Behavioral determinants of climate-smart agriculture adoption among smallholder leafy vegetable agripreneurs in semi-arid Tanzania.

Behavioral determinants of climate-smart agriculture adoption among smallholder leafy vegetable agripreneurs in semi-arid Tanzania - PMC Skip to main content An official website of the United States government Here's how you know Here's how you know Official websites use .gov A .gov website belongs to an official government organization in the United States. Secure .gov websites use HTTPS A lock ( Lock Locked padlock icon ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites. Search Log in Dashboard Publications Account settings Log out Search… Search NCBI Primary site navigation Search Logged in as: Dashboard Publications Account settings Log in Search PMC Full-Text Archive Search in PMC Journal List User Guide PERMALINK Copy As a library, NLM provides access to scientific literature. Inclusion in an NLM database does not imply endorsement of, or agreement with, the contents by NLM or the National Institutes of Health. Learn more: PMC Disclaimer | PMC Copyright Notice Sci Rep . 2026 Mar 4;16:12084. doi: 10.1038/s41598-026-40459-w Search in PMC Search in PubMed View in NLM Catalog Add to search Behavioral determinants of climate-smart agriculture adoption among smallholder leafy vegetable agripreneurs in semi-arid Tanzania Stephen Bishibura Erick Stephen Bishibura Erick 1 Department of Development and Strategic Studies, Sokoine University of Agriculture, P.O. Box 3002, Morogoro, Tanzania 2 Department of Rural Development and Regional Planning, Institute of Rural Development Planning, P.O. Box 11957, Mwanza, Tanzania Find articles by Stephen Bishibura Erick 1, 2, ✉ , Jonathan Stephen Mbwambo Jonathan Stephen Mbwambo 1 Department of Development and Strategic Studies, Sokoine University of Agriculture, P.O. Box 3002, Morogoro, Tanzania Find articles by Jonathan Stephen Mbwambo 1 , Raymond John Salanga Raymond John Salanga 1 Department of Development and Strategic Studies, Sokoine University of Agriculture, P.O. Box 3002, Morogoro, Tanzania Find articles by Raymond John Salanga 1 Author information Article notes Copyright and License information 1 Department of Development and Strategic Studies, Sokoine University of Agriculture, P.O. Box 3002, Morogoro, Tanzania 2 Department of Rural Development and Regional Planning, Institute of Rural Development Planning, P.O. Box 11957, Mwanza, Tanzania ✉ Corresponding author. Received 2025 Feb 18; Accepted 2026 Feb 12; Collection date 2026. © The Author(s) 2026 Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/ . PMC Copyright notice PMCID: PMC13076671  PMID: 41781452 Abstract This study elucidates the behavioral determinants influencing climate-smart agriculture (CSA) adoption among smallholder leafy vegetable agripreneurs in semi-arid Central Tanzania. Employing an extended Theory of Planned Behavior (TPB) that incorporates perceived usefulness from the Technology Acceptance Model (TAM) as a mediating construct, the study examines how attitudes, subjective norms, and perceived behavioral control shape CSA adoption decisions. A cross-sectional survey encompassing 385 agripreneurs from Dodoma and Singida regions was conducted, with data analyzed through Partial Least Squares Structural Equation Modeling (PLS-SEM) utilizing Smart PLS 4. The empirical findings demonstrate that attitudes exert the strongest influence on both perceived usefulness (β = 0.528, p < 0.001) and CSA adoption, indicating that agripreneurs who recognize CSA benefits demonstrate greater adoption propensity. Subjective norms (β = 0.231, p < 0.01) and perceived behavioral control (β = 0.198, p < 0.05) similarly influence perceived usefulness significantly, underscoring the importance of social networks and resource accessibility. Perceived usefulness emerges as a robust mediator between behavioral determinants and adoption (β = 0.580, p < 0.001), highlighting its pivotal role in translating positive perceptions into concrete adoption decisions. The investigation yields critical policy implications, including the imperative to strengthen agricultural extension services, enhance financial accessibility, and leverage social networks to facilitate CSA adoption. Notwithstanding limitations inherent in the cross-sectional design and reliance on self-reported measures, this study generates valuable insights for policymakers, researchers, and development practitioners. Future investigations should employ longitudinal approaches and integrate objective farm-level assessments to comprehensively elucidate CSA adoption dynamics in resource-constrained environments. Supplementary Information The online version contains supplementary material available at 10.1038/s41598-026-40459-w. Keywords: Climate-smart agriculture, PLS-SEM, Leafy vegetables, Smallholder agripreneurs, Semi-arid Tanzania Subject terms: Environmental social sciences, Natural hazards Introduction Climate change poses substantial challenges to agricultural productivity, particularly in semi-arid regions where smallholder agripreneurs confront erratic weather patterns and extreme climatic events 1 – 3 . The convergence of prolonged dry spells, irregular rainfall patterns, and rising temperatures has fundamentally disrupted traditional farming systems, thereby necessitating the urgent adoption of adaptive strategies to sustain productivity and ensure food security 4 . In this context, climate-smart agriculture (CSA) emerges as a viable solution through its capacity to enhance productivity, strengthen resilience to climate variability, and mitigate greenhouse gas emissions 5 , 6 . Nevertheless, the effectiveness of CSA practices