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Latin America and the Caribbean (LAC) region is one of the most important players in global agricultural trade. They have vast potential to strengthen their position as a result of the region's opportunities to increase agricultural production when combined with growing global demand, which could help the region's economy thrive. To discover the LAC potential agricultural trade pattern, this paper aims to analyse the determinants of LAC agricultural bilateral export for the period 1995-2019. The gravity model of trade was employed by estimating various Poisson pseudo-maximum likelihood (PPML) models including zero trade flows for panel data. The findings show that importers' GDP of LAC countries has a greater impact on agricultural trade compared to LAC exporters. Cultural similarities (common language) and countries' participation in Southern Common Market [Mercado Común del Sur (MERCOSUR)] stimulated agri-food export. Conversely, distance (transportation), past colonial links, and North American Free Trade Agreement (NAFTA) raised trade costs, having a negative impact on the export of agricultural products. The impacts of environmental regulations are ambiguous. This paper contributes to the literature by investigating the factors of agri-food export in LAC countries, which can be an important instrument for decision-makers adjusting agricultural trade policy.

This article deals with the implementation of innovations and quality improvements into operations of mainly small and medium-sized enterprises and family farms in the Czech Republic. The aim is to improve the competitiveness of production in internal, European, and global markets, as well as in the context of optimising the settings and recommendations for new subsidies within the Common Agricultural Policy for the forthcoming programming period. The dependence of the use of various forms of innovation in relation to financial crises was investigated, as well as the general (proactive vs. reactive) attitude to innovation, and also mutual operation with Local Action Groups (LAGs) as another source of support. Due to the structure of the obtained data, a general linear model (GLM) was used for the evaluation. Using the methods of advanced statistical testing, the two most important aspects of the implementation of innovations in agriculture enterprises were identified from the obtained data. These two key aspects are: cooperation with the LAG and the use of consultants for processing project applications. Thus, other factors, the size of the farm, the existence of financial problems and the length of farming are not statistically significant. This contribution is intended to help public administration bodies that have a power to set the support conditions for the Rural Development Programme.

The paper analyses the effect of electronic-trading (e-trading) on the wholesale prices of select commodities in agricultural marketplaces to aid agrarian income levels. Post a literature review, the researcher performed a field survey to get the opinions of 371 farmers and traders. The researcher also conducted the descriptive statistical analysis, the difference in differences analysis, and the t-test analysis to show the wholesale price improvement after the e-trading platform implementation. The field survey findings and the statistical analysis suggest an increase in average wholesale prices of select agri-commodities in select markets of India due to the National Agriculture Market (eNAM) e-trading platform effect. The suggestions to practitioners and social policymakers highlight an improvement in the functioning of e-trading in terms of better prices for farmers, lowering transaction costs, increased transaction speed, reduced administrative hurdles, improved infrastructure and eventually higher income for a farmer. The knowledge base developed in this paper will help researchers reduce the knowledge gap in agricultural pricing.

Globally, people started gravitating toward organic food as health consciousness rose. From the farm to the consumer's fork, organic food is produced using a comprehensive method. Organic farming has provided farmers and producers with many opportunities, but there are still difficulties concerning the cost of production and distribution. Due to environmental sustainability challenges, climate change, soil fertility, biological assortment, and consumer well-being, organic farming is attracting more attention than conventional farming. Organic farming can be done using standardised methods and has many common issues with conventional farming. Organic farming has some unique problems as well. With the right strategies, careful planning, and government assistance, many difficulties faced by farmers can be addressed. The downstream material flow of the supply chain, and in particular demand estimation, market price, and identifying customer segments, has been identified as a significant problem in organic farming. Massive losses have been incurred along with the entire supply chain a due to the inadequate demand estimation that has caused surpluses and shortages in the produce. A few farmers have resolved the cash flows and material information controlling problem. This article proposes various related hypotheses associated with identifying customer segments, forecasting demand for the product, and profitability as market price changes in the crop.

