Estimates for Upscaling Potential

1 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 Estimates for Upscaling Potential Project NOVASOIL Project title INNOVATIVE BUSINESS MODELS FOR SOIL HEALTH Work Package WP2. Analysis and Development of Business Models to Promote Soil Health Deliverable 2.3 Period covered M14-M35 Publication date 30.09.2025 Dissemination level PU - Public Organisation name of lead beneficiary for this report TUM Authors Carina Ober, Fabian Frick, Mohammed Hussen Alemu, Søren Bøye Olsen, Tobias Holmsgaard Rønn, Thomas Lundhede, Insa Thiermann, Liesbeth Dries, Ferdinand Lang, Cheng Chen, Bettina Matzdorf, Kerttu Tammik, Tiina Köster, Kalvi Tamm, Merili Toom, Mart Laugis, Dimitre Nikolov, Ekatherina Tzvetanova-Georgieva, Krasimir Kostenarov, Ivan Boevsky, Maria Raimondo, Fabio Bartolini, Lucrezia Abruzzo, Daniele Vergamini, Luciano Pagano, Francesco Riccioli, Dania Baldoni, Shade Amini, Gloria Minarelli Contributors UCPH, WU, Leeds, ZALF, METK, ZSA, NBU, UNIFE, UPM, UNIPI, IDECO, ASAJA-SEV NOVASOIL INNOVATIVE BUSINESS MODELS FOR SOIL HEALTH Grant agreement ID: 101091268 Ref. Ares(2025)8236516 - 30/09/2025 2 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 QUALITY ASSURANCE PROCEDURES This document has been shared to the consortium in order to ensure their quality and to include a multidisciplinary point of view. Following a description of the different reviews can be found. TABLE REVISION HISTORY DELIVERABLE Row Version Date Reviewers Description 1 V1.0 21/02/2025 TUM Draft structure circulated 2 V2.0 27/09/2025 All contributors Pre-final version circulated 3 V3.0 29/09/2025 All contributors Final version 3 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 Project Consortium Nº Participant organisation name Country 1 EVENOR TECH SLU ES 2 LEIBNIZ-ZENTRUM FUER AGRARLANDSCHAFTSFORSCHUNG DE 3 ZEMNIEKU SAEIMA LV 4 NEW BULGARIAN UNIVERSITY BU 5 CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE CNRS FR 6 KOBENHAVNS UNIVERSITET DK 7 TECHNISCHE UNIVERSITAET MUENCHEN DE 8 ASSEMBLEE DES REGIONS EUROPEENNES FRUITIERES LEGUMIERES ET HORTICOLES FR 9 ISTITUTO DELTA ECOLOGIA APPLICATA SRL IT 10 UNIVERSITA DEGLI STUDI DI FERRARA IT 11 WAGENINGEN UNIVERSITY NL 12 CENTRE OF ESTONIAN RURAL RESEARCH AND KNOWLEDGE EE 13 UNIVERSIDAD POLITECNICA DE MADRID ES 14 UNIVERSITA DI PISA IT 15 ASOCIACION AGRARIA JOVENES AGRICULTORES DE SEVILLA ES 16 UNIVERSITY OF LEEDS GB 4 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 Table of Contents 1. Table of Content Summary ......................................................................................................................................................................... 8 1. Introduction .......................................................................................................................................................... 9 2. Conceptual framework – acceptance of soil health promoting business models . 11 3. Methodological approach – Discrete Choice Experiments ...................................................15 4. Results – Country-specific analyses ..................................................................................................... 17 4.1 Germany: Carbon Farming (TUM) ...................................................................................................... 17 4.1.1 Introduction .............................................................................................................................................. 17 4.1.2 Literature review ................................................................................................................................... 18 4.1.3 Methodology ............................................................................................................................................ 19 4.1.4 Results ......................................................................................................................................................... 25 4.1.5 Market potential estimation ......................................................................................................... 27 4.1.6 Discussion .................................................................................................................................................. 32 4.2 Germany: AgoraNatura (ZALF) ............................................................................................................ 35 4.2.1 Context ........................................................................................................................................................ 35 4.2.2 Methodology ........................................................................................................................................... 35 4.2.3 Results ........................................................................................................................................................ 36 4.3.4 Market potential estimation ........................................................................................................ 37 4.3 Netherlands: Carbon credits (WU) ................................................................................................... 38 4.3.1 Introduction ............................................................................................................................................. 38 4.3.2 Analysed incentives ........................................................................................................................... 39 4.3.3 Methodology .......................................................................................................................................... 43 4.3.4. Results ...................................................................................................................................................... 47 4.3.5 Discussion and conclusion ............................................................................................................. 52 4.4 Italy: Italian consumers (UNIFE, UNIPI) ......................................................................................... 56 4.4.1 Case study description ..................................................................................................................... 56 4.4.2 Method ...................................................................................................................................................... 56 4.4.3 Survey results ........................................................................................................................................ 59 4.4.4 Market potential estimation ....................................................................................................... 60 5 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 4.5 Estonia: Seed centre (METK) ................................................................................................................. 61 4.5.1 Case study description ...................................................................................................................... 61 4.5.2 Methodology .......................................................................................................................................... 62 4.5.3 Results ........................................................................................................................................................ 63 4.5.4 Market potential .................................................................................................................................. 65 4.6 Bulgaria: Agrotourism (NBU) ............................................................................................................... 66 4.6.1 Introduction and case study description .............................................................................. 66 4.6.2 Method ...................................................................................................................................................... 66 4.6.3 Survey results ........................................................................................................................................ 68 4.6.4 Market potential estimation ......................................................................................................... 71 4.6.5 Discussion ................................................................................................................................................ 74 4.7 Denmark: Soil health label (UCPH) .................................................................................................. 76 4.7.1 Introduction and case study description .............................................................................. 76 4.7.2 Method ...................................................................................................................................................... 77 4.7.3 Survey results ........................................................................................................................................ 88 4.7.4 Market potential .................................................................................................................................. 99 4.8 Italy: “Sustainability District of the Sandy Soil Area of the Po Delta in the EmiliaRomagna Region” (IDECO) ......................................................................................................................... 102 4.8.1 Introduction and case study description............................................................................ 102 4.8.2 Method .................................................................................................................................................... 105 4.8.3 Survey results ...................................................................................................................................... 107 4.8.4 Market potential estimation....................................................................................................... 110 5. General discussion ............................................................................................................................................. 112 Business model potential matrix .............................................................................................................. 112 5.1 Germany: Carbon farming (TUM) ....................................................................................................... 113 5.2 Germany: AgoraNatura (ZALF) ........................................................................................................... 114 5.3 Netherlands: Carbon credit (WU) ...................................................................................................... 115 5.4 Italy: Italian consumers (UNIFE, UNIPI) ......................................................................................... 115 5.5 Estonia: Seed centre (METK) .................................................................................................................118 5.6 Bulgaria: Agrotourism (NBU) ............................................................................................................. 120 5.7 Denmark: Soil health label (UCPH) .................................................................................................. 121 5.8 Italy: “Sustainable Po Delta Sand District of the Emilia-Romagna Region” (IDECO) ........................................................................................................................................................................................ 121 6 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 6. Conclusions ........................................................................................................................................................... 123 6.1 Consumer acceptance and willingness-to-pay ................................................................... 123 6.2 Farmer adoption, profitability, and drivers of large-scale uptake .......................... 124 6.3 Societal benefits of upscaling ........................................................................................................ 125 6.4 Overarching conclusions and policy recommendations ............................................. 126 7. References ............................................................................................................................................................. 128 List of Figures Figure 1. Choice Card Farmers ...........................................................................................................................21 Figure 2. Projected supply curves ................................................................................................................. 28 Figure 3. Projected demand curves ............................................................................................................. 29 Figure 4. Market diagram for each business model............................................................................31 Figure 5. DCE Attributes and Levels ............................................................................................................ 67 Figure 6. An Example of a food basket shopping situation. ......................................................... 83 Figure 7. Choice frequencies of ingredients for burgers. ............................................................... 89 Figure 8. Choice frequencies of ingredients for chicken with vegetables. ......................... 89 Figure 9. Choice frequencies of ingredients for spaghetti Bolognese. ................................. 90 Figure 10. National territorial framework of the case study “Emilia-Romagna Region sand area”. ...................................................................................................................................................................103 Figure 11. Pilot case area, province of Ferrara (Emilia-Romana Region) ..............................103 Figure 12. Soil mapping of the Emilia-Romagna region with details of sand content in the 0-30 cm layer of the soils in the pilot area in the province of Ferrara. Source: MOKA geoportal, Emilia-Romagna Region. ......................................................................................................... 104 Figure 13. Soil mapping of the Emilia-Romagna region with details of organic matter content in the 0-30 cm layer of soils in the pilot area in the province of Ferrara. Source: MOKA Emilia-Romagna Region geoportal. .......................................................................................... 104 List of Tables Table 1. DCE Attributes and levels .................................................................................................................. 19 Table 2. Market Potential Scenarios .............................................................................................................. 23 Table 3. Farm characteristics of the sample ........................................................................................... 24 Table 4. Consumer characteristics of the sample ................................................................................ 25 Table 5. Mixed logit model to explain farmer’s decision for a business model contract. ............................................................................................................................................................................................. 26 Table 6. Mixed logit model to explain consumers’ decision for a business model contract. ......................................................................................................................................................................... 27 Table 7. Mean WTP and WTA ........................................................................................................................... 29 7 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 Table 8. Statements and statement labels .............................................................................................. 45 Table 9. Summary of the descriptive statistics of the participants. ......................................... 48 Table 10. Factor scores of the statements (E: pro-environmental entrepreneur, T: traditional food provider, C: carbon farming enthusiast) ............................................................... 49 Table 11. DCE Attributes and Levels .............................................................................................................. 57 Table 12. Example choice card ......................................................................................................................... 58 Table 13. Descriptive statistics of socio-demographic variables. ................................................ 59 Table 14. Mixed logit model results............................................................................................................... 60 Table 15. Summary of significant findings ................................................................................................ 64 Table 16. Meals and their main ingredients ............................................................................................. 79 Table 17. Detailed descriptions of the four ingredient variants. ................................................. 80 Table 18. Soil health improving practices considered in this study. ......................................... 81 Table 19. Sociodemographic distributions (in percentages) and representativity of samples. ......................................................................................................................................................................... 85 Table 20. Baseline utility (marginal utility at zero consumption) for meal ingredients 91 Table 21. Cross-utility estimates for burger dish ingredients. ...................................................... 93 Table 22. Cross-utility estimates for chicken with vegetable ingredients. .......................... 94 Table 23. Cross-utility estimates for spaghetti Bolognese dish .................................................. 95 Table 24. Price elasticities of demand for ingredients of burger. .............................................. 97 Table 25. Price elasticities of demand for ingredients of chicken ............................................. 98 Table 26. Price elasticities of demand for ingredients of chicken ............................................ 99 Table 27. Business model potential matrix. ............................................................................................ 112 Abstract Task 2.3 focused on assessing the potential for scaling up promising business and innovation models identified in previous tasks. One key aspect of this assessment involved investigating acceptance of these business models among potential buyers and sellers. Several partners conducted valuation studies in representative contexts to examine the willingness-to-pay for improvements in ecosystem services or certification and understand their interactions. Another important focus was on adoption studies among farmers and land managers. This involved identifying relevant drivers that influence the adoption of selected business models. Furthermore, the task sought to estimate the potential market value and by this the hypothetical societal value that could be created through the scaling up of the selected business models. For categorising the different business models, the work in this task built on results from T2.2. 8 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 Summary Deliverable 2.3 of the NOVASOIL project assesses the upscaling potential of promising business and innovation models for soil health. Building on earlier tasks, the work evaluates farmer and consumer perspectives through a set of discrete choice experiments (DCEs) and other surveys conducted in multiple European countries. The central aim was to explore the willingness-to-pay (WTP) for soil-related ecosystem services and certification schemes, the willingness-to-accept (WTA) compensation for adopting soil-friendly practices, and the societal benefits of scaling up such models. The findings highlight substantial heterogeneity in preferences across contexts. Farmers generally favoured familiar and less risky models, particularly agrienvironmental climate schemes (AECS), which provide relatively secure payments and shorter contract durations. In contrast, carbon farming initiatives often faced scepticism due to their long-term commitments, result-based monitoring, and uncertainty around certificate prices. Value chain approaches, such as certification schemes and eco-labels, proved more attractive in scenarios with flexible conditions and short-term obligations. From the consumer side, the type of business model was less relevant than its design. Consumers preferred shorter payment commitments and valued guarantees of measurable environmental outcomes. Although many expressed willingness to support soil-friendly products or offset carbon emissions, price sensitivity and reluctance to engage in long-term contracts limited their commitment. Overall, the results suggest that while significant market interest exists, large-scale adoption depends on designing business models that combine economic feasibility, flexibility for farmers, credible environmental outcomes, and consumer trust. The societal benefits of successful upscaling include enhanced carbon sequestration, biodiversity preservation, and more resilient food systems, yet these gains require coordinated policy support, effective monitoring frameworks, and stable market incentives. 