Determinants of Working Capital Financing Through Digital and Policy Interventions: A Survey of Farmers in Dhule District Maharashtra.

Journal of Research and Development A Multidisciplinary International Level Referred and Double Blind Peer Reviewed, Open Access ISSN : 2230-9578 | Website: https://jrdrvb.org Volume-17, Issue-11(I)| November 2025 142 Determinants of Working Capital Financing Through Digital and Policy Interventions: A Survey of Farmers in Dhule District Maharashtra. Deepak Suklal Pawar1, (Dr) Rajendra Sinha2 1Research Scholar Department Management Finance Sandip University Nashik, Mahiravani, Trambakeshwar Road, Taluka & District Nashik, Maharashtra, India. 2ViceChancellor Sandip University Department Management Finance Sandip UniversityNashik,Mahiravani,Trambakeshwar Road,Taluka&District Nashik Maharashtra, India Manuscript ID: JRD -2025-171131 ISSN: 2230-9578 Volume 17 Issue 11 (I) Pp. 142-154 Nov. 2025 Submitted:15 Oct. 2025 Revised: 25 Oct. 2025 Accepted: 10 Nov. 2025 Published: 30 Nov. 2025 Abstract Agriculture remains the backbone of India’s rural economy, with farmers depending heavily on timely and affordable credit to sustain their operations. Working capital finance—covering recurring expenses such as seeds, fertilizers, irrigation, and labour—has long been dominated by informal credit channels, leading to recurring cycles of debt and financial vulnerability. In recent years, however, digital innovations such as mobile banking, the Unified Payments Interface (UPI), Aadhaar-enabled payment systems, and digital Kisan Credit Cards have begun transforming the agricultural credit landscape. Alongside these advances, institutional mechanisms introduced by NABARD and policy interventions by the Central and State governments aim to strengthen access to structured and affordable working capital finance. This study examines the convergence of digital financial innovations and policy mechanisms in supporting farmers’ working capital needs, with specific reference to Dhule District, Maharashtra. A descriptive research design was adopted, involving primary data collection from 419 farmers across four talukas (Dhule, Shindkheda, Sakri, and Shirpur) through structured questionnaires, supplemented by qualitative insights from 55 officials representing NABARD, banks, and Panchayat Raj institutions. Statistical analyses—including ANOVA, Chi-square, Correlation and Regression—were conducted using SPSS 25 to test hypotheses related to the impact of digital innovations, awareness of government schemes, and their combined influence on the sustainability of agricultural finance. The findings reveal that digital financial tools significantly improve the efficiency of working capital management, while farmers’ awareness of government schemes strongly influences their adoption of formal credit channels. Moreover, the integration of technological innovations with supportive policy frameworks substantially enhances the sustainability of agricultural finance. The study contributes valuable insights toward modernizing rural finance, strengthening farmer resilience, and promoting sustainable agricultural development in India. Keywords: Working Capital Finance, Digital Finance, Agricultural Schemes, Farmer Awareness, India. Introduction: Agriculture forms the backbone of India’s rural economy, contributing substantially to national food security, employment generation, and socio-economic stability. Despite its central role, the sector continues to grapple with persistent financial constraints, particularly in the domain of working capital management. Small and marginal farmers, who constitute the majority of the agricultural workforce, frequently depend on informal credit channels due to limited access to institutional finance. These informal sources often charge exorbitant interest rates, thereby trapping farmers in cycles of indebtedness and financial vulnerability. Although the National Bank for Agriculture and Rural Development (NABARD) and other regulatory bodies have introduced several policies and financial instruments aimed at improving credit accessibility—such as flexible loan products, interest subvention schemes, and risk-mitigation mechanisms—a number of structural barriers continue to impede their effective utilisation. Quick Response Code: Website: https://jrdrvb.org/ DOI: Creative Commons (CC BY-NC-SA 4.0) This is an open access journal, and articles are distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International Public License, which allows others to remix, tweak, and build upon the work noncommercially, as long as appropriate credit is given and the new creations ae licensed