This paper analyses the market entry strategy of the Spanish wineries and their destination markets. For this purpose, channel adjustment was analysed. The novel aspect of this research is the use of exports on a winery level, basing the explanation of their export performance on a combination of internal decisions of the companies, and characteristics of the wine destination markets, in accordance with the purchasing patterns of their consumers. The results revealed the importance of strategic adjustment between winery and market destination, even though the importance of adjustment depends on the level of exports. Thus, channel adjustment is important for the probability of export and export intensity.

Based on panel data from 2010 to 2020 of 151 A-share listed food-related enterprises in China, this research uses a fixed-effect model to analyse the impact of digital transformation on total factor productivity (TFP) in food-related enterprises. Our findings indicated that digital transformation has a positive and significant catalytic effect on TFP improvement in food-related enterprises. The mechanism test revealed that both cost-saving and innovation capacity enhancement effects of digital transformation contributed to the promotion of TFP improvement in these enterprises. Moreover, our heterogeneity analysis suggested that digital transformation is more effective in enhancing TFP in state-owned enterprises (SOEs) in the food-related industry, indicating that SOEs play a representative role in promoting advanced productivity in agricultural development. We also found that capital-intensive and technology-intensitve food-related enterprises were experiencing productivity paradox traps. Our results confirmed that digital transformation brings catch-up effects to labor-intensive food-related enterprises and those located in major grain production regions. Overall, this research can provide valuable insights for policymakers to upgrade the digital-enabled food industry.

Geographical indication (GI) represents the specific good quality and reputation of the regional characteristics of agricultural products, which is a positive approach for stabilising the export of agricultural products, realising high quality and high prices for agricultural products and rural revitalisation. Based on the China-EU Geographical Indications Agreement, this paper discusses the differences between China and the European Union (EU) in terms of GI protection from three aspects: the institutional framework, the operational system, and the operational status of GIs. The purpose of the study is to identify the differences between China and the EU in the protection of GIs, China's shortcomings, and gaps, and to propose policy recommendations for China to protect GI products better, exploit the economic impact of GIs and enhance the competitiveness of China's exports.

In recent years, the external shock represented by COVID-19 has caused significant fluctuations in global corn prices. Based on the weekly data on international corn prices from 2020 to 2023, this paper constructs autoregressive conditional heteroskedasticity (ARCH) class and time-varying parameter – vector autoregression (TVP-VAR) models. After analysing the characteristics of corn price fluctuations, it further analyses the influence of external uncertainties such as COVID-19, international finance, the corn futures market, and international exports of corn on corn price fluctuations. The results show that international corn price fluctuations always have significant asymmetry. Nevertheless, the influence of past changes on the future will gradually disappear, and the corn market is not characterised by high risk and high return because of the phenomenon of flat or declining absolute returns during the periods of high volatility. All the selected external shocks also have a time-varying impact on corn price fluctuations, and there are differences in the impact size, impact direction, and impact duration. The external shocks led by COVID-19 had a transmission effect on other factors and then affected corn price fluctuations.

Farms are key to agricultural advancement and carbon emission reduction. Understanding the influence of farm size on emissions is vital for eco-friendly farming. Our study used an econometric model with instrumental variable adjustments to examine the effect of farm size on greenhouse gas emissions, revealing an inverted U-shaped relationship. The findings revealed that emissions increased with farm size until a peak and then decreased. We identified an optimal farm size range (0.45 km² to 0.58 km²) for lower emissions, where the farm size maintaining the lowest greenhouse gas emissions per unit area was 0.58 km², while the lowest greenhouse gas (GHG) emissions per capita occured at a farm size of 0.69 km². Reducing emissions intensity per unit area is easier than reducing GHG emissions per person. Policymakers should prioritise promoting the expansion to moderately sized farms as a means of achieving emission reduction targets rather than solely increasing the number of farms. Overall, these insights offer policymakers novel approaches for ecological farm planning and the transition toward a low-carbon agriculture sector.