9 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 1. Introduction Healthy soils are essential for producing nutritious food, preserving biodiversity, and enabling a circular economy. They are critical to preventing land degradation and desertification and are key to achieving climate neutrality (European Commission 2025a). However, around 60% of European soils are currently in poor condition due to unsustainable practices such as intensive farming, pollution, and soil compaction (European Commission 2025a). The resulting loss of vital ecosystem services, such as food and feed production, water regulation, pest control, and carbon sequestration, leads to annual costs of at least €50 billion (European Commission 2025a). To address this, the EU introduced the Soil Monitoring Law in July 2023, aimed at promoting sustainable land use and restoring soil health (European Commission 2023). Priority actions include reducing erosion, salinization, and contamination, with particular emphasis on conserving soil organic matter – an essential measure to meet the EU Green Deal’s goal of climate neutrality by 2050 (European Commission 2025b). Increasing soil organic carbon (SOC) is a proven method of removing CO₂ from the atmosphere and storing it in soils (McDonald et al. 2021). Effective SOC-enhancing practices include improved crop rotation (especially legumes), intercropping, conversion of arable land to grassland, reduced tillage, and organic farming (McDonald et al. 2021; Lahmar 2010; Casagrande et al. 2016). In addition to climate benefits, these practices improve soil structure, water retention, erosion resistance, and nutrient availability (Dumbrell et al. 2016). Despite these advantages, adoption can be hindered by short-term opportunity costs, for example, reduced profits from diverse rotations or high upfront investment in specialized equipment like flotation tires (Sattler and Nagel 2010). Research shows that financial incentives, both public (Schaub et al. 2023; Schulze et al. 2024) and private (Buck and Palumbo-Compton 2022; Mamine et al. 2020; Weituschat et al. 2023), can play a key role in encouraging farmers to adopt soil health practices. A study by McDonald et al. (2021), commissioned by the Committee on the Environment, Public Health and Food Safety (ENVI), identified four distinct models for supporting soil health friendly practices. While the models differ in the payment mechanism and the parties involved, they all result in farmers being paid for an extra effort that increases the SOC content and thus sequesters CO2. First, in land management practice payments, central funders provide financial rewards for climate-friendly, carbon-sequestering farming practices. A prominent example is the agri-environmental climate schemes (AECS) under the Common Agricultural Policy's (CAP) second pillar. 16 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 in estimated parameters (Canessa et al., 2023). The probability of participant n choosing alternative i in choice t, conditional on the individual coefficient vector 𝛽𝑛 is: 𝑃(𝑐ℎ𝑜𝑖𝑐𝑒𝑛𝑡 = 𝑖/𝛽𝑛)=exp(𝛽𝑛’𝑋𝑛𝑖𝑡) Σ𝑗=1 𝐽exp(𝛽𝑛 ′𝑋𝑛𝑖𝑡) (3) To calculate the marginal willingness to pay/accept (WTP/WTA) of consumers or farmers for different contract attributes, coefficients of the Logit Model are used: 𝑊𝑇𝑃 = −𝛽𝑎𝑡𝑡𝑟𝑖𝑏𝑢𝑡𝑒 𝛽𝑝𝑎𝑦𝑚𝑒𝑛𝑡 (4) where βattribute is the parameter associated with attribute x and βpayment is associated with the payment attribute. WTP (or WTA, respectively) is the ratio of the attribute and the price coefficient. 17 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 4. Results – Country-specific analyses 4.1 Germany: Carbon Farming (TUM) 4.1.1 Introduction As previously described McDonald et al. (2021), four distinct models for supporting soil health friendly practices. This first study in Germany, focuses on the first three approaches, i.e., an AECS type business model, a value chain model and a GHG certificate model involving payments for practices that enhance SOC, with the associated certificates being sold via an intermediary. Farmers voluntarily participate in these business models, making their acceptance one of the most important success factors. Therefore, numerous other studies, in addition to McDonald et al. (2021), have investigated farmers' acceptance of these business models. Previous research has typically examined soil health business models in isolation, without reflecting real-world conditions where farmers must choose among multiple, competing incentive schemes, selecting only one to finance soil organic carbon (SOC) improvements. Under EU Regulation 2024/3012, which introduces the EU’s first certification framework for permanent carbon removals, only practices that exceed legal and standard requirements qualify as additional and are eligible for certification (European Union, 2025). As a result, farmers cannot receive multiple payments for the same SOC-enhancing practice, reinforcing the need to choose a single, most suitable model (McDonald et al., 2021). Contrary to previous studies, to directly compare different business models this study includes multiple SOC-promoting business models simultaneously. This provides a more realistic view of farmer decision-making under exclusivity constraints and additionality requirements. To fully assess the potential of these models, both producer and consumer perspectives are essential. Since consumers also have discretion in how they offset emissions, this study employs two discrete choice experiments: one with farmers to assess preferences for SOC remuneration models, and one with consumers to gauge preferences for CO₂ offsetting options. By estimating farmers’ willingness to accept (WTA) and consumers’ willingness to pay (WTP), the study evaluates the market potential of three business models and common contract attributes. The research aims to: 1. Identify farmers’ preferences for SOC remuneration model design. 18 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 2. Assess consumer preferences for CO₂ offset models. 3. Integrate both perspectives to evaluate the overall market potential of different models. From this, policy recommendations can be derived to promote business models with the highest acceptance and impact. Case study description CO₂-Land is a non-profit initiative founded in 2021 that promotes regional partnerships between farmers, businesses, and municipalities in southwestern Germany. Its goal is to sequester atmospheric CO₂ in agricultural soils through soil-organic-carbon (SOC) - building farming practices, while simultaneously enhancing soil fertility, water retention, and biodiversity. The initiative has developed its own standard for calculating and certifying CO₂ storage based on ISO guidelines, allowing farmers to receive compensation for each additional ton of carbon stored, financed through the voluntary purchase of CO₂ certificates by companies and local governments. Soil management practices include cover cropping, diversified crop rotations, organic fertilization, and reduced tillage, all of which contribute to building organic carbon sinks in the soil. These practices are documented and validated through soil sampling and ISO-standard monitoring. Through regional climate partnerships, CO₂-Land encourages active participation from all stakeholders and aims to establish a scalable model for agricultural carbon sinks. 4.1.2 Literature review In this section, we examine key success factors for farmer adoption identified by the literature. One of the most critical elements is the payment mechanism. The primary distinction among the three business models lies in how payments are structured: carbon market schemes typically rely on hybrid or results-based payments, whereas AECS and value chain models may also include fixed payments. Notably, the European Union strongly favours results-based approaches, viewing them as more efficient and performance-oriented (McDonald et al., 2021). Contract duration is another pivotal factor, particularly for long-term goals like carbon sequestration, which require sustained commitment. However, studies show that most farmers prefer shorter contracts, often favouring five-year terms due to concerns about flexibility and long-term obligations (McDonald et al., 2021). Incorporating mechanisms such as inflation adjustments or adaptive terms may improve the attractiveness of longer-term agreements. 19 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 Farmers also show highly differentiated preferences for specific soil health practices. Many opt for low-cost measures such as leaving straw residues or conservation tillage, while more capital-intensive options like afforestation or biochar application are frequently rejected. Willingness to accept compensation varies not only by practice but also by regional context and implementation costs (D2.2). 4.1.3 Methodology 4.1.3.1 Attribute selection, design, and implementation of the DCE To understand the preferences of farmers and consumers, two approximately equal discrete choice experiments (DCEs) were conducted with 366 farmers and 959 consumers in Germany. Data collection was carried out via online surveys during the end of 2024. For the farmer survey, a link to the questionnaire was posted on a service portal where farmers apply for direct payments and agri-environmental-climate schemes. Consumer data was collected through a market research company. The study focuses on remuneration models aimed at increasing soil organic carbon (SOC) content, which sequesters CO₂ and plays a vital role in enhancing soil health. For farmers, this necessitates adapting their management practices to meet these environmental goals. However, such adaptations typically entail additional costs, potential revenue loss, and increased workload. Given that farmers are already accustomed to compensation for opportunity costs through various AECS, this survey examined how they believe the additional efforts involved in soil and climate-friendly farming should be remunerated. A remuneration model in this context consists of four attributes. The levels for these attributes were developed based on an extensive review of the literature and an analysis of existing business models (Table 1). TABLE 1. DCE ATTRIBUTES AND LEVELS Attribute Levels Type of business model AECS, Carbon farming, Value chain Contract duration 1, 5, 10, 20 Years Monitoring (Probability of reaching goals) Action-based (Low), Hybrid (Medium), Result-based (High) Payment 30, 60, 90, 120, 150 € 20 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 - Type of the business model The three types of business models investigated in this study are land management practice payments (agri-environmental measures), GHG certificates, and value chain (CO2 label) business models. For the farmer, these business models differ regarding contract partners, required performance, and risk. For the consumer survey, the type of business model was described from the consumer's point of view. AECS, therefore, means that a kind of CO2 tax is levied, the GHG certificate model allows certificates to be purchased, and the value chain approach allows consumers to offset their CO2 consumption by buying certified food. - Contract duration The duration of the contracts is specified in years and is a critical factor for the effectiveness of a business model, as sequestered carbon can be easily released again through intensification practices. For instance, a contract duration of 5 years requires the implementation of selected methods to increase soil organic carbon (SOC), such as conservation sowing techniques and winter greening integrated into crop rotation, to be maintained throughout this period. For consumers, this entails an obligation to make annual payments over the entire duration of the contract. The attribute levels range from 1 year (basic) to 5 and 10 years, which correspond to the standard durations of AECS and carbon farming initiatives, respectively. Lastly, a 20-year duration represents a desirable long-term target, offering greater sustainability and carbon sequestration stability. - Monitoring Farmers in AECS and value chains are usually rewarded for carrying out certain practices in an action-based manner (McDonald et al. 2021). Recently, there have also been result-based measures. Carbon farming initiatives are usually result-based or hybrid, i.e. a mix of a fixed payment at the beginning of the contract and a result-based payment at the end of the contract period, based on soil sample results. For consumers, the attribute was framed as ‘certainty of target achievement’ (i.e., CO2 storage in the soil). The levels were called ‘Low’ (action-based), ‘Medium’ (hybrid), and High (‘result-based’). 21 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 - Payment Payment is stated in euros per ton of CO2. We generated a Bayesian efficient experimental design optimized for mean Defficiency (Scarpa & Rose, 2008) using STATA15 in both surveys. The design concluded on 18 choice cards separated into three blocks (Figure 1). Each participant was randomly assigned to one block and answered six choice cards, where they could choose between two contract options or the option not to participate. FIGURE 1. CHOICE CARD FOR FARMERS Consumers who chose one of the two contract options were asked how many tons of CO2 they would purchase annually under this model. Farmers were asked which SOCimproving practices they would implement and to what extent (hectares). In this way, carbon sequestration and, thus, also CO2 storage can be calculated for the farmer. In addition to the choice experiment, the consumer questionnaire included sociodemographic questions and questions on beliefs and attitudes toward climate change. Farmers were asked about farm characteristics, socio-demographic aspects, and current implementation and attitudes towards soil health practices and incentives. Farmers and consumers were informed of political goals such as climate neutrality or preserving and improving soil health at the beginning of the survey. Consumers were 22 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 made aware of the option of offsetting their CO2 emissions, which average 10.3 tons of CO2 equivalent per person in Germany (Umweltbundesamt, 2025b). 4.1.3.2 Econometric estimation At the beginning of the data analysis, we estimated a conditional logit model. The significant Hausman test indicated that the hypothesis of independence of irrelevant alternatives did not hold, and consequently we estimated a mixed logit model, allowing for different preferences of individual study participants. For both farmers and consumers, the model that best represented the data was identified using the quality criteria log-likelihood value, AIC, and BIC. In both cases, the payment attribute followed a log-normal distribution to restrict the price coefficient to be always positive, while all other attributes were included as random variables specified to be normally distributed. In addition to the general preferences of the study participants, we wanted to analyse in more detail which business models have the greatest market potential. To this end, a market for the respective business model was simulated using a supply and demand curve. The supply and demand curves represent the amount of CO2 stored or purchased at a certain price. The willingness to pay of consumers and the willingness to accept of farmers are determined by the negative ratio of the attribute and price coefficients. To depict a supply and demand curve, the individual WTP / WTA is calculated using the individual participant coefficients of the mixed logit model. For each desired scenario, we calculate the individual WTP / WTA as the sum of the WTP / WTA estimates for attribute x multiplied by the individual level of the respective variable. Dummy variables have either 0 or 1 in the equation, depending on whether the attribute level applies. Thus, 𝑊𝑇𝑃 𝑛𝑜𝑟 𝑊𝑇𝐴𝑛= ∑𝑊𝑇𝑃𝑖 𝐼 𝑖=1 𝑜𝑟 𝑊𝑇𝐴𝑖 ∗ 𝛥𝑥𝑖𝑗 where n = individual consumer or producer; x = attribute levels (i = 1, ..., I); and j = scenario (basic, improved, optimum). As a result, we obtain WTA for each farmer in each scenario or individual WTP for the consumers, respectively. To this end, three scenarios were first defined for each business model in which the market will be mapped. The three business models are mapped in their current form in the ‘basic’ scenario. For AECS, this is a contract term of 5 years with action-based monitoring. An improved but still realistically implementable business model is designed in the ‘improved’ scenario. For AECS, this could mean switching from action- 23 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 based to results-based programs. In the ‘optimum’ scenario, all attribute levels are set to the most effective level for SOC content, i.e., results-based monitoring with a contract term of 20 years. Like AECS, value chain approaches have so far been mostly action-based. An exit from label programs like organic farming is usually possible anytime. The ‘basic’ scenario for the GHG certificate model was illustrated based on an existing German carbon farming initiative (Table 2). This initiative is a non-profit association that promotes climate protection and soil fertility in agriculture with the help of SOC increase. Farmers carry out SOC-increasing practices for 10 years. Farmers already receive annual payments based on the expected value during the 10 years, while after 10 years, the actual SOC increase is honoured through soil samples. TABLE 2. MARKET POTENTIAL SCENARIOS Business Model Scenario Contract duration Monitoring AECS Basic 5 Action Based AECS Improved 5 Result Based AECS Optimum 20 Result Based GHG certificates Basic 10 Hybrid GHG certificates Improved 10 Result Based GHG certificates Optimum 20 Result Based Value chain Basic 1 Action Based Value chain Improved 5 Result Based Value chain Optimum 20 Result Based To simulate the German market, farmers and consumers are scaled up to the German population. As the market product under consideration is CO2 storage, the agricultural area is ultimately decisive for the amount of carbon sequestered. Therefore, we have decided to scale farmers up based on area rather than the number of farmers. The 366 farmers in the sample cultivate a total of 15,888 hectares of arable land, corresponding to an average arable area of 43.4 ha. This corresponds to 0.136% of arable land in Germany. The CO2 sequestration of a farmer is therefore multiplied by 736 (the reciprocal of 0.136%). 959 consumers correspond to 0.00114% of the German population, which means that one study participant represents 87,069 consumers. 4.1.3.3 Descriptive statistics Table 3 shows farm and farmer characteristics of the 366 farmers in the study compared to the German average. 24 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 TABLE 3. FARM CHARACTERISTICS OF THE SAMPLE Variables Sample Germany Average farm size (ha) 59.78 66e Farm size by classes (%) <10 ha 8.20 25.3 10-19.9 ha 15.03 19.7 20-49.9 ha 30.05 22.9 50-99.9 ha 26.23 16.7 >= 100 ha 20.49 15.4 Average arable area (ha) 43.41 45.8f Share of rented land (%) 43.32 Full-time farms (%) 47,54 52.8g Organic farms (%) 30,87 11.4h Production typed) Cash crop 74.59 Forage 54.64 Permanent crops 8.47 Horticulture 1.09 Dairy 22.40 Age by classes (%) <55 years 70,22 61i >=55 years 29.78 39i Agricultural education (%) 77.05 85i e) BMEL-Statistik: Betriebsstruktur und Entwicklung landwirtschaftlicher Betriebe f) BMEL-Statistik: Bodennutzung in Deutschland g) Studie zum Nebenerwerb in der Landwirtschaft: So ist die Lage - Bauernzeitung h) BMEL-Statistik: Ökologischer Landbau i) BMEL - Agrarsozialpolitik - Studie zum Arbeitsmarkt Landwirtschaft in Deutschland The sample is representative regarding the average farm size in Germany and the average arable area. The proportion of full-time and part-time farmers is also close to the German average. Organic farms are slightly overrepresented. This is presumably due to the higher interest of organic farmers in environmental and climate aspects. Farm managers in the survey are slightly younger than the German average. 