32.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e6000\u0026ndash;7999\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e12.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e8000\u0026ndash;10000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e9.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;10000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e4.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eLand ownership status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eOwned\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e273\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e65%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eRented\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e16%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eProfit-sharing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e19%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eFarmer\u0026apos;s income each planting season\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;10,000,000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e117\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e27.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e10,000,000\u0026ndash;19,999,999\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e148\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e35.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e20,000,000\u0026ndash;29,999,999\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e22.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e30,000,000\u0026ndash;39,999,999\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e8.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e40,000,000\u0026ndash;50,000,000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e2.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;50,000,000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e3.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eA substantial proportion of farmers in Klaten Regency engage in off-farm employment. Approximately 62.1% of respondents report having secondary occupations, including trading, construction work, village administration, and civil service, while only 37.9% depend solely on agriculture as their primary source of income. This pattern reflects the limited economic capacity of small-scale rice farming to fully support household needs. Most farmers cultivate relatively small landholdings, typically between 0.1 and 0.5 hectares, generating gross revenues of around Rp 10\u0026ndash;20\u0026nbsp;million per planting season (approximately four months). However, this amount does not represent net income, as production costs average about Rp 2\u0026nbsp;million per 0.1 hectare. Although seasonal earnings may exceed the regional minimum wage of Rp 2,389,873 (Klaten Department of Industry and Manpower, 2026), household expenditures and farming costs remain substantial. Income constraints are further intensified for farmers who rent land or operate under sharecropping arrangements, which reduce their final returns.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\n \u003ch2\u003e4.2. Measurement model assessment\u003c/h2\u003e\n \u003cdiv id=\"Sec14\" class=\"Section3\"\u003e\n \u003ch2\u003e4.2.1. Measurement model evaluation\u003c/h2\u003e\n \u003cp\u003eIn this study, construct consistency was evaluated using Average Variance Extracted (AVE), Composite Reliability (CR), and Cronbach\u0026rsquo;s alpha. The results indicate that all constructs meet the recommended thresholds, with AVE values\u0026thinsp;\u0026ge;\u0026thinsp;0.50, CR\u0026thinsp;\u0026ge;\u0026thinsp;0.70, and Cronbach\u0026rsquo;s alpha\u0026thinsp;\u0026ge;\u0026thinsp;0.70, confirming adequate convergent validity and internal reliability (Hair et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Hasan et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2025b\u003c/span\u003e). Indicator performance was further assessed through outer loadings and collinearity statistics (VIF) (Hair et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Although the ideal loading threshold is above 0.70 (Kusnandar et al., 2023; Sutrisno et al., \u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), several indicators in this study show loadings between 0.480 and 0.680. Following established guidelines, indicators within the 0.40\u0026ndash;0.70 range were retained because the corresponding constructs continued to satisfy overall reliability and validity criteria (Hair et al.,\u0026nbsp;\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eConstruct validity and reliability\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"7\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eLatent Variable\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eIndicators\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eLoading Factor\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003eVIF\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003eAVE\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003eCR\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003eCronbach Alpha\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eCues To Action (CTA)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eCTA 1: I participate in agricultural extension programs because they encourage me to implement sustainable Rojolele Srinuk rice cultivation practices.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.888\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e3.205\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.713\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\n \u003cp\u003e0.925\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\n \u003cp\u003e0.898\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eCTA 2: Information from extension workers, farmer groups, or social media motivates me to implement environmentally friendly practices in my farming.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.888\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e3.676\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eCTA 3: Examples of sustainable practices from other farmers motivate me to emulate them.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.895\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e3.223\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eCTA 4: Government support (subsidies, regulations, and assistance with production facilities) encourages me to cultivate Rojolele Srinuk rice sustainably.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.816\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e2.283\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eCTA 5: Suggestions or requests from buyers/consumers trigger changes in my practices.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.721\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e1.871\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eEnvironmental Risk (ER)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eER 1: I believe the overuse of pesticides is reducing biodiversity.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.835\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e2.301\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.620\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\n \u003cp\u003e0.907\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\n \u003cp\u003e0.878\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eER 2: I am concerned that climate change is exacerbating the risk of crop failure.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.724\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e2.021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eER 3: I believe environmental sustainability is crucial to the future of agriculture.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.786\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e2.046\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eER 4: I believe soil erosion and land degradation are serious threats to farmers.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.778\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e2.259\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eER 5: I believe organic practices can reduce the risk of environmental damage.