This study aims to examine the relationship between domestic and international prices of di-ammonium phosphate (DAP) and urea fertilisers together with exchange rates in Türkiye using the non-linear autoregressive distributed lag (NARDL) model on monthly data for the period of January 2011 to September 2022. The result of the study provides empirical evidence about the presence of asymmetries in the short and long-run among these fertilisers. The findings of the study confirm that international prices of di-ammonium phosphate and urea fertilisers have a symmetric effect in the long-run and exchange rate of the Turkish lira to US dollars has an asymmetric effect on the domestic prices of fertilisers in the short run. This is the first study in Türkiye to delineate the dynamic simultaneous interaction among these markets and its findings can be extremely useful for academicians, and policymakers to make decisions regarding the market structure of countries that do not have sufficient domestic resources for fertiliser supply and are dependent on imports.

Rice productivity needs to be increased to feed Bangladesh’s growing population. Productivity can be increased by adopting improved varieties and management practices, which require additional capital inputs. In this article, we aim to estimate the effect of formal and semiformal credit on rice productivity in Bangladesh. We surveyed 500 rice farmers to achieve these objectives. We used descriptive statistics, propensity score matching and Heckman’s endogenous treatment effect model to analyse the data. The findings indicate that literacy, television ownership and training positively influenced access to formal credit. In general, credit recipients achieved higher productivity than did non-recipients. In the situation of credit source-specific effect, we found mixed results. Given the estimated difference of 438 kg/ha to 495 kg/ha, the results indicated that formal credit recipients had significantly higher productivity than did formal credit non-recipients. In contrast, endogenous treatment effect model results suggested that both formal and semiformal sources of credit had a significant effect on rice productivity. Increased agricultural loan disbursement through formal and semiformal credit institutions is strongly advocated. Farmers’ decision-making abilities regarding the most effective source of credit can be improved through training in financial literacy. The central bank of Bangladesh, along with the credit regulatory authorities of non-governmental organisations, can implement appropriate agricultural credit programmes for farmers.

In Spain, the leader in pesticide sales in the European Union, a high-tech and innovative company provides services to the wine industry to optimise phytosanitary work, reduce crop losses and lower production costs. Although the nature of its business encourages the transition to a sustainable agri-food system, it also involves risks associated with uncertainty. The objective of this article was to perform the valuation of the company through the real options approach, including an expansion option, analysing whether this company will be able to increase the value of its project by expanding its activity to a larger number of vineyards. Results showed that the application of the real options approach projected a higher result than the traditional net present value method, so that if the company makes additional investments in its precision agriculture project, these will increase the value by a 15%.

Fujian Province, China was chosen as the study area for estimating the marginal agricultural abatement costs within the province based on data for 2010–2020. The study employed these estimations as a pivotal factor affecting the efficiency of carbon emissions reduction, constructed an index model to gauge the potential of agricultural carbon emissions reduction, and delved into the urban agricultural carbon emissions reduction potential from the perspectives of economic development rights (equity) and carbon emissions reduction difficulty (efficiency). Our findings indicated a marked regional disparity in the marginal abatement costs of agriculture across Fujian Province, with the highest recorded at EUR 1.3771 × 108 per 104 tonnes and the lowest at EUR 0.6526 × 108 per 104 tonnes, albeit demonstrating general upward inter-annual trends. Furthermore, the assessment of agricultural carbon emissions reduction potential, grounded in the principles of equity and efficiency, revealed four distinct developmental tiers. Resource allocation pathways for carbon emissions reduction were subsequently delineated, informed by the stratification of high- and low-carbon emissions reduction potential indices alongside typological characteristics. The outcomes of this study offer strategic guidance to the government of Fujian Province in crafting suitable carbon emissions reduction strategies and in devising targeted action plans aimed at achieving the twin goals of 'carbon peaking' and 'carbon neutrality'.