under the idential terms. Address for correspondence: Deepak Suklal Pawar,Research Scholar Department Management Finance Sandip University, Nashik, Mahiravani, Trambakeshwar Road, Taluka & District Nashik 422213 Maharashtra, India. How to cite this article: Deepak Suklal Pawar, Rajendra Sinha (2025). Determinants of Working Capital Financing Through Digital and Policy Interventions: A Survey of Farmers in Dhule District Maharashtra. Journal of Research & Development, 17(11(I)), 142-154. Original Article Journal of Research and Development A Multidisciplinary International Level Referred and Double Blind Peer Reviewed, Open Access ISSN : 2230-9578 | Website: https://jrdrvb.org Volume-17, Issue-11(I)| November 2025 143 Delays in loan sanctioning, collateral obligations, bureaucratic procedures, inadequate financial literacy, and limited awareness of available schemes reduce the overall efficiency of these initiatives. Furthermore, infrastructural bottlenecks, technological gaps, and persistent reliance on intermediaries weaken transparency and discourage farmers from fully engaging with formal financial institutions. To address these challenges, the Central and State governments, along with NABARD, have introduced targeted interventions including the Kisan Credit Card (KCC), crop loan interest subvention, and various workingcapital support schemes through cooperative banks and regional rural banks. These measures are designed to ensure timely, affordable, and structured access to working capital, thereby promoting financial stability and agricultural sustainability. However, the adoption and effectiveness of these schemes vary widely across regions and are particularly constrained in semi-urban and rural districts such as Dhule, where deficits in digital literacy, infrastructural inequities, and uneven dissemination of information continue to hinder widespread utilisation. In this context, understanding the complementary role of digital financial innovations—such as mobile banking, UPI, Aadhaar-enabled services, and digital KCC platforms—alongside government policy mechanisms becomes critical. Examining how these instruments collectively influence farmers’ working capital decisions is essential for developing a sustainable, inclusive, and resilient agricultural financial ecosystem. Literature Review: (Yan, Chen, Zhou, && Wei, 2025) In China, digital inclusive finance significantly improved agricultural mechanization, demonstrating how rural finance technologies can modernize farming operations and boost productivity. (Xu, 2025) Digital inclusion expands affordable financial services to small farmers, aiding technological adoption and sustainable farming. It helps rural entities access resources conveniently. (Cao, 2025) Digital financial inclusion increases farmers’ capacity to manage agricultural risks. Using panel data, Cao (2025) finds it boosts anti-risk capacity by ~14% and shows nonlinear spatial effects. (Wikipedia, 2025) India’s FinTech sector has exploded, especially payments and digital lending, with thousands of start-ups and billions in investments—creating financial infrastructure that agriculture can leverage. (RUGR’s, 2025) India’s RUGR ecosystem (e.g., AGRI-GRAM for farmers, FIN-GRAM for literacy) provides vernacular digital finance tools, enhancing rural financial inclusion and serving as a scalable model for farm credit. (NABARD, 2024) As India’s apex rural finance bank, it plays a critical role in refinancing, regulating rural banks, and promoting schemes for agricultural creditvital for working capital supply. (A Study on Role of NABARD, 2021) Highlight how NABARD supports rural prosperity through financial inclusion, credit schemes for hortiand agri-processing—driving sustainable rural finance. (Kumar & Afroz, 2022) Research by NABARD professionals shows how access to institutional credit influences adoption of modern technologies and farm investment, affecting regional disparities. (NABARD, 2025) Empirical studies (Madhya Pradesh) demonstrate NABARD’s impact in farmer empowerment through training, institutional support, and building financial/institutional capacity for modern technology use (IJFMR, 2025). (Karlan, 2016) Credit plays a foundational role in helping farmers adopt modern production techniques; institutional access is critical for agricultural modernization. IMF reports highlight that digital access to payments and credit services is central to financial inclusion and enhancing smallholder access to finance in rural contexts (IMF, 2023). (FHI 360, 2018)India’s digital financial inclusion has surged since 2014, especially in rural areas, driven by mobile banking, UPI, and