959 consumers successfully participated in the consumer survey. The sample is representative regarding gender, age, education, and household income. The place of living is also representative (Table 4). 25 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 TABLE 4. CONSUMER CHARACTERISTICS OF THE SAMPLE Variable Sample Germany Male (%) a) 55.63 49.4 Age (%) b) 18-24 3.75 9.9 25-39 24.17 26.6 40-59 42.23 37.3 60-64 11.92 10.5 >65 17.88 15.7 Education (%) c) No degree 0.99 5.12 Low degree 21.19 23.47 Medium degree 34.66 30.23 High degree 43.16 37.58 Household Income (%) d) <1250 14.46 13.0 1250 – 2500 28.37 30.9 <1250 14.46 13.0 1250 – 2500 28.37 30.9 2500 – 3500 21.19 19.0 3500 – 5000 21.19 18.9 >5000 15.78 18.2 Place of Living e) Rural area (<5000) 19 13.55 Small town (- 20000) 22 26.55 Medium town (-100000) 21 27.59 Big city (-500000) 19 14.71 Metropole (>500000) 20 17.52 4.1.4 Results 4.1.4.1 Farmer preferences Farmers have a higher utility if they do not participate in any of the three business models (Table 5). If they decide to join a business model, AECS is favoured over a GHG certificates model and the value chain. The shorter the commitment period, the greater the utility for the farmer and the greater the willingness to participate. The discrete choice experiment shows that the willingness to accept (WTA) increases significantly more for contract durations between 5 and 10 years, while the increase decreases significantly between 10 and 20 years. This indicates a non-linear relationship in which the growth rate of the WTA is higher in the shorter contract periods and weakens in longer terms. In terms of monitoring, farmers favour actionbased monitoring over hybrid and result-based monitoring. 32 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 4.1.6 Discussion This study aimed to estimate the potential of different business models in comparison to each other by determining both producer and consumer preferences. The three business models investigated increase the soil's organic carbon content by storing CO2 from the atmosphere. The business models thus serve both soil health and greenhouse gas reduction by rewarding farmers for the effort required to implement the necessary practices. Farmers in our survey could choose between AECS (Agri-Environmental Climate Schemes), GHG certificates, value chain initiatives, or opt out of these measures entirely. In practice, many prefer not to participate at all, and if they do, they tend to favour AECS. This reluctance to engage in conservation schemes has been well documented (Greiner 2015; Hasler et al. 2019; Vaissière et al. 2018). A key reason behind this hesitation is the desire to maintain autonomy in farm management. Most farmers are resistant to additional restrictions, particularly given the already substantial bureaucratic burden associated with existing programs (Kuhfuss et al. 2016; Ruto and Garrod 2009). Flexibility is highly valued, and additional regulations are often perceived as an unwelcome constraint (Ruto and Garrod 2009; Ober et al. 2025). When farmers do choose to engage in a business model that compensates them for building soil organic carbon (SOC), AECS are generally preferred. This preference likely stems from farmers’ long-standing familiarity with AECS, which are well-established, offer secure payments, and are perceived as reliable (Lastra-Bravo et al. 2015). In contrast, newer models such as GHG certificates are often viewed with scepticism due to legal and pricing uncertainties (Raina et al. 2024; Dumbrell et al. 2016). The aversion to long-term contracts is also consistent across studies. Such contracts are seen as limiting farmers' ability to adapt to climatic or market fluctuations, thereby increasing perceived risk (Ruto and Garrod 2009; Lastra-Bravo et al. 2015; Figueredo 2024). Similarly, results-based monitoring is often considered riskier than action-based or hybrid approaches, further influencing farmers’ participation preferences (Canessa et al. 2023; Burton and Schwarz 2013). For consumers, the specific type of business model was rather unimportant, and they made little distinction between them. Instead, what mattered more were the duration of the payment obligation and the certainty of achieving climate-related targets. While consumers generally express interest in business models aimed at offsetting their CO₂ emissions, as supported by previous studies (Kragt et al. 2016), they are reluctant to commit to long-term financial obligations. In our study, consumers showed a clear preference for short-term engagements, rejecting payment commitments of 10 or even 20 years. 33 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 Moreover, when consumers do agree to make payments, they expect a guaranteed achievement of the stated environmental goals. Our findings also reinforce earlier research showing that individuals who place strong value on the opinions of their social circle are more likely to behave in environmentally conscious ways (Wuepper et al. 2019). Interestingly, the provision of additional information on the value of carbon farming had no statistically significant effect on consumer preferences. This is likely due to the extensive background information provided to all participants prior to the treatment phase. Before the choice experiment, we offered detailed explanations on how carbon sequestration works and how the different business models are structured. This foundational knowledge likely ensured a high baseline level of understanding across participants, leaving limited room for the additional treatment to have a measurable impact. For a business model to be viable, consumers’ willingness to pay (WTP) must at least match producers’ willingness to accept (WTA). When comparing average WTP and WTA across different scenarios, this condition was met in four out of nine cases, specifically, the ‘basic’ and ‘improved’ scenarios for both AECS and value chain models. The ‘basic’ scenarios represent current implementations. In the case of AECS, this typically involves five-year, action-based measures to enhance soil organic carbon (SOC), while value chain models generally offer greater flexibility and can often be terminated at any time (D2.2). However, permanence of SOC-enhancing practices is crucial; reverting to intensive practices can rapidly reduce SOC and release stored CO₂ (McDonald et al. 2021). For this reason, the ‘basic’ value chain scenario lacks ecological credibility. Similarly, action-based AECS can be inefficient, as they sometimes fail to provide additionality, i.e., farmers might undertake the same practices even in the absence of AECS, and the actual impact of measures is rarely verified (Burton and Schwarz 2013). Consequently, from an environmental standpoint, the basic AECS model is also not advisable. A major step toward increasing the ecological and economic effectiveness of these business models would be transitioning to results-based payments. Such a shift would ensure that only verifiable carbon sequestration is rewarded, aligning with EU regulations on carbon credits, which mandate the quantification of carbon removals (EU Carbon Removals and Carbon Farming (CRCF) Regulation (EU/2024/3012); European Union, 2025). Additionally, adopting multi-year commitments for value chain models could further improve their environmental integrity. Thus, the improved AECS and value chain models are preferable not only from an environmental perspective but also economically, as the average WTP exceeds the average WTA. 34 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 In contrast, GHG certificate models are characterized by a high average WTA among farmers. This scepticism stems from a combination of unfavourable conditions: these models typically requires results-based, long-term contracts, coupled with uncertainties around CO₂ certificate market prices. Farmers are often hesitant to invest in the necessary technologies under these conditions, fearing that price volatility could undermine profitability (Han & Niles, 2023; Dumbrell et al., 2016). While a policy instrument such as a guaranteed minimum price could theoretically stabilize the market, it risks creating a supply surplus if the market price falls below the guaranteed level. In such a scenario, farmers might abandon SOC-building practices once contracts expire, leading to adverse long-term ecological effects. An alternative could be to treat the market price per ton of CO₂ as a performance-based incentive, while offering fixed payments to fully or partially cover the implementation costs of carbon farming. The feasibility and acceptance of such hybrid models should be explored in future research. The supply and demand curves analysis shows a significantly stronger demand than supply for CO2 sequestration. This results from an average CO2 sequestration supply of 1.6 tons per hectare per year, which puts the available supply well below consumer demand. In order to increase greenhouse gas emission offset, farmers should ideally sequester more organic carbon and thus increase CO2 storage. There are two ways to embrace carbon sequestration in the future. Firstly, 15% of participating farmers in all choice cards have chosen the opt-out option. Future efforts should aim to attract these farmers to SOC practices, with clearly defined requirements, targeted advice, and stable prices as effective starting points. Secondly, the focus should be less on soil health measures on mineral soils and more on afforestation or agroforestry systems and peatland rewetting, as these approaches offer greater sequestration potential (McDonald et al. 2021). Agroforestry systems are applicable for all landowners and longterm by nature, while peatland rewetting is only possible in a limited area but is highly effective (McDonald et al. 2021). 35 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 4.2 Germany: AgoraNatura (ZALF) 4.2.1 Context Improving soil health and biodiversity on agricultural land within the European Union, as envisioned by the EU Soil Strategy for 2030 and the EU Biodiversity Strategy for 2030, necessitates addressing the current funding shortfall through enhanced private sector engagement. Despite this need, the potential of private consumer investment remains underutilized, owing in part to a scarcity of appealing investment vehicles and inadequately structured incentive mechanisms. To this end, our study explores the potential of private consumer investment for soil health and biodiversity improvements in agriculture. Moreover, we make use of an online marketplace for nature conservation projects – AgoraNatura – investigating the potential of such business models to bridge the current funding gap. Case study – AgoraNatura AgoraNatura is Germany’s first online marketplace for nature conservation projects in agriculture. Here, farmers are able to offer voluntary nature conservation projects and have them remunerated through interested donors (such as private citizens or private companies). For farmers, this means that they can develop their own project ideas and have them financed by interested donors through selling project certificates. The specific design of the projects, as well as the amount of remuneration, are determined by the farmers. Moreover, the projects are certified by experts according to the criteria of the “NaturPlus-Standard”. 4.2.2 Methodology We conducted a Discrete Choice Experiment (DCE) with 1,627 German residents capturing their stated preferences – measured in willingness to pay (WTP) – to explore the market potential of nature conservation certificates aimed at improving soil health and biodiversity on agricultural landscapes. Moreover, these certificates were characterized by two crucial concepts: ● Bundling: A mechanism where several environmental improvements are combined in one single certificate. In this case soil health and biodiversity improvements. ● Blending: A mechanism where public investments are mixed with private investments to leverage or ‘trigger’ private investment. With regards to bundling we selected three individual soil services for improvement: 1) pest control, 2) erosion control, and 3) soil-carbon storage. Moreover, we selected three individual biodiversity indicators for improvement: 1) animal diversity, 2) plant diversity, and 3) pollination. A nature conservation certificate was then characterised 36 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 by a single improvement of either soil health or biodiversity or a combination of respective improvements. Concerning blending we chose four different levels of public funding which each certificate may receive: 0%, 15%, 30% or 45%. Ultimately, we applied two different models to analyse private consumer WTP. A mixed-logit model in WTP-space as well as a latent class model in WTP-space. 4.2.3 Results Bundling Across our sample (mixed-logit model) we find positive mean WTP for all attributes and a strong negative mean WTP for the status-quo. This implies private consumers in our sample show support for the presented nature conservation projects and are willing to invest into respective certificates. With respect to individual soil health improvements, we observe positive mean WTP between approx. €41-47. Looking at soil health improvement bundles, the combination of all three soil health improvements leads to the highest mean WTP (approx. €74/certificate). Regarding individual biodiversity improvements, we find that consumers are willing to pay approx. an additional €38–55 per certificate. Similar to soil health improvements, the highest average WTP is observed for the bundle of all three improvements (€80/certificate). Consumer preferences exhibit segment-based heterogeneity, with four distinct classes identified. Class 1 (39%) – likely to be younger and environmentally conscious consumers – shows the highest mean WTP across all bundled soil health and biodiversity improvements. Class 2 (13%), more likely to be older and less educated male respondents, prefers the status quo but still values certain biodiversity bundles. Class 3 (28%) supports improvements but lacks price sensitivity, leading to insignificant WTP estimates. Class 4 (20%) values bundled soil health and biodiversity improvements but is highly price-sensitive, resulting in lower WTP overall. Blending We observe that respondents positively value increased public funding for nature conservation projects, implying that public funding may leverage or trigger increased private consumer investment. However, across our sample the increase in public funding only has a marginal positive effect on mean WTP: €13.2/certificate at 15%, €14.8/certificate at 30%, and €15.9/certificate at 45% public funding. However, we find 37 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 that for younger and environmentally conscious as well as price sensitive consumers mean WTP for public funding peaks at 30%. The class-weighted mean WTP of our latent class model supports these observations. 4.3.4 Market potential estimation Our research offers empirical insights into WTP of German residents for improvements in soil health and biodiversity. The results indicate considerable market potential for soil health and biodiversity certificates, thereby supporting public commitments under the EU Soil Strategy for 2030 and the EU Biodiversity Strategy for 2030. Furthermore, we find that combining improvements in both soil health and biodiversity substantially increases average mean WTP. Nevertheless, preference heterogeneity across consumer segments highlights the importance of designing targeted policy tools. Our findings also suggest that mixing public and private investments (blending) may enhance consumer investment, although public contributions exceeding 30% per project could reduce private engagement due to potential crowding-out effects. Therefore, such funding mechanisms should be developed with caution to incentivise participation. Lastly, online marketplaces for nature conservation certificates such as AgoraNatura may serve as effective channels to support such investment flows. While the findings are robust, limitations of stated preference methods, such as DCEs, persist. Future studies could incorporate realworld data and observed behaviours to improve the development of innovative funding approaches aligned with EU goals for soil health and agri-environmental policy. 38 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 4.3 Netherlands: Carbon credits (WU) 4.3.1 Introduction Under a neoclassical perspective, it would be expected that farmers provide public goods, such as carbon sequestration or biodiversity, when the provision helps them to maximise their profits by receiving additional payments over the incentive mechanisms (Whitby, 1994; Davies & Hodge, 2007). However, it is known that farmers adjust farm management for other reasons as well. This study seeks to explore how farmers respond to the expectation to store CO2 on farmland, how they perceive different incentive mechanisms, and which beliefs explain their perceptions. It presents the results from a Q-Methodology experiment. Q-Methodology combines quantitative and qualitative techniques. These experiments were already used, in example, by Davies & Hodge (2007), Braito et al. (2020). Davies and Hodge (2007) analyse how farmers perceive their roles in relation to environmental management, for instance, their responsibility to provide public goods. Braitio et al. (2020) determine farmers’ views on soil management and influential factors for their soil-management decisions. Both find that economic aspects are not equally important to all farmers. The experiment first informed farmers about potential soil health practices that potentially lead to carbon sequestration, the standards that need to be fulfilled for EUcertified carbon credits, and the underlying requirements for AES and private contracts with actors of the food value chain. Next, the participants were asked to order 36 statements in a so-called Q-sorting grid that reflected to which extent farmers agreed or disagreed with the individual statements. The statements referred to farmers’ management decisions, their attitudes towards environmental protection, the three analysed incentive models. The results are expected to be of interest to politicians as they allow them to identify which incentives might need to be offered alone or in combination to achieve better soil health and carbon sequestration. The subsections after the following case study description are structured as follows. First, the three main incentive mechanisms and their underlying legislative frameworks are summarised (Section 2). In section 3, the Q-Methodology and the setup of the experiment for the analysed context are described. The results are presented in section 4, before they are critically discussed in section 5. Case study description Rabo Carbon Bank is a private initiative by Rabobank that remunerates farmers for the implementation of sustainable soil management practices. Sustainable soil management practices enhance soil health while sequestering carbon in soils. The sequestered carbon amounts are then quantified and traded as carbon credits. Besides organising the trade of carbon credits, the bank advises farmers on 39 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 sustainable soil management practices and connects them with large companies (e.g. outside the agribusiness sector) that seek to buy carbon credits to offset parts of their CO2 emissions. Even though the Dutch case study is on carbon credit trade only, the NOVASOIL project focuses on two additional business models: These are public payments (e.g. for agri-environmental schemes or eco-schemes), and payments over the food value chain, where farmers receive a price premium on products produced with more sustainable practices. The Q-methodology experiment conducted for work package 2 seeks to provide deeper insights into why farmers choose to implement soil health promoting practices, and provides information on farmer’ evaluation of the three business models. Preliminary results of the Dutch experiment are presented in the following part. 4.3.2 Analysed incentives This article analyses farmers’ viewpoints on how to best promote soil health practices that potentially lead to carbon sequestration on farmland. The respondents received information on the incentives analysed. Three incentives were considered in the experiment: public payments for ecosystem services, payments through the value chain, where farmers receive an additional payment for a product that also fulfils certain environmental requirements, and carbon markets that organise the trade of carbon credits. Carbon credits are certified ‘carbon removal units’, where one unit represents one tonne of certified net carbon removal (McDonald et al., 2021). First, the participants received the information that carbon farming describes all activities where farmers and land users deliver the following outcomes: carbon removal and storage of carbon in biomass or soils, the avoidance of future CO2 and Greenhouse Gas (GHG) emissions or the reduction of existing CO2 and GHG emissions. Examples of carbon farming practices include i. afforestation and reforestation, ii. agroforestry and other forms of mixed farming (e.g. silvopasture), iii. soil health measures on arable land (for instance, reduced tillage, cover crops, improved fertilizer planning, arable land conversion to grassland), iv. the rewetting and restoration of peatlands (McDonald et al., 2021). Therefore, carbon farming refers to actions for carbon sequestration and not to a certain incentive mechanism, even though initiatives for carbon credit trade often state to perform carbon farming. Next, the participants received information on the incentives. 