Understanding Agricultural Producers’ Water Conservation Behavior Through Extended Theory of Planned Behavior

Understanding Agricultural Producers’ Water Conservation Behavior Through Extended Theory of Planned Behavior | 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 Agricultural Producers’ Water Conservation Behavior Through Extended Theory of Planned Behavior Ayşen EDİRNELİGİL, Hasan Gökhan Doğan, Ali GANİYUSUFOĞLU, Zeki BAYRAMOĞLU, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9434855/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract In the face of increasing water stress in agricultural production, understanding farmers’ decision process regarding water conservation has become increasingly critical. There is a lack of evidence regarding water conservation behaviors of farmers in Türkiye. Consequently, this study focuses on Konya which there a highly vulnerable agricultural center. Data was collected via survey. The research aims to explain water conservation behaviors of farmers by utilizing the Extended TPB framework by incorporating personal norms to the model. Partial Least Squares Structural Equation Modeling (PLS-SEM) is employed to quantitatively analyze. Accordingly, it was concluded that personal norms have a direct effect. Water scarcity sustainable agriculture behavioral intentions personal norms Figures Figure 1 Introduction Water scarcity and water security have become increasingly critical issues on a global scale in the 21st century. The United Nations and international platforms emphasize that the water crisis is often a ‘governance crises and that effective water governance is an urgent priority. Water governance refers to a framework that encompasses all political, social, economic and administrative systems related to the development and management of water resources (GWP 2003). In other words, decisions on how water is managed, distributed and used are shaped not only by technical considerations but also by political actors, institutions, social values and cultural norms. Indeed, environmental sociologists argue that the natural, social, economic, and cultural dimensions of water issues must be addressed together in an inseparable manner; without a holistic understanding of these dimensions, water management solutions cannot be effective (Ataei et al. 2022). From this perspective, stakeholder participation and transparent decision-making processes are considered vital for ensuring good governance practices (GWP 2003; Leroy et al. 2023). As a country with semi-arid climate regions, Türkiye faces similar governance challenges in relation to water scarcity risks. Water governance in the country has been carried out with a centralized approach for many years; institutional fragmentation and an inadequate legal framework have been obstacles to effective water governance. For example, the fact that a comprehensive ‘Water Law’ has not yet been enacted in Türkiye and the fragmented nature of existing regulations make it difficult to implement the principle of integrated water resources management (Tuna 2012). A recent study has shown that overly centralized water governance reduces effectiveness by creating a lack of coordination, and therefore each country needs to develop governance models that are sensitive to its own conditions (Yousefi et al. 2024). Therefore, the success of water policies in Türkiye depends not only on technical infrastructure investments but also on institutional structures and political will to manage water in an effective, fair and sustainable manner. The agricultural sector is one of the focal points of the water crisis, as it accounts for the largest share of water use both globally and in Türkiye. Globally, approximately 63–70% of total water consumption comes from agricultural irrigation (Ataei et al. 2022). A similar picture is observed in Türkiye: approximately 75% of the country's current water resources are used in agriculture (Ertek and Yılmaz 2014). Low irrigation efficiency and water waste are among the main factors increasing the risk of water scarcity. Changes in rainfall patterns due to climate change, increased frequency of droughts, and excessive use of groundwater are making access to water for agricultural production more difficult. Under these conditions, optimal water management in agriculture is vital to ensure food security and protect water resources. Optimal management encompasses not only technical measures but also farmers' behavior regarding water use (Grafton et al. 2018 ). In Türkiye, the construction and initial operation of large-scale irrigation infrastructures is carried out by the General Directorate of State Hydraulic Works (DSİ). However, with the authorization granted by Law No. 6200, the responsibility for the operation and maintenance of irrigation systems has been transferred over time to village legal entities, municipalities, cooperatives and especially irrigation unions (Shemsari and Bayraktar 2024). Although this “devolution of irrigation management” policy, implemented since the 1990s, aimed to increase local user participation and make the systems function more efficiently, various studies reveal that irrigation unions face serious problems in terms of administrative capacity, technical competence and level of participation (Özerol et al. 2012). Injustice in water distribution, lack of transparency, and accountability problems among farmers are frequently cited (Shunglu et al. 2022 ). This shows that irrigation systems are not only a technical infrastructure issue, but also a governance issue that requires the establishment of social trust and institutional consensus at the local level. The case of Türkiye demonstrates that for water governance reforms to be sustainable, it is imperative to consider the social and institutional context beyond technical interventions. Indeed, the sustainability of water resources depends largely on human behavior (Callejas Moncaleano et al. 2021). Many studies have shown that, in addition to natural factors, human factors are decisive in water scarcity crises (Ataei et al. 2022). Issues such as excessive and unplanned consumption of water resources, pollution, and environmental degradation stem from human behavior. Therefore, in the fight against water scarcity, examining and guiding individuals' water usage behavior is considered a critical element, as much as technical solutions and policy regulations (Ataei et al. 2022; Callejas Moncaleano et al. 2021). As emphasised in the GWP (2003) report; to be successful in water management, it is necessary to understand users' attitudes and habits and motivate them to save water. Particularly in the agricultural sector, it does not seem possible to achieve lasting improvements in water efficiency without changing farmers' traditional irrigation habits. In this context, theoretical models that examine the determinants of individual behavior have gained importance in the water management literature. The Theory of Planned Behavior (TPB) is one of the most widely used theoretical frameworks for explaining individuals' behavioral intentions and behaviors, including in environmental and agricultural areas. Also studies extend this model to include moral and personal norms and some other subjective constructs obtained higher explanatory power in explaining water conservation behavior. The current trend in the literature is toward applying extended TPB models to water governance studies. For example, a recent study examined Chinese farmers' decisions to adopt integrated water management technologies (e.g., innovative practices such as drip irrigation). The results revealed that farmers' adoption of these technologies was largely dependent on their perceptions of the technology. If a farmer believes that a new irrigation method will reduce their workload, be easier to implement, and provide higher economic returns compared to traditional flood irrigation, they are more likely to adopt this technology (Zheng et al. 2023 ). This finding shows that farmers' assessment of perceived benefits and costs plays a key role in their behavior, which confirms the practical importance of the TPB's attitude and control components. Similarly, a qualitative study conducted in Mexico showed that small-scale farmers' adaptation behaviors to water scarcity are guided by their perceptions of the causes and dynamics of water scarcity. This study notes that even in villages connected to the same irrigation network, farmers' measures to address water scarcity vary, with these differences stemming from contextual characteristics such as irrigation techniques, location of water collection points, production systems, and access to groundwater. Therefore, farmers' perspectives on water issues and their institutional-physical conditions shape their actions to conserve water. This finding emphasizes the need for water management policies to be designed in a manner that is sensitive to local conditions rather than generalizing (Leroy et al. 2023). While explaining conservation behavior is beneficial, sometimes explained individual behavior can cause unexpected overall results. Dagnino and Ward ( 2012 ) estimates increased depletions of the water source to occur in the face of increased drip irrigation subsidies in basins where no system of water rights exists. Individual farmers may have differing objectives and constraints that do not align with the optimization goals of water governance authorities and the cumulative effects of decentralized decision-making can produce unintended regional consequences” (el_Fartassi et al. 2025 ). Therefore, in these studies investigating behavioral determinants of water conservation, water governance in the region studied should be considered. The theoretical basis of the current study draws on the literature summarized above. In the context of agricultural water governance in Türkiye, a model was developed and empirically tested within the framework of the Extended Theory of Planned Behavior to understand farmers' water conservation behaviors. In addition to the classic components of TPB, this model also includes some additional