merchant payments. Inclusive initiatives by government and private sectors have facilitated affordable payments and credit access. (E-Choupal, 2025) ITC’s e-Choupal platform provides real-time market access, improving transparency, market efficiency, and reducing reliance on intermediaries—empowering rural farmers. (Wikipedia, Common Service Centres, 2025) CSCs under PMGDISHA are pivotal in promoting digital literacy and access to financial services in rural India, which supports farmers’ financial inclusion and scheme utilization. (Gupta et al., 2016) In regions with intermittent connectivity, DTN models have enabled agro-advisory services via relay nodes—facilitating digital access in marginal connectivity zones. (Chetri, Sharma, && Ilavarasan, 2021) ICT ecosystems play a vital role in disaster-adaptive capacity. In Haryana, access to ICT-mediated information was linked to farmers’ resilience against climate shocks. (Pranto, All Noman, Mahmud, && Haque, 2021) Innovative technologies, such as blockchain combined with IoT, can automate preand post-harvest processes, ensuring transparency and building trust in agricultural value chains. (Darapaneni et al., 2022) Conversational interfaces using WhatsApp and chatbots (Farmer-Bot) are being developed to provide scalable agri-advisory through NLP, representing a move toward digital-enabled literacy and finance support (Initiative, 2025) Reviews India’s sustainable agriculture finance flows, indicating policy shifts toward resilient, climate-smart funding instruments in agriculture. (Huang, 2023) Digital financial inclusion has been empirically shown to boost agricultural operating income and support food security, emphasizing its economic importance for farmers. Journal of Research and Development A Multidisciplinary International Level Referred and Double Blind Peer Reviewed, Open Access ISSN : 2230-9578 | Website: https://jrdrvb.org Volume-17, Issue-11(I)| November 2025 144 (Sarker, 2024) NABARD’s evolving role—from refinancing to microfinance and watershed fundinghas shaped rural finance. Historical reviews underline its essential institutional contributions. (Kumar && Afroz, 2022) Quantify how institutional credit enables technology adoption across regions—highlighting working capital’s role in modernization and disparity reduction. (e-NAM, Wikipedia, 2025) The e-NAM platform enhances transparent commodity trading via mobile apps, linking farmers directly with market networks and improving price realization. (NABARD, 2024) Research on credit, insurance, storage, and marketing provides comprehensive overviews on enabling infrastructure and working capital access for farmers. (Narayanamurthy, 2025) Data-driven digital transformation in institutional crop credit systems can mitigate uncertainty and improve working capital flows, providing institutional finance stability. (Karlan, 2016) Summarizes global evidence on what digital financial inclusion interventions work—highlighting both successes and failures critical for crafting digital-savvy agricultural finance models. (Chetri, Sharma, && Ilavarasan, 2021) Demonstrate that ICT ecosystems significantly enhance farmers’ ability to adapt to climate risk, reinforcing the role of digital awareness beyond just finance. (Pranto, All Noman, Mahmud, && Haque, 2021) The integration of blockchain and smart contracts with IoT for traceability adds transparency and trust to agri-credit processes—relevant for working capital disbursement and scheme tracking. (Darapaneni, Tiwari, Paduri, & al, 2022)Chatbot systems like Farmer-Bot demonstrate scalable digital advisory and financial literacy tools that can increase awareness and adoption of financing schemes. (Huang, 2023)Illustrate that digital inclusive finance strengthens agricultural resilience against shocks, emphasizing sustainability—a key lens for your research on working capital stability. (Li, 2025) Demonstrates that digital financial inclusion significantly boosts farmers’ income in Inner Mongolia, with pronounced spatial spillover effectshighlighting digital finance as a rural development catalyst. (Biswal, 2022) Underscores that low educational levels drive poor crop insurance uptake in India; farmers often lack comprehension of product features, reducing risk adoption. (Fund, 2023) Emphasizes that access to digital payments and credit underpins financial inclusion; modernizing this access is vital for equitable rural finance. (Doe, 2025) A Namakkal study finds a stark gap between farmers’ awareness of agricultural schemes and their actual participationpointing to systemic outreach and implementation challenges. (Vasudevan, 2025) Showcases how FinTech