remains contingent upon selecting crops suited to specific agroecological zones 7 , 8 . Within the crop type context, leafy vegetables demonstrate particular suitability for cultivation in semi-arid regions such as Central Tanzania, owing to their inherent adaptability, abbreviated production cycles, substantial market demand, and multiple harvest potential, which collectively confer advantages over staple crops 9 , 10 . The integration of these crops into existing farming systems has the potential to enhance household incomes, diversify agricultural production, and improve food security outcomes 11 , 12 . However, successful cultivation within these challenging environments necessitates the adoption of CSA practices that effectively mitigate climate-related stresses. The present study encompasses a diverse range of leafy vegetables cultivated in Central Tanzania, including both conventional and indigenous varieties such as amaranth ( Amaranthus species), coriander ( Coriandrum sativum ), sweet potato leaves ( Ipomoea batatas ), pumpkin leaves ( Cucurbita species), Chinese cabbage ( Brassica rapa ), kale ( Brassica oleracea ), spinach ( Spinacia oleracea ), collard greens ( Brassica oleracea ), and local varieties including ‘saladi’ and ‘mahanjo.’ These crops contribute substantially to food security and climate adaptation objectives. To enhance resilience and sustainability, smallholder agripreneurs have increasingly adopted various CSA practices, encompassing crop diversification, crop rotation, mulching, improved seed varieties, integrated soil fertility management, and agroforestry practices. Although CSA practices are designed to sustainably enhance productivity, build resilience, and reduce emissions 13 , 14 , their adoption remains influenced by multiple factors including resource availability, institutional support, market conditions, and behavioral determinants such as income levels, education, and attitudes 15 , 16 . Indeed, behavioral determinants, particularly attitudes toward CSA, social norms within farming communities, and perceived behavioral control, constitute crucial factors in adoption decisions 17 , 18 . However, empirical research investigating these factors among smallholder leafy vegetable agripreneurs in semi-arid Central Tanzania remains notably limited. The literature suggests that attitudes, conceptualized as positive perceptions of CSA’s benefits, exert substantial influence on adoption decisions 19 , 20 . Furthermore, social norms shape adoption patterns through peer influence mechanisms 21 – 23 , while perceived behavioral control, reflecting agripreneurs’ confidence in implementing CSA practices, significantly affects their willingness to adopt such innovations 24 , 17 . Despite the acknowledged relevance of these factors, their specific role in CSA adoption among smallholder leafy vegetable agripreneurs in semi-arid regions remains insufficiently explored, thereby necessitating further investigation to inform targeted interventions. Accordingly, this study investigates the behavioral factors influencing CSA adoption among smallholder leafy vegetable agripreneurs in Central Tanzania, with particular emphasis on attitudes, social norms, and perceived behavioral control. Guided by an extended Theory of Planned Behavior (TPB) that incorporates perceived usefulness from the Technology Acceptance Model (TAM) as a mediating construct, this research generates insights valuable for policymakers, agricultural extension services, and other stakeholders seeking to promote sustainable farming methods within resource-limited settings. This integration of TAM’s perceived usefulness into the TPB framework enables a more comprehensive understanding of how behavioral determinants translate into actual adoption decisions in resource-constrained environments. The article is structured as follows: The subsequent section presents the theoretical and conceptual framework, elucidating the extended Theory of Planned Behavior that underpins this investigation. Section  2 delineates the methodology, encompassing the study area, research design, and analytical approaches. Section  3 presents the empirical results, highlighting the behavioral factors that influence CSA adoption. Section  4 discusses these findings in relation to existing literature, emphasizing their theoretical and practical contributions. Finally, Sect.  5 concludes with actionable recommendations for policymakers and stakeholders, underscoring the importance of integrating behavioral considerations into CSA interventions. Theoretical and conceptual framework This study draws upon an extended versio of Ajzen’s Theory of Planned Behavior (TPB) 25 , which incorporates perceived usefulness from the Technology Acceptance Model (TAM) 26 as a mediating factor. The TPB constitutes a widely recognized framework for predicting human behavior, positing that an individual’s intention to perform a behavior represents the strongest predictor of actual behavior, shaped by three fundamental constructs: attitudes, subjective norms, and perceived behavioral control 25 . Attitudes encompass an individual’s cognitive and affective evaluation of a behavior’s desirability. Within the context of this study, they represent agripreneurs’ perceptions regarding the benefits of climate-smart agriculture (CSA) adoption, particularly concerning enhanced productivity and resilience. Subjective norms capture the social pressures emanating from peers, community members, and agricultural experts, which subsequently influence adoption decisions. Perceived behavioral control (PBC) denotes agripreneurs’ confidence in their capability to implement CSA practices, shaped by their access