This study examined the bidirectional impact of Chinese agricultural subsidy policies on agricultural efficiency and farmers’ income. It employed panel data from 2004 to 2020 across 31 Chinese provinces, and the three-stage least squares method was used for simultaneous estimation. Different regions and farmer types were analysed separately. The findings revealed a significant bidirectional impact of the agricultural subsidy policy on agricultural efficiency and farmers’ income, signifying a strong positive feedback loop. Varied types and levels of subsidy policies differently impacted regions and farmer categories, showcasing diverse outcomes and adaptive responses to subsidy policies. The ratio of total subsidy to GDP (SUBGDP) positively impacted production efficiency and per capita disposable income. This result suggests that the subsidy policy helped enhance agricultural production efficiency and increased farmers’ income levels. Conversely, the ratio of various subsidies to the total subsidy manifested different directions and degrees of impact on production efficiency and per capita disposable income, suggesting areas where the subsidy policy framework can be optimised. In addition to presenting a theoretical discussion on agricultural subsidy policies, this study provides theoretical insights and policy recommendations for the formulation and implementation of an optimal agricultural subsidy policy.

Corporate social responsibility (CSR) is also implemented in agriculture, where larger agricultural holdings have a higher influence. We focused on them and situated our study to a country with a large average farm acreage – the Czech Republic. The aim of the paper is to assess to what extent large agricultural holdings perceive socially responsible behaviour as being important and how it is manifested in their relationship to the stakeholders and the behaviour in economic, social and environmental areas using Carroll’s pyramid and concept of 3 ‘P’. It is also examined if the higher perception of CSR influences the assets. Firms were grouped according to the perceived CSR by a cluster analysis. The highest economic responsibility in cluster 1 corresponded to the relatively high value of the assets, but the highest was in cluster 2 and 3 with important legal and ethical responsibilities. Cluster 4 had the lowest CSR, the same as the value of the assets, but further investigation is needed. The most important stakeholders were the owners and employees, but also the range of activities was provided for the locals. CSR and the importance of the stakeholders in large Czech agricultural holdings were highly perceived, especially on an economic level and in the social area.

Adopting low-carbon agricultural technologies (LCATs) is fundamental to reducing carbon emissions in agriculture. Our study explores the factors influencing the adoption of LCATs and the roles of production outsourcing and specialised farming within the framework of off-farm employment. In this regard, survey data were collected from 1 040 farmers in the Yellow River region of China in 2020 to examine the effect of production outsourcing on the farmers’ adoption of LCATs. Potential mechanisms associated with specialised farming and off-farm employment are considered to comprehend this relationship. We also investigate the heterogeneous effects of production outsourcing on adopting LCATs, taking different education levels and arable land areas into account. The results show a positive association between production outsourcing and farmers’ LCATs adoption behaviour, even after considering self-selection bias. Specifically, outsourcing production can significantly increase the likelihood of farmers adopting low-carbon tillage, low-carbon irrigation, and low-carbon fertilisation technologies by 7.2%, 8.1%, and 7.3%, respectively. This effect is more pronounced among farmers with higher levels of education and smaller areas of arable land. Furthermore, production outsourcing increases the LCATs adoption by promoting specialised farming. The findings suggest that outsourcing is vital to alleviating the lack of LCATs adoption resulting from off-farm employment.

Agricultural subsidy policy can improve the planting enthusiasm of rural households by increasing their income. It is of great significance to assess and summarise the effect of the soybean and cotton target price subsidy policy and to determine future policy direction. Using the national rural fixed-observation point socioeconomic survey data from 2009 to 2017, the study employed the difference-in-differences (DID) method to evaluate the impact of the target price policy (TPP) on rural household income in China. TPP had no significant impact on the total income of rural households. Specifically, TPP increased the farm income of rural households but simultaneously reduced the wage income and had no significant impact on the other income. Moreover, the impact of TPP on rural household income varied with the planting scale and income level; the effect of TPP was strong among the non-poor or scale operation rural households. TPP implementation affected rural household farm and wage income by affecting farmers’ allocation of working time and cost input. Therefore, implementing TPP should consider farmers’ participation in non-farm employment, further adjust the subsidy intensity and scope, and combine direct subsidies with the poverty reduction effect in poor areas. The contribution of this article is to explore the implementation effect of target price subsidy policies from the perspective of farmers’ income, to deconstruct farmers’ income, and explore the mechanism of policy action. This paper provides a theoretical basis and policy inspiration for China to improve and adjust the agricultural subsidy policy, mobilise farmers’ enthusiasm to cultivate, and ensure national food security.