40 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 4.3.2.1 Public payments Public funding for environmentally friendly farm management can be granted over the CAP. Payments for ecosystem services can either be financed through Pillar i) the European Agriculture Guarantee Fund (EAGF) or Pillar ii) the European Agricultural Fund for Rural Development (EAFRD). These two funding pillars lead to payment schemes with different characteristics. Payments granted over the first pillar are, for example, annual, while payments granted over the second pillar are multi-annual. In addition, the second pillar payments are co-financed by the member states (European Commission, 2023a). Farmers must comply with certain conditions to receive payments from the first and second pillar. The so-called ‘enhanced conditionality’ consists of statutory management requirements that aim at sustainable farming. Farmers receive direct payments from the first pillar for these measures. The measures of the ‘enhanced conditionality’ aim at good agricultural and environmental conditions (GAEC) (European Commission, 2023a). Schemes for the climate, the environment, and animal welfare (Eco-schemes) are new tools to deliver the goals set by the European Commission. Practices can only qualify to become eco-schemes when they require management adjustments that go beyond the legislative requirements, and the enhanced conditionality (European Commission, 2023a). In the Netherlands, eco-schemes are implemented using a result-based point system. In the Dutch system, each activity converts into eco-points. They reflect the activities’ impact on different environmental objectives (climate, air and soil, water, landscape, biodiversity). The eco-points translate into hectare payments when farmers achieve enough points in total. Farmers can either use one eco-scheme with a high impact or multiple ones with lower ambitions to reach an entry level threshold and to qualify for a payment for all hectares of the farm. If they want to achieve higher payments, multiple measures referring to different objectives need to be combined to reach higher thresholds. There are three threshold levels: bronze (€ 60/ha for all hectares of the farm), silver (€ 100/ha for all hectares of the farm) and gold (€ 200/ha for all hectares of the farm) (Jongeneel & Gonzalez‐Martinez, 2023). Eco-schemes provide incentives for softer management restrictions, while other, more demanding measures are financed from the second pillar of the CAP. These measures include agri-environment-climate commitments, forest-environment-climate commitments, agroforestry, afforestation, and the conversion to and maintenance of organic farming, referred to as agri-environmental schemes (AES) in this study (European Commission, 2023a). Measures financed over the second pillar are multiannual as the environmental goals require longer and more complex engagement (Guyomard et al., 2023). The contracts usually cover five years (European Commission, 41 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 2023a). The Netherlands chose a collective implementation approach. Since 2016, farmer collectives have been responsible for the implementation of AES. The approach is believed to motivate farmers, to enhance the special coordination of measures (Barghusen et al., 2021). 4.3.2.2 Carbon markets for EU-certified carbon credits Overall, certified carbon credits should meet the so-called QU.A.L.ITY criteria. QU.A.L.ITY stands for the four requirements the removals need to fulfil to allow certification. In brief, the removals need to be quantified in an accurate and robust way, they should generate a net carbon removal benefit that is additional (at least above the existing legal requirements), they should ensure long-term storage of carbon and have a neutral impact or even a co-benefit for other sustainability objectives (European Commission, 2024). For the first criterion, the following is lined out: Carbon removals must be quantified in a manner that is relevant, accurate, complete, consistent, and comparable. Thirdparty auditing plays a crucial role in ensuring the credibility and reliability of carbon removals. To quantify the net carbon removal benefit, a two-step process is followed. First, the gross amount of additional carbon removals generated by a carbon removal activity compared to a baseline is calculated, utilizing standardized baselines. These baselines reflect the typical performance of similar activities in comparable social, economic, environmental, technological, and geographical contexts, aiming for objectivity, minimal compliance costs, and recognition of early movers. Second, any increase in greenhouse gas emissions associated with the implementation of the carbon removal activity is deducted. These emissions may arise from increased use of fertilizers, chemicals, fuel, energy, or changes in practices (European Commission, 2024). For the second criterion additionality, the following needs to consider: The activities need to exceed statutory requirements, ensuring that operators undertake actions not mandated by law. Therefore, the standardized baseline for farmers should reflect the carbon emissions of farms complying with existing legislative frameworks (European Commission, 2024). Given that almost all farmers receive CAP payments the enhanced conditionality requirements of the CAP most likely also need to be exceeded. Long-term storage means that ideally, carbon storage should be permanent. This is defined as centuries long and might be achieved through methods like geological storage or carbon mineralization. However, different carbon removal activities vary in processes, storage mediums, and timescales. Carbon farming on arable land, peatland rewetting or afforestation is considered to rather lead to removals spanning decades (European Commission, 2024). 48 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 TABLE 9. SUMMARY OF THE DESCRIPTIVE STATISTICS OF THE PARTICIPANTS. Description Mean Year of birth 1979 Share of male participants 87 % Share of participants with university degrees 44 % Share of organic producers 25 % Hectares of the farm 82 Share of arable farms 81 % Soil organic content of the farm 56 % (1-3% SOC) Predominant soil type 31 % sand, 68 % clay Share of farms with secure succession 63 % 4.3.4.2. Extraction and Specification of the Factors There is no general rule on how many factors to extract from the data analysed. One suggestion is to extract factors that display at least two significant factor loadings. An alternative is Humprey’s rule, that is that a factor should be extracted when the crossproduct of its two highest loadings exceeds twice the standard error (Davies & Hodge, 2007). Another option is to consider the Eigenvalue determined for different numbers of factors and to determine when the slope levels off. The latter rule was applied to extract three factors. The analysis explains 56 % of the underlying variation in the responses, with 14 of the 16 Q-sorts loading significantly on at least one factor. The names of the factors are based on the distinguishing statements of the identified factors. They reflect the views of similar-minded participants. The first factor represents the pro-environmental entrepreneurs, with nine farmers loading on this factor alone. The second factor stands for the traditional food providers, with three farmers loading on this factor alone. The third factor represents the carbon farming enthusiasts (two farmers). Table 10 holds information on the factor estimates for the statements. The distinguishing statement has a score that is significantly different from the scores of the other factors. The higher the factor estimate, the more important the statement (Akhtar-Danesh, 2018). 49 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 TABLE 10. FACTOR SCORES OF THE STATEMENTS (E: PRO-ENVIRONMENTAL ENTREPRENEUR, T: TRADITIONAL FOOD PROVIDER, C: CARBON FARMING ENTHUSIAST) No. Label Facto r 1 (E) Sig. Factor 1 Factor 2 (T) Sig. Factor 2 Facto r 3 (C) Sig. Factor 3 Consensu s Statement s 1 long-term increase 2 1 2 x 2 good farm management 3 -1 3 3 multiple public goods 1 x 3 4 4 resilience climate change 5 x 0 0 5 soil structure -1 5 x -3 6 hard measures -2 -5 -3 7 training & education 0 -1 -2 x 8 solutions food supply chain 3 x 0 1 9 termination option 0 -1 1 x 10 inflation 0 x 2 x 5 x 11 choose measures 1 4 1 12 short tenure 0 x 3 3 13 long-term contracts -1 -2 0 14 farmers' groups 0 0 4 x 15 soil sampling costs -2 -4 -2 16 result-based -4 -3 2 x 17 action-based payments 1 1 -1 18 CAP good incentives -3 -2 -1 x 19 hobby farmers -4 x 0 1 20 CM attractive -2 -2 0 21 payment combination -1 -3 x 0 22 existing initiatives -1 0 -1 x 23 CM risky -2 1 x -1 50 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 24 hybrid payments 0 -1 0 x 25 legislation 1 x -4 -4 26 high competition -3 x 2 2 27 entrepreneuria l 3 -1 1 28 green washing -1 x 1 x -5 x 29 productivity 2 x -2 -4 30 future generations 1 0 -2 x 31 freedom to farm -3 2 x -1 32 short-term income 2 x -3 -3 33 nature protectionists 2 1 3 x 34 soil conditions are good -5 x 2 x -2 x 35 balance 4 4 2 36 focus farming 4 3 0 x The Pro-environmental entrepreneurs There are 12 distinguishing statements for the factor. The pro-environmental entrepreneurs believe that soil health-friendly farming helps to make their enterprise more resilient against climate change (no. 4) and would even accept short-term income losses to improve their soil quality in the end (no. 32). This might be driven by perceiving the quality of Dutch soils as relatively poor (no. 34), or by their agreement that productivity does not mainly drive their farm management decisions (no. 29). They further believe that the market allows farmers to extensity their operations (no. 16), and that the public should remunerate the various public goods provided by soil health practices (no. 3). Considering potential financial numerations, they agree that the actors involved in the food supply chains need to find solutions to remunerate public goods (no. 8). Besides this, they might be open to participating in AES - they disagree with the statement ‘AES and eco-schemes are for hobby farmers and for farmers on poor quality soils’ (no. 19). They might have a slight interest in carbon markets, as they slightly (-1) oppose the statement that ‘To state that CO2 emissions are lowered by soil health practices is greenwashing’ (no. 28), in addition, they perceive long contracts as acceptable (no. 12). 51 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 The Traditional Food Providers The traditional food providers do not share this attitude, seven statements are distinguishing for them. This might be explained by their agreement to the statement ‘The Dutch soils are in good condition’. They also state that other measures that determine soil quality (e.g., water holding capacities, low erosion) are more important to them than the soil organic carbon content (no. 5). They further agree that carbon farming activities would limit their ability to run their enterprise as they like (no. 31). This belief might explain why they rather oppose carbon markets which might be indicated by their slight agreement with the statement ‘To state that CO2 emissions are lowered by soil health practices is greenwashing’ (no. 1). Moreover, they strongly oppose the idea that ‘It would be a good incentive when it would be allowed to combine payments from the CAP (AES and eco-schemes) and private payments (from the value chain or over carbon markets)’ (no. 21). Hence, none of the analysed incentives might help to motivate this group. The Carbon Farming Enthusiasts The last group represents carbon farming enthusiasts with eight distinguishing statements. The group was named carbon farming enthusiasts as they strongly oppose the statement ‘To state that CO2 emissions are lowered by soil health practices is greenwashing’ (no. 28). This could indicate an interest in selling carbon offsets. Furthermore, they agree with ‘Result based payments should exclude farmers having high carbon contents in soils to promote additional action against climate change’ (no. 16). This indicates a willingness for ambitious action against climate change. Furthermore, they value inflation-adjusted payments (no. 10) as additional incentives. This aspect might be of special importance to them as carbon credit trade requires relatively long contracts. Furthermore, they would rather participate in initiatives from farmers groups (no. 14). These are the most common set-ups of current early trails for carbon credit trade in the Netherlands. Last, their disagreement with statement no. 7 ‘Additional training and education are good enough incentives to motivate me to implement additional soil health practices’. indicates that they demand financial incentives to adjust their farm management and that they will not take action for free. Consensus Statements Besides these distinguishing statements, some consensus statements are identified. A consensus statement displays similar scores across all factors. Farmers slightly agree that they must play a role in nature protection (no. 33 ‘nature protection)’ and that ‘Soil health practices can reliably increase the soil organic carbon content in the long run’. Furthermore, they uniformly disagree with statement no. 18 ‘The payments offered over the CAP (AES and eco-schemes) are high enough to set financial incentives’. For other statements that referred to potential additional incentives, such as no. 9 52 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 ‘termination option’, no. 24 ‘hybrid payments’ and no.22 ‘Existing initiatives’ rather neutral perceptions are found across all factors. 4.3.5 Discussion and conclusion The analysis yielded three different viewpoints: i. the pro-environmental entrepreneur (E), ii. the traditional food provider (T), iii. the carbon farming enthusiast (C). The next section discusses the main characteristics of the groups, their evaluations of the different incentives, and provides insights into how to promote soil health measures among these farmers. The section closes with the implications of the findings for the market potential of the different incentives. 4.3.5.1 Incentivising the pro-environmental entrepreneurs The pro-environmental entrepreneurs show a stronger interest in solutions with value chain partners. From a research perspective, there is a need for further exploration into, for instance, what farmers expect from value chain partners and how to ensure fairness. Currently, only one experiment conducted by Weituschat et al. (2023) investigates value chain contracts for soil health, and it does not cover these aspects. Weituschat et al.'s (2023) article determines farmers’ willingness to participate in production contracts under Barillas' sustainable farming initiative, and they strongly focus on the measures demanded. Furthermore, it might be of interest to investigate consumer preference and whether they respond to soil health claims as well, as claims for climate neutrality might become more difficult. Additionally, there is potential for researchers to enhance Dutch AES, the most significant funding source of the CAP, as its current incentives were negatively perceived by all groups (no. 18). The 'pro-environmental entrepreneurs' might be interested in both value chain payments and AES. They strongly disagree that AES are only for hobby farmers and those on low quality soils only (no. 19). It might be that improved AES are well accepted by farmers in factor one. Improvements in the CAP payments that lead to higher take-up rates are also of special interest to the Netherlands, where participation rates are among the lowest across Europe (Zimmermann & Britz, 2016). The finding that farmers display a certain interest in AES compared to carbon markets would also be in line with the literature from the US (Canales et al., 2024; Gramig & Widmar, 2018). They find that farmers are more interested in AES than carbon markets because AES more commonly offer action-based payments 53 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 4.3.5.2 Incentivising the Carbon Farming Enthusiasts For the third factor, ‘the carbon farming enthusiasts’, it should be critically evaluated if carbon credit trade for soil health measures is likely to become a reality. While the quantification process for EU-certified credits is still undergoing development, certain measures with significant potential for carbon storage and positive co-benefits for biodiversity are already being identified for prioritisation. Notably, carbon storage in peat soils, reforestation, and agroforestry are emerging as promising alternatives, both in terms of their scalability and environmental impact (COWI et al., 2021; McDonald et al., 2021; Mcdonald et al., 2023). Soil health measures are currently subject to critical evaluation, especially because carbon sequestration is easily reversible on farmland (Paul et al., 2023). Farmers across all groups disagreed with the statement that they might plant additional trees or rewet peatland to be able to store more CO2. This dislike towards harder measures is commonly described, for instance, also by Weituschat et al. (2023) for different practices on arable land, by Norris et al. (2021) for peatland rewetting in the Netherlands and by Dumbrell et al. (2016) for the planting of trees. Researchers and other stakeholders interested in farmers’ willingness to engage in carbon credit trade could further explore the carbon credit trade initiatives already set up by groups of farmers. Farmers, on the third factor, agreed that they would rather participate when part of farmers’ groups being in the Netherlands, such a group is ZLTO. ZLTO is a farmer’s organisation that started early trials on the topic (ZLTO, 2024). The positive perception of activities from farmers’ groups might also be particularly evident in the Netherlands, where farmers’ collectives have organised nature protection activities since 2016 (Terwan, 2016). The importance of tight social networks that might exist in such collectives is also highlighted by Braito et al. (2020) as an essential factor to promote soil health. Besides these social aspects, another reason why farmers’ groups are perceived positively is that monitoring costs for carbon farming are expected to be substantial, and a collective implementation might help to share costs for monitoring and administration (Buck & Palumbo-Compton, 2022; Tiusanen et al., 2022). 4.3.5.3 Incentivising the Traditional Food Providers Farmers sorted into the second factor ‘traditional food providers’ seem less likely to improve their soil health with the help of any of the three suggested incentives. Other soil quality aspects that are closer linked to the production potential are more important to this group than carbon sequestration. However, many improvements, for instance, of soil structure and in the availability of nutrients and water go hand in hand with higher carbon contents (Lal, 2016). This should be emphasised when talking to traditional food providers. 