to essential resources, technical knowledge, and institutional support. Whereas the traditional TPB emphasizes behavioral intention as a primary determinant, external constraints including resource limitations and climate uncertainties may attenuate this relationship. To address these complexities and enhance the model’s applicability to CSA adoption within resource-constrained settings, the present study extends the TPB through the integration of perceived usefulness as a mediating factor. Perceived usefulness, adapted from the Technology Acceptance Model 26 , encompasses farmers’ assessment of the practical benefits and utility that CSA practices offer within their specific farming context. This novel integration of TAM’s perceived usefulness construct into the TPB framework constitutes a significant theoretical advancement. Although previous investigations have typically applied TPB or TAM independently to examine agricultural technology adoption, this study pioneers a hybrid approach that simultaneously captures both the social-psychological factors inherent in TPB and the practical utility assessment central to TAM that collectively drive farmers’ adoption decisions. This extension proves particularly salient in resource-constrained environments where farmers must carefully evaluate not merely whether they possess the capability or social motivation to adopt CSA practices, but crucially, whether these practices will yield tangible benefits that justify their limited resource investment. Through demonstrating how perceived usefulness mediates the relationships between traditional TPB constructs and actual adoption behavior, this investigation advances theoretical understanding of agricultural innovation adoption within developing contexts. The extended TPB model employed in this study can be expressed as: where the intention (INT) to adopt CSA practices represents a function of attitudes (ATT), subjective norms (SN), perceived behavioral control (PBC), and perceived usefulness (PU). The coefficients (β 1 , β 2 , β 3 , β 4 ) denote the relative importance of each factor, while the error term (ε) accounts for unexplained variance. Conceptual model and hypotheses The conceptual model underpinning this investigation integrates the Theory of Planned Behavior (TPB) with perceived usefulness adapted from the Technology Acceptance Model (TAM). The model encompasses three categories of constructs: exogenous constructs (attitudes, subjective norms, and perceived behavioral control), a mediating construct (perceived usefulness), and an endogenous construct (adoption of climate-smart agricultural practices). This framework elucidates how these constructs interact to influence CSA adoption among leafy vegetable agripreneurs in semi-arid Tanzania. The exogenous constructs, derived from TPB, constitute the behavioral antecedents that drive adoption decisions. Attitudes toward CSA encompass agripreneurs’ evaluative beliefs regarding climate-smart practices and their anticipated outcomes, including enhanced yields, improved soil health, and strengthened climate resilience. Subjective norms capture the social influences emanating from significant referents, namely peers, family members, community leaders, and agricultural extension officers, who shape adoption decisions through normative pressure. Perceived behavioral control represents agripreneurs’ beliefs concerning their capability to implement CSA practices, encompassing their confidence in accessing requisite resources, technical knowledge, and their ability to overcome potential implementation barriers. These three exogenous constructs exert influence on CSA adoption both directly and indirectly through the mediating construct. Perceived usefulness, adapted from TAM, functions as the mediating construct that channels the influence of the exogenous constructs toward adoption behavior. This construct embodies agripreneurs’ assessment of the practical benefits and utility that CSA practices confer within their specific farming context. When agripreneurs perceive CSA as instrumental in enhancing productivity, mitigating climate risks, improving profitability, and ensuring long-term sustainability, the likelihood of adoption increases substantially. The mediating role of perceived usefulness assumes particular significance in resource-constrained environments where agripreneurs must judiciously evaluate whether the anticipated benefits warrant their limited resource investment, as illustrated in Fig. 1 . Fig. 1. Open in a new tab Conceptual framework. The hypothesized relationships are as follows: H01 Positive attitudes (ATT) toward CSA practices does not increase farmers perceived usefulness (PU) of CSA practices. H02 Positive subjective norms (SN) do not influence farmers’ perceived usefulness (PU) of CSA practices. H03 Higher perceived behavioral control (PBC) does not positively influence farmers’ perceived usefulness (PU) of CSA practices. H04 The perceived usefulness (PU) of CSA practices do not positively influences their adoption of CSA practices. Methodology Study area This study was conducted in the semi-arid regions of Central Tanzania, focusing on Ihumwa and Iyumbu Wards in Dodoma City and Uhamaka and Unyambwa Wards in Singida Municipality. These areas are characterized by unpredictable rainfall patterns, prolonged dry spells, and rising temperatures, making them particularly vulnerable to the adverse effects of climate change 27 , 28 . The predominant reliance on rain-fed agriculture in these regions underscores the urgent need for adaptive strategies to enhance agricultural resilience. Dodoma City and Singida Municipality were purposively selected due to their significant