Document Type : Research Paper
Authors
1 Department of Accounting, Faculty of Management and Accounting, Hazrat-e Masoumeh University, Qom, Iran
2 Department of Accounting, University of Kurdistan, Sanandaj, Iran.
Abstract
Keywords
Extended Abstract
Objectives
The banking system plays a central role in driving economic development by efficiently allocating financial resources and providing credit facilities, thereby stimulating production, investment, and overall economic growth. The Agricultural Bank, given its specialized mandate to support the agricultural sector, holds a strategic position in advancing food security, fostering rural development, and mitigating regional inequalities. However, without an effective supervisory framework, the disbursement of credit can result in resource misallocation, rising levels of non-performing loans, and a decline in overall banking efficiency. Agriculture, by its nature, is exposed to unique risks—including climate variability, price fluctuations, and market unpredictability—making robust, adaptive, and intelligent oversight essential. A major systemic challenge is the overreliance on formal, document-based controls, which often fail to ensure that funds are used for their intended purposes. To address this, a comprehensive supervisory system is urgently needed—one that combines on-the-ground monitoring, advanced technologies, and active stakeholder engagement with existing administrative mechanisms. Using a grounded theory approach and informed by the real-world experiences of sector experts, this study develops a context-sensitive, locally tailored, and operationally practical supervisory model specifically designed for the Agricultural Bank.
Methodology
This study is applied in purpose and qualitative in design, utilizing a grounded theory approach. By drawing directly on empirical data—and deliberately avoiding preconceived theoretical frameworks—this methodology facilitates the emergence of a theory grounded in real-world contexts and practical experiences. The central aim is to develop a model for the supervisory system governing credit facilities at the Agricultural Bank, firmly situating the research within the domain of applied inquiry. The study’s population comprises experienced experts from the bank, selected through purposive sampling using the snowball technique: each participant helped identify subsequent interviewees, enabling access to a relevant and knowledgeable sample. Data collection proceeded until theoretical saturation was achieved; while initial indicators of saturation emerged after the fifteenth interview, two additional interviews were conducted to ensure comprehensiveness and guard against premature saturation. Ultimately, 17 in-depth interviews were completed with seasoned professionals, significantly enriching the conceptual texture and analytical depth of the findings. Data were collected via semi-structured interviews—a method that preserved focus on core research themes (including root causes of supervisory weaknesses, structural conditions, and intervening factors) while allowing participants the flexibility to express their insights and lived experiences freely. This openness contributed substantially to the richness, nuance, and diversity of the outcomes.
Results and Discussion
During the data analysis process, the initially extracted categories were refined and consolidated based on semantic overlap and conceptual coherence, allowing them to evolve into more abstract, higher-order analytical constructs. These were ultimately organized into six core domains: the central category, causal conditions, contextual conditions, intervening conditions, strategies, and outcomes. Causal conditions encompassed structural and managerial weaknesses, insufficient specialized human resources, and gaps in supervisory procedures—all of which demand organizational restructuring, capacity building, and procedural reform. The central category, “Enhancement of the Supervisory System,” captures the current inefficiencies, the negative consequences of weak oversight, and the critical need for a formalized, transparent, and systematic approach to supervision. Contextual conditions include institutional constraints and broader socio-economic pressures—such as inflation, policy misalignment, and geographic dispersion—that undermine supervisory effectiveness and call for structural adaptation and proactive environmental management.
Intervening conditions involve non-expert institutional interference, challenges in outsourced monitoring, and fragmented technological systems—obstacles that can be mitigated through minimizing irrelevant external influence, improving oversight partnerships, and integrating digital tools. Five strategic pillars were proposed to strengthen supervision: enhancing transparency and feedback loops, fostering inter-organizational coordination, reforming operational processes, engaging stakeholders through participatory mechanisms, and deploying smart technologies such as AI-driven monitoring. The anticipated outcomes include more effective project implementation, optimal resource use, reduced non-performing loans through continuous oversight, and enhanced national agricultural productivity. Collectively, this model affirms that an intelligent, structured, and adaptive supervisory framework is indispensable for sound financial governance and the long-term realization of sustainable agricultural development at both local and national levels.
Conclusion
Employing a grounded theory approach, this study develops a context-sensitive, practical model for supervising agricultural credit facilities within the Agricultural Bank. Findings reveal that structural inefficiencies, a lack of specialized human capital, and gaps in supervisory procedures are primary contributors to diminished oversight effectiveness. To counter these challenges, the study advocates for a multidimensional strategy encompassing greater transparency, improved inter-organizational collaboration, process reengineering, active stakeholder engagement, and the integration of smart technologies. These interventions not only curb resource misallocation but also boost loan repayment rates and elevate the productivity of agricultural initiatives across local and national levels. While the research is constrained by its qualitative methodology and focus on a single institution, the proposed model offers a flexible framework adaptable to other financial organizations operating in similar contexts.
Theoretically, this study advances credit risk management literature by foregrounding the role of organizational dynamics, environmental stressors, and institutional interventions—factors often overlooked in quantitative analyses. Practically, it recommends concrete measures such as reinforcing data-centric monitoring systems, delivering targeted capacity-building programs for staff, adopting artificial intelligence for real-time oversight, and implementing hybrid supervisory models that combine internal controls with external audits. These actions collectively support the reduction of non-performing loans, enable continuous performance tracking, and foster sustainable agricultural growth. Beyond its immediate application, the model provides a conceptual foundation for future quantitative validation and cross-sectoral comparative studies, while serving as an actionable blueprint for optimizing financial governance in economically vital, risk-prone sectors.
The second author was responsible for conducting the interviews and preparing the literature review and theoretical framework, whereas all other tasks were performed by the first author.
“Not applicable”
The authors would like to thank all participants of the present study. The Directorate of Research and Technology at the University of Tehran has also supported this research, which is highly acknowledged.
The authors avoided data fabrication, falsification, plagiarism, and misconduct.
The author declares no conflict of interest.
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