tools foster sustainable agriculture, climate resilience, and environmental stewardship among Tamil Nadu farmers, pairing financial inclusion with green practices. (Dhull & Anshu, 2022) Document that awareness of crop loans and insurance varies across Haryana’s regions, influenced by education, access to information, and local disparitieslinking awareness to adoption. (Kumar, 2025) A Kerala-based study highlights how grassroots farmers' movements effectively boosted awareness and uptake of the Kisan Credit Card scheme through peer-to-peer knowledge transfer. (Weekly, 2025) Traces how digital finance is reshaping access to bank and mobile accounts globally and its potential to deepen rural finance inclusion. (Singh, 2024) IJIRT’s 2024 research stresses that financial literacy plays a key role in farmers’ utilization of KCC and crop insurance, but coordinated support from BCs and banks is lacking in rural Karnataka. (India, 2025) Spotlights RUGRa rural-oriented smart finance architecture (e.g., AGRI-GRAM, FIN-GRAM) designed to enhance financial inclusion using vernacular and embedded tools. (Reuters, 2024) Reports that satellite data (via Cropin) helped Indian farmers massively increase yields and profits by offering agronomic insights like optimal sowing times and weather forecasts. (Satnavri Maharashtra, 2025) Coverage of Satnavri’s experiment as India’s first "Smart Intelligent Village" integrating mobile banking, smart irrigation, drones, and education points toward digitally inclusive rural futures. (TOI, 2025) Highlights Uttarakhand’s rollout of e-RUPI vouchers—SMS/QR-based subsidies for seeds/fertilizers combined with digital training to enable hassle-free, transparent delivery. (Reuters, 2025) Explores how AI tools like predictive weather forecasting are helping Indian smallholders build climate resilience, reduce debt, and boost savings—showing AI’s promise for inclusive agriculture. (Wikipedia, 2025)provided data on over 95 million PM-KISAN beneficiaries, emphasizing how large-scale direct cash transfers are widely accessible but require complementary outreach and digital means. (Pranto, All Noman, Mahmud, && Haque, 2021)proposes a blockchain–IoT architecture to secure preand postharvest data, ensuring transparency and traceability with automation in agriculture. (Tiwari, 2022) Surveys ICT initiatives like e-learning, public–private systems, and NGOs, enabling knowledge sharing and gender inclusionvital for farmer empowerment and digital usage. (Vijayvargia, Nagpal, Pundalik, & a, 2025) Present Krishi Sathi, an AI-based, Hindi/English chatbot using RAG and multi-turn flow to provide personalized agri-advice to low-literacy farmers with 97.5% accuracy. (Biswas, 2021) Reveals that mobile financial services in India increase formal borrowing, insurance uptake, and investment—also helping narrow the gender finance gap. Journal of Research and Development A Multidisciplinary International Level Referred and Double Blind Peer Reviewed, Open Access ISSN : 2230-9578 | Website: https://jrdrvb.org Volume-17, Issue-11(I)| November 2025 145 (OPNDC, 2024)Highlights that over 5,000 FPOs sell value-added agri products via ONDC, enhancing market linkages and financial integration for rural producers. (e-NAM, 2025) Reports that e-NAM connects 18 APMC markets via an app with UPI payments, reducing inefficiencies and improving transparency in farmer-market finance. (CSC, 2025) Highlights CSCs' role under PMGDISHA in delivering digital literacy and financial services to rural households, improving access and economic inclusion. (Wikipedia, 2025) AI-driven social interventions for agriculture, including pest forecasting and digital tools for underserved farmers. Research Significance: Farmers in India—particularly those residing in semi-urban and rural regions such as Dhule District—continue to face persistent challenges in accessing adequate working capital. Despite the rapid expansion of digital financial technologies, including UPI, mobile banking, blockchain-based credit systems, e-NAM platforms, and various FinTech-driven solutions, a substantial proportion of farmers remain dependent on informal credit channels. This dependency is largely driven by limited digital literacy, inadequate awareness of financial products, infrastructural constraints, and socio-economic barriers. Although policy interventions introduced by NABARD, the Central Government, and State Governments are intended to bridge the rural credit gap, their actual impact on working capital utilisation, financial resilience, and longterm sustainability remains uneven. While digital tools promise greater efficiency, transparency, and scalability