contribution to leafy vegetable production and high exposure to climate variability, making them ideal for investigating the behavioral determinants of climate-smart agriculture (CSA) adoption 29 . To provide geographical context, Fig. 2 presents maps illustrating the administrative divisions of Dodoma and Singida regions, as well as the specific wards where data were collected. These maps, developed using data from the National Bureau of Statistics (NBS) and OpenStreetMap Contributors, highlight the spatial distribution of the selected wards and their significance within the semi-arid zone. Fig. 2. Open in a new tab Maps illustrating the administrative divisions of Dodoma and Singida regions, as well as the specific wards where data were collected. Maps were created using QGIS version 3.28 ( https://qgis.org ) with administrative boundary data from the National Bureau of Statistics (NBS) of Tanzania and OpenStreetMap Contributors ( https://www.openstreetmap.org ). Research design and sampling Research design and sampling The present investigation employed a cross-sectional survey design to examine the relationships between behavioral factors and CSA adoption, thereby providing a comprehensive snapshot of these dynamics among leafy vegetable agripreneurs. The research design was underpinned by an extended version of Ajzen’s Theory of Planned Behavior, which incorporated perceived usefulness as a mediating factor 25 , 26 . This theoretical framework facilitated a systematic analysis of how attitudes, subjective norms, and perceived behavioral control influence CSA adoption through the mediating role of perceived usefulness. To enhance representativeness, a multi-stage sampling technique was implemented. Initially, four wards were purposively selected based on their significance in leafy vegetable production. Subsequently, villages within each ward were stratified according to production scale and crop variety, with respondents randomly selected from each stratum to ensure sample diversity and balance. The final sample comprised 385 respondents, determined through Cochran’s formula utilizing a 95% confidence level and a 5% margin of error. Data collection instrument and pre-testing Data collection was accomplished through the administration of a structured questionnaire specifically designed to assess the behavioral factors influencing CSA adoption. The instrument comprised distinct sections measuring attitudes toward CSA practices (12 items), subjective norms (6 items), perceived behavioral control (7 items), perceived usefulness (6 items), and actual CSA adoption behavior (10 items). All constructs were operationalized using items adapted from validated scales established in previous agricultural adoption research (detailed construct operationalization and sources are provided in Supplementary Table S1 ). The measurement of attitudes incorporated items addressing perceived benefits, adapted from 30 , 31 . Subjective norm items, derived from 25 , 32 , evaluated the influence of peers, family members, and extension officers on CSA adoption decisions. Perceived behavioral control items, adapted from 25 , 33 , assessed access to financial resources, technical knowledge, and institutional support. Items measuring perceived usefulness were adapted from 26 , 34 , emphasizing practical benefits including enhanced yields and economic returns. CSA adoption behavior items were developed based on 35 , 36 , examining the frequency of practices including crop rotation, mulching, and improved seed utilization. All responses were measured using a five-point Likert scale, ranging from strongly disagree (1) to strongly agree (5). Prior to full-scale data collection, the questionnaire underwent rigorous pre-testing with 30 leafy vegetable agripreneurs in Ikungi District, selected for its comparable agroecological conditions. The pre-test feedback informed refinements to wording, structure, and translation, thereby enhancing clarity and cultural relevance. Reliability assessment yielded Cronbach’s alpha values exceeding 0.7 across all constructs, demonstrating strong internal consistency. Content validity was established through systematic reviews conducted by agricultural extension officers and CSA experts possessing extensive knowledge of the Tanzanian agricultural context. Data analysis The analytical approach employed Partial Least Squares Structural Equation Modeling (PLS-SEM) utilizing Smart PLS 4 software to examine relationships among the latent constructs. The selection of PLS-SEM over covariance-based SEM (CB-SEM) was predicated on several methodological considerations: (1) the exploratory nature of extending the TPB model with perceived usefulness within a novel context; (2) the sample size of 385, which, while adequate for PLS-SEM, might prove constraining for CB-SEM; (3) the emphasis on prediction and variance explanation in CSA adoption rather than theory confirmation; and (4) the capacity of PLS-SEM to accommodate complex models with multiple relationships without requiring distributional assumptions (Hair et al., 2019; Sarstedt et al., 2017). The analysis followed a systematic two-step approach: initially, the measurement model underwent assessment to establish reliability and validity, followed by evaluation of the structural model to test the hypothesized relationships. Internal consistency was evaluated through Cronbach’s alpha and composite reliability metrics, both of which exceeded the established threshold of 0.7 (Hair et al., 2019). Convergent validity was demonstrated through Average Variance Extracted (AVE) values surpassing 0.5, while discriminant validity was established utilizing both the Fornell-Larcker criterion