The ACABC scheme was launched by Government of India with the objective of strengthening agricultural extension services while promoting self-employment among agricultural graduates. The ACABC (The Agri Clinic and Agri-business center) scheme, launched in 2002, it was introduced to address unemployment among the agricultural graduates and strengthen extension services. Afroz et al., (2022), studies on ACABC scheme reveal that it play a significant role in promoting agripreneurship and self-employment among agricultural graduates by improving access to training, credit and extension services. Bairwa et al., (2014), highlighted constraints such as limited access to institutional credit, delays in subsidy release and inadequate post-training support affecting the establishment of agriventures. Socio-economic factors, motivation, training quality, institutional support influence on success of ventures in agri-business. Bairwa et al. (2023), assessed the impact of socio-economic factors on the progress of the ACABC scheme in Rajasthan and found that education level, access to credit and entrepreneurial motivation significantly influenced agriventure establishment. Every year, almost 15,000 agricultural graduates pass out, but only 2500 secure formal employment. The ACABC scheme provides structured training, institutional support, bank credit and a 25% capital subsidy to promote agripreneurship. Gulsia (2024) observed that broader disruptions in the agri-food sector, such as those triggered by the COVID-19 pandemic, intensified supply-chain and market-access challenges for agri-based ventures, underscoring the continued relevance of structured support schemes like ACABC in sustaining agripreneurship.
        
The scheme is implemented by the Ministry of Agriculture and Farmers Welfare (MOA and FW), MANAGE (National Institute of Agricultural Extension Management) Hyderabad acts as nationally coordinated for training and overall administration, for financial support under scheme is provided in the form of a capital subsidy of 33% of the total project cost, with institutional credit through NABARD( National Bank for Agricultural and Rural Development), which encourages commercial banks, RRBs and cooperative banks to extend loans to trained agripreneurs. Balasoundari et al., (2021), found that the quality of services provided by selected ACABC units in Puducherry and found that most agriclinics delivered satisfactory advisory and input services to farmers. Bharathi and Sudhakar (2022), evaluated the performance of the ACABC scheme in Andhra Pradesh and found that it positively contributed to employment generation and agripreneurial development among agriculture graduates. Bharathi and Sudhakar (2023), evaluating the scheme at the national level, examined its progress on a state-by-state, training-institute-by-training-institute and project-by-project basis and found uneven performance across states, pointing to disparities in scheme implementation across India. Chaitra et al., (2020), noted challenges such as financial constraints and market competition affecting youth retention. Also highlighted that ACABC improved income opportunities, self-employment and professional identity of agriculture graduates. Hove and Tarisai (2013), examined internal factors influencing the growth and survival of small and micro agribusiness firms and found that managerial competence, financial management and entrepreneurial skills were critical determinants of success. Kumari (2025), the study highlighted that agri-clinics strengthened extension outreach in hilly regions, though issues such as limited infrastructure and accessibility affected service effectiveness. Also examined that role of agri-clinics in Himachal Pradesh had improved farmers access to technical advice, input supply and farm management services. Hashemi and Hedjazi (2011), analyzed factors influencing members evaluation of agribusiness ventures effectiveness and found that managerial skills, access to resources and market orientation significantly affect performance.
        
Since its inception, the ACABC has emerged as a significant agripreneurship development program in India, in diverse areas such as agriclinics, value addition, organic farming, etc. Afroz et al., (2021), analyzed the ACABC scheme using a combined SWOT-AHP (Analytic Hierarchy Process) approach and found that employment generation and agripreneurial motivation are its major strengths, while delays in credit and subsidy and limited practical exposure are key weakness. The scheme offers a two-month free residential training program, followed by one year of handholding support by Nodal Training Institutes (NTIs) selected by MANAGE based on prescribed criteria. Eligible candidates include agriculture and allied disciplines such as horticulture, veterinary, fishery, forestry etc. The maximum project cost of 10 lakh for individual ventures and 50 lakhs for group ventures. Bondre et al., (2017), noted that agripreneurs contribute to improved farm advisory and agribusiness services at the grassroots level, need for better implantation, follow-up and institutional handholding for long-term sustainability. Burman et al., (2020), found that effective training, market linkage and extension support played a crucial role in sustaining agribusiness enterprises. Study also reveals that behavioral pattern of farmer-entrepreneurs and the success factors influencing agribusiness establishments under ACABC scheme.
        
