Journal of Agricultural Economics & Development

Abstract Introduction
Energy production from agricultural residue is an important research area with significant potential for sustainable energy production. In Iran, the use of agricultural waste for energy production, due to its favorable geographical characteristics, has the potential to address energy security, reduce greenhouse gas (GHG) emissions, and create economic opportunities for rural communities. Rice and wheat are major crops in Iran, which produce residue in the form of rice husk and wheat straw, respectively, which can be converted into energy sources. Biomass energy production from agricultural residue is currently being carried out worldwide. Although biomass energy is believed to be an effective option in terms of domestic renewable energy production, its ability to improve social welfare is controversial. Therefore, this study aims to examine the extent to which increases in biomass prices affect social welfare. It also investigates the potential for reducing greenhouse gas emissions through electricity generation using biomass derived from two major agricultural crops, wheat and rice.

Materials and Methods
This study evaluates the welfare and environmental impacts of using biomass derived from two major crops, wheat and rice. To achieve this objective, a partial equilibrium model was employed to maximize the total surplus of biomass producers and consumers, subject to resource availability constraints, thereby assessing the economic implications of biomass utilization. In addition, the potential for carbon dioxide emission reduction was estimated through a life cycle assessment of biomass-based electricity generation and by comparing its emissions with those associated with electricity generated from fossil fuels.

Results and Discussion
The results of the model simulation show that the welfare of biomass consumers decreases and that of biomass producers increases; so that the maximum social welfare is achieved at a price of 28.63 million Tomans per ton for wheat biomass and 27.59 million Tomans per ton for rice biomass. The results also showed that an increase in the price of biomass leads to an increase in biomass production, and by using this biomass produced from the two crops wheat and rice in electricity generation, greenhouse gas emissions can be reduced by 8.2 percent in the country.

Conclusion
Wheat straw and rice straw are among the agricultural residues that are used to produce electrical energy. Increasing the price of electrical energy produced from crop residue will increase the supply of biomass from wheat and rice crops, because straw and stubble can be a source of income for farmers in addition to the main wheat and rice crops, and on the other hand, by collecting straw and stubble, their burning in the fields is prevented. Given the increasing demand for electrical energy in the country, this study can be a basis for the government and policymakers to think of a solution for generating electricity from agricultural waste on a large scale that can produce clean energy and manage agricultural land residue. Therefore, according to the results of this study, it is suggested that by setting an appropriate price for wheat and rice straw and stubble, it is possible to collect them and not burn them in the fields, and to invest in biomass energy plants to produce clean energy. In this study, agricultural producers and power plants are considered as biomass consumers, and potential electricity market effects are ignored. To inform the sustainable use of biomass resources, the proposed model can be extended to the electricity sector consumed by the government and households. In addition, further research is needed to examine environmental impacts, such as biodiversity and water consumption, in a broader manner. The authors leave these explorations to future work.