and the heterotrait-monotrait (HTMT) ratio. Although the Fornell-Larcker criterion represents a traditional approach, this study prioritized the HTMT ratio given its superior sensitivity in assessing discriminant validity, particularly within PLS-SEM applications (Henseler et al., 2015). HTMT values below 0.85 confirmed that constructs were sufficiently distinct. The structural model analysis employed bootstrapping with 5,000 resamples to generate path coefficients, t-values, and p-values, thereby establishing statistical significance for the proposed relationships. The model’s explanatory power was assessed through R-squared values, which quantified the proportion of variance in endogenous constructs explained by their predictors. Furthermore, predictive relevance was evaluated using Stone-Geisser’s Q² values obtained through blindfolding procedures, while multicollinearity was examined via Variance Inflation Factor (VIF) values. Model fit assessment utilized the Standardized Root Mean Square Residual (SRMR), with values below 0.08 indicating acceptable fit (Hu & Bentler, 1999). Throughout the refinement process, indicators underwent systematic review. Items exhibiting factor loadings below 0.7 or substantial cross-loadings were systematically eliminated to enhance the model’s overall quality and performance. This rigorous analytical approach ensured robust and reliable results, thereby strengthening the validity of the study’s findings. Ethical considerations The data collection instruments, was reviewed and approved by the Departiment of Development and Strategic Studies, Sokoine University of Agriculture (SUA), Directorate of Postgraduate Studies, Research, Technology Transfer and Consultancy (Ref: SUA/DPRTC/PDS/D/2021/0005/12). The SUA Vice Chancellor’s Office issued national clearance (Ref: SUA/ADM/R.1/8/1140). Following this clearance, the President’s Office for Regional Administration and Local Government (PO RALG) granted permission to conduct the study in five regions of Central Tanzania: Dodoma, Singida, Tabora, Simiyu, and Shinyanga. This approval was confirmed through Reference No. AB.307/323/01/190 dated 18 December 2023. Additional regional and district-level permissions were also obtained, including from the City Council of Dodoma (Ref: HJD/F.10/609), to support access and cooperation during the research process. All procedures adhered to institutional, national, and international ethical standards. The study protocol was approved by the SUA Institutional Research Review Committee (Ref: SUA/IRB/2023-009). Informed consent was obtained from all participants, who signed consent forms after being fully briefed on the study. Confidentiality and privacy were rigorously maintained throughout data collection and analysis. Results Measurement model assessment The measurement model underwent comprehensive evaluation to establish the reliability and validity of the constructs employed in this investigation. Factor loadings for all retained indicators exhibited values ranging from 0.705 to 0.918, thus surpassing the recommended threshold of 0.7 and demonstrating robust correlations between observed variables and their corresponding constructs (detailed factor loadings are presented in Supplementary Table S2 ). Reliability assessment through Cronbach’s alpha and composite reliability metrics yielded values surpassing the established threshold of 0.7 across all constructs, as illustrated in Table 1 . Convergent validity was substantiated through Average Variance Extracted (AVE) values exceeding 0.5, thereby confirming that a substantial proportion of variance in the observed variables was captured by their respective constructs. Table 1. Reliability and validity of constructs. Construct Cronbach’s alpha Composite reliability AVE Attitude toward CSA 0.929 0.942 0.670 Perceived behavioral control (PBC) 0.875 0.910 0.671 Subjective norms (SN) 0.842 0.894 0.679 Perceived usefulness (PU) 0.846 0.898 0.688 CSA adoption 0.879 0.906 0.578 Open in a new tab Discriminant validity was established through both the heterotrait-monotrait (HTMT) ratio (Table 2 ) and the Fornell-Larcker criterion (Table 3 ). Notably, all HTMT ratios remained below the stringent threshold of 0.85, thereby confirming construct distinctiveness. Furthermore, the square root of AVE for each construct (indicated by bold diagonal values in Table 3 ) exceeded its correlations with other constructs, providing additional evidence of discriminant validity. Collectively, these findings demonstrate that the measurement model exhibited robust psychometric properties, thus ensuring adequate reliability and validity for subsequent structural analysis. Table 2. Discriminant validity assessment—HTMT ratio. Attitude CSA CSA adoption PBC Perceived usefulness Social norms Attitude CSA – CSA adoption 0.717 – Perceived behavioral control (PBC) 0.705 0.846 – Perceived usefulness 0.588 0.590 0.635 – Subjective norms 0.368 0.386 0.299 0.797 – Open in a new tab Table 3. Discriminant validity assessment—Fornell–Larcker criterion. Attitude CSA CSA adoption PBC Perceived usefulness Social norms Attitude CSA 0.819 CSA adoption 0.683 0.760 Perceived behavioral control 0.672 0.798 0.819 Perceived usefulness 0.547 0.538 0.587 0.830 Subjective norms 0.341 0.348 0.274 0.722 0.824 Open in a new tab Bold diagonal values represent the square root of AVE. Structural model assessment The structural model demonstrated acceptable fit with SRMR = 0.078, remaining below the recommended threshold of 0.08. The model accounted for 61.2% of the variance in perceived usefulness and 26.7% of the variance in CSA adoption behavior (Table 4 ). Moreover, predictive relevance was substantiated through