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.823\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e2.236\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eER 6: I believe the sustainability of farming depends on environmental sustainability.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.774\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e2.035\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eFarmer Behavior (FB)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eFB 1: I have reduced my use of chemical fertilizers compared to the previous year.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.783\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e2.158\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.559\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\n \u003cp\u003e0.896\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\n \u003cp\u003e0.865\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eFB 2: I regularly apply organic fertilizers or manure to some of my land.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.831\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e2.423\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eFB 3: I implement integrated pest management (a balance between biological/botanical and chemical pesticides) depending on the pests that attack me.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.791\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e2.217\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eFB 4: I implement more efficient water management practices on my land.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.481\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e1.574\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eFB 5: I have participated in training/mentoring on sustainable agricultural techniques in the past 12 months.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.772\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e1.982\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eFB 6: I market my crops with an emphasis on quality/sustainability (e.g., local/premium labels).\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.665\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e1.849\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eFB 7: I actively engage other farmers and share my experiences to improve sustainable practices.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.844\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e2.865\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eFarmer Sustainability Knowledge (FSK)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eFSK 1: I understand the basic concepts of sustainable agriculture.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.658\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e1.452\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.535\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\n \u003cp\u003e0.888\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\n \u003cp\u003e0.850\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eFSK 2: I understand the effects of chemical fertilizer use on soil fertility.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.710\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e2.257\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eFSK 3: I understand the benefits of organic fertilizer and how to make it.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.811\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e2.743\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eFSK 4: I know integrated pest management (IPM) techniques suitable for rice.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.772\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e2.070\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eFSK 5: I know harvesting and post-harvest practices that maintain rice quality.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.743\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e1.940\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eFSK 6: I understand how to access markets or certification for sustainable products.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.545\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e1.310\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eFSK 7: I am aware of the relationship between sustainable practices and long-term health/economy.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.838\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e2.365\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eHealth Risk (HR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eHR 1: I am concerned about the impact of pesticide use on my health.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.898\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e3.498\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.670\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\n \u003cp\u003e0.924\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\n \u003cp\u003e0.900\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eHR 2: I believe the use of chemicals in agriculture can cause disease.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.806\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e2.202\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eHR 3: I feel the quality of the air and water around the rice fields affects my family\u0026apos;s health\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.805\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e2.387\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eHR 4: I feel their quality of life is declining due to exposure to hazardous materials.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.693\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e1.843\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eHR 5: I feel it is important to reduce my exposure to chemicals for my health.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.869\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e3.238\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eHR 6: I believe that protecting the health of farmers is as important as protecting the harvest.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.823\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e2.734\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003ePerceived Barriers (PBAR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003ePBAR 1: Additional costs (e.g., using organic fertilizers) make me hesitate to fully implement sustainable farming.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0,810\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e1.316\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.503\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\n \u003cp\u003e0.797\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\n \u003cp\u003e0.722\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003ePBAR 2: Labor shortages make implementing sustainable practices difficult.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0,839\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e1.379\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003ePBAR 3: Changing farming habits feels difficult and reduces my desire to change.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.597\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e1.944\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003ePBAR 4: Short-term economic risks hold me back from implementing sustainable practices.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.545\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e1.869\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003ePerceived Benefit (PB)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003ePB 1: I believe that implementing sustainable agriculture improves the quality of Rojolele Srinuk rice.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.811\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e2.267\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.615\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\n \u003cp\u003e0.905\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\n \u003cp\u003e0.875\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003ePB 2: Environmentally friendly practices can reduce production costs in the long term.