Abstract Introduction The rapid growth of the global population, ongoing climate change, and limited production resources have intensified concerns about food security. Sustainable food production systems, particularly grazing-based livestock production, play a vital role in addressing these challenges. However, these systems face numerous obstacles in developing countries and arid/semi-arid regions, including heavy reliance on natural resources, climate change impacts, and drought vulnerability, lower efficiency compared to other production methods, high greenhouse gas emissions, and competition for agricultural land allocated to feed production. Additionally, high operational costs and susceptibility to livestock diseases have significantly reduced both the profitability and sustainability of these systems. In Iran, livestock production systems remain predominantly traditional and are evaluated as unsustainable in terms of environmental, economic, and social indicators. Kermanshah Province, with approximately 2,500 rangeland systems and 63,000 rural and nomadic households, represents one of the most important livestock production hubs in western Iran. However, the presence of 1.4 million livestock units exceeding rangeland carrying capacity, combined with significant climatic changes over the past three decades (including rising temperatures, declining precipitation, and intensifying droughts), has made this region an ideal case study for examining sustainability challenges in livestock production systems. This study aims to identify and analyze the challenges facing livestock production systems in relation to climate change impacts in Kermanshah Province. Materials and Methods This research was conducted in Kermanshah Province, located in the middle part of the Zagros Mountains. Kermanshah Province, as one of the livestock breeding hubs in the Middle Zagros, plays an important role in providing livestock feed from rangelands. The province contains approximately 2,500 rangeland systems supporting about 63,000 rural and nomadic households. These households primarily rely on rangeland grazing to meet their livestock feed requirements. Based on forage production capacity, the rangelands can sustainably support only 1.5 million livestock units, while the current livestock population exceeds this capacity by approximately 1.4 million units. Recent studies indicate significant climatic changes in the province over recent decades, particularly increased drought intensity and duration, which have directly impacted natural forage availability and threatened the sustainability of livestock production systems. Methodologically, this quantitative, applied research employed a survey approach. The study population consisted of 140 experts and specialists in livestock production and natural resources management from Kermanshah Province, with 131 participants studied through census method (with 93 % rate of return) based on their research and practical experience in livestock production systems and associated challenges. Data were collected using a researcher-developed questionnaire, designed through literature review and interviews with livestock production experts. Content validity was assessed by agricultural and natural resources experts from Kermanshah and faculty members from the University of Tehran's Agricultural Management Department. Discriminant validity was confirmed using average variance extracted (AVE). Reliability was evaluated through Cronbach's alpha and composite reliability. Data processing utilized SPSS 27 and Smart PLS 3 software packages. Results and Discussion The findings revealed that the most critical sustainability challenges for grazing-based livestock systems in Kermanshah Province were, in order of significance: environmental (β=0.756), economic (β=0.683), managerial (β=0.669), technical (β=0.593), social (β=0.563), and legal challenges (β=0.454). Environmental challenges emerged as the foremost sustainability barrier, underscoring their pivotal role in determining the overall sustainability of pastoral livestock systems according to expert assessments. Among environmental factors, climate variability and drought (factor loading=0.858) were identified as the most severe environmental challenges. Given that climate change impacts are projected to exacerbate system vulnerability - particularly when combined with rapid population growth and economic development that intensify food demand - these findings highlight the urgent need for adaptive strategies to mitigate climatic effects. Economic challenges represented the second most significant sustainability obstacle. Within this category, high prices for production inputs and animal feed (factor loading = 0.856) emerged as the most prominent economic constraint. This finding reflects the substantial financial burden on pastoralists for procuring inputs and animal feed, which increases production costs and may compromise their capacity for sustainable rangeland utilization. Managerial challenges ranked third, with poor community organization in local associations for coordinated action and inadequate service provision (factor loading=0.837) representing critical management shortcomings. Technical challenges represented another key sustainability barrier, where low productivity of grazing livestock was identified as a fundamental technical constraint. This emphasizes the importance of enhancing livestock productivity to improve overall system efficiency and profitability in the province. Social challenges ranked fifth, with insufficient awareness and knowledge regarding drought management and its impacts on rangelands (factor loading=0.853) being the primary social challenge. This underscores the critical need for educational interventions to improve pastoralists' understanding of drought management and rangeland conservation. Finally, legal challenges (β=0.454) were ranked as the least severe sustainability obstacle. Within this category, insufficient government budgeting and credit allocation for natural resource conservation and rangeland management (factor loading=0.874) emerged as the most significant legal constraint. This hierarchical challenge structure provides valuable insights for prioritizing intervention strategies to enhance the sustainability of grazing-based livestock systems in semi-arid regions. Conclusion Understanding these challenges can contribute to developing practical solutions for enhancing the sustainability of these systems. To improve the sustainability of livestock production systems, several strategies are proposed, including: establishing local cooperatives, enhancing access to technical training, developing innovative technologies, and providing financial support to livestock producers.