54 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 In addition, research from the Netherlands shows that the inclusion of more soil health promoting practices (e.g. more cattle manure, more catch crops and higher grain shares) can increase the income from arable farming in the long run (Kik et al., 2023). Some farmers seem to already share this belief - potential improvements in long-term profitability are described as decisive in multiple articles on farmers’ acceptance of soil health AES or carbon credit contracts (Buck & Palumbo-Compton, 2022; Canales et al., 2024; Tiusanen et al., 2022). Even though farmers in the third group strongly disagreed that better knowledge provision and training are enough to change farm management, training opportunities should be explored further. In theory the profitoriented traditional food providers should be interested in strategies that increase their income in the long run. That some groups of farmers are difficult to motivate is confirmed by other authors. Their perception is shared by Commodity Conservationists and Jeffersonians farmers in Davies & Hodge (2007), or Braito et al.’s (2020) traditional food providers and profit maximisers. 4.3.5.4 Perception of other incentives Besides these differences, the experiment also allowed to identify statements the farmers agreed upon. One is the already discussed negative evaluation of the current financial incentives offered over the eco-schemes or the AES. Another statement is no. 33 ‘Farmers are both producers of agricultural products and nature protectionists’. As expected, the first and third viewpoints agree more strongly with this statement. For the second viewpoint (traditional food providers), the question arises how to support action. One option to promote pro-environmental action might be to better educate on the effects climate change will have on Dutch agriculture. Hail, floods and storms have already become more common and challenging for Dutch agriculture (The Ministry of Agriculture Nature and Food Quality, 2023). Only farmers in factor one believe that their farm will become more resilient to climate change when soil health practices are implemented. Nevertheless, that farmers tend to agree with statement 33 raises hope that better soil health can be achieved in the Netherlands. Besides statements that might allow identifying farmers interested in the three major incentive mechanisms (public payments, carbon credit trade and contracts with value chain partners), some statements referred to additional incentives that could be offered as being part of all other contracts. One statement that displays significant loading for the second and third factors is no. 10 ‘inflation’. It deserves attention on how to make long contacts more attractive and inflation-adjusted payments could be a solution for contracts including action-based payments. Furthermore, the experiment included a termination option for a successor. This was included because Rochecouste et al. (2017) describe that farmers dislike long nature conservation and carbon farming contracts because they do not like to limit their flexibility and the flexibility of their 55 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 successor. This statement ‘I would find carbon farming contracts more attractive when my successors would be able to leave the contract’ (no. 9) is rather neutrally perceived across all groups. However, the idea might still deserve attention in up-coming experiments. For nature protection it is commonly described as problematic that farmers are unwilling to opt for long contracts (>10 years) (Harmanny & Schulp, 2023; Mamine et al., 2020; Schaub et al., 2023). Last, a word of caution is necessary as this article uses Q-methodology. The underlying sample is not representative of the Netherlands. As common in Q-methodology experiments, it was aimed to include a diverse set of farmers and many face-to-face interviews, farmers more interested in the topic might have been more likely to agree to participate. Therefore, the result that most farmers have an interest in value chain payments and might be interested in improved AES might not represent the general farming population. Still, the conducted Q-methodology experiment highlights that farmers perceive the incentives on offer quite differently, and that some farmers (traditional food providers) will be difficult to motivate. Furthermore, the method detected additional incentives, namely AES improvements, that might be of interest for the first factor ‘pro environmental entrepreneurs’ and the last factor ‘carbon farming enthusiasts. Collective implementation of carbon farming with farmer groups could help to motivate these farmers. 4.3.5.5 Market potential of the different incentives The results suggest that farmers in this sample display an interest in private contracts with value chain payments (the pro-environmental entrepreneurs). Half of the sample of farmers are grouped in this category. Some farmers are also interested in the opportunity to sell carbon credits (carbon farming enthusiasts, 20% of the sample)). However, the group 'traditional food providers (20% of the sample) is not interested in any of the incentive mechanisms. Across all groups, farmers agree that the CAP currently fails to set good incentives over eco-schemes or AES. Overall, the results are in line with the finding of Braito et al. (2020) that not all farmers respond equally well to the financial incentives on offer. 56 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 4.4 Italy: Italian consumers (UNIFE, UNIPI) 4.4.1 Case study description The Italian case study was carried out by the University of Ferrara (UNIFE) and the University of Pisa (UNIPI). The study investigates the willingness of Italian consumers to financially support farmers in adopting conservation agriculture practices to improve soil health. While UNIFE made the experimental design and collected 414 observations, UNIPI collected 600 observations. The overall sample (1014 observations) is representative of age, gender and education. Three hypothetical programs have been considered: i) area-based payment, ii) result-based payment and iii) hybrid payments. The area-based scheme consists of a fixed payment per hectare granted to farmers who adopt conservation agriculture practices. By contrast, the result-based scheme provides payments linked to the certified increase in soil organic matter. Finally, the hybrid scheme combines both approaches, with 50% of the payment based on area and 50% on results). This study contributes to the development of alternative mechanisms to public funding and provides valuable insights for designing contracts between consumers and farmers to effectively increase soil health in Italy. 4.4.2 Method Questionnaire Structure The questionnaire submitted to Italian consumers was divided into five distinct sections, aiming to systematically and coherently explore preferences regarding the willingness to pay for soil health-related conservation agricultural practices. The sections are described in detail below: 1. Discrete Choice Experiment (DCE): The first and central section of the questionnaire consisted of a series of “choice cards” designed to simulate realistic program scenarios. Consumers were asked to choose between two program options (A and B), each with different characteristics, or to reject both via the “opt out” option. The aim was to investigate preferences regarding the duration of program commitment, the estimated increase of organic matter in the soil, the type and structure of payment and the amount of payment per hectare. 57 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 3. Socio-demographic Section: This section collected personal information, including age, gender, education of respondent and the household level of income. 4. Socio-psychological Constructs: Consumers were asked to express their level of agreement with statements about their social and personal norms, their trust in other people as well as in institutions, their environmental concerns and their perception of impacts on human health. 5. Environmental Risk Perception Section: This section explored how consumers perceive the risk associated with soil degradation in the area where they live. It included questions on perceived degradation of chemical, physical and biological soil factors. Attribute Selection and DCE Design To design a Discrete Choice Experiment (DCE), it is essential to select relevant, understandable, and realistic attributes for participants, in this case, consumers. The attributes were chosen based on scientific literature on adopting agri-environmental practices (Franceschini et al., 2023; Franceschinis et al., 2022). Four main attributes were considered: TABLE 11. DCE ATTRIBUTES AND LEVELS Attribute Levels Description Annual payment per hectare 100 €, 200 € Compensation to farmers who adopt conservation practices Type of payment 100% fixed; 50% fixed + 50% result-based; 100% result-based Payment modalities: fixed, performance-based or hybrid Estimated organic matter increase Low, Medium, High Represents the certified increase of organic matter in the soil Commitment duration 5, 10, 20 years Minimum period of commitment Payments from €100 to €200/ha reflect realistic ranges, consistent with CAP incentives and marginal costs associated with practices such as no-till farming and cover crops. Durations from 5 to 20 years reflect the time required to obtain tangible soil benefits. 64 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 WTP for environmentally labelled inputs When asked about paying more for environmentally produced agricultural inputs (seeds, fertilizers, fuel), the majority of respondents (n = 101) answered no. Only 9 were willing to pay up to 10% more, and 51 agreed to a 5% premium. Income Effect: Respondents with 1500–2000€ (p = 0.0374) and 3500–5000€ (p = 0.0079) monthly income levels were significantly more likely to accept a higher price for environmentally friendly products. Producer Support Belief: A consistently significant negative effect was found across models: farmers who agreed with the statement that seed producers should be supported through sustainable purchasing were themselves less likely to pay more for labelled inputs (p = 0.0025). Summary of significant findings TABLE 15. SUMMARY OF SIGNIFICANT FINDINGS Factor Effect on WTP Significance Male gender Higher WTP for market advantage; lower for offsets p < 0.05 Applied higher education Higher WTP for market advantage and offset p < 0.05 Income (1500–5000€) Higher WTP for ESG value and eco-labelled inputs p < 0.05 Belief in tech solutions Lower WTP for ESG-based carbon labelling p < 0.05 Support for seed producers Lower WTP across offset and environmental scenarios p < 0.01 Interpretation The findings highlight that Estonian farmers’ willingness to support sustainability through seed choices is shaped more by economic pragmatism and personal worldviews than by generalized environmental values. Market-based benefits, income level, and education drive positive responses, while indirect or collective benefits (e.g., carbon credit schemes or ESG metrics) receive less support. The consistent negative impact of the “support for seed producers” belief suggests a 65 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 potential gap between normative attitudes and personal action in sustainabilityrelated decision-making. 4.5.4 Market potential The study shows that in Estonia, farmers’ willingness to pay for carbonor environmentally labelled seeds remains limited, with most respondents unwilling to pay a premium unless the label brings a clear market advantage. This reflects a broader pattern of economic pragmatism: farmers are more likely to support sustainability through seed choices when it helps them secure better prices, access new markets, or strengthen their competitive position, rather than out of abstract environmental motivation. Higher education, mid-to-higher income levels, and in some cases gender play a role in shaping openness to premiums, but overall, the Estonian market potential is modest and likely concentrated in niche segments. Early adopters will most likely be farmers who supply premium food chains, restaurants, and export markets where sustainability labelling already matters. At the same time, there is a perception that the costs of sustainability should be borne by input suppliers or offset by tangible benefits, which suggests that labelled seeds must demonstrate either agronomic gains (such as better resilience or reduced input needs) or downstream financial rewards to find traction. The wider EU market presents a different picture. In Western and Northern Europe, consumers, retailers, and policymakers are already driving demand for carbon labelling in food, and input markets are more closely tied to sustainability schemes. Here, carbonor eco-labelled seeds could gain significant ground if positioned as tools for farmers to meet market and policy requirements. The European Green Deal, CAP eco-schemes, and the forthcoming Soil Health Law are strong policy levers that can accelerate adoption, especially when combined with private certification schemes or corporate ESG commitments. In these contexts, carbon-labelled seeds can move from a niche product into the mainstream, particularly when linked to supply contracts or sustainability-oriented cooperatives. Taken together, the findings suggest that while Estonia may serve as a valuable testbed for piloting these seeds in high-value niche markets, large-scale uptake will only follow if clear financial or agronomic benefits are visible. In contrast, the EU-wide potential is far greater, especially in markets where consumer demand, ESG obligations, and policy incentives converge. Success depends less on the label itself and more on the ability to position it as a business opportunity: a way to secure contracts, reduce risks, and strengthen profitability while contributing to broader sustainability goals. 66 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 4.6 Bulgaria: Agrotourism (NBU) 4.6.1 Introduction and case study description Introduction The case study in the Plovdiv and Pazardzhik regions, which employs the business model of "Integrated production in vineyards with a winery and rural tourism," is important for increasing production efficiency, reducing marketing costs, and improving competitiveness in rural areas. Additionally, it can provide many ecosystem functions and services, such as water and nutrient cycling, biodiversity, and economic viability. Environmental challenges and the socio-economic setting are two focal points that must be considered. From an environmental perspective, there are two major focal points. First, there are the climatic conditions, which are exacerbated by climate change: floods, droughts, landslides, hurricane winds, and hailstorms. The increased frequency of heavy rainstorms, characterized by high intensity and short duration, will lead to increased short-term surface runoff and the risk of water erosion on slopes. Most of the aforementioned events are purely natural and difficult to foresee and control; however, they put pressure on everyday operations. On the other hand, agricultural practices may lead to soil erosion, one of the biggest soil problems in Bulgaria. Case study description The aim of the Case Study is to value the potential of local traditional and regional traditional products in the wine sector and strengthen their relationship with communities in order to develop the local economy and agricultural sector. 4.6.2 Method The aim of the survey is to analyse the production and consumption of traditional products (wine), as well as their integration with rural tourism as a result of applying the business model “Integrated Vineyard Production with Wine and Rural Tourism” in the Plovdiv and Pazardzhik regions. In this context, we seek to assess consumer attitudes toward the consumption of wines produced with and without agrienvironmental measures (AEM) aimed at preventing soil erosion, and their combination with rural tourism. The questionnaire is divided into three parts: Part A – General Questions; Part B – Choice Experiment Card; Part C – Questions related to environmental protection. For the purposes of this study, we selected the implementation of one specific agri- 67 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 environmental measure (AEM) – cover crops in the inter-rows of vineyards – to reduce soil erosion and improve soil health. Cover crops are considered to offer multiple benefits for the soil, including reducing erosion, decreasing compaction, increasing organic matter, and more. In the choice experiment respondents are asked to choose between several hypothetical alternatives that differ in specific characteristics (attributes). In this particular case, participants choose between four versions of a wine product, with each alternative described by a combination of the following attributes: the presence or absence of agri-environmental measures (AEM), the impact on soil erosion (reduces or does not reduce), the provision or absence of cultural services (such as wine tourism), and the price of the product (8 EUR, 10 EUR, 14EUR, or 18 EUR per bottle). The respondent’s task is to select the preferred alternative among the four options presented in each choice card. FIGURE 5. DCE ATTRIBUTES AND LEVELS The methodology involves creating an experimental design in which the different levels of the attributes are systematically combined to generate realistic but varied product profiles. Each respondent views one or several such cards and makes a choice, allowing researchers to collect data on their preferences. Using statistical models (e.g., logit models), the analysis identifies which attributes most strongly influence decisionmaking. Additionally, the respondents’ willingness to pay (WTP) for various nonmonetary benefits – such as environmental or cultural services – is estimated, as well as the trade-offs consumers are willing to make between price and additional product benefits. 68 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 The aim of this approach is to determine which factors are most significant to consumers when choosing wine products, the extent to which they value additional characteristics such as contributions to environmental protection or the development of wine tourism, and whether they are willing to pay a higher price for these benefits. The questionnaire was distributed electronically and the survey finished in late 2024. From the distributed survey, 431 to 284 valid responses were collected, depending on the specific questions analysed. 4.6.3 Survey results Analysis of preferences by age Option 3 (with AEM, no tourism) was the most preferred overall (123 of 284 respondents). Younger respondents (18–40) showed a strong preference for AEM options, especially Option 3. Cultural services (wine tourism) in Option 2 and Option 4 influenced some preferences, but not as much as the presence of AEM. The p-values > 0.05 indicate that no statistically significant relationship exists between age group and product choice at the conventional 5% significance level. However, the Linear-by-Linear Association test result (p = 0.052) is marginal, suggesting a potential weak trend – perhaps younger consumers are more inclined toward environmentally friendly options, but the evidence is not strong enough to confirm this definitively. Environmental sustainability matters: The majority preferred options using agrienvironmental measures, even when those options were more expensive. This suggests willingness to pay for environmental benefits like soil erosion reduction. Cultural services have secondary importance: Wine tourism added value but was not the primary driver of choice. Option 3 (no tourism, with AEM) was more popular than Option 4 (with both AEM and tourism), likely due to price sensitivity. Age influence might exist, but not significant: Younger respondents (18–40) are more open to eco-friendly wine options, but the difference by age is not statistically significant. Price sensitivity persists: While consumers valued AEM, there was still a noticeable drop-off at higher price points (Option 4 at €18 was less preferred despite offering both AEM and cultural services). Producers should consider adopting and communicating the use of AEM in wine production, as it positively affects consumer preference. Marketing efforts could highlight environmental benefits rather than just cultural experiences. 