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.771\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e2.065\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003ePB 3: I believe sustainable practices can increase income through the premium specialty rice market.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.787\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e2.056\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003ePB 4: I believe that sustainable cultivation maintains the health of the soil, water, and the surrounding environment.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.725\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e1.672\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003ePB 5: I believe that adopting conservation techniques increases production resilience to climate change.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.831\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e2.276\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003ePB 6: I believe that sustainability helps maintain Rojolele Srinuk production for future generations.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.776\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e2.033\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003ePerceived Severity (PSVR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003ePSVR 1: I believe that excessive pesticide use will negatively impact my health and that of my family.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.819\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e2.074\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.596\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\n \u003cp\u003e0.852\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\n \u003cp\u003e0.766\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003ePSVR 2: I believe that soil degradation due to excessive chemical fertilization will reduce future farming productivity.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.900\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e2.532\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003ePSVR 3: I believe that if sustainable practices are not implemented, the sustainability of Rojolele Srinuk rice will be threatened.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.580\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e1.217\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003ePSVR 4: I believe that sustainable farming is crucial to ensuring the well-being of future generations.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.753\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e1.476\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003ePerceived Susceptibility (PSCP)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003ePSCP 1: I feel the sustainability of my farming business depends on implementing sustainable farming practices.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.636\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e1.472\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.522\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\n \u003cp\u003e0.843\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\n \u003cp\u003e0.766\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003ePSCP 2: I believe the market is demanding more environmentally friendly products.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.652\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e1.528\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003ePSCP 3: I am concerned that my farming business is threatened by climate change.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.761\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e1.855\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003ePSCP 4: I believe smallholder farmers are more vulnerable to the risk of crop failure.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.690\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e1.985\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003ePSCP 5: I believe the risk of losses will increase if farming practices remain unchanged.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.850\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e2.087\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eSelf Efficacy (SE)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eSE 1: I am confident in my ability to implement sustainable Rojolele Srinuk rice cultivation techniques.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.834\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e2.464\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.662\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\n \u003cp\u003e0.907\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\n \u003cp\u003e0.872\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eSE 2: I believe that training and mentoring will help my farming business become independent.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.803\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e1.834\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eSE 3: I feel capable of overcoming technical challenges in implementing sustainable farming.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.854\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e2.570\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eSE 4: I am confident in my ability to maintain the sustainability of my farming business and ensure its profitability.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.736\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e1.734\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eSE 5: I am confident in my ability to overcome community/peer resistance in implementing new practices.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.834\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e2.183\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eSocio Ethical Risk (SR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eSR 1: I believe environmentally friendly practices are more in line with society\u0026apos;s moral values.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.836\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e2.043\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.604\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\n \u003cp\u003e0.882\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\n \u003cp\u003e0.830\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eSR 2: I feel social pressure is pushing me to farm more sustainably.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.553\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e1.208\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eSR 3: I believe consumers prefer environmentally friendly products.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.823\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e1.947\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eSR 4: I believe ethical farming is important for maintaining social relationships among farmers.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.757\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e1.699\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eSR 5: I believe agricultural sustainability is a moral obligation for farmers.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.874\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e2.479\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eCollinearity was assessed using the Variance Inflation Factor (VIF). In PLS-SEM, a VIF value below 5 indicates the absence of serious multicollinearity and is the most commonly accepted threshold (Hair et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). A stricter criterion of VIF\u0026thinsp;\u0026lt;\u0026thinsp;3.3 suggests very low collinearity and is often applied in models that require higher sensitivity to multicollinearity issues. In contrast, VIF values above 5 indicate potential collinearity concerns, while values exceeding 10 signal serious multicollinearity problems that require indicator removal or model revision. In this study, most indicators exhibit VIF values below 3.3, and only two indicators show VIF values slightly above 3.3 but still below 5. These results indicate that collinearity is well within acceptable limits and that the structural model can be considered statistically sound.