Rice cropped policy has been constantly changing, affecting the value of irrigated land. This study aims to examine distribution patterns of irrigated land value from a new perspective of uncertainties in single- and double-cropped rice policies in China. The real options approach was employed to calculate irrigated land value under policy uncertainty, and Moran’s index was applied to identify the spatial distribution characteristics of irrigated land value at the provincial level. The empirical results were as follows: significantly positive spatial correlations existed between the land value under two cropped rice policies. The northeast region of China had a low-value clustering effect based on geographical characteristics. In contrast, the southern provinces of China had a high-value clustering effect based on the criteria of administrative regions. This study considered policy uncertainty when evaluating the economic effect on irrigated land when revealing spatial correlation in land value. We provide a theoretical and empirical basis for the formulation of cropped rice policies.

Agro-based small and medium enterprises (SMEs) are currently receiving top priority among policymakers of the South Asian Association for Regional Cooperation (SAARC) nations  due to their great contribution to employment and GDP growth. This study examines the impact of financial literacy on the sustainable competitive performance of agro-based SMEs, with a focus on the mediating role of access to digital finance and the moderating role of business experience. Using Partial Least Squares Structural Equation Modelling (PLS-SEM), we analysed data from 345 SME owner-managers. The results indicate that financial literacy positively affects sustainable competitive performance, with access to digital finance serving as a significant mediator. However, business experience does not moderate the relationship between financial literacy and access to digital finance. These findings suggest that improving financial literacy and enhancing digital finance access are critical for the sustainable development of agro-based SMEs in the SAARC region.

The issue of productivity and performance in agriculture is significant because it affects a country’s competitiveness, sustainability, and self-sufficiency in agricultural production and is reflected in European policy. This study aims to determine which country had the most efficient large farms compared to other V4 countries and whether efficiency in each country translates into the performance of large farms. The data were obtained from the EU FADN (Farm Accountancy Data Network) database from 2005 to 2019. These data were then evaluated using the statistical methods DEA: CCR-O (Data Envelopment Analysis: constant returns to scale), DEA: BCC-O (Data Envelopment Analysis: variable returns to scale), and Pearson correlation coefficient. Regarding international comparisons in achieving efficiency as measured by DEA, Hungary is the best performer among the countries compared, followed by Czechia, Poland, and Slovakia. The correlation between efficiency and performance measured by Farm Net Value Added was demonstrated only for Hungary. The international comparison provided information about which country had the most efficient large farms, what the ranking of countries was in terms of efficiency, and for which countries efficiency had / did not have a potential impact on performance. At the same time, the relationships regarding the efficiency and performance of farms with an economic size above EUR 500 000 of standard output were clarified.

Policy constraints and market incentives have made it an important foundation for developing countries such as China to develop agricultural green transition policies. This study employed the panel data of 31 provinces in China from 2003 to 2022 and the three-dimensional framework of ‘institutions, technology, and marketisation’ to probe whether environmental regulation constraints or expected economic revenue incentives play a critical role in China’s current agriculture development. Whether the green transition of agriculture depends on environmental regulatory policy constraints and expected economic revenue incentives is related to the level of agricultural technology development and market development. Technology and market play a positive role in the agricultural green transition by enabling the realisation of agricultural green production and the realisation of the agricultural green market.

The widespread application of Internet technology in rural development has significantly facilitated the modernisation of agriculture and profoundly and positively impacts sustainable rural development. This study empirically investigates the effect of Internet access on farmers‘ participation in farmer professional cooperatives based on a sample of 3 349 participants from the 2020 China Rural Revitalization Survey (CRRS), using both probit regression and instrumental variable probit (Ivprobit) regression models. The results indicate that, firstly, Internet access significantly enhances farmers‘ participation in farmer professional cooperatives. Secondly, Internet access influences farmers' decisions to join professional cooperatives differently, with older farmers, those with less education, and non-cadre individuals being more significantly affected in their willingness to participate. The findings deepen the understanding of the relationship between digital technology and organisational participation in rural development and provide empirical evidence for formulating more targeted rural development policies.