69 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 Analysis of preferences by gender Option 3 (wine with AEM, no tourism, €14) is the most preferred option across both genders. It reflects a strong interest in environmentally sustainable wine, even without added tourism or the lowest price. Men favoured Option 3 (67 responses) slightly more than women (56 responses). Men showed higher preference for Option 2 (45 men vs. 37 women) – indicating somewhat more interest in wine tourism, even without AEM. Women were slightly less inclined to select the cheapest, least sustainable option (Option 1: 5 women vs. 14 men). Both genders prioritize environmental sustainability (AEM) over wine tourism and price – but men are marginally more responsive to the cultural/tourism value, while women show slightly more consistent environmental preferences. All p-values are above 0.05, which means there is no statistically significant difference in wine product preferences between men and women. Gender does not strongly influence the choice between the four wine options in this sample. Environmental sustainability (AEM use) is a stronger driver of preference than price or tourism, regardless of gender. Wine tourism has moderate appeal, especially among men, but it's not a dominant factor. Price is not the only concern – even higher-priced, environmentally friendly wines (Option 3 and 4) are widely preferred. Analysis of preferences by education Across all education levels, Option 3 (AEM, no tourism, €14) is the most preferred. However, the degree of preference shifts significantly with education level. Primary education shows more balanced spread across all options. Option 2 (with tourism but without AEM) is most selected (22), showing interest in wine tourism even without environmental benefits. Lower concern for AEM; suggests less awareness or lower prioritization of environmental impact. Option 3 slightly leads (20 responses) in high school education, indicating growing awareness of AEM benefits. Less interest in Option 1 (only 3 selected it), indicating shift away from the lowest-price option. High school with specialization shows strong preference for Option 3 (82 responses) and Option 4 (44 responses) - both with AEM. Indicates high environmental awareness and willingness to pay more for sustainable and experiential products. Option 2 (with tourism only) also gets strong support (48), showing dual value of sustainability and tourism in this group. 70 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 All p-values are below 0.05, indicating a statistically significant association between education level and product preference confirming that higher education correlates with stronger preference for environmentally sustainable wine products. As a conclusion environmental sustainability (AEM) is increasingly important with higher education. Primary education group values lower prices and tourism experiences more than soil health or AEM. Specialized education group is most environmentally and culturally engaged, showing readiness to pay for added value (AEM + tourism). Analysis of preferences by income Lower income groups (< €1,500) shows more evenly spread choices; Option 3 (AEM, no tourism) is most popular, but not dominant. Significant selection of Option 2 (with tourism but no AEM), especially among the lowest group. Price appears to be a stronger constraint; interest in sustainable wine exists, but affordability limits preference for the highest-priced Option 4. Middle income (1,500 – 2,500 €) group shows strong preference for Option 3 (AEM, €14) – sustainability clearly matters. Option 2 is also popular among these groups, suggesting a balance between tourism and environmental values. For higher income groups (> €2,500) Option 4 (AEM + tourism, €18) becomes increasingly dominant. At €3,500 – €5,000: 13 out of 17 chose Option 4 (76%); At €5,000+: all 5 respondents selected Option 4 (100%). These groups clearly prioritize quality, sustainability, and experience over price. As income increases, preference shifts toward environmentally sustainable and culturally rich (tourism) wine, even at higher price points. The very low p-values (< 0.001) indicate a strong, statistically significant association between income level and wine product preference. The linear-by-linear association confirms a clear upward trend: higher income strongly correlates with choosing more expensive, sustainable, and experience-oriented wines. Environmental sustainability (AEM) is a universal preference across income groups, but willingness to pay for it increases with income. Wine tourism is appreciated more as income rises, especially in the high-income brackets. Price sensitivity is higher in low-income groups, who still value sustainability but make more balanced choices. 71 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 4.6.4 Market potential estimation The survey results clearly show that environmental sustainability – represented by the use of agri-environmental measures (AEM) – is the strongest factor influencing wine product preference. Across all demographic groups, Option 3 (wine with AEM, no tourism, €14) was the most preferred, suggesting that consumers are willing to pay a higher price for environmentally friendly wine. Although wine tourism and pricing influenced choices to some extent, they were secondary to the perceived ecological benefits. This trend highlights a growing public awareness and valuation of ecosystem services such as soil erosion prevention in agricultural production. Education and income emerged as statistically significant predictors of preference. Respondents with higher education levels, particularly those with specialized training, demonstrated a stronger inclination toward sustainable and experiential wine options. Similarly, higher-income consumers were more likely to select premium options that combine environmental benefits with cultural services (e.g., wine tourism), despite higher prices. These groups show a clear readiness to pay for added value in wine products, making them prime targets for premium, environmentally sustainable wine marketing strategies. In contrast, age and gender did not show statistically significant associations with wine preference, although some trends were noted. Younger consumers tended to favour sustainable options more than older ones, and men showed slightly greater interest in wine tourism than women. Still, both genders prioritized environmental attributes over price or cultural add-ons. These findings suggest that sustainability messaging has universal appeal across age and gender, but that tailored marketing efforts should focus more on education and income segments, where preferences and purchasing power align most strongly with sustainable and premium wine offerings. Demographic profile of support for sustainable wines The survey results show strong overall support for traditional wines produced with agri-environmental measures (TWAEM), with a clear majority of respondents agreeing that these wines provide significant environmental, health, and quality benefits. Statements regarding the role of TWAEM in improving health (Q6.4), reducing soil erosion (Q6.5), and justifying a higher price due to health benefits (Q6.7) received particularly high levels of agreement – above 85% in most cases. Respondents also widely recognized the role of TWAEM in supporting sustainable consumption and landscape conservation, though statements about taste (Q6.1) received slightly more varied responses. Despite the price being a potential barrier, the data indicate a general willingness to pay more for wine that offers environmental and health advantages. 72 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 When analysed by demographic groups, the data reveal important distinctions. Age showed no statistically significant differences, but there was a clear trend: younger participants (ages 18–40) were more likely to agree with the benefits of TWAEM across nearly all statements. Gender differences were generally minimal, with both men and women supporting TWAEM benefits; however, men were more likely to value landscape conservation (Q6.2), the only statement with a significant difference by gender (p = 0.046). On the other hand, education level showed several statistically significant effects, particularly in questions related to health (Q6.4), erosion control (Q6.5), and health-based price justification (Q6.7). This suggests that higher education – especially specialized education – correlates with stronger environmental and health awareness related to wine consumption. Trust and uncertainty in TWAEM benefits Across the sample, most respondents disagreed with statements expressing scepticism about TWAEM. For example, 67% disagreed that TWAEM have poorer taste (Q7.1), and 55% disagreed that their quality does not match the price (Q7.2). While some uncertainty exists about whether health claims might be exaggerated (Q7.3) and whether TWAEM directly reduce erosion (Q7.4), the majority of respondents were either disagreeing or unsure – indicating limited but present scepticism. By age, younger respondents (18–40) were more confident in the benefits of TWAEM, with higher disagreement on negative statements. Notably, Q7.2 showed a statistically significant difference (p = 0.014), suggesting that age impacts how respondents perceive value for money in TWAEM. Gender differences were minimal across all risk statements, with no statistically significant variation. However, men were slightly more likely to agree that quality may not justify price (Q7.2) and that health benefits might be exaggerated (Q7.3). Education level played a more significant role. Respondents with only primary education were more likely to agree with negative statements, particularly regarding taste (Q7.1, p = 0.010). Those with specialized education were less sceptical overall, supporting the notion that education correlates with greater confidence in the integrity and value of TWAEM. Income level also influenced perceptions. For Q7.4 (erosion benefits), income differences were statistically significant (p = 0.001). Higher income groups were more confident that TWAEM contribute to reducing erosion, while lower income groups were more uncertain or sceptical. This suggests that trust in environmental claims grows with income, potentially reflecting exposure to environmental education or value alignment. 73 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 Exploring support for wine tourism: The role of education and income Support for wine tourism as a cultural service was overwhelmingly positive. Over 83% agreed that visiting wineries enhances knowledge of local traditions (Q8.1), and nearly 90% valued vineyard tours (Q8.3). The overall wine tasting experience (Q8.2) was the highest-rated, with 254 of 284 respondents (89%) in agreement. Additional tourism services (Q8.4) were slightly less supported but still viewed positively (59% agreement). Age differences in tourism preferences were negligible, with no statistically significant results, indicating that cultural interest in wine tourism spans generations. Similarly, gender analysis revealed that women and men are equally enthusiastic about the wine tourism experience. However, Q8.2 and Q8.4 showed significance by gender (p = 0.018), with women being marginally more positive toward additional services. In contrast, education showed significant effects. Respondents with specialized education were significantly more likely to value educational and experiential tourism elements (Q8.1, p = 0.001; Q8.2, p = 0.032). This implies that education not only influences product trust but also shapes cultural and experiential expectations. Lastly, income significantly influenced support for additional services (Q8.4, p = 0.000). Higher income respondents were more likely to value complementary activities like eco-trails and horseback riding, indicating that disposable income enhances appreciation for expanded tourism offerings. Socioeconomic Influences on Environmental Values The survey reveals that most respondents acknowledge the importance of soil-related ecosystem services, such as reducing soil erosion (Q9.1), increasing nutrients (Q9.2), and improving biodiversity (Q9.3). Agreement was strongest on nutrient enrichment (Q9.2), with over 88% responding positively. While differences by age and gender were not statistically significant for these questions, educational background and income did show strong effects. Respondents with higher education levels, especially those with specialized training, were more likely to agree with all three environmental statements, with significant differences in Q9.2 (p = 0.000) and Q9.3 (p = 0.002). Similarly, income had a significant effect on perceptions of nutrient improvement (Q9.2, p = 0.000), confirming that environmental literacy and economic resources correlate with greater appreciation of soil health practices. When it comes to climate change beliefs and mitigation behaviours, the findings show a general belief in climate change, but with significant divisions by income and gender. While 103 respondents stated they believe climate change is real (Q10), men were more sceptical, with a larger share expressing doubt. The gender gap here was 80 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 TABLE 17. DETAILED DESCRIPTIONS OF THE FOUR INGREDIENT VARIANTS. Ingredient variant Description Food label Conventional In conventional production (the most common form of agriculture in Denmark), food is cultivated with general consideration for the soil’s ability to support agricultural production in the long term. However, no specific attention is given to broader aspects of soil health, and there are no explicit requirements related to soil health in the cultivation practices Not available Soil health labelled This type of production requires farmers to implement specific measures aimed at promoting soil health. These include reduced ploughing, more frequent crop rotation, maintaining continuous plant cover, or integrating crops and livestock. Imagine that food produced in this way will, in the future, be labelled with a new icon, a plant symbol with soil, which can be seen here. Organic In organic production, food is cultivated without the use of synthetic fertilizers or pesticides. Instead, farmers must focus on natural substances and processes – for example, combining crops with livestock or rotating crops from year to year – so that the soil can support food production in a way that benefits the environment, people, and animals. Food produced in this way is labelled with the red Ø-label. organic with a soil health label It is possible to combine organic farming with specific measures aimed at promoting soil health. Food produced in this way will be labelled with both labels. The soil health practices that farmers can implement on their land are described in Table 18. These practices were identified through literature review and expert consultations. Before viewing the descriptions, respondents were introduced to the potential negative effects of intensive agriculture on soil health and how farmers can help reverse it. This was explained as follows: “Intensive farming practices can damage soil health, for example, through excessive ploughing or by growing the same crops year after year. However, farmers can actively promote healthy soil by implementing various targeted measures when cultivating their land.” 81 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 TABLE 18. SOIL HEALTH IMPROVING PRACTICES CONSIDERED IN THIS STUDY. Soil health improving practice Description No or reduced tillage Farmers can reduce or completely avoid ploughing their agricultural land to minimize soil disturbance, leaving crop residues such as leaves, stems, and roots on the soil surface. This helps preserve the soil structure and its microorganisms and can also increase the amount of organic matter in the soil. Continuous plant cover Farmers can ensure that living plants cover their agricultural land throughout the year to protect the soil from erosion caused by wind and rain. This helps restore and maintain the organic matter in the soil. More diverse crop rotation Farmers can rotate different crops more frequently than usual. This can help reduce plant diseases and pests and contribute to maintaining a good balance of nutrients in the soil. Combining Crop Cultivation and Livestock Farming Farmers often have the opportunity to both grow crops and keep livestock, such as cows or pigs, on the same land at different times. For example, animals can graze on fields with cover crops. Manure from the animals naturally adds nutrients to the soil, and their trampling can improve soil structure and conditions for microorganisms. For the food shopping scenario to function effectively, the price of each product must be specified. Using scanner purchase data, market price assessments, and input from two focus group interviews (each with eight participants), we identified three price levels for each product to reflect realistic potential market fluctuations, such as discounts, inflation, or other influencing factors. These prices reflect real market values, enhancing the realism of the BBCE in this study. With four variants for each of the seven main food products, we created a BBCE design containing 28 products in each food shopping scenario for each meal context. Consistent with previous BBCE studies (e.g. Caputo & Lusk, 2022), an orthogonal fractional factorial design with 81 food shopping tasks (food basket choice questions) was produced for each meal, ensuring that the price levels are uncorrelated across shopping tasks. To minimize cognitive fatigue, the 81 shopping tasks were divided into 9 blocks, with each respondent completing 9 shopping tasks. Focus group interviews confirmed that respondents could process 9 shopping tasks within a reasonable time frame, and no negative reactions were observed during the focus group interviews. Each shopping task was identical except for the prices, which varied across questions (see Table A1 in the 82 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 Appendix for the price ranges). An example of one of the shopping tasks for burgers is shown in Figure 6 (in Danish). The focus group interviews also confirmed that the ingredient lists for each dish, as well as the pictorial presentation of the ingredients, were understandable to respondents who may not necessarily have expertise or prior knowledge related to the topic. Which of the following food items would you buy to prepare burgers for dinner for your household? Remember, the items you choose will count toward your weekly food budget, which you previously indicated to be approximately (XXX) DKK/week. Imagine that you already have some additional ingredients (such as dressing, cheese, bacon, etc.) at home. Hypothetical food shopping scenario descriptions: The hypothetical food shopping scenario centred on preparing a dinner meal. The scenario begins by informing respondents that farmers can adopt the soil health improving practices described earlier. Although some farmers already use these practices, there are currently no labelling mechanisms indicating soil health considerations on food products in Denmark. Before participating in the BBCE, respondents were asked to choose one of the three meals, i.e. burgers, chicken with vegetables, or spaghetti Bolognese, that they had prepared for dinner in their household within the past year. If they had prepared more than one of these meals, they were asked to select the one they had prepared most recently. If they had not prepared any of the three, they were randomly assigned to one of the meals. Depending on the selected meal, respondents were directed to the corresponding shopping scenario in the BBCE. Respondents were also asked to provide their weekly food budget, which they were reminded of during the BBCE. The subsequent scenario description then focuses on their selected meal. Next, respondents were told to imagine that they are in a grocery store shopping for ingredients to prepare their selected meal for dinner for their household. They were also instructed to imagine that the store carries only the foods typically used to make that meal. However, each food item is available in four different variants, corresponding to the four soil-health improving practices described earlier, and all the food items are produced in Denmark. They were then presented with the first food-basket choice question where they were asked: “Which of the following food items would you buy to prepare (meal) for dinner for your household? Remember, the items you choose will count toward your weekly food budget, which you previously indicated to be approximately [XXX] DKK/week. Imagine that you already have some additional ingredients (such as dressing, cheese, bacon, oil, salt etc.) at home.” 83 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 FIGURE 6. AN EXAMPLE OF A FOOD BASKET SHOPPING SITUATION. The BBCE online supermarket software allows respondents to see the types and total number of food products selected, as well as the total price, similar to online shopping systems used in real market settings. During focus group interviews, participants indicated that there should not be too much information provided before the first shopping task, as they preferred to gain experience by answering the first question before proceeding to subsequent ones. Therefore, we moved some of the explanatory 84 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 text about the shopping experiment to appear after the first shopping task. At that point, respondents were presented with the following text: “In the following questions, you will be presented with several shopping situations that are very similar to each other. However, you should consider them as completely independent. For example, you can think of them as shopping trips spread out over different times during the coming year. You are asked to indicate which products you would buy in each situation. The same products will be available in each shopping situation, but the prices will vary from one situation to the next – just like in real stores, where prices also fluctuate, for example depending on whether a particular item is on sale or not. It is important that, as far as possible, you make your choices in the same way as you would if you were actually shopping in a real grocery store. So if you think some of the items are too expensive compared to what you would actually be willing to pay, you always have the option to not buy them. You can also choose not to buy anything at all.” Respondents then completed the remaining eight food basket choice questions. Data collection: The sample frame for the data collection included Danish citizens aged 18 to 70 years. In preparation for the main data collection, four key steps were undertaken: First, the questionnaire was tested through two focus group interviews to assess its content and ensure it was understandable to respondents. The outcome of this step revealed the need for a few changes, for example, removing questions deemed irrelevant and reducing the amount of information provided in the BBCE related to food shopping. Second, once the questionnaire had been validated through the focus groups, it was implemented online using a Python-based open-source software called oTree, hosted on the UCloud server (a cloud-based supercomputer) administered by the University of Southern Denmark (https://docs.cloud.sdu.dk/). Third, a random – and thus, representative – sample of 60,000 individuals was drawn from the Danish Civil Registration System (CPR) via the Danish Health Data Authority. Because this process involved handling personal data, permission was obtained from the University of Copenhagen’s legal department. Invitation letters with personalized links to the online questionnaire were sent via e-Boks – a secure digital mailbox mandatory for all Danish citizens aged 15 and above. Fourth, a pilot study was conducted with 2,500 respondents to evaluate the technical functionality of the BBCE and obtain initial survey response rate. The results of the pilot study indicated that the setup worked as expected and that a 10% response rate could be achieved. 