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec15\" class=\"Section3\"\u003e\n \u003ch2\u003e4.2.2. Structural model evaluation\u003c/h2\u003e\n \u003cp\u003eThe results of the inner model evaluation, presented in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, show the explanatory power of the structural model through R\u0026sup2; values. In PLS-SEM, R\u0026sup2; values are generally interpreted as follows: above 0.67 indicates a strong model, above 0.33 indicates a moderate model, and above 0.19 indicates a weak model (Hair et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Solimun et al., 2022). The R\u0026sup2; statistic reflects the extent to which endogenous constructs are explained by their corresponding exogenous predictors, with higher values indicating greater predictive capability (Hassan et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). In this study, strong R\u0026sup2; values are observed for farmer behaviour, perceived susceptibility, and perceived severity. Moderate explanatory power is found for cues to action, perceived benefits, and self-efficacy. In contrast, perceived barriers exhibit a relatively weak R\u0026sup2; value, indicating that this construct is explained to a lesser extent by the predictors included in the model.\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\n \u003ch2\u003e4.3. Relationship between variables\u003c/h2\u003e\n \u003cp\u003eThis study examines the structural relationships among multidimensional risk perception, HBM constructs, and farmers\u0026rsquo; sustainable behaviour. The results indicate that perceived health risk, perceived environmental risk, and perceived socio-ethical risk are significantly associated with several HBM components, which in turn influence farmer behaviour. In addition, perceived benefits affect farmer behaviour with sustainability knowledge acting as a moderating variable.\u003c/p\u003e\n \u003cp\u003eUsing a 5% significance level, the analysis shows that perceived susceptibility, perceived benefits, perceived barriers, self-efficacy, and cues to action have significant relationships with farmer behaviour in supporting the sustainability of Rojolele Srinuk rice farming (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Perceived barriers exhibit a negative relationship, while the others show positive effects. In contrast, perceived severity does not have a significant direct relationship with farmer behaviour (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e\n \u003cp\u003eRegarding the antecedents of HBM constructs, perceived health risk, perceived environmental risk, and perceived socio-ethical risk each have significant positive relationships with perceived susceptibility and perceived severity (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Perceived health risk and perceived socio-ethical risk significantly influence perceived benefits, whereas perceived environmental risk does not. For perceived barriers, only socio-ethical risk shows a significant relationship, while health and environmental risks do not. All three dimensions of risk perception demonstrate positive and significant relationships with self-efficacy and cues to action (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eRelationship between variables\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"11\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\n \u003cp\u003eRelationship between the variables\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003ecoefficient\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003et value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003esig\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c8\"\u003e\n \u003cp\u003eR\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\n \u003cp\u003eQ\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c11\"\u003e\n \u003cp\u003edecision\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003ePerceived health risk\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\" style=\"width: 2.0332%;\"\u003e\n \u003cp\u003e\u0026rarr;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\" style=\"width: 17.5601%;\"\u003e\n \u003cp\u003ePerceived susceptibility\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\n \u003cp\u003e0.445\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e6.960\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\n \u003cp\u003e0.695\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003e0.905\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c11\"\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003ePerceived environmental risk\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\" style=\"width: 2.0332%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\" style=\"width: 17.5601%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\n \u003cp\u003e0.200\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e2.457\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c11\"\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003ePerceived socio ethical risk\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\" style=\"width: 2.0332%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\" style=\"width: 17.5601%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\n \u003cp\u003e0.251\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e4.366\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c11\"\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003ePerceived health risk\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\" style=\"width: 2.0332%;\"\u003e\n \u003cp\u003e\u0026rarr;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\" style=\"width: 17.5601%;\"\u003e\n \u003cp\u003ePerceived severity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\n \u003cp\u003e0.419\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e8.976\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\n \u003cp\u003e0.720\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003e0.921\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c11\"\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003ePerceived environmental risk\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\" style=\"width: 2.0332%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\" style=\"width: 17.5601%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\n \u003cp\u003e0.331\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e6.183\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c11\"\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003ePerceived socio ethical risk\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\" style=\"width: 2.0332%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\" style=\"width: 17.5601%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\n \u003cp\u003e0.157\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e3.060\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c11\"\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003ePerceived health risk\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\" style=\"width: 2.0332%;\"\u003e\n \u003cp\u003e\u0026rarr;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\" style=\"width: 17.5601%;\"\u003e\n \u003cp\u003ePerceived benefits\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\n \u003cp\u003e0.200\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e2.533\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\n \u003cp\u003e0.412\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003e0.649\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c11\"\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003ePerceived environmental risk\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\" style=\"width: 2.0332%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\" style=\"width: 17.5601%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\n \u003cp\u003e0.130\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e1.320\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e0.187\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c11\"\u003e\n \u003cp\u003eNot Supported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003ePerceived