The aim of this paper is to investigate whether the more pro-environmental attitudes of farmers influence the technical efficiency of agricultural sectors in EU regions (NUTS-2). To answer this, I employed data envelopment analysis (DEA) for efficiency analysis combined with the double bootstrapped truncated regression to investigate the relationship between environmental attitudes and technical efficiency. I found that this relationship is positive, i.e. pro-environmental attitudes were related to greater efficiency. An increase in the environmental attitude variable by one standard deviation led to an improvement in efficiency of 2.8–6 p.p. The higher share of farmers with formal training also proved to be a positive and significant determinant of efficiency. The share of arable land on which conventional tillage was used, and soil erosion proved to be significant but negative determinants of efficiency. Policymakers should present to farmers the environmental benefits of agricultural policy but should also highlight that greater environmental awareness translates into a more efficient operation.

This study investigates peer effects and agglomeration impacts on the cost efficiency of South Korean rice farms using a five-year panel dataset of production costs. We employed a time-varying stochastic frontier cost function approach to estimate cost efficiency and a linear-in-means model to quantify peer influences. The findings underscore peer effects as central to understanding and enhancing farm productivity, particularly in rice farming regions. Both specialisation and diversity of agglomeration positively influenced efficiency, with specialisation having a larger impact. Peer effects were stronger in highly rice-specialised areas. These findings indicate the necessity of incorporating peer influences and regional specialisation in agricultural policymaking for productivity enhancement. A nuanced, evidence-based approach leveraging peer dynamics and agglomeration economies is advocated to boost the efficiency of farming practices.

Agribusiness is currently faced with the challenge of providing sufficient quality food for a growing population with limited natural resources. Egg production, as an important source of nutrition, is a dynamically developing sector of livestock production on a global scale. Simultaneously, the increasing public and legal considerations of animal welfare affect egg-producing operations. This paper aims to provide insight into missing evidence in the trade-offs between animal welfare and efficiency in egg-producing farms in the Czech Republic and the European Union. Detailed data were gathered on the extent of the enriched cage and indoor cage-free housing systems (aviaries/barns) among the main 30 Czech table-egg-producers. Original micro data enlarged the information on table-egg producers collected using the Orbis database. For the efficiency analysis at the EU level, data on the housing systems were obtained from Eurostat and combined with aggregated data from the Orbis database. A robust data envelopment analysis was applied which benefits from including animal-welfare variables directly into the efficiency evaluation. The results showed a negative, but statistically insignificant, relationship between the animal welfare and efficiency of the egg producers for the Czech Republic table-egg producers as well as those on the EU-country level.

This study comprehensively examines multifaceted risk factors influencing wheat production among Turkish farmers, aiming to deepen understanding of how these factors shape farmers’ perceptions and decision-making processes. Utilising Structural Equation Modeling (SEM), we analysed the interplay of climate-related issues (F1), market dynamics (F2), and external events (F3), like COVID-19 and wars, alongside socio-demographic factors such as education, income, and land ownership. Findings revealed that higher education and increased agricultural income reduced price-related risks while expanding wheat cultivation areas heightened risk perceptions. Farmers in irrigated regions prioritised cyclical risks, whereas those in dry areas perceived climatic risks as more severe. Capital-intensive practices and storage facilities mitigate climate change and market variability risks, with committed wheat producers showing lower climate change risk perceptions. External factors like the Russian-Ukrainian war and the COVID-19 pandemic disproportionately impact irrigated area farmers. This study contributes to the existing literature by using empirical evidence from Turkish wheat farming to explore diverse risk perceptions, employing SEM to unravel complex risk factors and decision-making processes, thereby offering new insights for future agricultural risk management research.