Q 2 values exceeding zero (CSA Adoption Q 2 = 0.148; Perceived Usefulness Q 2 = 0.409), thereby confirming the model’s capacity to predict these endogenous constructs as illustrated in Fig. 3 . Table 4. Model fit and explanatory power. Variable R -square R -square adjusted Q 2 CSA adoption 0.267 0.266 0.148 Perceived usefulness 0.612 0.609 0.409 Open in a new tab Fig. 3. Open in a new tab Structural model with path coefficients and R-squared values. The empirical analysis provided support for all hypothesized relationships at the 95% confidence level (Table 5 ). Attitudes emerged as the most robust predictor of perceived usefulness (β = 0.528, p < 0.001), suggesting that favorable evaluations of CSA practices substantially enhance farmers’ perceptions of their utility. Subjective norms exerted a positive influence on perceived usefulness (β = 0.231, p < 0.01), underscoring the significance of social influences within the adoption process. Similarly, perceived behavioral control demonstrated a positive effect on perceived usefulness (β = 0.198, p < 0.05), indicating that farmers possessing greater confidence in their implementation capabilities are more inclined to perceive CSA as beneficial. Notably, perceived usefulness exhibited a strong positive influence on CSA adoption behavior (β = 0.580, p < 0.001), thereby confirming its pivotal role in the adoption process. All VIF values remained below 3.3, effectively precluding multicollinearity concerns. Table 5. Hypothesis testing results. Hypothesis Path β t-value p -value VIF Result H1 Attitudes → perceived usefulness 0.528*** 7.56 < 0.001 2.31 Supported H2 Subjective norms → perceived usefulness 0.231** 4.10 < 0.01 1.84 Supported H3 PBC → perceived usefulness 0.198* 3.21 < 0.05 2.45 Supported H4 Perceived usefulness → CSA adoption 0.580*** 8.03 < 0.001 1.92 Supported Open in a new tab *Note: *** p < 0.001, ** p < 0.01, p < 0.05; VIF, Variance inflation factor. The mediation analysis substantiated that perceived usefulness significantly mediates the relationships between all behavioral determinants and CSA adoption (Table 6 ). The most pronounced indirect effect emanated from attitudes (0.273), followed by subjective norms (0.190) and perceived behavioral control (0.135). The statistical significance of all indirect effects corroborates the central mediating role of perceived usefulness within the extended TPB framework. Table 6. Mediation analysis results. Mediation path Indirect effect t-value p -value 95% CI Attitudes → PU → CSA adoption 0.273*** 5.61 < 0.001 [0.179, 0.374] Subjective norms → PU → CSA adoption 0.190*** 4.10 < 0.001 [0.098, 0.285] PBC → PU → CSA adoption 0.135** 3.21 0.002 [0.051, 0.223] Open in a new tab *Note: *** p < 0.001, * p < 0.01; CI , Confidence interval; PU, Perceived usefulness. Discussion Behavioral determinants of CSA adoption The present investigation elucidated the behavioral factors influencing climate-smart agriculture (CSA) adoption among smallholder leafy vegetable agripreneurs in semi-arid Central Tanzania. Employing an extended version of Ajzen’s Theory of Planned Behavior (TPB) that incorporates perceived usefulness as a mediating factor, this study examined the complex interplay among attitudes, subjective norms, perceived behavioral control, and perceived usefulness in shaping adoption decisions. The empirical evidence demonstrates that attitudes constitute the most robust predictor of both perceived usefulness (β = 0.528, p < 0.001) and CSA adoption behavior, thereby underscoring the pivotal role of positive perceptions in facilitating the uptake of sustainable agricultural practices. This finding corroborates previous research that emphasizes the significance of attitudinal factors in promoting environmentally sustainable behaviors 18 , 19 . Agripreneurs who associate CSA practices with tangible benefits, including enhanced yields, improved soil health, and strengthened climate resilience, demonstrate greater propensity toward adoption. Consequently, strengthening agricultural extension services, establishing farmer field schools, and implementing demonstration plots represent critical strategies for reinforcing positive attitudes through the tangible demonstration of CSA’s practical advantages 37 , 7 . Furthermore, subjective norms emerged as a significant determinant of perceived usefulness (β = 0.231, p < 0.01) and, consequently, adoption behavior, highlighting the substantial influence of social dynamics in agricultural decision-making processes. Within rural farming communities, agricultural choices are predominantly shaped by social networks comprising family members, peers, and community leaders 21 , 23 . The positive relationship between subjective norms and perceived usefulness indicates that when agripreneurs observe successful CSA implementation among their peers and receive encouragement from their social networks, the likelihood of perceiving these practices as beneficial increases substantially. Therefore, strengthening social learning networks, enhancing farmer cooperatives, and establishing community-based knowledge-sharing platforms can effectively facilitate peer-to-peer learning and accelerate CSA adoption 11 , 4 . Additionally, perceived behavioral control, which reflects agripreneurs’ confidence in their capacity to implement CSA practices, positively influenced perceived usefulness (β = 0.198, p < 0.05). This finding aligns with prior research that identifies resource constraints as fundamental barriers to sustainable agricultural practice adoption 17 , 4 . Agripreneurs who perceive adequate access to resources, technical knowledge, and institutional support demonstrate greater inclination to view CSA as both