socio ethical risk\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\" style=\"width: 2.0332%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\" style=\"width: 17.5601%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\n \u003cp\u003e0.361\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e4.207\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c11\"\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003ePerceived health risk\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\" style=\"width: 2.0332%;\"\u003e\n \u003cp\u003e\u0026rarr;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\" style=\"width: 17.5601%;\"\u003e\n \u003cp\u003ePerceived barriers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\n \u003cp\u003e-0.126\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e1.549\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e0.121\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\n \u003cp\u003e0.308\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003e0.515\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c11\"\u003e\n \u003cp\u003eNot Supported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003ePerceived environmental risk\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\" style=\"width: 2.0332%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\" style=\"width: 17.5601%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\n \u003cp\u003e0.178\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e1.812\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e0.070\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c11\"\u003e\n \u003cp\u003eNot Supported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003ePerceived socio ethical risk\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\" style=\"width: 2.0332%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\" style=\"width: 17.5601%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\n \u003cp\u003e-0.597\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e8.057\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c11\"\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003ePerceived health risk\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\" style=\"width: 2.0332%;\"\u003e\n \u003cp\u003e\u0026rarr;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\" style=\"width: 17.5601%;\"\u003e\n \u003cp\u003ePerceived self - efficacy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\n \u003cp\u003e0.146\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e2.132\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e0.033\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\n \u003cp\u003e0.496\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003e0.742\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c11\"\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003ePerceived environmental risk\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\" style=\"width: 2.0332%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\" style=\"width: 17.5601%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\n \u003cp\u003e0.265\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e3.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c11\"\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003ePerceived socio ethical risk\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\" style=\"width: 2.0332%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\" style=\"width: 17.5601%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\n \u003cp\u003e0.345\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e4.406\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c11\"\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003ePerceived health risk\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\" style=\"width: 2.0332%;\"\u003e\n \u003cp\u003e\u0026rarr;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\" style=\"width: 17.5601%;\"\u003e\n \u003cp\u003eCues to action\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\n \u003cp\u003e0.257\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e3.538\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\n \u003cp\u003e0.509\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003e0.755\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c11\"\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003ePerceived environmental risk\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\" style=\"width: 2.0332%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\" style=\"width: 17.5601%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\n \u003cp\u003e0.263\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e5.433\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c11\"\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003ePerceived socio ethical risk\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\" style=\"width: 2.0332%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\" style=\"width: 17.5601%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\n \u003cp\u003e0.406\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e5.978\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c11\"\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003ePerceived susceptibility\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\" style=\"width: 2.0332%;\"\u003e\n \u003cp\u003e\u0026rarr;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\" style=\"width: 17.5601%;\"\u003e\n \u003cp\u003eFarmer behavior\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\n \u003cp\u003e0.154\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e3.438\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\n \u003cp\u003e0.742\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003e0.929\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c11\"\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003ePerceived severity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\" style=\"width: 2.0332%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\" style=\"width: 17.5601%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\n \u003cp\u003e0.031\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e0.604\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e0.546\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c11\"\u003e\n \u003cp\u003eNot Supported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003ePerceived benefits\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\" style=\"width: 2.0332%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\" style=\"width: 17.5601%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\n \u003cp\u003e0.120\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e2.341\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e0.019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c11\"\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003ePerceived barriers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\" style=\"width: 2.0332%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\" style=\"width: 17.5601%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\n \u003cp\u003e-0.092\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e2.677\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c11\"\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003ePerceived self - efficacy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\" style=\"width: 2.0332%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\" style=\"width: 17.5601%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\n \u003cp\u003e0.110\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e2.229\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e0.026\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c11\"\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eCues to action\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\" style=\"width: 2.0332%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\" style=\"width: 17.5601%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\n \u003cp\u003e0.263\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e5.433\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c11\"\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eFarmer sustainability knowledge x Perceived susceptibility\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\" style=\"width: 