The main research objective of this study is to present the dynamics of land productivity changes in EU agriculture in the years 2012–2020 and evaluate the influence of direct subsidies received by farmers on land productivity. The source data for 2012–2020 are secondary and come from Eurostat. The research results were prepared for the entire European Union (EU-28), and divided into ‘old’ countries (EU-15) and ‘new’ countries (EU-13). The results were developed using the method of assessing convergence (in terms of differences in land productivity in individual countries) using the coefficient of variation and the relative index of changes in individual Member States in relation to the EU average over the period under study. Results showed that between 2012 and 2020, average land productivity in the EU increased by 7%. At the same time, differences in land productivity between EU countries decreased. The correlation analysis confirmed a statistically significant relationship between land productivity and the amount of direct payments per ha of agricultural land. Additionally, results of the correlation between productivity per 1 ha and the total area of agricultural land in EU countries confirmed the law of decreasing marginal productivity of land.

Fruits and vegetables form the basis of a nutritional diet for the population. In addition to the basic determinants, such as market prices and consumer income, other factors influence consumer demand.  This paper aims to investigate how the age and gender of consumers influence the demand for fruit and vegetables in different European countries. In this paper, the demand for fruit and vegetables is understood through the population’s preferences for fruit and vegetable consumption, i.e., the proportion of the population that prefers to consume fruit and vegetables five or more times a day. The paper uses data from Eurostat. Factor, cluster and correlation analyses were performed using the SPSS software. The results of the analyses showed that the gender significantly determines the demand for fruit and vegetables in favour of women. Regarding the effect of age, this determinant was positively correlated with the preference for 5FV consumption in most countries. Potential interventions to promote fruit and vegetable consumption should mainly target men aged 15–19 and 75+ in Bulgaria, the Czech Republic, Latvia, Austria, Slovenia and Sweden, men aged 35–44 and 75+ in Croatia, Italy, Poland and Romania and women aged 15–19 and 55+ in Bulgaria and Romania, where their preference for 5FV was the lowest.

This article aims to highlight the importance of climate and environmental challenges for agricultural economics and policy. Empirical research based on the Data Envelopment Analysis (DEA) method determined the average technical efficiency and scale efficiency of farms in the European Union in total and in economic size classes in the period 2004–2020. The results indicate that agriculture is generally characterised by high technical efficiency and scale efficiency. Analysis by economic size classes of farms, defined by the standard sum of their agricultural output, shows that the relationship between the scale of production and technical efficiency of farms is U-shaped. The highest technical efficiency and scale efficiency are characterised by small, large and very large farms economic classes. Economies of scale shift the burden of food production to large farms, which provide food security and are technically efficient but excessively burdensome for the climate and the environment. Small farms produce environmentally friendly food but on a small scale. Therefore, increasing the technical efficiency of medium-sized farms can contribute to more sustainable food production that meets both food security and climate and environmental objectives. The Common Agricultural Policy 2023–2027 provides greater access to financial support for moderate-scale farms and farms undertaking ecosystem restoration activities. This may affect the strength and direction of the relationship between farm scale and productivity, including technical efficiency.

Farmers, often vulnerable within the agricultural supply chain, frequently encounter difficulties accessing and affording loans. This study introduces an innovative credit risk evaluation framework for farmers tailored to the agricultural supply chain. It includes three key aspects: farmers’ credit characteristics, the operational status of the agricultural supply chain, and overall credit conditions. Initially, the analytic hierarchy process (AHP) was used to assign weight coefficients to indicators. Then, the Elimination et Choix Traduisant la Réalité III (ELECTRE III) model was employed to determine farmers’ credit ratings. To demonstrate the impact of the agricultural supply chain on microfinance, the model’s effectiveness was then tested with 398 microfinance survey responses from Fuping County (World Dairy Goat Industry Development Demonstration Zone), Shaanxi Province, China, and its accuracy was further verified using BP neural network analysis. The results demonstrated the model’s proficiency in assessing farmers’ credit levels within the agricultural supply chain, which can aid in the resolution of various credit assessment and rating challenges. Furthermore, this study offers valuable insights into the integration of multi-criteria decision-making and machine-learning methods.