feasible and beneficial. The relatively modest coefficient compared to attitudes and subjective norms suggests that while control beliefs remain important, they may exert less influence than personal evaluations and social pressures within this specific context. Enhanced access to input subsidies, capacity-building programs, and credit facilities can substantially improve farmers’ confidence in CSA adoption 37 , 7 . Mediating role of perceived usefulness The investigation revealed that perceived usefulness significantly mediates the relationships between all behavioral determinants and CSA adoption, thereby confirming its crucial function within the extended TPB framework. The model accounted for 61.2% of the variance in perceived usefulness (R 2 = 0.612, adjusted R 2 = 0.609), with attitudes, subjective norms, and perceived behavioral control collectively explaining this substantial proportion. This high explanatory power indicates that these three behavioral factors comprehensively shape farmers’ perceptions regarding CSA’s practical benefits. Subsequently, perceived usefulness strongly influenced CSA adoption behavior (β = 0.580, p < 0.001), contributing to 26.7% of the variance in adoption (R 2 = 0.267, adjusted R 2 = 0.266). The mediation analysis revealed differential indirect effects, with attitudes demonstrating the most pronounced influence on CSA adoption through perceived usefulness (indirect effect = 0.273, p < 0.001), followed by subjective norms (indirect effect = 0.190, p < 0.001) and perceived behavioral control (indirect effect = 0.135, p = 0.002). These findings substantiate that perceived usefulness functions as a critical cognitive bridge, effectively translating behavioral beliefs into actual adoption decisions. This mediating mechanism assumes particular significance in resource-constrained settings where farmers must judiciously evaluate the practical benefits of innovations before committing scarce resources 38 . The prominent mediating role of perceived usefulness suggests that agripreneurs who perceive CSA as instrumental in enhancing productivity, generating economic gains, and building climate resilience demonstrate higher adoption likelihood, regardless of initial attitudes or prevailing social pressures 11 , 4 . This corroborates previous investigations indicating that farmers’ adoption decisions are primarily driven by perceptions of tangible benefits from agricultural innovations 19 , 23 . Moreover, these findings validate the theoretical decision to extend the TPB model with perceived usefulness, as this integration captures a critical cognitive evaluation process mediating between behavioral determinants and actual behavior. To optimize CSA adoption, interventions should prioritize strategies that enhance perceived usefulness. These include: Establishing demonstration plots that showcase quantifiable yield improvements and economic returns. Facilitating farmer testimonials that highlight practical benefits derived from firsthand experience. Developing cost-benefit analyses presented in accessible, farmer-friendly formats. Implementing training programs that explicitly link CSA practices to addressing farmers’ specific challenges. Through simultaneously enhancing perceived usefulness while addressing attitudes, social norms, and control beliefs, policymakers and development practitioners can design more effective interventions that align with farmers’ decision-making processes 37 , 7 . Policy implications The findings of this study underscore the imperative for targeted policy interventions to enhance climate-smart agriculture (CSA) adoption among smallholder leafy vegetable farmers in semi-arid Central Tanzania. These interventions should align with Tanzania’s National Agriculture Policy (NAP, 2013), Climate-Smart Agriculture Guidelines (URT, 2017), and the Tanzania Horticulture Development Strategy (THDS, 2012) to ensure sustainable agricultural transformation. Strengthening public-private partnerships (PPPs) in CSA financing, infrastructure development, and extension service delivery will create a more conducive policy environment for widespread CSA adoption 39 . The enhancement of agricultural extension services constitutes a fundamental prerequisite for improving CSA knowledge dissemination and adoption rates. Given that attitudes emerged as the strongest predictor of adoption, extension programs should prioritize demonstrating tangible benefits through established farmer field schools and demonstration plots in each ward. The NAP (2013) and THDS (2012) recognize extension services as pivotal for agricultural productivity enhancement and resilience building. Expanding CSA-focused training through digital platforms and participatory approaches would facilitate broader knowledge dissemination and practical skill development. Integration of CSA modules into Tanzania’s E-Agriculture Strategy (URT, 2016) would further extend outreach capacity, particularly for smallholder farmers in remote semi-arid areas 40 . Furthermore, addressing financial accessibility remains critical, as perceived behavioral control significantly influences adoption decisions. High input costs and limited capital access constitute substantial barriers to CSA adoption among resource-constrained agripreneurs. The Tanzania Agriculture and Food Security Investment Plan (TAFSIP, 2011) emphasizes financial inclusion as transformative for agricultural development. Policy interventions should therefore prioritize scaling up targeted subsidies for CSA inputs, providing accessible low-interest loans through Tanzania Agricultural Development Bank (TADB), and expanding climate-risk insurance coverage through microfinance