2.0332%;\"\u003e\n \u003cp\u003e\u0026rarr;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\" style=\"width: 17.5601%;\"\u003e\n \u003cp\u003eFarmer behavior\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\n \u003cp\u003e-0.036\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e0.776\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e0.438\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\n \u003cp\u003e0.742\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003e0.929\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c11\"\u003e\n \u003cp\u003eNot supported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eFarmer sustainability knowledge x Perceived severity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\" style=\"width: 2.0332%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\" style=\"width: 17.5601%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\n \u003cp\u003e0.018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e0.332\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e0.740\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c11\"\u003e\n \u003cp\u003eNot supported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eFarmer sustainability knowledge x Perceived benefits\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\" style=\"width: 2.0332%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\" style=\"width: 17.5601%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\n \u003cp\u003e0.067\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e1.655\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e0.098\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c11\"\u003e\n \u003cp\u003eSupported in alpha 0.100\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eFarmer sustainability knowledge x\u003c/p\u003e\n \u003cp\u003ePerceived barriers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\" style=\"width: 2.0332%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\" style=\"width: 17.5601%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\n \u003cp\u003e0.027\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e0.793\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e0.428\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c11\"\u003e\n \u003cp\u003eNot supported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eFarmer sustainability knowledge x Perceived self \u0026ndash; efficacy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\" style=\"width: 2.0332%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\" style=\"width: 17.5601%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\n \u003cp\u003e-0.046\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e0.317\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c11\"\u003e\n \u003cp\u003eNot supported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eFarmer sustainability knowledges x Cues to action\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\" style=\"width: 2.0332%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\" style=\"width: 17.5601%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\n \u003cp\u003e-0.038\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e0.923\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e0.356\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c11\"\u003e\n \u003cp\u003eNot supported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eThis study also identifies a moderating effect of farmers\u0026rsquo; sustainability knowledge on sustainable behaviour. The results indicate that sustainability knowledge strengthens the positive relationship between perceived benefits and farmer behaviour, with significance at the 10% level (p\u0026thinsp;=\u0026thinsp;0.098\u0026thinsp;\u0026lt;\u0026thinsp;0.10). This finding suggests that farmers with higher sustainability knowledge are more likely to translate perceived benefits into concrete sustainable farming actions.\u003c/p\u003e\n \u003cp\u003eThe coefficient of determination (R\u0026sup2;) values indicate the explanatory power of the structural model for each endogenous construct. Strong R\u0026sup2; values are observed for perceived susceptibility (0.695), perceived severity (0.720), and farmer behaviour (0.742), suggesting that these variables are well explained by their respective predictors. Moderate explanatory power is found for perceived benefits (0.412), self-efficacy (0.496), and cues to action (0.509). In contrast, perceived barriers show a relatively weak R\u0026sup2; value (0.308). The R\u0026sup2; statistic reflects the extent to which endogenous variables can be explained by exogenous variables within the research model, with higher values indicating stronger predictive capacity (Thi Nguyen \u0026amp; Dang, \u003cspan citationid=\"CR99\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Beside that, the model also validated with Q\u003csup\u003e2\u003c/sup\u003e value for evaluate the model predictive ability. Table \u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e show that Q\u003csup\u003e2\u003c/sup\u003e value are strong predictive relevance with score more than 0.00 (Hair et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e"},{"header":"5. Discussions","content":"\u003cp\u003eThe integration of the Health Belief Model (HBM) with multidimensional risk perception and sustainability knowledge provides a comprehensive explanation of farmers\u0026rsquo; behaviour in sustaining Rojolele Srinuk rice cultivation in Klaten Regency. The findings indicate that behavioural change emerges from an interconnected psychosocial process in which perceived risks shape core HBM constructs, which subsequently influence behavioural outcomes. This confirms the relevance of HBM in agricultural sustainability contexts characterised by uncertainty, health concerns, and social responsibility. Health, environmental, and socio-ethical risk perceptions consistently function as antecedents that influence farmers\u0026rsquo; cognitive and motivational evaluations. Their positive association with perceived susceptibility suggests that farmers internalise both personal and collective consequences of conventional practices, including health exposure, land degradation, and moral responsibility toward consumers and the community (Abrams et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Mathew \u0026amp; Tholath, \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Omi et al., \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Tenchini et al., \u003cspan citationid=\"CR98\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Rather than acting independently, these risk dimensions collectively construct a sense of vulnerability that forms the psychological basis for behavioural assessment.\u003c/p\u003e \u003cp\u003eRisk perception also extends beyond vulnerability and influences perceived severity, benefits, barriers, self-efficacy, and cues to action, although with varying intensity. The strong relationship between risk perception and perceived severity indicates that farmers recognise the seriousness of declining land productivity, household health risks, and social consequences of unsustainable farming (Li et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Nguena \u0026amp; Bindoumou, \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Simarmata et al., \u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Sodhi et al., \u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). However, the absence of a direct effect of perceived severity on behaviour suggests that recognising seriousness alone does not guarantee action. Long-term or familiar risks may become normalised within routine agricultural practice, reducing their motivational force (Bagambilana \u0026amp; Rugumamu, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Kyire et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe analysis of perceived benefits and barriers reveals a more pragmatic decision-making pattern. Perceived benefits are significantly shaped by health and socio-ethical risks, indicating that farmers respond more strongly to tangible and socially meaningful outcomes, such as protecting family health and maintaining community reputation (Dey et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Negi et al., \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Pratama et al., \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). In contrast, environmental risk perception does not significantly enhance perceived benefits, suggesting a cognitive separation between environmental awareness and personal gain. Environmental risks may be viewed as collective and long-term, whereas benefits are evaluated through immediate and economically salient considerations (Byfuglien et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). This asymmetry explains why environmental awareness alone often fails to drive benefit-based behavioural change without concrete incentives.