Abstract Introduction Smart agriculture refers to the use of modern technologies- such as artificial intelligence, the Internet of Things (IoT), big data analytics, and other innovations- to enhance agricultural productivity. It represents a transformative paradigm in modern farming practices, leveraging advanced technologies to boost efficiency, productivity, and sustainability. At its core, smart agriculture integrates a diverse array of technological components, beginning with the deployment of sensors and IoT devices. Smart agriculture operates based on key principles such as resource optimization, precision and accuracy in farming practices, data-driven decision-making, sustainability, and integration with market access platforms. Virtual reality is transforming the way we experience and interact with digital content. By creating a simulated environment capable of replicating real-world scenarios, it offers unprecedented levels of interaction and immersion .In agriculture, virtual reality and augmented reality assist in training farmers through simulations of new farming methods, examining farm conditions to monitor plant and soil status, and simulating various scenarios. Digital transformation is defined as a process of fundamental change enabled by the innovative use of digital technologies combined with the leveraging of strategic resources and key capabilities aimed at radically improving an organization and redefining its value proposition for stakeholders. Digital transformation is widely regarded as a driver of change across all field particularly in business and impacts every aspect of human life that relies on technology. The term "transformation" encompasses the ability to recognize and undertake necessary actions when confronted with new technologies, and it should not be confused with simple change. Materials and Methods In terms of purpose, this study was applied, and regarding its methodological nature, it was descriptive-correlational. The statistical population consisted of all agricultural producers in Ardabil Province. Given the infinite size of the population, a sample size of 384 was determined using Cronbach's alpha formula; these individuals were selected from the population via simple random sampling, and the research questionnaire was distributed among them. The validity of the questionnaires was assessed and confirmed through confirmatory factor analysis, while their reliability was verified using Cronbach's alpha. Data analysis was conducted using structural equation modeling with the aid of SPSS 26 and Smart-PLS 3 software. Results and Discussion Data analysis was conducted using the structural equation modeling (SEM) method with the aid of SPSS 26 and Smart-PLS 3 software. The findings indicate that virtual reality, augmented reality, and digital transformation have a positive and significant impact on smart agriculture. As an emerging technology in this field, virtual reality can enhance training, decision-making, system design, and farm management. Augmented reality technologies facilitate the simulation of various agricultural stages and methods, allowing collected data to inform relevant decisions; meanwhile, digital transformation by establishing technological infrastructure and fostering smart advancements, productivity gains, and resource optimization—creates a robust foundation for the development of smart technologies. Conclusion This study was conducted to analyze the roles of virtual reality and augmented reality technologies in the development of smart agriculture, with digital transformation serving as a mediating factor. It posits that, given the necessary infrastructure, virtual reality has a positive and significant impact on smart agriculture—a finding consistent with the results of research by Chatterjee et al. (2025). Accordingly, it can be concluded that virtual technologies play a significant role in the development of smart agriculture. Indeed, as an emerging technology in this field, virtual reality can facilitate improvements in training, decision-making, system design, and even farm management. Given the existence of the necessary infrastructure, augmented reality has a positive and significant impact on smart agriculture. This finding aligns with the results of research conducted by Sara et al. (2024). Accordingly, it can be stated that augmented reality plays a vital role in the development of smart agriculture by integrating the real world with digital data within agricultural processes; specifically, through the use of smart glasses or augmented reality-based applications, agricultural producers can visualize—in real-time and in a graphical format—data collected by specialized tools. Given the existence of the necessary infrastructure, virtual reality has a positive and significant impact on digital transformation. This finding aligns with part of the results from the study by Rath et al. (2019). Consequently, virtual reality can be considered a key technology in the process of digital transformation; by enabling users to be present in digital environments, this shift from mere viewing to actual experiencing renders human interaction with technology deeper, more natural, and more effective. Given the existence of the necessary infrastructure, augmented reality has a positive and significant impact on digital transformation. This finding aligns with the results of the study by Rath et al. (2019). Accordingly, it can be stated that augmented reality can play a crucial role in digital transformation. Given the existence of the necessary infrastructure, digital transformation acts as a bridge between virtual reality and smart agriculture. As a key technology within digital transformation, virtual reality transforms agriculture from a traditional activity into a smart, data-driven, and sustainable system.