elements that have been highlighted in the literature. Thus, our study not only presents an applied behavioral model but also aims to expand and question the theoretical boundaries of the TPB in the context of agricultural water management. In this regard, the study offers a unique contribution to the water governance literature by filling the gap between micro-level behaviors and macro-level governance elements. Indeed, a study on adaptation to the groundwater crisis has shown that TPB can be adapted to explain farmers' intentions to diversify their income through a socio-psychological model developed for this purpose; this model, which incorporates an expanded TPB approach including emotional and instrumental attitudes and self-efficacy beliefs, explaining 55% of the variance in farmers' intentions to adopt alternative livelihood strategies and 36% of the variance in actual income diversification behavior. Similarly, our study uses an expanded TPB to explain water-saving behavior in Turkish agriculture, thereby applying a critical test to the existing theory in a new context. Various studies support the notion that effective water governance is possible not only through infrastructural investments but also through the behavior of water users. This study, which examines farmers' water conservation behavior in agricultural irrigation in Türkiye, responds to a gap in the literature by offering a holistic approach that combines the institutional context with psychological factors. Considering the current debates and theoretical approaches mentioned in the Introduction section, the article will first summarize the current situation regarding agricultural water management and farmer behavior in Türkiye, then present the methods and findings of the research, and finally reveal the theoretical contributions of our expanded TPB model. Thus, the study aims to establish a strong theoretical connection with the water governance literature from institutional, social, and cultural perspectives, while also presenting a perspective that develops and questions existing theories specifically regarding farmer behavior. Theoretical Framework According to the TPB, attitudes are not direct determinants of behavior; rather the intention to realize it is. In this case, attitudes determine behavior through intentions. Intentions toward behavior show individuals’ willingness to behave (Ajzen and Fishbein 1980 ). TPB assumes that a behavior is influenced by three fundamental psychological components: attitudes (positive/negative evaluations of the behavior), subjective norms (social pressures or others' expectations), and perceived behavioral control (the individual's confidence in performing the behavior and their perception of barriers) (Ajzen 1991 ). In this model, attitude is defined as an individual’s subjective judgment about performing a certain behavior, regardless of whether an action has positive or negative outcomes. Subjective norm refers to an individual’s perception of what others will think about his/her behavior. Lastly perceived behavioral control is explained as an individual’s belief about if he/she can act or not (Abrahamse and Steg 2009; Guo et al. 2018). Hence, the ultimate determinants of any behavior are subjective judgments about how one performs the behavior, beliefs about its consequences, and judgments of others' opinions (Ajzen and Fishbein 1980 ). This model has been successfully applied in numerous studies examining farmers' environmental behaviors in different countries. For example, in a study examining farmers' intentions to adopt water-saving measures in Italy, TPB components (particularly attitudes and perceived benefits) were found to significantly explain these intentions (Pino et al., 2017 ). Similarly, studies conducted in countries such as Saudi Arabia and Spain have also sought to identify the attitudinal and social factors underlying resistance to or willingness for water conservation through the TPB (Almulhim and Abubakar 2023; Martínez-Espiñeira and García-Valiñas 2012 ). On the other hand, Yazdanpanah et al. ( 2014 ) stated that the TPB may not always be valid and that it was less predictive in their samples of perceived behavioral control. While the Theory of Planned Behavior typically emphasizes the individual's rational decision-making processes, it has been observed that additional psychosocial factors can influence complex environmental actions such as water conservation behavior. The TPB model has been criticized for its explanatory power since it does not include the altruistic behavior and personal norms. Therefore, in recent years, there has been a notable trend in the literature towards expanding the TPB to develop more comprehensive models (Savari et al. 2023). Studies combining TPB with norm-based theories have shown that elements such as personal norms (an individual's sense of moral responsibility) and habits are decisive in water conservation behavior. For instance, Lam ( 1999 ) included additional variables such as moral obligation and perception of water rights in the TPB model to better explain individuals' intentions to conserve water. Zhang et al. ( 2024 ) discuss that moral norms may play a role in forming behavior, also, rational factors tend to dominate farmers’ behavior. Also, Tsai and Tan (2022) add moral norms to the TPB model as a predictor of attitudes, subjective norms and perceived behavioral control. Furthermore, there are other research that include risk perception to the TPB model (Savari and Khaleghi 2023; Wang et al. 2024). Mosavian et al. (2023) focused on the conservation motivation theory (PMT). Accordingly, it was concluded that farmers' drought risk perception and self-efficacy affect protective behaviors in cases of drought. To increase explanatory power of the framework, researchers include personal norms too. Personal norms reflect the individual’s internalized moral standards, and it is a significant element of actual behavior (Sargani et al. 2023; Yuan et al. 2022). Boazar et al. (2019) saw habit as a descriptive of farmers’ intentions. They developed the Theory of Interpersonal Behavior (TIB). In their study, they revealed the importance of moral norms and personal obligations in water conservation. A study in Iran found that social norms and personal norms have a positive and significant effect on farmers' intentions to conserve water, meaning that social pressures and moral values related to environmental protection are strong motivators. Additionally, this study demonstrated that factors such as objective conditions (e.g., physical barriers, access to resources) and subjective conditions (e.g., perceived difficulties) also influence both intention and actual behavior (Ataei et al. 2022). Similarly Russell and Knoeri (2019) shows that psychosocial and behavioral factors are significant determinants of water conservation intentions and household water use. They suggest that both subjective norms (feeling social pressure) and personal norms (feeling morally obliged) lead to stronger intention to conserve water. These findings indicate that it is necessary to go beyond the classical TPB variables and adopt a richer theoretical framework to understand water-saving behaviors. Nasiri et al. ( 2024 ) concluded that perceived barriers, moral norms, and subjective norms affect farmers' intention to grow medicinal plants instead of water-intensive crops. Meanwhile, Wang et al. (2023) show that subjective norms and attitudes affect intentions towards water-saving measures, but their results may vary depending on the technology (e.g., drought-resistant crops with drip irrigation). Castillo et al. (2021) found that farmers affected by social factors (social capital and subjective norms) wanted to use pressurized irrigation systems more. Zobeidi et al. (2022) and Savari et al. ( 2021 ) revealed how threat assessment, social discourse, and personal norms affect farmers' adaptive responses. Finally, models such as the Values-Identity-Personal Norms (VIP) model (Azadi et al. 2024 ) and the extended Value-Belief-Norm (VBN) theory (Su et al. 2021) confirm that adopted normative processes significantly explain farmers' water conservation behaviors. According to this literature review on the use of TPB and Extended TPB models to predict water conservation behaviors of farmers, we develop our ETPB and hypotheses as below. Research hypotheses H1: Attitudes of producers towards irrigation affect personal norms. H2: Subjective norms of producers affect personal norms towards irrigation. H3: Perceived behavioral control of producers towards irrigation affects personal norms. H4: Producers personal norms on irrigation affect water conservation behavior. H5: Producers personal norms on irrigation affect water conservation intention. Study Area and Data Collection This study aims to identify the factors that influence the farmers’ intention of water conservation in agricultural production. Konya was selected as the study area due to its status as a center for agriculture in Turkiye and its high vulnerability in the face of the water crisis. The agricultural production in Konya is highly dependent on rainfall. Although it is possible to do irrigated agriculture using groundwater in some places, due to the increasing demand, many water wells have been drilled and much more than the safe withdrawable water has been withdrawn in the region. For this reason, the population of farmers in Konya is representative of the intention and behavior of farmers in similar regions of Central Anatolia in Türkiye. The questionnaire survey was conducted in Konya in January 2025. The required sample size (s) was calculated to be 270 farmers, according to the following formula, with the population of farmers in Konya being approximately 106,833 (N). $$\:s=\frac{\text{N}\:\text{P}(1-\text{P})}{\left(N-1\right){\sigma\:}^{2}+P(1-P)}$$ The required sample size (s) is calculated using the population size (N), population proportion (P), assumed to be 0.5 for maximum sample size, and variance ( \(\:{\sigma\:}^{2}\) ). A 5% margin of error and 90% confidence limits were used to determine the sample