\u003c/p\u003e \u003cp\u003ePerceived barriers further illustrate the differentiated role of risk dimensions. Health and environmental risk perceptions do not significantly reduce perceived barriers, indicating that awareness of risk is insufficient to overcome structural constraints such as limited capital, labour requirements, or access to inputs. In contrast, socio-ethical risk perception significantly reduces perceived barriers, highlighting the influence of social norms and moral responsibility in lowering psychological resistance to change (Karimi \u0026amp; Ataei, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Collective expectations appear more effective than individual risk awareness in facilitating behavioural adjustment.\u003c/p\u003e \u003cp\u003eSelf-efficacy and cues to action emerge as critical mechanisms translating awareness into action. The positive effects of all three risk dimensions on self-efficacy suggest that risk awareness, particularly when framed within social and ethical contexts, strengthens farmers\u0026rsquo; confidence in implementing sustainable practices ((Truelove et al., \u003cspan citationid=\"CR101\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Yanakittkul \u0026amp; Aungvaravong, \u003cspan citationid=\"CR107\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Similarly, risk perceptions stimulate cues to action through extension programs, policy initiatives, peer influence, and direct farming experiences (Hochman et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Nelson et al., \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). These findings indicate that risk perception acts primarily as a catalyst activating multiple HBM pathways rather than directly driving behaviour.\u003c/p\u003e \u003cp\u003eAt the behavioural level, perceived susceptibility, perceived benefits, self-efficacy, perceived barriers, and cues to action jointly explain farmers\u0026rsquo; adoption of sustainable practices. The positive effect of perceived susceptibility confirms that farmers who feel personally vulnerable are more inclined to act (Li et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). The strong influence of perceived benefits and self-efficacy, together with the negative effect of perceived barriers, indicates that decisions are grounded in a rational evaluation of expected gains, implementation feasibility, and personal capability (Methamontri et al., \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Sharna et al., \u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Cues to action reinforce the importance of institutional support and social engagement in converting intention into practice.\u003c/p\u003e \u003cp\u003eThe moderating role of sustainability knowledge adds important nuance to these relationships. Knowledge does not uniformly strengthen all behavioural pathways. The non-significant or negative moderation of vulnerability suggests that more informed farmers rely less on emotional risk perception and more on deliberate planning (Ahmad et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Khai et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Conversely, the positive moderation of perceived benefits (significant at the 10% level) indicates that knowledge enhances farmers\u0026rsquo; ability to translate recognised advantages into concrete action. The absence of significant moderation for barriers, self-efficacy, and cues to action suggests that knowledge alone cannot eliminate structural constraints or substitute for institutional support (Krisnawati et al., 2025; Son et al., \u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOverall, this study advances sustainability behaviour research by demonstrating that multidimensional risk perception operates as an integrated psychosocial catalyst within the HBM framework, while sustainability knowledge functions as a selective enhancer of benefit-oriented reasoning. These findings challenge the assumption that increasing knowledge alone will automatically promote sustainable behaviour. Instead, effective sustainability strategies must align knowledge dissemination with tangible benefits, supportive social norms, and enabling institutional structures.\u003c/p\u003e"},{"header":"6. Conclusion","content":"\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e6.1. General conclusion and implication\u003c/h2\u003e \u003cp\u003eThis study demonstrates that sustainable farming behaviour among Rojolele Srinuk rice farmers is primarily shaped by perceived susceptibility, perceived benefits, self-efficacy, and cues to action, whereas perceived severity plays a limited direct role due to the normalization of risk in routine agricultural practice. By integrating multidimensional risk perception and sustainability knowledge into the HBM framework, this research extends HBM-based sustainability studies beyond simple direct-effect explanations. Sustainability knowledge does not uniformly strengthen all behavioural pathways; instead, it selectively reinforces benefit-oriented reasoning, refining the theoretical application of HBM in agricultural contexts. These findings contribute to broader development goals, particularly SDG 2 (Zero Hunger) through sustainable food production, SDG 3 (Good Health and Well-being) through reduced exposure to chemical risks, and SDG 12 (Responsible Consumption and Production) through environmentally responsible farming. In the Indonesian context, the results provide empirical support for policies aimed at building a resilient and sustainability-oriented agricultural transformation.\u003c/p\u003e \u003cp\u003ePolicy implications emerge clearly from the identified behavioural mechanisms. Extension strategies should move beyond fear-based risk communication and emphasise tangible economic, health, and social benefits of sustainable practices. Strengthening farmers\u0026rsquo; self-efficacy through participatory training, demonstration plots, and peer learning is essential to translate awareness into action. Social and ethical norms should be leveraged to reduce perceived barriers by reinforcing collective responsibility and local identity. Finally, supportive market and institutional mechanisms (including improved market access, price incentives, and targeted input support) are necessary to ensure that perceived benefits outweigh structural constraints and enable the long-term sustainability of local rice farming systems.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003e6.2. Limitations and further research\u003c/h2\u003e \u003cp\u003eThis study has several limitations that should be acknowledged. First, the cross-sectional design limits the ability to capture dynamic changes in farmers\u0026rsquo; perceptions and behaviour over time, particularly given that sustainability adoption is gradual and iterative. Second, the analysis relies on self-reported survey data, which may be affected by social desirability and recall bias, especially in contexts where sustainable agriculture is normatively promoted. Third, the geographic focus on Rojolele Srinuk farmers in Klaten Regency limits the generalisability of the findings to other agroecological and institutional settings. Finally, although sustainability knowledge is modelled as a moderating variable, broader structural factors (such as market incentives, policy enforcement, and institutional capacity) are not explicitly incorporated into the interaction framework.