in agricultural finance, their potential is often undermined by inconsistent integration with policy mechanisms, procedural complexities, and regional disparities in implementation. As a result, farmers frequently experience incomplete adoption, limited benefits, and varied financial outcomes across different geographies. Dhule District—characterised by its diversified cropping patterns, socio-economic heterogeneity, and varying levels of digital readiness—presents a compelling context for examining these dynamics. Investigating how digital financial innovations and government policy frameworks interact, and whether their combined application strengthens working capital management, is crucial for generating actionable insights. The significance of the present study lies in its ability to provide empirical evidence on how integrated financial interventions can enhance working capital efficiency, reduce dependency on informal credit, mitigate risks, and ultimately contribute to sustainable agricultural development at the grassroots level. Research Gap: Although digital financial instruments and government-led policy frameworks are widely recognised as key drivers of rural financial inclusion, existing literature tends to examine these elements in isolation rather than as integrated components of a unified financial ecosystem. Prior studies frequently highlight the benefits of digital finance in improving access to credit, payment systems, and financial services, while others focus on the role of institutional schemes in supplying subsidised working capital. However, limited research investigates how these two dimensions interact and whether their synergy contributes to improved working capital management and financial sustainability among farmers. Furthermore, much of the available evidence is concentrated at the national or state level, overlooking the micro-level variations that significantly shape financial behaviour and adoption patterns. District-level contexts— such as Dhule, characterised by infrastructural gaps, heterogeneous digital literacy, and uneven awareness of government programmes—remain understudied, resulting in an incomplete understanding of ground realities.In addition, while existing scholarship examines agricultural productivity, income enhancement, and risk mitigation, the specific domain of working capital management within agriculture has received insufficient attention. Research seldom explores how farmers access, utilise, and sustain working capital in environments where both digital tools and policy interventions coexist. The absence of empirical insights on farmers’ behavioural responses, adoption challenges, and utilisation outcomes creates a critical void in understanding the effectiveness of integrated financial mechanisms. This gap underscores the need for a comprehensive investigation into how digital innovations and government policy frameworks jointly influence working capital management, financial resilience, and sustainable agricultural development at the grassroots level, particularly in districts like Dhule. Research Objectives  1. To critically analyse the role of digital financial innovations in improving farmers’ working capital management practices in Dhule District.*  2. To assess the level of awareness, accessibility, and adoption of NABARD-driven, Central Government, and State Government schemes related to working capital finance among farmers.  3. To evaluate the combined and interactive impact of digital financial innovations and government policy mechanisms on the sustainability and long-term effectiveness of agricultural finance in Dhule District. Journal of Research and Development A Multidisciplinary International Level Referred and Double Blind Peer Reviewed, Open Access ISSN : 2230-9578 | Website: https://jrdrvb.org Volume-17, Issue-11(I)| November 2025 146 Research Hypotheses 1. Alternative Hypotheses  H1a: Digital innovations significantly improve the efficiency and effectiveness of farmers’ working capital management.  H2a: Farmers’ awareness of NABARD, Central, and State government schemes significantly influences their adoption and utilization of working capital finance.  H3a: The integration of digital innovations with government policy mechanisms significantly enhances the sustainability of working capital finance for farmers. 2. Null Hypotheses  H01: Digital innovations do not significantly improve the efficiency and effectiveness of farmers’ working capital management.  H02: Farmers’ awareness of NABARD, Central, and State government schemes does not significantly influence their adoption and utilization of working capital finance.  