size (Newbold 1995). Within the scope of this study, a survey was applied to 270 farmers. Face-to-face interviews were conducted to ensure the reliability of the results. In this context, the PLS-SEM method was used. This method is considered suitable for quantitative analysis due to its robustness in testing indirect effects with complex models. The TPB scale measurement items were adapted from Si et al. ( 2022 ). The measures from Si et al. ( 2022 ) were modified to fit the context of agricultural water conservation. Water conservation behavior and personal norm scales were developed using Savari et al ( 2021 ). The questionnaire consisted of two parts: one addressing socioeconomic and operational farm characteristics, and another focusing on TPB construct measures. Variables were measured using a five-point Likert scale, with scores ranging from 1 to 5 based on the degree of confirmation. Results Most farmers in the sample are between 40 and 60 years old, suggesting that the farmer population is predominantly middle-aged or older. Approximately 60% of farmers have only primary education, indicating limited formal education, which may affect their ability to adopt advanced irrigation technologies. When the farms' land holdings are analyzed, 34.9% of them have less than 10 ha, 32% of them have between 10.1–30 ha and 33.1% of them have more than 30 ha of agricultural land. In addition, the average land size was calculated as 32 ha. When the social security status of enterprises is analyzed, 83.8% of them has social security. Table 1 Structural model reliability and convergence validity test results Construct Indicator Loading Cronbach's Alpha AVE CR Attitude 0.727 0.844 0.644 ATT1: Measures to address the water crisis can improve agricultural land productivity and ensure high production capacity. 0.705 ATT2: Water-saving practices are a good idea. 0.830 ATT3: Actively responding to the water crisis can ensure the supply security of agricultural products. 0.793 Subjective Norm 0.752 0.889 0.800 SN1: My family supports me in saving water to address the water crisis. 0.912 SN2: My relatives, friends, and neighbors think it is wise to change farming methods to tackle the water crisis. 0.877 Perceived Behavioral Control 0.689 0.821 0.607 PBC1: I can afford the necessary capital costs to address the water crisis. 0.705 PBC2: I have the knowledge about the skills and tools needed to tackle the water crisis. 0.853 PBC3: I think effectively combating the water crisis in dryland farming is not difficult. 0.772 Personal Norm 0.853 0.901 0.695 KN1: I feel I should do something positive to combat water scarcity. 0.787 KN2: It is my moral responsibility to conserve water in the region. 0.892 KN3: I feel I am a better farmer if I use less water. 0.767 KN4: I believe I have a moral obligation to use water correctly and efficiently. 0.882 Water Conservation Behavior 0.824 0.876 0.586 WCB1: Changing irrigation timing. 0.762 WCB2: Reducing the frequency of irrigation per week. 0.757 WCB3: Using modern irrigation technologies to reduce water loss. 0.761 WCB6: Implementing drought-tolerant crop varieties to reduce water usage. 0.756 WCB7: Using pipes for water transportation to reduce evaporation. 0.792 Water Conservation Intention 0.810 0.868 0.568 WCI1: I intend to change irrigation timing to reduce water usage. 0.760 WCI2: I intend to reduce the frequency of irrigation per week. 0.736 WCI5: I intend to ensure the use of ponds and water collection. 0.712 WCI6: I intend to implement drought-tolerant varieties to reduce water usage. 0.822 WCI7: I plan to use pipes for water transportation to reduce evaporation. 0.734 Table 1 shows the results of validity and reliability analysis on the items of TPB constructs. The loadings for each measurement item are above 0.5 and Cronbach Alpha coefficients for attitude, subjective norm, personal norm, conservation behavior and intention are higher than suggested value of 0,7 by Gliem & Gliem ( 2003 ). Only CA coefficient for PBC is lower but very close to cutting value. This implies internal consistency is sufficient and constructs in the measurement model are reliable. Also, Average Variance Extracted (AVE) of all constructs are higher than cutting value (0.5) showing the convergent validity of the model. Table 2 Extended TPB Model Results Indicator ETPB Model R 2 Q 2 PN 0,250 0.163 WCB 0,249 0.142 WCI 0,257 0.137 SRMR 0,085 Explained variance ratio by ETPB model is 25.7% for water conservation intention (WCI) and 25% for water conservation behavior (WCB), as can be seen in Table 2 by the coefficients of determination (R 2 s). Moreover, cross validation redundancy (Q 2 ) is approximately 14% for both WCI and WCB. This means extended TPB model by incorporating personal norms provides a good explanatory and predictive power in terms of both intention and behavior. Table 3 Discriminant validity test for Extended TPB Model PBC PBC PN WCB AT CI SN 0.779 PN 0.382 0.834 WCB 0.273 0.499 0.766 AT 0.207 0.392 0.215 0.803 WCI 0.259 0.507 0.736 0.353 0.754 SN 0.402 0.300 0.173 0.403 0.239 0.895 To evaluate discriminant validity, we employed the Fornell-Larcker criterion. This criterion requires that the square root of the Average Variance Extracted (AVE) for each construct should exceed its correlations with any other construct in the study. In Table 3 , the diagonal value (square root of AVE) is greater than all off-diagonal correlations for each construct. This indicates that all the constructs satisfy the Fornell-Larcker criterion for discriminant validity in Extended TPB model. The strongest correlation is observed between WCI (Water Conservation Intention) and WCB (Water Conservation Behavior), with a value of 0.736. Nevertheless, the square roots of AVE for both CI (0.754) and WCB (0.766) surpass this correlation, thereby confirming discriminant validity. Table 4 Path Analysis H1 Path Original Sample Sample Mean Standard Deviation t-stat p value VIF ATT ->PN 0.308 0.309 0.071 4.355 0.000 1.198 H2 SN->PN 0.057 0.059 0.062 0.928 0.354 1.367 H3 PBC-> PN 0.295 0.297 0.054 5.455 0.000 1.196 H4 PN -> WCB 0.499 0.502 0.045 10.974 0.000 1.000 H5 PN-> WCI 0.507 0.512 0.046 11.101 0.000 1.000 Table 4 presents the results of the Extended TPB model. ETPB model explains water conservation intention (WCI) and behavior (WCB) based on personal norm (PN) which is determined by perceived behavioral control (PBC), attitude (ATT), and subjective norm (SN). According to Table 4 , while PBC (β = 0.30, t = 3.11) and ATT (β = 0.31, t = 5.52) demonstrate a positive significant direct influence on PN, SN exhibits a small insignificant effect (B = 0.06). Consequently, individuals with favorable attitudes and higher perceived control over conserving water are more likely to have personal norms more favorable to water conservation. Accordingly, personal norms (PN) exert a strong and highly significant impact on both water conservation intention (β = 0.51, t = 11.10) and behavior (β = 0.50, t = 10.97). ATT and PBC influence WCI and WCB solely through PN, whereas SN demonstrates no significant impact. Discussion and Conclusion This study applied an extended version of the Theory of Planned Behavior (TPB) to understand the water conservation behaviors of farmers in Konya region, one of the important agricultural production centers of Türkiye. Findings from this study suggest that TPB's emphasis on subjective norms may be less predictive in regions where collective norms are weakly institutionalized, or where informal irrigation practices prevail. This invites reconsideration of how social influence is conceptualized in TPB and highlights the importance of integrating contextualized understandings from water governance literature. The findings show that attitudes and perceived behavioral control have an obvious and significant effect on farmers' personal norms. The weak effect of subjective norms differs from some previous studies in the literature. For example, Castillo et al. (2021) and Wang et al. (2023) found that subjective norms have a stronger effect on farmers' behavior than attitudes. This difference may be due to differences in social and cultural structures in the Turkish context or weak institutionalization of collective norms in the region. In line with the existing findings in the literature (Nasiri et al. 2024; Azadi et al ., 2024; Harland et al ., 1999), our study also reveals the importance of personal norms on farmers' water conservation intentions and behaviors. Nasiri et al. ( 2024 ) and Azadi et al. ( 2024 ) emphasized the strong effect of personal norms as a determinant of farmers' environmental behaviors. Harland et al. ( 1999 ) showed that personal norms play a critical role in predicting environmentally friendly behaviors. In this context, it is concluded that strengthening the sense of moral and social responsibility of farmers can be achieved through policy and education programs. The expansion of TPB to include personal norms constitutes the theoretical contribution of our study and supports similar studies in the literature (Lam 1999 ; Zhang et al. 2024 ; Tsai and Tan 2022). Lam ( 1999 ) enhanced the explanatory power of the model by adding moral obligation and perceived water rights to the TPB model. Zhang et al. ( 2024 ) emphasized the importance of moral norms as well as rational decision factors in farmers' climate change adaptation and mitigation behaviors. In this context, our study also reveals the critical role of personal norms as well as rational elements in farmers' water conservation behaviors. On the other hand, farmers' water conservation behaviors should be considered not only in terms of psychological and personal norms, but also independently of the economic, political and institutional framework. Economic factors such as the low cost of water and the prevalence of illegal wells in Türkiye negatively affect farmers' motivation to conserve water. This situation shows that farmers' water conservation behaviors should be supported by effective policies and institutions. Similarly, in the literature, Dagnino and Ward ( 2012 ) emphasized the importance of the local context by drawing attention