\u003c/p\u003e \u003cp\u003eFuture research should adopt longitudinal or quasi-experimental designs to better examine how psychosocial factors and sustainability knowledge evolve over time and to strengthen causal inference. The HBM framework could be expanded by incorporating institutional support, policy incentives, and market access as moderating or contextual variables to assess how structural conditions shape behavioural responses. Comparative studies across different regions, rice varieties, or farming systems would help test the robustness of the selective moderation effect identified in this study. Additionally, integrating behavioural SEM models with biophysical or sustainability performance indicators such as soil health metrics, input efficiency, or multidimensional sustainability indices would strengthen the link between farmer behaviour and measurable environmental outcomes.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe author acknowledges to the research funding specifically Indonesia Ministry of Higher Education, Science, and Technology with PMDSU Postgraduate Research Scheme under contract number 105/C3/DT.05.00/PL/2025 and National Taiwan University for supporting in publication funding.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was funded by\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eIndonesia Ministry of Higher Education, Science, and Technology with PMDSU Postgraduate Research Scheme under contract number 105/C3/DT.05.00/PL/2025\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets produced and/or analysed in the current work are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study has obtained ethical approval from the Research Ethics Committee of the Faculty of Medicine, Universitas Sebelas Maret (Approval Number: 39/UN27.06.11/KEP/EC/2026). All research procedures were conducted in accordance with the ethical guidelines and regulations of Universitas Sebelas Maret, Indonesia.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eResearch participants, particularly male and female farmers aged above 20 years, were provided with an explanation by the researcher through informed consent, which was approved by the research ethics committee, and participants consented to participate in this study voluntarily and without coercion.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe author declares that there is no conflict of interest, either financial or related, with the reviewer or publisher in the publication of this article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical Trial\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNugroho Hasan: Writing original draft, methodology, conceptualization, and data analysis. Mohamad Harisudin: Writing \u0026ndash; review, editing, and supervision. Kusnandar: Review and supervision. Putriesti Mandasari: Writing \u0026ndash; review, editing, supervision, investigation. Li \u0026ndash; Fen Lei: Review and supervision\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAbdollahzadeh G, Sharif M. Journal of the Saudi Society of Agricultural Sciences Predicting farmers \u0026rsquo; intention to use PPE for prevent pesticide adverse effects: An examination of the Health Belief Model (HBM). J Saudi Soc Agricultural Sci. 2021;20(1):40\u0026ndash;7. ttps://doi.org/10.1016/j.jssas.2020.11.001.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAbrams AL, Carden K, Teta C, W\u0026aring;gs\u0026aelig;ther K. Water, sanitation, and hygiene vulnerability among rural areas and small towns in south africa: Exploring the role of climate change, marginalization, and inequality. 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Biol Conserv. 2024;292(96). ttps://doi.org/10.1016/j.biocon.2024.110544.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZoundji GC, Magnon YZ, Adjaka FN. Agricultural Insurance Adoption in the Context of Climate Change: Influencing Factors in Benin (West Africa). Agricultural Sci Digest. 2024;44(5):823\u0026ndash;9. ttps://doi.org/10.18805/ag.DF-622.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"discover-sustainability","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"disu","sideBox":"Learn more about [Discover Sustainability](https://www.springer.com/43621)","snPcode":"","submissionUrl":"","title":"Discover Sustainability","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Sustainable rice farming, Health Belief Model, Psychosocial determinants, Risk perception, Sustainability knowledge, Farmer behaviour","lastPublishedDoi":"10.21203/rs.3.rs-9024162/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9024162/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eMoving from risk perception to concrete farm action remains a central challenge in sustainable agriculture. Farmers may be aware of environmental and health risks, but such awareness does not automatically translate into sustainable practices without supportive beliefs and enabling conditions. To explain this gap, this study applies an extended Health Belief Model (HBM) to analyse sustainable rice farming practices in Indonesia, focusing on Rojolele Srinuk cultivation in Klaten Regency, Central Java. The framework includes perceived susceptibility, severity, benefits, barriers, self-efficacy, and cues to action. It is extended with multidimensional risk perception health, environmental, and socio-ethical risks. Sustainability knowledge is added as a moderating variable to capture cognitive differences among farmers. Data from 420 farmers were collected through stratified random sampling and analysed using Partial Least Squares\u0026ndash;Structural Equation Modeling (PLS-SEM). The results show that perceived susceptibility, perceived benefits, self-efficacy, and cues to action significantly encourage sustainable behaviour. Perceived barriers reduce it. Perceived severity has no significant effect, suggesting that long-term risks may be normalized in routine practice. Multidimensional risk perception strengthens self-efficacy and cues to action. Sustainability knowledge shows a limited but meaningful moderating role. These findings provide behavioural insight for designing context-sensitive sustainability policies in developing-country agriculture.\u003c/p\u003e","manuscriptTitle":"Understanding psychosocial determinants of sustainable farming behaviour among local rice farmers in Indonesia","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-10 17:19:25","doi":"10.21203/rs.3.rs-9024162/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-04-28T06:07:30+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-27T16:49:41+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-25T23:36:04+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"196184940299607200130179291703856014039","date":"2026-04-23T02:15:01+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"5048531273452545887033413689483653860","date":"2026-04-22T12:17:16+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"34943119111271650235150567965050366232","date":"2026-04-20T23:57:12+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-14T09:58:54+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-12T02:45:08+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"95137872190766215926286179918903422062","date":"2026-04-06T21:33:00+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"934176639618550205951582949407874680","date":"2026-04-06T04:28:39+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-06T04:13:41+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-21T09:25:06+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-03-13T06:40:50+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-10T15:31:40+00:00","index":"","fulltext":""},{"type":"submitted","content":"Discover Sustainability","date":"2026-03-10T11:20:16+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"discover-sustainability","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"disu","sideBox":"Learn more about [Discover Sustainability](https://www.springer.com/43621)","snPcode":"","submissionUrl":"","title":"Discover Sustainability","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"1f17546e-2b72-48be-aeeb-8947427ae4a9","owner":[],"postedDate":"April 10th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-11T20:08:32+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-10 17:19:25","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9024162","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9024162","identity":"rs-9024162","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}