Pal and Sharma (2021) major constraints identified were inadequate institutional support, delays in credit linkage and limited post-training handholding, affecting long-term sustainability of ventures. Also identified improved income level and entrepreneurial skills among beneficiaries. Pal and Sharma (2023) further analyzed the barriers faced by agripreneurs in starting and operating agriventures under the ACABC scheme and found that lack of own funds, confusion between seeking a job versus entrepreneurship, inadequate handholding support from NTIs, limited family support and difficulties in loan documentation were the major constraints at the establishment stage, while heavy market competition, infrastructural gaps, product perishability and insufficient working capital hindered operation of established ventures. Prabha (2025) revealed that agripreneurship significantly improved rural women’s income, decision-making power and participation in household and community affairs. Also highlighted enhanced skill development, self-confidence and access to productive resources among women in ventures. Prakash et al., (2020) highlighted the need for better post-training follow-up, credit facilitation and region-specific customization to improve enterprise establishment rates. Saghaian et al., (2022), identified access to finance, managerial competence, innovation capacity and market orientation as the most significant factors influencing agribusiness entrepreneurial success. Also found that human capital variables like education, experience, etc showed strong positive relationship with business performance. Sharma and Deb (2025) found that private sector banks in Nagaon provide a range of financial services to agro-based industries, mainly in the form of term loans, working capital finance and digital banking products.
        
Pal and Sharma (2021), identified major barriers faced by agripreneurs under the ACABC scheme as delays in bank credit, collateral security requirements and procedural complexities. Inadequate post-training support, limited mentoring and weak market linkages were found to hinder the smooth operation o agriventures. Vandeburg et al., (2000) found that economic pressures, market competition and the need for scale efficiency were the primary driving forces behind mergers, acquisitions, joint ventures and strategic alliances among local cooperatives. Venkattakumar et al. (2016) concluded that policy support and post-training handholding are essential to ensure sustainability and long-term success of ACABC enterprises. Verma et al., (2025) found that scheme related to credit support, insurance, input subsidies and technology dissemination significantly influence farmer adoption behavior. Also emphasized the need for better convergence, effective implementation and awareness creation to maximize the impact of agricultural policies and schemes. While the studies above document ACABC performance in states such as Rajasthan, Madhya Pradesh, Puducherry and Himachal Pradesh, comparatively little empirical work has evaluated beneficiary-perceived service quality of ACABC-linked banking and institutional support specifically in Andhra Pradesh, despite the state showing one of the lowest trained-to-established conversion rates (29.27%) among major implementing states. This study addresses that gap by applying the SERVQUAL framework to assess beneficiary perceptions and expectations of ACABC-related services in Andhra Pradesh.

The present study was carried out at the Indian Institute of Plantation Management, Bangalore, during the research period 2024-2025. This includes the design of the study and the methods to do research work and analysis. Location, sampling design, method of data collection and the tools used for analyzing the data are explained here. The methodology used in the research is both qualitative and quantitative method. Sampling design study area: The research is conducted among the agri-ventures in Andhra Pradesh. Hence, purposively the regions (state) have been selected to know their perception towards performance and success rate after the implication of ACABC scheme in Andhra Pradesh and some important information gathered for my research. Sample unit and size: The total sample size is 100 and the targeted respondents are related to agri-clinics, agri-business centers, animal feed units, farm machinery unit, fisheries development, nursery, value addition, seed processing units, vermi compost unit, veterinary clinics, dairy, poultry, etc units, mushroom units and apiary hence purposively the sample size (heterogeneous) was distributed among all.  A sample of 100 respondents was considered adequate for this exploratory, purposive study given the practical constraints of accessing a dispersed and heterogeneous population of ACABC beneficiaries across the state and is broadly consistent with sample sizes used in comparable SERVQUAL-based service-quality studies. However, this sample size is not derived from a formal statistical power calculation and the findings should be interpreted as indicative of beneficiary perceptions rather than statistically generalizable to the entire population of agripreneurs in Andhra Pradesh.