to the fact that the total effect of individual farmer behaviors may deviate from policy objectives. Leroy et al. (2023) also reveals that farmers' behaviors towards water scarcity are not independent of the local context and perceptions. Considering these findings, our current study emphasizes that farmer behaviors in Türkiye are closely related to the economic, political and institutional framework and the importance of considering these factors. In conclusion, this study provides important theoretical and practical contributions to the water management literature in the context of farmer behavior by using the extended version of the TPB. It suggests that current water policies should be more inclusive and context-oriented in shaping farmer behavior by emphasizing the importance of personal norms and local context. It is recommended that future research provide a more holistic perspective to the water governance literature by examining in more depth how farmer behavior interacts with broader social, political and economic factors. Declarations Ethic Approval: The ethics committee approval of the research was received from the Selçuk University Faculty of Agriculture Scientific Ethics Evaluation Board on 31.12.2024 with the document number E-29529695-050.99-910094. Funding: The authors declare that no funds, grants, or other support were received during the preparation of this manuscript. Competing Interests : The authors have no relevant financial or non-financial interests to disclose. Author Contributions : All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed. All authors read and approved the final manuscript. Data Availability: Data may be provided upon reasonable request. 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Int J Water Resour Dev 39(5):773–795. https://doi.org/10.1080/07900627.2022.2142203 Martínez-Espiñeira R, García-Valiñas MaríaA (2012) Adopting versus Adapting: Adoption of Water-Saving Technology versus Water Conservation Habits in Spain. Int J Water Resour Dev 29(3):400–414. https://doi.org/10.1080/07900627.2012.721695 Mosavian SH, Rostami F, and Mohammad Tatar (2023) Modeling Farmers’ Intention to Water Protection Behavior: A New Extended Version of the Protection Motivation Theory. J Environ Psychol 90:102036. https://doi.org/10.1016/j.jenvp.2023.102036 Nasiri AR, Kerachian R, Mashhadi M, Shahangian SA, and Tahereh Zobeidi (2024) Extending the Theory of Planned Behavior to Predict the Behavior of Farmers in Choosing Low-Water-Intensive Medicinal Plants. J Environ Manage 369:122333. https://doi.org/10.1016/j.jenvman.2024.122333 Pino G, Toma P, Rizzo C, Miglietta PP, Peluso AM, and Gianluigi Guido (2017) Determinants of Farmers’ Intention to Adopt Water Saving Measures: Evidence from Italy. Sustainability 9(1):77. https://doi.org/10.3390/su9010077 Russell S, and Christine Knoeri (2019) Exploring the Psychosocial and Behavioural Determinants of Household Water Conservation and Intention. Int J Water Resour Dev 36(6):940–955. https://doi.org/10.1080/07900627.2019.1638230 Savari M, Abdeshahi A, Gharechaee H, and Omid Nasrollahian (2021) Explaining Farmers’ Response to Water Crisis through Theory of the Norm Activation Model: Evidence from Iran. Int J Disaster Risk Reduct 60:102284. https://doi.org/10.1016/j.ijdrr.2021.102284 Savari M, and Behnam Khaleghi (2023) Application of the Extended Theory of Planned Behavior in Predicting the Behavioral Intentions of Iranian Local Communities toward Forest Conservation. Front Psychol 14. https://doi.org/10.3389/fpsyg.2023.1121396 Shunglu R, Köpke S, Kanoi L, Nissanka TS, Withanachchi CR, Gamage DU, Withanachchi SS (2022) Barriers in Participative Water Governance: A Critical Analysis of Community Development Approaches. Water 14(5):762. https://doi.org/10.3390/w14050762 Si H, Duan X, Zhang W, Su Y, and Guozhu Wu (2022) Are You a Water Saver? Discovering People’s Water-Saving Intention by Extending the Theory of Planned Behavior. J Environ Manage 311:114848. https://doi.org/10.1016/j.jenvman.2022.114848 Yazdanpanah M, Hayati D, Stefan Hochrainer-Stigler, and, Gholam H, Zamani (2014) Understanding Farmers’ Intention and Behavior Regarding Water Conservation in the Middle-East and North Africa: A Case Study in Iran. J Environ Manage 135:63–72. https://doi.org/10.1016/j.jenvman.2014.01.016 Zhang Y, Geng L, Liang X, Wang W, and Yu Xue (2024) Which Is More Critical in Predicting Farmers’ Adaptation and Mitigation towards Climate Change: Rational Decision or Moral Norm Factors? J Clean Prod 434:139762. https://doi.org/10.1016/j.jclepro.2023.139762 Zheng H, Ma W, Boansi D, and Vincent Owusu (2023) Farmers’ Perceptions, Adoption and Impacts of Integrated Water Management Technology under Changing Climate. Int J Water Resour Dev 40(3):425–447. https://doi.org/10.1080/07900627.2023.2196351 Zobeidi T, Yaghoubi J, and Mohammad Yazdanpanah (2022) Farmers’ Incremental Adaptation to Water Scarcity: An Application of the Model of Private Proactive Adaptation to Climate Change (MPPACC). Agric Water Manage 264:107528. https://doi.org/10.1016/j.agwat.2022.107528 Additional Declarations No competing interests reported. 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The United Nations and international platforms emphasize that the water crisis is often a \u0026lsquo;governance crises and that effective water governance is an urgent priority. Water governance refers to a framework that encompasses all political, social, economic and administrative systems related to the development and management of water resources (GWP 2003). In other words, decisions on how water is managed, distributed and used are shaped not only by technical considerations but also by political actors, institutions, social values and cultural norms. Indeed, environmental sociologists argue that the natural, social, economic, and cultural dimensions of water issues must be addressed together in an inseparable manner; without a holistic understanding of these dimensions, water management solutions cannot be effective (Ataei et al. 2022). From this perspective, stakeholder participation and transparent decision-making processes are considered vital for ensuring good governance practices (GWP 2003; Leroy et al. 2023).\u003c/p\u003e \u003cp\u003eAs a country with semi-arid climate regions, T\u0026uuml;rkiye faces similar governance challenges in relation to water scarcity risks. Water governance in the country has been carried out with a centralized approach for many years; institutional fragmentation and an inadequate legal framework have been obstacles to effective water governance. For example, the fact that a comprehensive \u0026lsquo;Water Law\u0026rsquo; has not yet been enacted in T\u0026uuml;rkiye and the fragmented nature of existing regulations make it difficult to implement the principle of integrated water resources management (Tuna 2012). A recent study has shown that overly centralized water governance reduces effectiveness by creating a lack of coordination, and therefore each country needs to develop governance models that are sensitive to its own conditions (Yousefi et al. 2024). Therefore, the success of water policies in T\u0026uuml;rkiye depends not only on technical infrastructure investments but also on institutional structures and political will to manage water in an effective, fair and sustainable manner.\u003c/p\u003e \u003cp\u003eThe agricultural sector is one of the focal points of the water crisis, as it accounts for the largest share of water use both globally and in T\u0026uuml;rkiye. Globally, approximately 63\u0026ndash;70% of total water consumption comes from agricultural irrigation (Ataei et al. 2022). A similar picture is observed in T\u0026uuml;rkiye: approximately 75% of the country's current water resources are used in agriculture (Ertek and Yılmaz 2014). Low irrigation efficiency and water waste are among the main factors increasing the risk of water scarcity. Changes in rainfall patterns due to climate change, increased frequency of droughts, and excessive use of groundwater are making access to water for agricultural production more difficult. Under these conditions, optimal water management in agriculture is vital to ensure food security and protect water resources. Optimal management encompasses not only technical measures but also farmers' behavior regarding water use (Grafton et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn T\u0026uuml;rkiye, the construction and initial operation of large-scale irrigation infrastructures is carried out by the General Directorate of State Hydraulic Works (DSİ). However, with the authorization granted by Law No. 6200, the responsibility for the operation and maintenance of irrigation systems has been transferred over time to village legal entities, municipalities, cooperatives and especially irrigation unions (Shemsari and Bayraktar 2024). Although this \u0026ldquo;devolution of irrigation management\u0026rdquo; policy, implemented since the 1990s, aimed to increase local user participation and make the systems function more efficiently, various studies reveal that irrigation unions face serious problems in terms of administrative capacity, technical competence and level of participation (\u0026Ouml;zerol et al. 2012). Injustice in water distribution, lack of transparency, and accountability problems among farmers are frequently cited (Shunglu et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). This shows that irrigation systems are not only a technical infrastructure issue, but also a governance issue that requires the establishment of social trust and institutional consensus at the local level. The case of T\u0026uuml;rkiye demonstrates that for water governance reforms to be sustainable, it is imperative to consider the social and institutional context beyond technical interventions.