85 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 TABLE 19. SOCIODEMOGRAPHIC DISTRIBUTIONS (IN PERCENTAGES) AND REPRESENTATIVITY OF SAMPLES. Variable Burgers Chicken with vegetable Spaghetti Bolognese Danish population Significance (Chi-square test) Gender (NS) (*), (*) Female 48.27 59.9 54.65 50.2 Male 50.06 39.8 44.64 49.8 Other 0.67 0.28 0.71 - Age (*), (*), (*) Under 35 18.1 11.7 16.7 35-54 38.0 29.6 35.4 36.0 Over 54 43.9 58.7 47.9 31.0 Household size (*), (*), (*) 1 17.9 21.8 22.1 18 2 or more 82.1 78.2 77.9 82 Education (*), (*), (*) Primary school 7.1 4.4 5.2 26 Upper secondary or Vocational 27.3 21.7 24.4 42 Higher education 65.6 73.9 70.4 32 Yearly gross incomea in DKK2 (*), (*), (*) Under 200.000 5.2 6.3 7.4 15 200.000-399.999 16.6 19.9 19.4 35 400.000-599.999 21.5 21.9 22.3 18 600.000 and above 45.9 41.4 41.7 31 Note: The last column reports tests for sample representativity of the Danish population. The three sets of parentheses in the last column correspond to the three samples from the three meals, meaning that each sample’s distribution is tested against the distribution of the Danish population using the chi-square test. (NS) indicates no significant difference, while (*) indicates that the difference between the sample distribution and the Danish population distribution of the socio-demographic variable is statistically significant at the 1% level or lower. a Around 10% of the respondents answered “I don't know” or “I do not want to answer” to the question about their yearly gross income. Hence, the percentage distribution reported for the samples here do not sum to 100. The chi-square test is based only the income distribution of those who have answered the question. The main data collection took place between April and June 2025. A total of 5,386 fully completed responses were obtained after sending one reminder, resulting in an overall response rate of 10%, which aligns with the findings from the pilot study. These responses were distributed across the three meal types as follows: 1,794 for burgers, 2 DKK is Danish kroner. 100DKK ~ 13,4EUR. 86 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 1,792 for chicken with vegetables, and 2108 for spaghetti Bolognese. Because data collection was conducted in three waves to achieve roughly equal sample sizes, the spaghetti Bolognese meal received a disproportionately larger number of responses. To test the robustness of our analysis, we tried randomly removing around 300 respondents from this sample, but the results did not change markedly, so we chose to retain the full sample. In addition, in the econometric analysis described below, we removed anomalous responses in which participants made random or inconsistent choices – for example, selecting burger patties without also selecting burger buns, which violated the survey design requiring respondents to choose at least one type of bun to form a burger meal. The sample characteristics across the three meals are shown in Table 19. Although we obtained a representative sample from the Danish Health Data Authority, our final sample is only representative of the Danish population in terms of gender for the burger sample. This suggests the presence of a self-selection. Because respondents were not randomly assigned to the three meal contexts – rather, they chose a meal based on their prior experience – we do not expect to observe balance in the three meal samples across characteristics. Econometric analysis: We analyse our data using a conceptual framework for multiproduct consumer choice, based on Neill and Lahne (2022), Palma and Hess (2022), and the literature cited therein. The decision of what and how much to choose is commonly framed as a discrete-continuous choice problem. Consumer choice often involves selecting among combinations of products, a complex decision that can be conceptualized using classical consumer utility maximization theory (Palma & Hess, 2022). Accordingly, a consumer 𝑛 must decide which product 𝑑 to purchase. The utility maximization problem can thus be expressed as: Where n represents consumers, with n =1,…,N, d indexes alternative products, with d = 1,…,D, represents the amount of an outside or numeraire good consumed, is the quantity consumed of alternative d, is the quantity consumed of alternative l, is the price of alternative d, and is the consumer’s total budget. Since we focus on consumer demand for food, the inside good in our analysis refers to d, that is, the 87 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 consumption of food (e.g., ingredients for a burger, chicken, or spaghetti Bolognese dish). The outside good includes any goods consumed other than the inside good (e.g., transport, leisure, housing) (Palma & Hess, 2022). The utility maximization problem in Equation (1) can be broken down into three parts for ease of understanding: the utility of the outside good , the utility of the inside good , and the utility of combinations of the inside goods. We refer the reader to Palma and Hess (2022) for a detailed econometric specification. Based on Equation 1 above, analysts are interested in estimating three key parameters: the base utility for alternative d, the satiation parameter for the same alternative, and the interaction parameters, which indicate substitution or complementary effects. The base utility is defined as the marginal utility at zero consumption, i.e., the utility associated with the initial unit of consumption of selected ingredients. This is also referred to as the scale of utility for a product, in our case, alternative d. The satiation parameter represents the utility obtained from subsequent consumption of a product, with higher values indicate greater consumption of alternative d. The interaction parameter captures complementarity and substitution effects. A positive value indicates a complementary relationship, i.e. that consumption of one alternative increases the consumption of the other. A negative value indicates a substitution effect, i.e., that consumption of one alternative reduces the consumption of the other. We use the extended multiple discrete continuous extreme value model to properly estimate these three key parameters (see Palma & Hess, 2022 for a detailed presentation of this model). Due to the complexity of the model and the large number of parameters than can be estimated in the extended Multiple Discrete-Continuous Extreme Value model, Palma and Hess (2022) provide guiding principles to support model identification and improve performance. First, they introduce a version of the model that does not require a budget constraint in the estimation. They argue that food expenditure may represent only a small fraction of total expenditure, with the outside good accounting for the majority. Therefore, a model that does not rely on a budget constraint may be more appropriate than one that does. Second, Palma and Hess (2022 suggest that model identification and convergence can be improved by limiting the number of interaction parameters, i.e., the parameters which represent substitution and complementarity effects. This can be achieved by defining a single parameter for a group of similar products or by fixing some interaction parameters, e.g., those considered less relevant for substitution and complementarity, to zero. In this study, we estimate the interaction parameters for within-product interactions defined by the different food labels (e.g., soil health-labelled, organic, and soil healthand organic-labelled beef burger patties) to investigate the role of the soil health label 88 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 in influencing substitution and complementarity effects. The interaction parameters for products not belonging to the same food group (e.g., soil health-labelled beef burger patties versus soil health-labelled burger buns) are fixed to zero. Furthermore, to reduce dimensionality, we aggregate products within the same food group. For example, burgers can be prepared with beef patties, chicken breast, or plant-based patties, which are therefore collapsed into a single product. We tested several model specifications in which varying numbers of products with similar functions (e.g., burger patties or vegetables) were collapsed. Ultimately, we selected models that were not overly restrictive in terms of the number of interaction parameters and in which only protein components were collapsed (i.e., the different patties for burgers, chicken breast and plant-based mince for the chicken with vegetable dish, and meat and plant-based mince for spaghetti Bolognese) to ensure consistency across meal contexts. Finally, because the interaction parameters capture only cross-utility effects and not price sensitivity (Caputo & Lusk, 2022; Richards et al., 2018), we also calculate price elasticities to assess how the demand for soil health-labelled products respond to changes in their own prices and the prices of other product variations. This allows us to better understand the extent to which demand for foods carrying a soil health label is influenced by price changes. 4.7.3 Survey results We present results from both descriptive and parametric analyses. The descriptive analysis examines the choice frequency of food ingredients, specifically conventional, soil health-labelled, organic, and those labelled with both the soil health and the organic label. Descriptive analysis: The choice frequencies for ingredients in burgers, chicken with vegetables, and spaghetti Bolognese are shown in Figures 7, 8 and 9, respectively. These frequencies are calculated as the percentage of times a product is chosen, i.e., the total number of times it is selected divided by the total number of times it is available. As shown in the figures, in most cases, products labelled with both the soil health and the organic farming label were chosen more frequently than the others. This is particularly true for plant-based ingredients, suggesting that respondents may have recognized their direct association with soils, as their growth depends on soils in general and soil health in particular. The soil health label without the organic label did not attract more choices compared to conventional farming, with choice frequencies being almost the same or even lower than for conventional options. However, in the case of the chicken meal, this label was chosen more frequently for five out of seven ingredients. 89 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 FIGURE 7. CHOICE FREQUENCIES OF INGREDIENTS FOR BURGERS. FIGURE 8. CHOICE FREQUENCIES OF INGREDIENTS FOR CHICKEN WITH VEGETABLES. 96 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 For example, in the burger meal, approximately 1% of choice frequencies represent combinations of ingredients within the beef burger patties category. Such purchasing behaviour may be particularly relevant for household members with varying preferences, for example, between organic and conventional products. Overall, we observe that meat, chicken breast or mince, and plant-based proteins exhibit the largest substitution effects across labels, compared to vegetables such as lettuce, bell peppers, and cucumber. This suggests that while all four version of all products in our analysis are substitutes, vegetable categories are more likely to be purchased together across labels, whereas protein categories generate stronger negative cross-utilities and are therefore less likely to be chosen together. Caputo and Lusk (2022), citing Richards et al. (2018), noted that the cross-utility effects (such as those presented in Tables 6–8) do not indicate substitution effects in response to price changes. For example, the substitution patterns observed in Tables 6–8 may not be driven by price effects, as these results are not based on predicted consumption. Price elasticities are better suited to capture predicted consumption responses, making it necessary to estimate them in order to understand how demand for specific ingredients changes in response to price fluctuations. This prediction is especially important for understanding how a soil health label might influence demand for different food products in the market. In other words, we aim to explore whether a soil health label can serve as a viable business model by assessing the demand for food and the implications for farmers who implement soil health practices. We estimate both own-price and cross-price elasticities in Tables 9–11 to better understand how soil health labels affect consumer demand for food products. Focusing on burger ingredients, the own-price elasticities are all negative, suggesting that when the price of an ingredient increases by 1%, demand for that product decreases by approximately 1.927% to 3.975%. Meat and plant-based burger patties are highly price elastic compared to vegetables. In terms of cross-price elasticities, there appears to be a strong substitution effect between conventional and soil healthor organic-labelled ingredients. Specifically, a 1% increase in the price of conventional ingredients consistently leads to greater substitution (demand) for soil health-labelled ingredients compared to other alternatives. For instance, while the demand for soil health-labelled lettuce increases by 0.319%, the corresponding increases are 0.145% for organic and only 0.019% for soil health-and-organic-labelled ingredients. There is also a strong substitution effect, i.e., higher demand for conventional ingredients when the price of ingredients carrying both soil health and organic labels increases by 1%. For example, when the price of soil health-and-organic-labelled cucumbers rise by 1%, demand for conventional cucumbers increases by 0.815%, while demand for organic cucumbers increases by 97 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 0.357%. The largest cross-price elasticities are observed for lettuce (1.196%) and tomatoes (1.367%), indicating that increasing the price of lettuce and tomatoes with both the soil health and the organic labels leads to a strong shift in demand toward conventional alternatives of similar product versions. Because the prices of these ingredients with both labels were set higher by design, further price increases are more likely to strongly shift demand toward other product versions. This is also reflected in the lower cross-price elasticities for these products when the prices of other ingredients increase by 1%. By contrast, increases in the prices of soil healthlabelled ingredients without the organic label lead to only modest substitution effects, as their cross-price elasticity estimates are often lower than those of other ingredients. TABLE 24. PRICE ELASTICITIES OF DEMAND FOR INGREDIENTS OF BURGER. A 1% increase in price of Percentage of change in demand for Burger patties Conventional Soil health Organic Soil health + organic Conventional -2.898 0.185 0.151 0.062 Soil health 0.085 -3.089 0.069 0.069 Organic 0.078 0.088 -3.191 0.099 Soil health + organic 0.185 0.149 0.116 -3.207 Burger buns Conventional -3.975 0.375 0.361 0.237 Soil health 0.118 -3.060 0.228 0.137 Organic 0.193 0.178 -2.401 0.184 Soil health + organic 0.615 0.612 0.023 -2.229 Lettuce Conventional -2.142 0.319 0.145 0.019 Soil health 0.029 -2.425 0.184 0.048 Organic 0.222 0.050 -2.282 0.178 Soil health + organic 1.196 0.605 0.058 -2.005 Tomatoes Conventional -2.256 0.278 0.107 0.011 Soil health 0.084 -2.543 0.135 0.058 Organic 0.189 0.061 -2.617 0.184 Soil health + organic 1.367 0.411 0.068 -2.515 Cucumber Conventional -2.166 0.332 0.148 0.011 Soil health 0.052 -2.044 0.128 0.039 Organic 0.201 0.091 -1.962 0.118 Soil health + organic 0.815 0.357 0.055 -1.927 The results for the chicken with vegetables and pasta Bolognese meals broadly mirror those for burgers. Notably, an increase in the price of conventional ingredients leads to higher demand for soil health-labelled alternatives. For example, a 1% increase in 98 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 the price of chicken breast or plant-based mince raises demand for the soil healthlabelled option by 0.233%, compared to 0.120% for the organic option and 0.041% for the soil health-and-organic option. Additionally, price increases for ingredients carrying both soil health and organic labels result in higher demand for other ingredients, especially conventional ones. Price changes for soil health-labelled ingredients alone are still associated with moderate substitution effects, although the effect is slightly stronger in the case of spaghetti Bolognese. TABLE 25. PRICE ELASTICITIES OF DEMAND FOR INGREDIENTS OF CHICKEN A 1% increase in price of Percentage of change in demand for Chicken breast or plant-based ground mince Conventional Soil health Organic Soil health + organic Conventional -2.400 0.233 0.120 0.041 Soil health 0.084 -2.397 0.099 0.079 Organic 0.139 0.025 -2.604 0.111 Soil health + organic 0.309 0.064 0.001 -2.563 Potatoes Conventional -2.139 0.136 0.095 0.012 Soil health 0.035 -2.030 0.074 0.072 Organic 0.076 0.006 -1.866 0.142 Soil health + organic 0.550 0.111 0.007 -1.764 Lettuce Conventional -2.714 0.123 0.058 0.019 Soil health 0.136 -2.696 0.001 0.060 Organic 0.339 0.143 -3.034 0.188 Soil health + organic 1.027 0.442 0.054 -1.972 Onion Conventional -4.322 0.095 0.208 0.047 Soil health-labelled 0.436 -5.349 0.275 0.073 Organic 0.190 0.520 -2.040 0.107 Soil health + organic 1.638 0.330 0.007 -1.820 Tomatoes Conventional -2.583 0.189 0.089 0.043 Soil health 0.068 -2.294 0.133 0.053 Organic 0.178 0.069 -2.330 0.146 Soil health + organic 0.639 0.456 0.110 -2.286 Bell pepper Conventional -2.351 0.230 0.189 0.032 Soil health 0.054 -3.117 0.034 0.029 Organic 0.156 0.088 -1.985 0.159 Soil health + organic 1.509 0.521 0.226 -4.774 99 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 TABLE 26. PRICE ELASTICITIES OF DEMAND FOR INGREDIENTS OF CHICKEN A 1% increase in price of Percentage of change in demand for Meat or plant-based mince Conventional Soil health Organic Soil health + organic Conventional -3.028 0.405 0.193 0.197 Soil health 0.107 -3.672 0.137 0.098 Organic 0.174 0.145 -4.101 0.204 Soil health + organic 0.172 0.176 0.066 -4.819 Pasta Conventional -2.167 0.388 0.160 0.025 Soil health 0.029 -2.557 