Data source
 
Primary and secondary data are collected to research the perception towards performance and success rate after the implication of ACABC scheme in Andhra Pradesh. Primary data is used for the analysis where the data is collected through Google form questionnaires, face-to-face interview and circulating among the agri allied ventures and data was collected based on the objective of the research. The questionnaire is grouped into well structure to capture all the necessary information required for my research. Method of data collection: Primary data is collected through structured questionnaires using Google Forms, which mostly have close-ended questions. Secondary data is collected through research papers, journals, success stories, department of agriculture Andhra Pradesh, directorate of extension, ministry of agriculture, MANAGE, NABARD and other organizations associated with the management of scheme like strategies adopted by the commercial banks to lend the loans in the scheme of ACABC was collected from NABARD regional areas for study purpose.
 
Sampling technique
 
Non-probability and purposive sampling techniques are used for the study area, sample size selection and selection of agri and allied ventures, as they are selected based on language, time duration, some telephonic interviews, etc and convenience sampling is used for the preparation of the questionnaire through Google form as it is easy to circulate among the agri and allied ventures, so the non-probability sampling technique is chosen. Statistical designing: Descriptive statistics are used to analyze the statistical facts and patterns in the collected data, using this data on the profile of agri and allied ventures and technical information was presented in the form of charts and tables. Statistical tools such as Reliability analysis framework using  SERVQUAL scale; 5-point Likert scale; Method was Cronbach’s Alpha were performed, SERVQUAL analysis- Expectations, Perceptions and Gap: ACABC scheme-Andhra Pradesh: using Mean and SD (Standard Deviation) were performed and Chi-Square Test Results (Perception ratings across SERVQUAL dimensions using advanced Excel. The 17-item SERVQUAL instrument was distributed across the five dimensions as follows: Tangibles (4 items), Reliability (4 items), Responsiveness (3 items), Assurance (3 items) and Empathy (3 items), as detailed in Table 11.

The ACABC scheme has made a significant contribution to agripreneurship development in Andhra Pradesh. As of 2024-25, from above Table 1 source agri-business ventures had been successfully established, indicating a reasonably positive conversion rate from training to enterprise creation. The temporal growth of the scheme reveals a steady increase in both trained candidates and ventures established, particularly after 2017, reflecting improved awareness, institutional support and policy focus on agripreneurship. Gap between trained candidates and bank-sanctioned projects remain showed persistent challenges in credit linkage and financial accessibility for first-generation agripreneurs.


        
In comparison with leading states such as Maharashtra and Uttar Pradesh, it can be seen from Table 2 Andhra Pradesh’s absolute numbers are relatively lower; nevertheless, the state demonstrates consistent performance and gradual expansion under the scheme. The presence of a diversified set of agribusiness ventures, including input supply, advisory services, customer hiring centers and post-harvest activities, underscores the scheme’s role in strengthening agricultural extension and rural entrepreneurship in the state.


        
Trend analysis from Table 3 indicates a steady increase in the number of candidates trained and agribusiness ventures established under the ACABC scheme in Andhra Pradesh during the last 5 years, however, the ventures conversion rate shows a gradual decline from 36.61% in 2019-20 to 29.27% in 2023-24, suggesting that while participation has increased, challenges such as access to institutional credit, procedural delays and market risks may have constrained enterprise establishment.