\u003c/p\u003e \u003cp\u003eIndeed, the sustainability of water resources depends largely on human behavior (Callejas Moncaleano et al. 2021). Many studies have shown that, in addition to natural factors, human factors are decisive in water scarcity crises (Ataei et al. 2022). Issues such as excessive and unplanned consumption of water resources, pollution, and environmental degradation stem from human behavior. Therefore, in the fight against water scarcity, examining and guiding individuals' water usage behavior is considered a critical element, as much as technical solutions and policy regulations (Ataei et al. 2022; Callejas Moncaleano et al. 2021). As emphasised in the GWP (2003) report; to be successful in water management, it is necessary to understand users' attitudes and habits and motivate them to save water. Particularly in the agricultural sector, it does not seem possible to achieve lasting improvements in water efficiency without changing farmers' traditional irrigation habits.\u003c/p\u003e \u003cp\u003eIn this context, theoretical models that examine the determinants of individual behavior have gained importance in the water management literature. The Theory of Planned Behavior (TPB) is one of the most widely used theoretical frameworks for explaining individuals' behavioral intentions and behaviors, including in environmental and agricultural areas. Also studies extend this model to include moral and personal norms and some other subjective constructs obtained higher explanatory power in explaining water conservation behavior. The current trend in the literature is toward applying extended TPB models to water governance studies. For example, a recent study examined Chinese farmers' decisions to adopt integrated water management technologies (e.g., innovative practices such as drip irrigation). The results revealed that farmers' adoption of these technologies was largely dependent on their perceptions of the technology. If a farmer believes that a new irrigation method will reduce their workload, be easier to implement, and provide higher economic returns compared to traditional flood irrigation, they are more likely to adopt this technology (Zheng et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). This finding shows that farmers' assessment of perceived benefits and costs plays a key role in their behavior, which confirms the practical importance of the TPB's attitude and control components. Similarly, a qualitative study conducted in Mexico showed that small-scale farmers' adaptation behaviors to water scarcity are guided by their perceptions of the causes and dynamics of water scarcity. This study notes that even in villages connected to the same irrigation network, farmers' measures to address water scarcity vary, with these differences stemming from contextual characteristics such as irrigation techniques, location of water collection points, production systems, and access to groundwater. Therefore, farmers' perspectives on water issues and their institutional-physical conditions shape their actions to conserve water. This finding emphasizes the need for water management policies to be designed in a manner that is sensitive to local conditions rather than generalizing (Leroy et al. 2023).\u003c/p\u003e \u003cp\u003eWhile explaining conservation behavior is beneficial, sometimes explained individual behavior can cause unexpected overall results. Dagnino and Ward (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) estimates increased depletions of the water source to occur in the face of increased drip irrigation subsidies in basins where no system of water rights exists. Individual farmers may have differing objectives and constraints that do not align with the optimization goals of water governance authorities and the cumulative effects of decentralized decision-making can produce unintended regional consequences\u0026rdquo; (el_Fartassi et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Therefore, in these studies investigating behavioral determinants of water conservation, water governance in the region studied should be considered.\u003c/p\u003e \u003cp\u003eThe theoretical basis of the current study draws on the literature summarized above. In the context of agricultural water governance in T\u0026uuml;rkiye, a model was developed and empirically tested within the framework of the Extended Theory of Planned Behavior to understand farmers' water conservation behaviors. In addition to the classic components of TPB, this model also includes some additional elements that have been highlighted in the literature. Thus, our study not only presents an applied behavioral model but also aims to expand and question the theoretical boundaries of the TPB in the context of agricultural water management. In this regard, the study offers a unique contribution to the water governance literature by filling the gap between micro-level behaviors and macro-level governance elements. Indeed, a study on adaptation to the groundwater crisis has shown that TPB can be adapted to explain farmers' intentions to diversify their income through a socio-psychological model developed for this purpose; this model, which incorporates an expanded TPB approach including emotional and instrumental attitudes and self-efficacy beliefs, explaining 55% of the variance in farmers' intentions to adopt alternative livelihood strategies and 36% of the variance in actual income diversification behavior. Similarly, our study uses an expanded TPB to explain water-saving behavior in Turkish agriculture, thereby applying a critical test to the existing theory in a new context.\u003c/p\u003e \u003cp\u003eVarious studies support the notion that effective water governance is possible not only through infrastructural investments but also through the behavior of water users. This study, which examines farmers' water conservation behavior in agricultural irrigation in T\u0026uuml;rkiye, responds to a gap in the literature by offering a holistic approach that combines the institutional context with psychological factors. Considering the current debates and theoretical approaches mentioned in the Introduction section, the article will first summarize the current situation regarding agricultural water management and farmer behavior in T\u0026uuml;rkiye, then present the methods and findings of the research, and finally reveal the theoretical contributions of our expanded TPB model. Thus, the study aims to establish a strong theoretical connection with the water governance literature from institutional, social, and cultural perspectives, while also presenting a perspective that develops and questions existing theories specifically regarding farmer behavior.\u003c/p\u003e"},{"header":"Theoretical Framework","content":"\u003cp\u003eAccording to the TPB, attitudes are not direct determinants of behavior; rather the intention to realize it is. In this case, attitudes determine behavior through intentions. Intentions toward behavior show individuals\u0026rsquo; willingness to behave (Ajzen and Fishbein \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e1980\u003c/span\u003e). TPB assumes that a behavior is influenced by three fundamental psychological components: attitudes (positive/negative evaluations of the behavior), subjective norms (social pressures or others' expectations), and perceived behavioral control (the individual's confidence in performing the behavior and their perception of barriers) (Ajzen \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e1991\u003c/span\u003e). In this model, attitude is defined as an individual\u0026rsquo;s subjective judgment about performing a certain behavior, regardless of whether an action has positive or negative outcomes. Subjective norm refers to an individual\u0026rsquo;s perception of what others will think about his/her behavior. Lastly perceived behavioral control is explained as an individual\u0026rsquo;s belief about if he/she can act or not (Abrahamse and Steg 2009; Guo et al. 2018). Hence, the ultimate determinants of any behavior are subjective judgments about how one performs the behavior, beliefs about its consequences, and judgments of others' opinions (Ajzen and Fishbein \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e1980\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThis model has been successfully applied in numerous studies examining farmers' environmental behaviors in different countries. For example, in a study examining farmers' intentions to adopt water-saving measures in Italy, TPB components (particularly attitudes and perceived benefits) were found to significantly explain these intentions (Pino et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Similarly, studies conducted in countries such as Saudi Arabia and Spain have also sought to identify the attitudinal and social factors underlying resistance to or willingness for water conservation through the TPB (Almulhim and Abubakar 2023; Mart\u0026iacute;nez-Espi\u0026ntilde;eira and Garc\u0026iacute;a-Vali\u0026ntilde;as \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). On the other hand, Yazdanpanah et al. (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) stated that the TPB may not always be valid and that it was less predictive in their samples of perceived behavioral control.