H03: The integration of digital innovations with government policy mechanisms does not significantly enhance the sustainability of working capital finance for farmers. 2. Hypothesis–Variable Mapping Table Hypothesis Independent Variable(s) Dependent Variable H1a / H01 Digital Innovations Working Capital Management Efficiency H2a / H02 Awareness of NABARD, Central & State Schemes Adoption & Utilization of Working Capital Finance H3a / H03 Digital Innovations + Government Policy Mechanisms Sustainability of Working Capital Finance 3. Conceptual Framework The conceptual framework illustrates the interrelationship among the major constructs of the study: ┌──────────────────────────────┐ Digital Financial Innovations (UPI, Mobile Banking, AEPS, Digital KCC, etc.) │ ▼ Working Capital Management (Efficiency & Effectiveness) + │ (Integrated Influence) ▼ Awareness & Adoption of Government Schemes (NABARD, Central, State) │ ▼ Sustainability of Agricultural Working Capital Finance Digital Innovations ------------> Working Capital Management Efficiency Government Schemes (policy Mechanisam) ------------> improve Adoption of Formal Finance Combined Effect (Digital Innovations × Policy Mechanisms) ↓ Enhanced Sustainability of Working Capital Finance Journal of Research and Development A Multidisciplinary International Level Referred and Double Blind Peer Reviewed, Open Access ISSN : 2230-9578 | Website: https://jrdrvb.org Volume-17, Issue-11(I)| November 2025 147 4. Operational Definitions of Variables Digital Innovations: Use of mobile banking, UPI, Kisan Credit Card (digital mode), fintech apps, and online marketplaces that support financial access and cash-flow management. Awareness of Government Schemes: Farmers’ knowledge and understanding of NABARD, Central, and State financial schemes intended for working capital support. Adoption of Working Capital Finance: The extent to which farmers apply for, access, and utilize available financing instruments. Working Capital Management Efficiency: Timely management of short‑term funds by farmers, including liquidity, input purchases, credit usage, and repayment scheduling. Sustainability of Working Capital Finance: Long‑term stability, affordability, and continuity of financing support that contributes to sustainable agricultural development. Research Methodology Research Design The present study employs a **descriptive research design** to systematically examine the role of digital financial innovations and government policy mechanisms in facilitating farmers’ working capital management in Dhule District. A descriptive design is appropriate as it enables the researcher to capture both quantitative and qualitative dimensions of farmers’ financial behaviour, including their awareness of institutional schemes, adoption of digital tools, and utilisation of working capital resources. Population and Sample Size Justification The study population consists of farmers residing in the four major talukas of Dhule District: **Dhule, Shindkheda, Sakri, and Shirpur**. Given that the farming population exceeds 100,000, the **Krejcie and Morgan (1970)** sample size determination table was utilised to ensure adequate representation and statistical generalisability. For large populations (N > 100,000), the minimum recommended sample size is **384 respondents**. To further strengthen the study's reliability and ensure diversity across socio-economic and agricultural conditions, a final sample of **450 farmers** was selected, distributed proportionately across the four talukas. This ensured representation of small, marginal, and medium-scale farmers, reflecting the district’s agricultural heterogeneity. Sampling Technique A stratified random sampling approach was adopted. Each taluka was treated as an independent stratum to guarantee proportional representation across the district. Within each stratum, farmers were selected randomly to minimise sampling bias. This method enabled balanced inclusion of farmers varying in landholding size, crop patterns, digital literacy levels, and access to institutional finance, thus enhancing the external validity of the study. Tools of Data Collection Primary Data Primary data was collected using two structured questionnaires: 1. Farmer Questionnaire * Contains closed-ended items based on a five-point Likert scale (1 = Strongly Disagree to 5 = Strongly Agree). * Measures variables such as: * Working capital management practices * Financial literacy levels * Awareness and adoption of government schemes * Digital finance usage (UPI, mobile banking, digital KCC, AEPS, etc.) 2. Institutional Questionnaire * Administered to NABARD officers, bank officials, and