        
It is observed from Table 4 that the ACABC data for Andhra Pradesh from 2019-20 to 2024-25 show a rise in agribusiness ventures from 280 to 516, indicating improved outreach of the scheme. Growth is mainly observed in service oriented, low capital enterprises, particularly Agri input dealerships, Agri-clinics and customer hiring centers. In contrasts, the share of capital-intensive ventures such as food processing, nursery units and organic enterprises has declined, suggesting constraints related to credit access and investment risk. Overall, while the scheme has expanded entrepreneurial participation, stronger post training support and improved credit linkage are required to promote diversifies and high impact agri-business ventures in the state.


        
Estimated credit mobilized projects × typical loan size is shown in Table 5 with, loan size ranges are based on ACABC operational guidelines and bank product norms. Subsidy linkage is back ended and routed through NABARD (36% for General and 44% for Women/SC/ST/NE/Hill. Bank wise analysis reveals that public sector banks play a dominant role in ACABC financing, mobilizing an estimated 166-295 crore of institutional credit. State Bank of India alone accounts for nearly 20% of sanctioned projects nationally, highlighting its leadership in agripreneurship financing. RRBs contributing smaller but critical loans, supporting micro-scale agri ventures. These figures reflect national-level ACABC bank financing (consistent with the India-level lending data in Table 8) and should not be read as Andhra Pradesh-specific; the state-level project-sanction figures for Andhra Pradesh are reported separately in Table 1 (21 projects sanctioned) and Table 8 (15 projects financed).


        
From Table 6, the land holding pattern in Andhra Pradesh is dominated by small and marginal farmers, with nearly 88.60 % of operational holdings blow 2 ha and an average holding size of only 0.94 ha. This data of small holder predominance not only influences cropping choices but also explains the preference for low capital agri business services under ACABC scheme, as small holders often lack in the scale and collateral for capital intensive ventures.


       
Based on the land-holding and venture-trend findings, Table 7 translates these patterns into actionable recommendations. Since Andhra Pradesh’s farm base is overwhelmingly small and fragmented, low capital, service-oriented ventures are the natural fit for ACABC promotion, while cluster and FPO based models can help offset the scale disadvantage individual smallholders face. The persistent gap between trained candidates and bank-financed ventures points to credit access, not training, as the binding constraint, making simplified and collateral-free lending products a priority. Stronger post-training mentoring is also proposed to address early enterprise mortality and encourage diversification beyond advisory and input services into higher-value activities.


       
From Table 8, bank lending behavior under ACABC can be interpreted through a risk-appraisal lens. The relatively low training-to-venture conversion nationally, combined with a declining trend in recent years, reflects growing caution among banks rather than a shortage of trained candidates. Andhra Pradesh’s comparatively small financing footprint and subsidy disbursement lag suggest that procedural delays, more than demand, are limiting scheme uptake in the state. The prevailing loan-size ceilings, collateral norms, and back-ended subsidy structure together indicate a conservative institutional lending posture that favors low-risk, easily appraisable ventures over capital-intensive ones.


       
The five SERVQUAL dimensions, as contextualized in Table 9, reflect actual ACABC service delivery in the state. Infrastructure upgrades and ICT support have strengthened the tangibles dimension, while reliability is constrained mainly by subsidy-related delays rather than lending inconsistency. Responsiveness benefits from dedicated local coordinators, and assurance is reinforced by capacity-building efforts from NABARD and MANAGE, which appear to have built greater beneficiary trust in public sector banks. Empathy is evident in the targeted handholding extended to disadvantaged and first-generation entrepreneurs, suggesting banks are adapting service delivery to the specific vulnerabilities of ACABC beneficiaries.


       
Table 10 establishes the representativeness of the sample used for the SERVQUAL analysis. The respondent profile skewed toward mid-career, agriculture-educated, socially diverse participants engaged mainly in low capital ACABC activities mirrors the broader pattern of smallholder driven, service-oriented entrepreneurship identified earlier in the study. This alignment strengthens the validity of the perception and gap score findings, as the sample closely reflects the population the ACABC scheme is designed to serve.