\u003c/p\u003e \u003cp\u003eWhile the Theory of Planned Behavior typically emphasizes the individual's rational decision-making processes, it has been observed that additional psychosocial factors can influence complex environmental actions such as water conservation behavior. The TPB model has been criticized for its explanatory power since it does not include the altruistic behavior and personal norms. Therefore, in recent years, there has been a notable trend in the literature towards expanding the TPB to develop more comprehensive models (Savari et al. 2023). Studies combining TPB with norm-based theories have shown that elements such as personal norms (an individual's sense of moral responsibility) and habits are decisive in water conservation behavior. For instance, Lam (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e1999\u003c/span\u003e) included additional variables such as moral obligation and perception of water rights in the TPB model to better explain individuals' intentions to conserve water. Zhang et al. (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) discuss that moral norms may play a role in forming behavior, also, rational factors tend to dominate farmers\u0026rsquo; behavior. Also, Tsai and Tan (2022) add moral norms to the TPB model as a predictor of attitudes, subjective norms and perceived behavioral control. Furthermore, there are other research that include risk perception to the TPB model (Savari and Khaleghi 2023; Wang et al. 2024). Mosavian et al. (2023) focused on the conservation motivation theory (PMT). Accordingly, it was concluded that farmers' drought risk perception and self-efficacy affect protective behaviors in cases of drought. To increase explanatory power of the framework, researchers include personal norms too. Personal norms reflect the individual\u0026rsquo;s internalized moral standards, and it is a significant element of actual behavior (Sargani et al. 2023; Yuan et al. 2022). Boazar et al. (2019) saw habit as a descriptive of farmers\u0026rsquo; intentions. They developed the Theory of Interpersonal Behavior (TIB). In their study, they revealed the importance of moral norms and personal obligations in water conservation. A study in Iran found that social norms and personal norms have a positive and significant effect on farmers' intentions to conserve water, meaning that social pressures and moral values related to environmental protection are strong motivators. Additionally, this study demonstrated that factors such as objective conditions (e.g., physical barriers, access to resources) and subjective conditions (e.g., perceived difficulties) also influence both intention and actual behavior (Ataei et al. 2022). Similarly Russell and Knoeri (2019) shows that psychosocial and behavioral factors are significant determinants of water conservation intentions and household water use. They suggest that both subjective norms (feeling social pressure) and personal norms (feeling morally obliged) lead to stronger intention to conserve water. These findings indicate that it is necessary to go beyond the classical TPB variables and adopt a richer theoretical framework to understand water-saving behaviors.\u003c/p\u003e \u003cp\u003eNasiri et al. (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) concluded that perceived barriers, moral norms, and subjective norms affect farmers' intention to grow medicinal plants instead of water-intensive crops. Meanwhile, Wang et al. (2023) show that subjective norms and attitudes affect intentions towards water-saving measures, but their results may vary depending on the technology (e.g., drought-resistant crops with drip irrigation). Castillo et al. (2021) found that farmers affected by social factors (social capital and subjective norms) wanted to use pressurized irrigation systems more. Zobeidi et al. (2022) and Savari et al. (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) revealed how threat assessment, social discourse, and personal norms affect farmers' adaptive responses. Finally, models such as the Values-Identity-Personal Norms (VIP) model (Azadi et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) and the extended Value-Belief-Norm (VBN) theory (Su et al. 2021) confirm that adopted normative processes significantly explain farmers' water conservation behaviors. According to this literature review on the use of TPB and Extended TPB models to predict water conservation behaviors of farmers, we develop our ETPB and hypotheses as below.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eResearch hypotheses\u003c/p\u003e \u003cp\u003eH1: Attitudes of producers towards irrigation affect personal norms.\u003c/p\u003e \u003cp\u003eH2: Subjective norms of producers affect personal norms towards irrigation.\u003c/p\u003e \u003cp\u003eH3: Perceived behavioral control of producers towards irrigation affects personal norms.\u003c/p\u003e \u003cp\u003eH4: Producers personal norms on irrigation affect water conservation behavior.\u003c/p\u003e \u003cp\u003eH5: Producers personal norms on irrigation affect water conservation intention.\u003c/p\u003e"},{"header":"Study Area and Data Collection","content":"\u003cp\u003eThis study aims to identify the factors that influence the farmers\u0026rsquo; intention of water conservation in agricultural production. Konya was selected as the study area due to its status as a center for agriculture in Turkiye and its high vulnerability in the face of the water crisis. The agricultural production in Konya is highly dependent on rainfall. Although it is possible to do irrigated agriculture using groundwater in some places, due to the increasing demand, many water wells have been drilled and much more than the safe withdrawable water has been withdrawn in the region. For this reason, the population of farmers in Konya is representative of the intention and behavior of farmers in similar regions of Central Anatolia in T\u0026uuml;rkiye. The questionnaire survey was conducted in Konya in January 2025. The required sample size (s) was calculated to be 270 farmers, according to the following formula, with the population of farmers in Konya being approximately 106,833 (N).\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:s=\\frac{\\text{N}\\:\\text{P}(1-\\text{P})}{\\left(N-1\\right){\\sigma\\:}^{2}+P(1-P)}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eThe required sample size (s) is calculated using the population size (N), population proportion (P), assumed to be 0.5 for maximum sample size, and variance (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\sigma\\:}^{2}\\)\u003c/span\u003e\u003c/span\u003e). A 5% margin of error and 90% confidence limits were used to determine the sample size (Newbold 1995). Within the scope of this study, a survey was applied to 270 farmers. Face-to-face interviews were conducted to ensure the reliability of the results. In this context, the PLS-SEM method was used. This method is considered suitable for quantitative analysis due to its robustness in testing indirect effects with complex models.\u003c/p\u003e \u003cp\u003eThe TPB scale measurement items were adapted from Si et al. (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The measures from Si et al. (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) were modified to fit the context of agricultural water conservation. Water conservation behavior and personal norm scales were developed using Savari et al (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The questionnaire consisted of two parts: one addressing socioeconomic and operational farm characteristics, and another focusing on TPB construct measures. Variables were measured using a five-point Likert scale, with scores ranging from 1 to 5 based on the degree of confirmation.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eMost farmers in the sample are between 40 and 60 years old, suggesting that the farmer population is predominantly middle-aged or older. Approximately 60% of farmers have only primary education, indicating limited formal education, which may affect their ability to adopt advanced irrigation technologies. When the farms' land holdings are analyzed, 34.9% of them have less than 10 ha, 32% of them have between 10.1\u0026ndash;30 ha and 33.1% of them have more than 30 ha of agricultural land. In addition, the average land size was calculated as 32 ha. When the social security status of enterprises is analyzed, 83.8% of them has social security.\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\u003eStructural model reliability and convergence validity test results\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" 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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConstruct\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIndicator\u003c/p\u003e \u003cp\u003eLoading\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCronbach's\u003c/p\u003e \u003cp\u003eAlpha\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAVE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCR\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAttitude\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.727\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.844\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.644\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eATT1: Measures to address the water crisis can improve agricultural land productivity and ensure high production capacity.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.705\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eATT2: Water-saving practices are a good idea.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.830\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eATT3: Actively responding to the water crisis can ensure the supply security of agricultural products.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.793\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSubjective Norm\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.752\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.889\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.800\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSN1: My family supports me in saving water to address the water crisis.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.912\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSN2: My relatives, friends, and neighbors think it is wise to change farming methods to tackle the water crisis.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.877\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePerceived Behavioral Control\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.689\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.821\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.607\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePBC1: I can afford the necessary capital costs to address the water crisis.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.705\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePBC2: I have the knowledge about the skills and tools needed to tackle the water crisis.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.853\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePBC3: I think effectively combating the water crisis in dryland farming is not difficult.