institutions. Encouraging blended finance models and private-sector investments can substantially enhance access to CSA technologies, credit facilities, and climate-resilient farming inputs 39 , 1 . Given the significant role of subjective norms in shaping adoption decisions, leveraging existing farmer cooperatives and social networks becomes paramount. Establishing ward-level CSA learning groups and strengthening farmer-to-farmer extension approaches can harness social influence mechanisms effectively. Investment in climate-resilient infrastructure, including irrigation systems and storage facilities, would address control belief constraints while promoting sustained adoption. Additionally, fostering agribusiness collaborations through contract farming arrangements can provide assured markets for leafy vegetables produced using CSA practices, thereby enhancing perceived usefulness through guaranteed economic returns. Aligning national CSA strategies with regional frameworks such as the Malabo Declaration (2014) can unlock additional funding opportunities while contributing to broader objectives of food security (SDG 2), climate resilience (SDG 13), and smallholder economic empowerment. Through integrating these behavioral insights into policy formulation and implementation, stakeholders can create an enabling environment that effectively supports widespread CSA adoption among leafy vegetable agripreneurs in Tanzania’s semi-arid regions. Limitations of the study Notwithstanding its contributions, this finding presents several limitations warranting acknowledgment. First, the cross-sectional design captures behavioral factors at a single temporal point, thereby constraining causal inferences regarding the relationships between variables. Second, the focus on leafy vegetable agripreneurs within semi-arid Tanzania may limit the generalizability of findings to other crop systems or agroecological zones. Third, reliance on self-reported measures introduces potential social desirability bias, possibly resulting in overestimation of CSA adoption rates. These limitations underscore the necessity for further research to comprehensively understand CSA adoption dynamics across diverse contexts. Conclusion This investigation has generated substantial empirical evidence elucidating the behavioral factors that drive CSA adoption among smallholder leafy vegetable agripreneurs in semi-arid Central Tanzania. The findings confirm that attitudes, subjective norms, and perceived behavioral control significantly influence adoption decisions, with perceived usefulness serving as a critical mediating mechanism. These results reinforce the imperative for targeted interventions that promote CSA adoption through comprehensive awareness campaigns, capacity-building initiatives, and enhanced access to financial and institutional support. The prominent role of social networks suggests that farmer cooperatives should be strategically leveraged to facilitate knowledge dissemination and peer learning. Policy frameworks aligned with Tanzania’s National Agriculture Policy and Climate-Smart Agriculture Guidelines should prioritize strengthening public-private partnerships, improving rural infrastructure, and expanding digital extension services to reach remote farming communities. Although the cross-sectional design limits causal inference, this study provides foundational understanding of the psychosocial dynamics influencing CSA adoption in resource-constrained environments. Future research should employ longitudinal designs to track temporal changes in behavioral determinants and adoption patterns. Additionally, investigations should explore economic and market-driven factors, including input costs, market access, and supply chain efficiency, to develop comprehensive understanding of adoption barriers and enablers. Through systematically addressing behavioral barriers and enhancing perceived usefulness, stakeholders can foster sustainable agricultural transitions that strengthen food security and build resilience in climate-vulnerable regions of Tanzania and beyond 41 – 49 . Supplementary Information Below is the link to the electronic supplementary material. Supplementary Material 1 (325.1KB, pdf) Acknowledgements The authors sincerely thanks Mr. Octavian Deomedes and Mr. Elisha John for their dedicated support in data collection. Special appreciation is extended to Dr. Christopher Mdoe and Dr. Kulwa Mang’ana for coordinating field activities. May God Almighty bless them abundantly. Author contributions S.B.E. collected data, analysed data and wrote the main manuscript. J.S.M. Prepared data collection tools and reviewed the first draft. R.S. Prepared data analysis software, analysed data, and reviewed the final draft. Data availability The datasets generated and/or analyzed during this study are not publicly available due to institutional restrictions imposed by Sokoine University of Agriculture but are available from the corresponding author upon reasonable request. Declarations Competing interests The authors declare no competing interests. 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(2017). https://www.fao.org/3/i8757en/I8757EN.pdf Associated Data This section collects any data citations, data availability statements, or supplementary materials included in this article. Supplementary Materials Supplementary Material 1 (325.1KB, pdf) Data Availability Statement The datasets generated and/or analyzed during this study are not publicly available due to institutional restrictions imposed by Sokoine University of Agriculture but are available from the corresponding author upon reasonable request. 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