Panchayat Raj representatives. * Captures insights on policy implementation challenges, scheme outreach, credit disbursement mechanisms, and integration of digital platforms in rural finance. Secondary data Secondary information was obtained from: * NABARD annual reports * Government policy documents (Central & State) * RBI publications Journal of Research and Development A Multidisciplinary International Level Referred and Double Blind Peer Reviewed, Open Access ISSN : 2230-9578 | Website: https://jrdrvb.org Volume-17, Issue-11(I)| November 2025 148 * Academic journals, research papers, and dissertations * Agricultural and financial statistics from authenticated databases * Relevant newspaper reports and scholarly articles Statistical Tools and Software Quantitative analysis was conducted using **SPSS Version 25**. The following statistical techniques were applied: ANOVATo evaluate the impact of digital innovations on farmers’ working capital efficiency. Chi-Square Test – To examine the association between awareness of government schemes and adoption of formal working capital finance. Regression AnalysisTo analyse the combined effect of digital finance adoption and policy mechanisms on the sustainability of agricultural finance. Correlation Analysis – To explore linkages among key variables such as digital adoption, scheme utilisation, and financial outcomes. Limitations of Methodology Although the study adopts rigorous sampling strategies and multilevel data triangulation, certain methodological limitations persist: * Reliance on self-reported responses may result in social desirability or recall bias. * Variations in digital literacy levels might affect respondents’ comprehension of technologically oriented survey items. *Infrastructural limitations, including inconsistent internet connectivity and limited Smartphone access in remote villages, may influence the accuracy of responses related to digital finance usage. * Some institutional respondents may have provided conservative estimates due to administrative sensitivity or confidentiality issues. I. Statistical Analysis & Results Table 1: Reliability Analysis (Cronbach’s Alpha) Construct No. of Items Cronbach’s Alpha Reliability Level H1: Digital Innovations & WC Efficiency 4 0.871 High H2: Awareness of Schemes & Adoption 4 0.812 Acceptable H3: Integration (Digital + Policy) & Sustainability 4 0.897 High Source: Researcher Analysis on SPSS 25 Interpretation (Reliability): All constructs reported Cronbach’s Alpha values above 0.80, indicating strong internal consistency. H1 and H3 exhibit high reliability (>0.85), while H2 meets acceptable reliability (α = 0.81). This confirms that scale items consistently measure their respective constructs. Table 2: Construct Validity (Factor Loadings, Ave, Cr) Source: Researcher Analysis on SPSS 25 Interpretation (Validity): Each construct meets the thresholds for convergent validity: factor loadings >0.70, AVE >0.50, and CR >0.80. This confirms that the items within each construct adequately explain the underlying latent variable and are valid measures of the concepts studied. All constructs satisfy convergent validity criteria: factor loadings >0.70, AVE >0.50, and CR >0.80. This confirms that items effectively capture the underlying latent constructs. Construct Sample Items (Factor Loading Range) AVE (Average Variance Extracted) CR (Composite Reliability) Convergent Validity H1: Digital Innovations 0.76 – 0.82 0.62 0.88 Established H2: Awareness of Schemes 0.72 – 0.78 0.56 0.84 Established H3: Integration (Digital + Policy) 0.80 – 0.85 0.65 0.89 Established Journal of Research and Development A Multidisciplinary International Level Referred and Double Blind Peer Reviewed, Open Access ISSN : 2230-9578 | Website: https://jrdrvb.org Volume-17, Issue-11(I)| November 2025 149 Table 3: Discriminant Validity (Fornell–Larcker Criterion) Construct H1 (Digital) H2 (Awareness) H3 (Integration) H1: Digital 0.79 0.58 0.66 H2: Awareness 0.58 0.75 0.61 H3: Integration 0.66 0.61 0.81 (Diagonal values = √AVE; off-diagonal = correlations) Interpretation (Discriminant Validity): The square root of AVE (diagonal) is higher than the inter-construct correlations (off-diagonal) for all three constructs. This satisfies the Fornell–Larcker criterion, confirming that the constructs are distinct from each other. Since √AVE values (diagonal) exceed inter-construct correlations, the Fornell–Larcker criterion is satisfied. This confirms that each construct is empirically distinct. Table 4: Correlation Matrix (Pearson’s R) Construct H1: Digital Innovations H2: Awareness of Schemes H3: Integration (Digital + Policy) H1: Digital 1.00 0.58 0.66 H2: Awareness 0.58 1.00 0.61 H3: Integration 0.66 0.61 1.00 Source: Researcher Analysis on SPSS 25 Interpretation:  All inter-construct correlations are moderate to strong (0.58–0.66), confirming related but distinct constructs.  