Abstract Introduction Iran’s agricultural sector plays a strategic role in ensuring food security and generating non-oil export revenues. However, growing water scarcity, climatic constraints, and global market instability have posed serious challenges to the sustainability of agricultural exports. Policies restricting exports of water-intensive crops-often implemented without considering economic water productivity-have further distorted the export structure and reduced overall efficiency. This study aims to identify the optimal export pattern of low water-consuming agricultural products in Iran while examining the dynamics and stability of target export markets. The central research question is whether Iran can restructure its agricultural exports in a way that either (a) maximizes export revenue for a given level of virtual water consumption, or (b) minimizes virtual water consumption while maintaining the same export earnings. To address this, a hybrid analytical framework combining the Markov chain model and mathematical programming was developed. Materials and Methods The research consisted of two complementary stages: Stage one: Market Stability Analysis (Markov Chain Model): The Markov model was applied to analyze the persistence and transition probabilities of Iran’s major agricultural exports across key destination markets during 2013–2022. This probabilistic approach enabled the identification of market stability, volatility, and dependence patterns for products such as saffron, pistachios, dates, apples, raisins, figs, almonds, and watermelons. Stage two: Export Optimization (Mathematical Programming): Two models were formulated: Model a: Maximize export revenue subject to a constraint on virtual water consumption. Model b: Minimize virtual water consumption subject to a constraint on export earnings. These models were solved under different water and income scenarios to explore the trade-offs between economic performance and water sustainability. Scenario analyses tested the impacts of stricter or more relaxed water constraints on the optimal export composition. Results and Discussion 1. Market Stability and Dynamics The Markov chain analysis revealed that Iran’s agricultural exports are highly unstable and geographically concentrated, relying heavily on a few volatile markets. Generally, smaller markets showed greater stability, whereas larger markets were more volatile. Saffron: Afghanistan, with only a 5% share, showed the highest stability (57%), while Spain-despite a large share-was highly unstable. Pistachios: China and “other destinations” had the highest stability (27%), whereas the UAE, which absorbed most exports, was volatile. Dates: India was the most stable destination (73%) with a moderate share. Apples: Iraq was both the dominant and most stable destination (44% share, 24% stability). Similar trends were observed for raisins, figs, almonds, and watermelons, indicating the need for market diversification and strategic reorientation toward more stable destinations. 2. Optimal Export Composition The optimization results demonstrated a clear trade-off between water use and income. When stricter water constraints were applied, low water-consuming crops (e.g., saffron, figs, and almonds) gained larger shares in the optimal export mix. Conversely, under relaxed constraints, water-intensive crops (e.g., watermelons, apples) expanded, yielding higher revenues but lower water productivity. Among all crops, saffron emerged as the most efficient in both water and economic terms, consistently appearing as a core component in all optimal scenarios. Quantitatively, restructuring the export composition could reduce virtual water use by 5-40% without lowering export income, or increase export revenue by 5-55% while maintaining current water consumption. These findings underscore the potential of aligning trade policies with water resource management to enhance both economic and environmental outcomes. 3. Policy Implications The results indicate that export earnings could increase by approximately 5–55% while maintaining water consumption at its current level in the export pattern. Considering these findings, export incentives for products that the optimal pattern recommends reducing could provide an effective policy instrument. The findings also call for a shift in the basis for classifying agricultural products from physical water intensity to economic water productivity. Even under a virtual-water minimization objective, the export of some physically water-intensive products may remain economically justified when they generate high economic returns per unit of water. Export policy should also account for demand conditions in individual destination markets. Accordingly, agricultural export policies should adopt a destination-oriented approach, with decisions to restrict or promote the export of each product informed by economic water indicators, the importance of the destination market, demand in the target market, and the strategic contribution of each market-product combination to national foreign-exchange earnings. Conclusion Integrating Markov chain analysis with optimization modeling provides a practical framework for sustainable export policy design. The results indicate that Iran’s current export strategy compromises both market stability and water efficiency. Strategic market diversification and prioritization of water-efficient crops can simultaneously enhance export performance and reduce water stress. This study suggests that Iran can save up to 40% of virtual water without reducing export income or increase export earnings by up to 55% while maintaining current water use. These findings align with Article 11, Clause 2 of Iran’s Seventh Development Plan, and emphasizing incentives for water-efficient agricultural exports. Future research should incorporate climatic variability, global price fluctuations, and partner-country trade policies to refine the model further, ultimately promoting alignment between agricultural trade strategy and sustainable water management.