 
Reliability analysis framework
 
Scale used= SERVQUAL; Sample size=100 ACABC beneficiaries in Andhra Pradesh; Measurement = 5-point Likert scale; Method= Cronbach’s Alpha.
Cronbach’s Alpha α =

 
k = Number of items.
Σσ²i- = Sum of variance of the total scores.
σ²x - Variance of the total score.
        
From Table 11, All α-values more than 0.70; both expectation and perception scales are internally consistent. Perception coefficients are higher than expectation coefficients. It indicates actual service delivery is more consistently perceived. Common and theoretically valid in SERVQUAL studies.


 
SERVQUAL analysis- Expectations, Perceptions and Gap: ACABC scheme-Andhra Pradesh:
 
Mean= √Σ/n; SD (Standard Deviation) = √Σ(E-E)2 /n-1
 
Objective-To test whether beneficiary perception-level ratings (Low/Medium/High) are distributed differently across the five SERVQUAL dimensions.
Hypothesis-Ho= No significant association between SERVQUAL dimension and perception-level category.
H1= Significant association exists between SERVQUAL dimension and perception-level category.
        
From Table 12, The SERVQUAL gap analysis reveals negative gap scores in all five dimensions, it indicates that banking services under ACABC scheme in Andhra Pradesh fall short of beneficiary’s expectations; the highest gap is observed in the reliability (-0.56) dimension followed by responsiveness (-0.55), highlighting delays in loan processing and service responsiveness.


        
From Table 13, A chi-square test of independence was used to test whether beneficiary perception ratings (Low/Medium/High) are distributed differently across the five SERVQUAL dimensions - Tangibles, Reliability, Responsiveness, Assurance and Empathy. The test found no statistically significant association between dimension and perception-level category (χ² = 7.60, df = 8, p = 0.474), indicating that beneficiaries’ perception ratings are broadly similar in distribution across all five service-quality dimensions.


        
The combined analysis of Cronbach’s alpha, gap scores and the chi-square test of dimension-wise perception distribution demonstrates that the ACABC banking scheme in Andhra Pradesh is perceived as partially meeting beneficiaries’ expectations. The highest service gaps are observed in reliability and responsiveness, indicating operational delays and in-consistent service delivery. Tangibles, assurance and empathy also show notable gaps, although to a lesser extent. The high reliability coefficients confirm that the survey instrument was consistent and suitable for measuring these perceptions. Overall, the findings suggest the need for targeted interventions to reduce service gaps, particularly in physical in physical infrastructure and operational reliability, to enhance customer satisfaction and scheme effectively.

The ACABC scheme has been effective in attracting agricultural graduates for training. However, converting trained graduates into successful agripreneurs remains a major challenge. Nodal training institutes play a crucial role in shaping entrepreneurial motivation. The study shows that easy loan availability and hand holding support are the main drivers of participation. Only a small proportion of trainees join the program primarily to gain entrepreneurial knowledge. This limits the long-term impact of the scheme on agri-business development. Sustainable agripreneurship depends more on skill development and practical learning than on financial support alone. Therefore, training approaches need to be more experiential and business oriented. Strengthening mentoring, exposure visits and real time business planning is essential. Such improvements can enhance the effectiveness of the ACABC scheme in creating successful agripreneurs.

The present study was supported by Indian Institute of Plantation Management-Bangalore, ANGRAU University- Bapatla, Gayatri college of science and management-Srikakulam, supporters and my parents. 
 
Disclaimers
 
The views and conclusions expressed in this article are solely those of the authors and do not necessarily represent the views of their affiliated institutions. The authors are responsible for the accuracy and completeness of the information provided, but do not accept any liability for any direct or indirect losses resulting from the use of this content.
 
Informed consent
 
No animal procedures used for this research.

The authors declare that there are no conflicts of interest regarding the publication of this article. No funding or sponsorship influenced the design of the study, data collection, analysis, decision to publish, or preparation of the manuscript.