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.772\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePersonal Norm\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.853\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.901\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.695\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKN1: I feel I should do something positive to combat water scarcity.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.787\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKN2: It is my moral responsibility to conserve water in the region.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.892\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKN3: I feel I am a better farmer if I use less water.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.767\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKN4: I believe I have a moral obligation to use water correctly and efficiently.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.882\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWater Conservation Behavior\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.824\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.876\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.586\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWCB1: Changing irrigation timing.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.762\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWCB2: Reducing the frequency of irrigation per week.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.757\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWCB3: Using modern irrigation technologies to reduce water loss.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.761\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWCB6: Implementing drought-tolerant crop varieties to reduce water usage.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.756\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWCB7: Using pipes for water transportation to reduce evaporation.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.792\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWater Conservation Intention\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.810\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.868\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.568\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWCI1: I intend to change irrigation timing to reduce water usage.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.760\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWCI2: I intend to reduce the frequency of irrigation per week.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.736\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWCI5: I intend to ensure the use of ponds and water collection.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.712\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWCI6: I intend to implement drought-tolerant varieties to reduce water usage.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.822\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWCI7: I plan to use pipes for water transportation to reduce evaporation.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.734\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows the results of validity and reliability analysis on the items of TPB constructs. The loadings for each measurement item are above 0.5 and Cronbach Alpha coefficients for attitude, subjective norm, personal norm, conservation behavior and intention are higher than suggested value of 0,7 by Gliem \u0026amp; Gliem (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). Only CA coefficient for PBC is lower but very close to cutting value. This implies internal consistency is sufficient and constructs in the measurement model are reliable. Also, Average Variance Extracted (AVE) of all constructs are higher than cutting value (0.5) showing the convergent validity of the model.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eExtended TPB Model Results\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eIndicator\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eETPB Model\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eQ\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0,250\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.163\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWCB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0,249\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.142\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWCI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0,257\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.137\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSRMR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e0,085\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eExplained variance ratio by ETPB model is 25.7% for water conservation intention (WCI) and 25% for water conservation behavior (WCB), as can be seen in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e by the coefficients of determination (R\u003csup\u003e2\u003c/sup\u003es). Moreover, cross validation redundancy (Q\u003csup\u003e2\u003c/sup\u003e) is approximately 14% for both WCI and WCB. This means extended TPB model by incorporating personal norms provides a good explanatory and predictive power in terms of both intention and behavior.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDiscriminant validity test for Extended TPB Model\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\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=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePBC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePBC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eWCB\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAT\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSN\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e0.779\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.382\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.834\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWCB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.273\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.499\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.766\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.207\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.392\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.215\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.803\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWCI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.259\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.507\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.736\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.353\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.754\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.402\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.173\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.403\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.239\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.895\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTo evaluate discriminant validity, we employed the Fornell-Larcker criterion. This criterion requires that the square root of the Average Variance Extracted (AVE) for each construct should exceed its correlations with any other construct in the study. In Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, the diagonal value (square root of AVE) is greater than all off-diagonal correlations for each construct. This indicates that all the constructs satisfy the Fornell-Larcker criterion for discriminant validity in Extended TPB model. The strongest correlation is observed between WCI (Water Conservation Intention) and WCB (Water Conservation Behavior), with a value of 0.736. Nevertheless, the square roots of AVE for both CI (0.754) and WCB (0.766) surpass this correlation, thereby confirming discriminant validity.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePath Analysis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\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=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eH1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePath\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOriginal Sample\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSample Mean\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eStandard Deviation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003et-stat\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ep value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eVIF\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eATT -\u0026gt;PN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.308\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.309\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.071\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.355\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.198\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eH2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSN-\u0026gt;PN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.057\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.059\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.062\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.928\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.354\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.367\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eH3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePBC-\u0026gt; PN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.295\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.297\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.054\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.455\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.196\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eH4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePN -\u0026gt; WCB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.499\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.502\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.045\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10.974\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eH5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePN-\u0026gt; WCI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.507\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.512\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.046\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11.101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e presents the results of the Extended TPB model. ETPB model explains water conservation intention (WCI) and behavior (WCB) based on personal norm (PN) which is determined by perceived behavioral control (PBC), attitude (ATT), and subjective norm (SN). According to Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, while PBC (β\u0026thinsp;=\u0026thinsp;0.30, t\u0026thinsp;=\u0026thinsp;3.11) and ATT (β\u0026thinsp;=\u0026thinsp;0.31, t\u0026thinsp;=\u0026thinsp;5.52) demonstrate a positive significant direct influence on PN, SN exhibits a small insignificant effect (B\u0026thinsp;=\u0026thinsp;0.06). Consequently, individuals with favorable attitudes and higher perceived control over conserving water are more likely to have personal norms more favorable to water conservation. Accordingly, personal norms (PN) exert a strong and highly significant impact on both water conservation intention (β\u0026thinsp;=\u0026thinsp;0.51, t\u0026thinsp;=\u0026thinsp;11.10) and behavior (β\u0026thinsp;=\u0026thinsp;0.50, t\u0026thinsp;=\u0026thinsp;10.97). ATT and PBC influence WCI and WCB solely through PN, whereas SN demonstrates no significant impact.\u003c/p\u003e"},{"header":"Discussion and Conclusion","content":"\u003cp\u003eThis study applied an extended version of the Theory of Planned Behavior (TPB) to understand the water conservation behaviors of farmers in Konya region, one of the important agricultural production centers of T\u0026uuml;rkiye. Findings from this study suggest that TPB's emphasis on subjective norms may be less predictive in regions where collective norms are weakly institutionalized, or where informal irrigation practices prevail. This invites reconsideration of how social influence is conceptualized in TPB and highlights the importance of integrating contextualized understandings from water governance literature. The findings show that attitudes and perceived behavioral control have an obvious and significant effect on farmers' personal norms. The weak effect of subjective norms differs from some previous studies in the literature. For example, Castillo et al. (2021) and Wang et al. (2023) found that subjective norms have a stronger effect on farmers' behavior than attitudes. This difference may be due to differences in social and cultural structures in the Turkish context or weak institutionalization of collective norms in the region.\u003c/p\u003e \u003cp\u003eIn line with the existing findings in the literature (Nasiri et al. 2024; Azadi et al ., 2024; Harland et al ., 1999), our study also reveals the importance of personal norms on farmers' water conservation intentions and behaviors. Nasiri et al. (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) and Azadi et al. (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) emphasized the strong effect of personal norms as a determinant of farmers' environmental behaviors. Harland et al. (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e1999\u003c/span\u003e) showed that personal norms play a critical role in predicting environmentally friendly behaviors. In this context, it is concluded that strengthening the sense of moral and social responsibility of farmers can be achieved through policy and education programs.\u003c/p\u003e \u003cp\u003eThe expansion of TPB to include personal norms constitutes the theoretical contribution of our study and supports similar studies in the literature (Lam \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e1999\u003c/span\u003e; Zhang et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Tsai and Tan 2022). Lam (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e1999\u003c/span\u003e) enhanced the explanatory power of the model by adding moral obligation and perceived water rights to the TPB model. Zhang et al. (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) emphasized the importance of moral norms as well as rational decision factors in farmers' climate change adaptation and mitigation behaviors. In this context, our study also reveals the critical role of personal norms as well as rational elements in farmers' water conservation behaviors.\u003c/p\u003e \u003cp\u003eOn the other hand, farmers' water conservation behaviors should be considered not only in terms of psychological and personal norms, but also independently of the economic, political and institutional framework. Economic factors such as the low cost of water and the prevalence of illegal wells in T\u0026uuml;rkiye negatively affect farmers' motivation to conserve water. This situation shows that farmers' water conservation behaviors should be supported by effective policies and institutions. Similarly, in the literature, Dagnino and Ward (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) emphasized the importance of the local context by drawing attention to the fact that the total effect of individual farmer behaviors may deviate from policy objectives. Leroy et al. (2023) also reveals that farmers' behaviors towards water scarcity are not independent of the local context and perceptions. Considering these findings, our current study emphasizes that farmer behaviors in T\u0026uuml;rkiye are closely related to the economic, political and institutional framework and the importance of considering these factors.\u003c/p\u003e \u003cp\u003eIn conclusion, this study provides important theoretical and practical contributions to the water management literature in the context of farmer behavior by using the extended version of the TPB. It suggests that current water policies should be more inclusive and context-oriented in shaping farmer behavior by emphasizing the importance of personal norms and local context. It is recommended that future research provide a more holistic perspective to the water governance literature by examining in more depth how farmer behavior interacts with broader social, political and economic factors.\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthic Approval:\u0026nbsp;\u003c/strong\u003eThe ethics committee approval of the research was received from the Sel\u0026ccedil;uk University Faculty of Agriculture Scientific Ethics Evaluation Board on 31.12.2024 with the document number E-29529695-050.99-910094.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eThe authors declare that no funds, grants, or other support were received during the preparation of this manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e: The authors have no relevant financial or non-financial interests to disclose.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e: All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability:\u003c/strong\u003e Data may be provided upon reasonable request.\u003c/p\u003e\u003cp\u003eParticipant Consent Statement: Informed consent was obtained from all participants involved in the study. Participation was voluntary and respondents were informed that the data would be treated confidentially and used solely for research purposes.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAbrahamse W, and Linda Steg (2009) How Do Socio-Demographic and Psychological Factors Relate to Households\u0026rsquo; Direct and Indirect Energy Use and Savings? J Econ Psychol 30(5):711\u0026ndash;720\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAjzen I (1991) The Theory of Planned Behavior. 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Agric Water Manage 264:107528. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.agwat.2022.107528\u003c/span\u003e\u003cspan address=\"10.1016/j.agwat.2022.107528\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"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":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Water scarcity, sustainable agriculture, behavioral intentions, personal norms","lastPublishedDoi":"10.21203/rs.3.rs-9434855/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9434855/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIn the face of increasing water stress in agricultural production, understanding farmers\u0026rsquo; decision process regarding water conservation has become increasingly critical. There is a lack of evidence regarding water conservation behaviors of farmers in T\u0026uuml;rkiye. Consequently, this study focuses on Konya which there a highly vulnerable agricultural center. Data was collected via survey. The research aims to explain water conservation behaviors of farmers by utilizing the Extended TPB framework by incorporating personal norms to the model. Partial Least Squares Structural Equation Modeling (PLS-SEM) is employed to quantitatively analyze. Accordingly, it was concluded that personal norms have a direct effect.\u003c/p\u003e","manuscriptTitle":"Understanding Agricultural Producers’ Water Conservation Behavior Through Extended Theory of Planned Behavior","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-22 07:02:46","doi":"10.21203/rs.3.rs-9434855/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"29ee8a83-3658-4ea3-b855-c23996cabeb0","owner":[],"postedDate":"April 22nd, 2026","published":true,"recentEditorialEvents":[{"type":"decision","content":"Rejected","date":"2026-05-02T11:51:17+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-05-02T11:54:35+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-22 07:02:46","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9434855","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9434855","identity":"rs-9434855","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}