Abstract Introduction Despite its vital importance, the agricultural sector in Iran faces structural challenges and weaknesses in an efficient marketing system. The issue of gaining competitive advantage and higher profitability must be accompanied by a full understanding of international and export markets. The development of greenhouse cultivation is expanding owing to water-saving policies under climate change conditions. The international entrepreneurial marketing (IEM) approach, as an innovative and opportunity-oriented strategy for creating value in foreign markets, is a strategic necessity for greenhouse units in Tehran Province. However, in practice, numerous obstacles, such as structural and operational barriers, have limited the ability of these entrepreneurs to transform global opportunities into economic value and sustainable economic development and have negatively affected the key dimensions of IEM, namely, risk-taking and innovation at the international level. The main objective of this study was to identify, analyze, and prioritize the barriers and limitations of international entrepreneurial marketing of greenhouse products from the perspective of greenhouse producers in Tehran Province. Materials and Methods This study was applied in terms of its objective and employed a descriptive–survey (quantitative) research design. The statistical population comprised 1,934 greenhouse producers across four counties in Tehran Province. A sample of 322 producers was selected using stratified simple random sampling. The main data collection instrument was a researcher-made questionnaire, the face and content validity of which were confirmed by an expert panel. To conduct an overall evaluation of the measured indicators, the preliminary draft of the survey and questions prior to the interview stage with rural respondents were reviewed by an expert panel consisting of faculty members in agricultural extension and education, environmental sciences, psychology, social sciences, sociology, and rural planning. Based on their views, the necessary revisions were applied until final approval was obtained. Cronbach’s alpha coefficient was used to assess the internal reliability of the research instrument, which ranged from 0.7 to 0.9. The barriers to international entrepreneurial marketing were measured using seven latent variables (economic-financial, supportive-legal, infrastructural-institutional, policy-planning, green marketing, educational-informational, and socio-cultural) and 28 observed variables. To analyze the barriers, confirmatory factor analysis (CFA) was performed using SmartPLS v.3. Results and Discussion Confirmatory factor analysis (CFA) results indicated that the seven-factor structure of the barriers demonstrated satisfactory model fit, validity, and reliability, and all components were statistically significant at the 99% confidence level. Economic and financial barriers (path coefficient = 0.848), supportive-legal barriers (0.820), infrastructural-institutional barriers (0.819), green marketing barriers (0.766), educational-informational barriers (0.753), socio-cultural barriers (0.627), and policy-planning barriers (0.607) were ranked first to seventh, respectively. Among all dimensions, economic and financial barriers emerged as the most critical constraints in international entrepreneurial marketing. Within the economic and financial dimensions, factor loadings highlighted that the lack of adequate capital for standardizing and equipping greenhouse production units, coupled with insufficient governmental support in providing loans and financial incentives, particularly the high interest rates of bank loans, represented the most significant challenges. Following this, supportive-legal barriers were strongly characterized by government-imposed sanctions, restricted access to high-quality and authorized production inputs, and procedural difficulties in obtaining permits for exports and international marketing. The infrastructural-institutional dimension ranked next, primarily due to the absence of smart digital infrastructures for global and online marketing and persistent weaknesses in the transportation systems. Green marketing barriers ranked fourth, influenced by global market threats such as inflation, economic sanctions, and geopolitical conflicts, alongside the lack of governmental support for guaranteed purchasing of certified green or healthy products. The fifth-ranked dimension, educational-informational barriers, was driven by shortages of specialized human resources in market management and international trade and the absence of effective training and extension programs related to export procedures. Socio-cultural barriers were also notable, including insufficient cultural and educational foundations for entrepreneurship, creativity, and innovation, and low levels of public trust in online purchasing platforms. Finally, the policy and planning barriers, characterized by weaknesses in agricultural insurance systems and limited awareness of national strategies for regional and international markets, were ranked last but remained significant barriers to international entrepreneurial marketing from the perspective of greenhouse producers in Tehran Province. Conclusion The results further indicate that macro-level environmental and institutional barriers, particularly economic and financial constraints, constitute the most fundamental and influential challenges limiting international entrepreneurial marketing. The prominence of economic and financial barriers as the highest-priority constraint suggests that the primary obstacles originate from the external business environment rather than from entrepreneurs themselves. As long as stable access to credit, investment support, and relief from sanctions are not available to facilitate production standardization, innovation, and risk-taking, progress along the export pathway will remain constrained. Furthermore, the findings indicate that these barriers have direct negative effects on the key dimensions of international entrepreneurial marketing (IEM). Therefore, overcoming these constraints requires substantial government intervention in export financing, administrative facilitation, and the development of smart infrastructure and cold supply chains. In this regard, designing a mechanism for targeted export investment facilities with low interest rates-aimed at standardizing and mechanizing cold storage and packaging equipment in greenhouse units-is recommended. In other words, addressing or reducing a single barrier alone cannot lead to a significant improvement in the performance of international entrepreneurial marketing. Instead, a comprehensive and coordinated approach is required that simultaneously considers economic, legal, infrastructural, and human capacity dimensions. These findings highlight the importance of designing and implementing integrated policies and programs by the government, supporting institutions, and the private sector to enhance export capacity and increase the international market share of greenhouse units.