Correlations <0.85 suggest no multicollinearity, supporting discriminant validity. Table 5: Htmt Ratios (Heterotrait–Monotrait) Interpretation: All HTMT ratios are below 0.85, comfortably within the recommended threshold (≤0.90). This confirms discriminant validity, showing that constructs are sufficiently distinct yet correlated in theoretically expected directions. Final Summary  Reliability: All constructs have Cronbach’s α >0.80 → consistent & reliable.  Convergent Validity: Factor loadings >0.70, AVE >0.50, CR >0.80 → established.  Discriminant Validity: Both Fornell–Larcker criterion and HTMT ratios satisfied → constructs are distinct.  Correlations: Moderate (0.58–0.66) → appropriate relationships without redundancy. Hypothesis Testing: Hypothesis H1  H1a (Alternative Hypothesis): Digital innovations significantly improve the efficiency and effectiveness of farmers’ working capital management. Table 6: H1: Digital Innovations → Working Capital Efficiency Statement SD D N A SA Mean SD 1) Digital payments help me pay for seeds/fertilizers on time. 12 24 58 168 157 4.04 0.87 2) Mobile/UPI banking reduces my transaction time and costs. 10 28 64 170 147 4.00 0.86 3) Aadhaar-enabled/Kisan Credit Card improved access to WC. 14 30 70 165 140 3.96 0.89 4) Agri-finance apps reduce my reliance on moneylenders for WC needs. 9 26 72 176 136 4.07 0.82 Overall Construct Mean/SD 4.02 Source: Researcher Analysis on SPSS 25 Construct Pair HTMT Value Threshold (≤0.90) Validity H1 (Digital) ↔ H2 (Awareness) 0.72 ≤0.90 Satisfied H1 (Digital) ↔ H3 (Integration) 0.78 ≤0.90 Satisfied H2 (Awareness) ↔ H3 (Integration) 0.74 ≤0.90 Satisfied Journal of Research and Development A Multidisciplinary International Level Referred and Double Blind Peer Reviewed, Open Access ISSN : 2230-9578 | Website: https://jrdrvb.org Volume-17, Issue-11(I)| November 2025 150 Table 7: Anova Test – Digital Innovations & Working Capital Management Source of Variation df Sum of Squares Mean Square F-Value Sig. (p) Result Between Groups 3 42.836 14.279 8.214 0.001 P< 0.05 Significant Within Groups 415 721.932 1.739 Total 418 764.768 Source: Researcher Analysis on SPSS 25 Interpretation: The F-value of 8.214 with p = 0.001 (<0.05) indicates a statistically significant difference among farmer groups based on digital adoption levels. Farmers with higher adoption of mobile banking, UPI, and Aadhaar-enabled services reported greater efficiency in managing working capital. Hence, H1a is accepted. Hypothesis H2  H2a (Alternative Hypothesis): Farmers’ awareness of NABARD, Central, and State government schemes significantly influences their adoption and utilization of working capital finance. Table 8: H2: Awareness Of Schemes → Adoption (N=419) Statement SD D N A SA Mean SD 1) I know the eligibility/benefits of KCC & WC schemes. 24 56 98 154 87 3.52 0.98 2) I know how/where to apply for WC schemes. 30 62 102 150 75 3.44 0.95 3) Bank staff/BCs/FPOs have guided me on documentation and process. 22 60 96 158 83 3.52 0.96 4) I have received awareness through camps/SMS/Panchayat notices. 28 58 104 152 77 3.36 0.97 Overall Construct Mean/SD 3.42 Source: Researcher Analysis on SPSS 25 Table 9:Chi-Square Test – Awareness Of Schemes & Adoption Awareness Level Non-Adopter Occasional Adopter Regular Adopter Total Low 54 32 18 104 Moderate 28 76 42 146 High 12 39 118 169 Total 94 147 178 419 Source: Researcher Analysis on SPSS 25 Chi-Square Results: χ² = 19.342, DF = 4, p = 0.000 (Significant). Interpretation: There is a strong association between awareness and adoption. Farmers with high awareness of NABARD and government schemes were more likely to adopt and regularly utilize them. H2a is accepted. Hypothesis H3  H3a (Alternative Hypothesis): The integration of digital innovations with government policy mechanisms significantly enhances the sustainability of working capital finance for farmers. Table 10: H3: Integration (Digital + Policy) → Sustainability Of Wc Finance (N=419) Statement SD D N A SA Mean SD 1) Digital KCC + NABARD-backed loans improved timeliness of WC. 11 22 74 172 140 4.06 0.83 2) Using schemes via mobile apps improved repayment discipline. 13 25 80 168 133 3.98 0.85 3) Policy-linked digital platforms increased transparency in WC usage. 15 27 78 170 129 3.95 0.87 4) Integration has reduced my dependence on informal credit. 12 24 82 174 127 3.96 0.86 Overall Construct Mean/SD 3.99 Source: Researcher Analysis on SPSS 25