Abstract Introduction
Global population growth and shrinking natural resources have intensified pressure on agricultural systems, positioning sustainable waste management as a national priority, particularly in arid and semi-arid countries like Iran. Agricultural activities generate substantial biomass residues, yet inefficient handling (e.g., open burning, uncontrolled dumping) contributes significantly to greenhouse gas (GHG) emissions (CO₂, CH₄), energy overuse, and economic losses. Globally, one-third of food production is lost or wasted (FAO, 2011, 2013), with profound environmental and food security implications. In this context, the Circular Waste-Based Bioeconomy (CWBE) framework offers a strategic pathway: integrating circular economy principles into agricultural systems to transform waste into compost, biogas, animal feed, and bio-based materials—thereby enhancing resource efficiency and reducing environmental footprints. However, existing efficiency assessments in agricultural waste management in Iran predominantly ignore undesirable outputs, yielding an incomplete picture of sustainability. This study addresses that gap by evaluating the Eco-efficiency of agricultural waste recycling across Iran’s 31 provinces over 2014–2019 (1393–1398), using a Dynamic Network Data Envelopment Analysis (DN-DEA) model that jointly accounts for desirable and undesirable outputs.

Materials and Methods
We construct a dynamic network model inspired by Lu et al. (2022), conceptualizing waste recycling as a two‑stage system: (1) waste collection and preprocessing, and (2) valorization and environmental mitigation. The DN‑DEA model allows efficiency scores to reflect carry‑over effects—such as investment in fixed assets—across time periods, making it suitable for assessing policy persistence and technological lock‑in.
Inputs include: (i) monetary cost of managing agricultural waste (IRR, adjusted for inflation), and (ii) energy consumption (GJ) in collection, transport, and processing. Desirable output is the quantity of recycled biomass (tonnes), while undesirable outputs encompass: (a) CO₂ emissions (tonnes), (b) CH₄ emissions (tonnes), (c) total energy consumption (as above, dual‑counted to penalize inefficiency), and (d) waste management cost (as a proxy for incomplete valorization). Data were compiled from the Statistical Center of Iran, Agricultural Jihad provincial reports, and the Central Bank’s economic databases. All monetary values were deflated using the consumer price index (base = 1390), and emission factors were standardized using IPCC Tier 1 guidelines adapted to Iran’s agronomic conditions. The model was solved using GAMS 36.2.0 (with CONOPT solver), and statistical validation—including Pearson correlation matrices and significance tests—was performed in SPSS 28.
Results and Discussion
Results reveal striking regional heterogeneity. Five provinces—Tehran, Bushehr, Ilam, Khuzestan, and South Khorasan—consistently achieved full efficiency (score = 1.00) across all six years, functioning as benchmarks. In contrast, Golestan (avg. θ = 0.34), Kurdistan (0.35), Sistan & Baluchestan (0.36), East Azerbaijan (0.41), and Kermanshah (0.41) exhibited chronic underperformance. Nationally, average efficiency declined from 0.72 in 2014 to 0.61 in 2019, signaling systemic deterioration—potentially linked to subsidy distortions, energy price volatility, or drought-induced feedstock scarcity.
Crucially, Pearson correlation analysis confirmed strong, positive, and statistically significant (p < 0.01) relationships between recycling efficiency and the management of undesirable outputs. This implies eco-efficiency synergy: provinces excelling in one dimension (e.g., lowering disposal costs) tend to outperform across all environmental and economic metrics. Moreover, undesirable outputs are highly inter correlated (e.g., energy–CO₂: r = 1.000; CO₂–CH₄: r = 0.999), suggesting that interventions targeting energy efficiency will likely reduce multiple emissions simultaneously. Spatial mapping (Figure 2) further confirms a pronounced east–west efficiency gradient, with high-efficiency clusters in central/southern/eastern provinces and low-efficiency zones concentrated in the northwest and southwest—mirroring disparities in infrastructure, technology access, and institutional capacity.

Conclusion
This study advances the literature by: (i) applying DN-DEA to Iranian agricultural waste for the first time; (ii) integrating four undesirable outputs simultaneously; and (iii) linking efficiency diagnostics to concrete, region-specific policy levers. Findings underscore that a one-size-fits-all approach is inadequate: instead, precision sustainability governance, where efficiency metrics inform spatially differentiated interventions, is essential. We recommend:
Region-targeted interventions for low-performing provinces (e.g., Golestan, Kurdistan, Sistan & Baluchestan).
Knowledge diffusion mechanisms, such as peer-learning networks, to transfer best practices from benchmark provinces
Efficiency-based budgeting, where provincial subsidies or green credit access are tied to annual DN-DEA scores.
Ultimately, improving eco-efficiency in agricultural waste recycling is not merely a technical challenge but a governance imperative, one that can simultaneously bolster rural livelihoods, enhance resource security, and advance Iran’s commitment to low-carbon development.