0.191 0.092 Organic 0.366 0.244 -2.587 0.049 Soil health + organic 2.307 1.181 0.311 -2.613 Potatoes Conventional -2.282 0.341 0.220 0.042 Soil health 0.033 -2.613 0.193 0.077 Organic 0.208 0.131 -2.255 0.057 Soil health + organic 1.380 0.662 0.177 -2.542 Chopped tomatoes Conventional -4.064 0.872 0.393 0.204 Soil health 0.018 -2.442 0.166 0.061 Organic 0.385 0.078 -2.443 0.273 Soil health + organic 0.762 0.342 0.049 -2.215 Carrots Conventional -2.717 0.333 0.147 0.027 Soil health 0.059 -2.803 0.160 0.049 Organic 0.292 0.143 -2.649 0.205 Soil health + organic 1.911 1.230 0.118 -2.343 4.7.4 Market potential Our results suggest that respondents have higher baseline utilities for products carrying both soil health and organic farming labels. These products also show stronger negative cross-utilities, meaning that when chosen, they are less frequently purchased together with other product versions in the same category. Such substitution effects are more pronounced for meat and chicken-based products than for vegetables such as lettuce, bell peppers, and cucumber. Our price elasticity estimates indicate that all products, including soil health-labelled versions, have negative own-price elasticities, suggesting that respondents, as expected, are price sensitive and that demand for soil health-labelled products decreases when their price increases. Cross-price elasticities reveal that higher prices on conventional food products increase demand for soil health-labelled versions, whereas dual-labelled ingredients with both soil health and organic labels are less responsive to changes in the prices of other products. When the price of items with both labels rises, demand 100 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 shifts toward conventional and, to a lesser extent, organic product versions. In contrast, price increases for soil health-labelled ingredients alone induce only modest substitution toward other versions. Our results have several implications for using soil health labels as a business model to enhance ecosystem services and promote sustainable agriculture. First, the finding that soil health-labelled ingredients are more appealing to respondents at the baseline level, and that they serve as substitutes for conventional, unlabelled food products, suggests that soil health labels can be applied to food products in market places. This indicates a potential role for such labels in shaping consumer choices. As a result, policies should support and create the conditions for voluntary or mandatory labelling schemes to facilitate the adoption and marketing of soil health labels. Second, although products with both soil health and organic labels are overall preferred, respondents are more likely to switch to other product versions when the prices of these dual-labelled products rise. Since these products were already priced higher than the other alternatives, this demand shift is expected, and further price increases are likely to reduce demand. Therefore, appropriate pricing mechanisms may be necessary, including incentives for organic farmers to adopt soil healthimproving practices, in order to maintain market potential without further price increases. Third, because soil health-labelled products without the organic label induce only a moderate shift in demand toward other ingredients (i.e. lower crossprice elasticies), respondents may reduce or postpone consumption of these products without necessarily substituting them with conventional alternatives. However, given that soil health-labelled ingredients are highly price elastic with respect to their own price, creating and maintaining market potential requires appropriate pricing mechanisms to preserve market share and increase consumption of these ingredients. Overall, our results can inform policymakers on how to sustain demand for soil healthlabelled products by introducing, for example, subsidies for agricultural practices that improve soil health. Such subsidies are crucial for maintaining the market competitiveness of products derived from these practices, thereby encouraging consumer adoption of soil health labels on foods and creating the economic security farmers need to invest in soil health improvements. At the same time, our results imply that the price sensitivity of soil health-labelled products should be considered when policymakers design taxes on agricultural practices and products more generally. 101 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 Appendix Table A1. Price levels of food products in DKK (Low, Medium, High) Burgers Ingredients Conventional Soil health Organic Soil health + organic Beef burger patties (500g) 25, 43, 60 33, 49, 65 40, 55, 70 48, 61, 75 Chicken breast (500g) 20, 30, 40 35, 55, 80 50, 85, 125 65, 115, 170 Plant-based burger patties (500g) 30,40,50 35,45,55 40,50,60 45,55,65 Burger buns (300g) 10, 16, 21 13,18,25 15,21,28 18,25,33 Lettuce (1 piece) 5,9,12 6,9,13 6,10,14 7,11,15 Tomatoes (500g) 12,22,32 16,26,35 20,30,38 24,34,40 Cucumber (1 piece) 4,7,10 4,9,13 ,5,11,17 6,13,20 Chicken with vegetables Chicken breast (500g) 20,30,40 35,55,80 50,85,125 65,115,170 Plant-based mince (500g) 30,45,60 35,56,77 40,67,95 45,78,112 Potatoes (500g) 6,16,25 7,18,28 8,19,30 9,21,33 Lettuce (1 piece) 5,9,12 6,9,13 6,10,14 7,11,15 Onions (1kg) 5,9,12 6,10,13 7,11,15 8,12,16 Tomatos (500g) 12,22,32 16,26,35 20,30,38 24,34,40 Bell peppers (1 piece) 5,8,11 8,10,13 10,13,15 13,15,17 Spaghetti Bolognese Minced beef (500g) 30,45,60 50,60,70 70,75,8 90,95,100 Minced chicken (500g) 25,43,58 55,75,90 85,110,130 110,140,170 Plant-based mince (500g) 30,45,60 35,56,77 40,67,95 45,78,112 Pasta (500g) 5,7,10 7,8,11 8,10,12 9,11,13 Onions (1kg) 5,9,12 6,10,13 7,11,15 8,12,16 Chopped tomatoes (400g in can) 6,8,10 7,12,15 8,13,18 9,15,22 Carrots (500g) 5,8,10 6, 9, 11 7, 10, 12 9, 11, 13 102 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 4.8 Italy: “Sustainability District of the Sandy Soil Area of the Po Delta in the Emilia-Romagna Region” (IDECO) 4.8.1 Introduction and case study description The case study "Sustainability District of the Sandy Soil Area of the Po Delta in the Emilia-Romagna Region" aims to foster local development, competitiveness, business collaboration in the sandy soil area, and the dissemination of a culture of agrienvironmental sustainability among consumers. Collaboration between businesses aims to maintain an active dialogue with local institutions regarding threats to the fertility and health of sandy soils. The creation of a Food District represents an innovative business model for the health of sandy soils in the Emilia-Romagna Region. The "Food District" strategy is identified in Regional Council Resolution No. 1816 of October 28, 2019. The document identifies various methodologies for territorial aggregation. Our case study focuses on the "Sustainability District" typology, i.e., "local production systems characterized by the presence of cultivation, livestock farming, processing, food preparation, and agro-industrial activities carried out using organic methods or in compliance with environmental sustainability criteria, in accordance with current European, national, and regional legislation." The case study's operational area encompasses several municipalities in the province of Ferrara: Mesola, Goro, Codigoro, Lagosanto, Comacchio, and Ostellato; the municipalities cover a usable agricultural area of approximately 18,600 hectares. Part of the area falls within the Emilia-Romagna Po Delta Park, which was recognized as a Biosphere Reserve under the UNESCO MaB Programme in 2015. The operational area highlights the potential for promoting the products and businesses associated with it, which share the presence of sandy soils, a distinctive element compared to all other areas of the region (Figures 10-11). This area has always been characterized by a strong agricultural and rural-tourist vocation. 103 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 FIGURE 10. NATIONAL TERRITORIAL FRAMEWORK OF THE CASE STUDY “EMILIA-ROMAGNA REGION SAND AREA”. FIGURE 11. PILOT CASE AREA, PROVINCE OF FERRARA (EMILIA-ROMANA REGION) The main crops grown in the sandy area are potatoes, carrots, tomatoes, durum wheat, common wheat, and fruit nurseries. In these areas, cultivated soil is often located more than 2 meters below sea level. The soil is classified as sandy because its sand content exceeds 60%. Sandy soils are poorly structured, light, and loose, with limited water retention and high permeability, as well as low organic matter content. These characteristics require careful soil management to preserve its physical, chemical, and microbiological properties, allowing farms operating in the area to continue to produce high-quality, environmentally and economically sustainable crops well into the future. The sandy soils in the study area are characterized by two critical issues: - salinization and salt ingression, which lead to reduced yields (Figure 12); - low organic matter content (Figure 13). 104 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 Salt ingression is caused by denser, salty seawater coming into contact with coastal aquifers; this phenomenon is favoured by the lowering of the freshwater level underground due to excessive use of groundwater for irrigation and by pumping for reclamation purposes ("salt wedge"). FIGURE 12. SOIL MAPPING OF THE EMILIA-ROMAGNA REGION WITH DETAILS OF SAND CONTENT IN THE 0-30 CM LAYER OF THE SOILS IN THE PILOT AREA IN THE PROVINCE OF FERRARA. SOURCE: MOKA GEOPORTAL, EMILIA-ROMAGNA REGION. FIGURE 13. SOIL MAPPING OF THE EMILIA-ROMAGNA REGION WITH DETAILS OF ORGANIC MATTER CONTENT IN THE 0-30 CM LAYER OF SOILS IN THE PILOT AREA IN THE PROVINCE OF FERRARA. SOURCE: MOKA EMILIA-ROMAGNA REGION GEOPORTAL. 105 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 The Sustainable Sand District represents the business model hypothesized for the case study, most suitable for testing integrated soil management approaches aimed at greater adaptation and resilience to ongoing climate change. 4.8.2 Method The survey questionnaire was addressed to farmers (farms and agricultural cooperatives), land managers such as local authorities, the Po Delta Park of the EmiliaRomagna Region, the Land Reclamation Consortium, environmental associations, foundations, and non-profit organizations. The objective was to understand the stakeholders' attitudes toward sandy soil protection and address common challenges through adoption and participation in innovative business models. Stakeholders were also asked questions about the possibility of applying other business models, such as carbon farming and the application of best practices for business competitiveness, and participation in research projects, taking into account environmental, social, and economic factors. Approximately 60 stakeholders working in the sandy area were involved. Specifically, the following categories were interviewed: ● agricultural companies and cooperatives operating on sandy soils and participating in the PIL (Political Innovation Lab); ● land managers such as local authorities; specifically, the questionnaire was distributed to the departments of environment, agriculture, and land-use and cultural planning, land reclamation consortia for irrigation management, the Emilia-Romagna Po Delta Park, agricultural trade associations, and environmental associations; ● technicians and freelancers such as local geologists and agronomists. The questionnaire was created using Google Forms and divided into 7 sections. Stakeholders were asked to express their opinions by assigning a score on a scale from 1 (completely disagree) to 5 (completely agree). The questionnaire sections are as follows: SECTION 1 - General data: category, municipality, hectares cultivated, production type, gender, age, and education of the respondent; SECTION 2 - Business models for sandy soil health: Users were asked to express their preferences regarding the application of different business models (e.g., carbon farming, sustainability districts, research projects, collective actions), their advantages, disadvantages, and implementation methods; SECTION 3 - Best practices for sandy soil management: Users were asked to express their preferences regarding the application of different best practices (e.g., minimum 112 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 5. General discussion Business model potential matrix The following Table 27 summarises the results of the presented studies in the form of a market potential matrix to identify promising business models. High potential demand that is met by high potential supply hints at a high market potential. On the other hand, low or medium potential on either of the two sides limits a business models potential, as far as it can be judged by the studies’ results (not all case studies investigated both the supply and demand side). TABLE 27. BUSINESS MODEL POTENTIAL MATRIX. Partner Soil health business model Consumer acceptance Farmer adoption Potential value TUM AECS Medium to High High High TUM Carbon farming Low Low Low TUM Value chain Medium to High Medium Medium ZALF Soil health and biodiversity certificates Medium to High High Medium to high WU Carbon farming + carbon credit trade n.a. Medium Low WU Carbon farming + value chain payments n.a. Medium High WU Carbon farming + CAP payments n.a. Low Low UCPH Soil health label Medium n.a. High UNIFE/UNIPI Area basedpayment (AECS) Low n.a. Low UNIFE/UNIPI Result-based payment High n.a. High UNIFE/UNIPI Hybrid Medium n.a. Medium METK Low-carbon seed Low Low-Medium Medium NBU Agrotourism High n.a. High IDECO Sustainable food district n.a MediumHigh High Note: n.a. = not applicable, as not in all case studies both the demand and supply side were studied. 113 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 5.1 Germany: Carbon farming (TUM) Based on the preferences of both farmers and consumers, AECS (Agri-Environmental Climate Schemes) and value chain approaches emerge as the most promising business models for enhancing soil organic carbon (SOC) and delivering climate benefits. In contrast, GHG certificate models currently face significant barriers to widespread acceptance. From the farmers’ perspective, flexibility, simplicity, and familiarity are critical factors influencing their willingness to participate in environmental schemes. AECS are favoured because they are well-established, provide reliable payments, and involve action-based measures that many farmers already understand and implement. Similarly, value chain approaches, especially those that can be terminated at any time, offer a level of autonomy that aligns with farmers' strong preference for avoiding longterm contractual commitments and additional bureaucracy. Farmers are generally reluctant to adopt measures that limit their decision-making freedom or impose a high administrative burden, particularly when market conditions are volatile. When comparing average willingness to pay (WTP) and willingness to accept (WTA), both AECS and value chain models, particularly in their improved forms, prove economically viable. From an ecological standpoint, the improved versions of these models, which include results-based payments and longer-term commitments, are also preferable because they ensure verified carbon sequestration and better align with emerging EU regulations (e.g., CRCF Regulation (EU/2024/3012)). Consumers, for their part, are generally supportive of climate mitigation efforts and are open to paying for CO₂ offset initiatives. However, their preferences hinge on two key conditions: short-term commitments and guaranteed environmental outcomes. They express strong aversion to long-term payment obligations (e.g., 10-20 years) and are more likely to support business models where target achievement is assured. Depending on the monitoring character, consumer potential of the business models is either medium (for action-based monitoring) or high (for result based monitoring). Result-based AECS and improved value chain models meet consumers expectations more effectively than GHG certificate models. In contrast, GHG certificate modelsface scepticism from both stakeholders. Farmers are deterred by the requirement for long-term, results-based contracts and uncertainty around the future prices of CO₂ certificates. Many are hesitant to invest in new practices and technologies when market fluctuations could undermine profitability. While policy tools like minimum price guarantees could theoretically address this issue, they carry the risk of oversupply and may lead to ecological backsliding once contracts expire. These factors contribute to a high WTA among 114 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 farmers, making GHG certificate modelseconomically and practically less attractive at this stage. In conclusion, both AECS and the value chain approach offer a promising path forward for promoting soil carbon sequestration. They are better aligned with the preferences and risk tolerances of farmers, meet key consumer expectations, and, if adapted with results-based elements, can deliver measurable and reliable climate benefits. By contrast, GHG certificate models, while conceptually robust, require further policy support, risk mitigation strategies, and trust-building measures to become a feasible and widely accepted model. 5.2 Germany: AgoraNatura (ZALF) Our study provides a novel contribution to the ongoing debate on how to enhance private funding for environmental improvements in agriculture. We examined private consumers’ WTP for soil health and biodiversity certificates which are determined by bundling and blending. Moreover, we made use of an existing online marketplace acting as a facilitator and intermediary of such funding. The insights of our research for leveraging private investment are manifold. First, our findings align with existing studies indicating that private consumers in Germany show a willingness to contribute financially to soil health and biodiversity on farmland. This trend may indirectly reflect public support for the EU’s Soil Strategy and Biodiversity Strategy. Our results also encourage decision-makers to continue recognising soil health and biodiversity on farmland as priority in policy initiatives. Second, policymakers may acknowledge that bundling can increase private investment. Therefore, when designing incentive schemes within current policy initiatives (e.g. the EU’s Roadmap towards Nature Credits) bundling environmental improvements under single certificates should be considered. However, the heterogeneity in preferences for bundled improvements implies that while bundling responds to public demand, policy design should ensure a variety of bundle types to fully harness funding potential. Third, blending public and private funding offers opportunities to enhance investment. Nevertheless, public spending must be carefully balanced to prevent crowding out of private funding. Our results underline that excessive public subsidies may crowd out private willingness to pay. Experiences from UK ecosystem markets and European peatland initiatives provide valuable insights here. Specifically, 115 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 mechanisms such as trigger funds, similar to those tested in our study, could successfully encourage private funding while limiting crowding-out effects. Lastly, our results provide evidence that online marketplaces for soil health and biodiversity certificates, such as AgoraNatura, may be a useful business model to attract private funding. 5.3 Netherlands: Carbon credit (WU) The Dutch case study identified three distinct farmer perspectives: pro-environmental entrepreneurs, traditional food providers, and carbon farming pragmatics. Each group holds different attitudes towards incentives for improving soil health. While proenvironmental entrepreneurs and carbon farming pragmatics may be more open to new incentives such as value chain payments or carbon farming contracts, traditional food providers appear more difficult to engage through these contracts. Since soil health, carbon storage, and agricultural productivity are closely connected, emphasising these links could help motivate farmers with more conservative views. Although some farmers responded positively to value chain contracts and carbon credit trading, several aspects of these incentives require further consideration before they are widely promoted. For value chain contracts, fairness in negotiating agreements with actors who may have greater market influence is important. It is also necessary to consider public expectations regarding products that claim to be more sustainable. In the case of carbon credit trade, questions remain about whether soil health measures can deliver the intended long term carbon storage. The study also shows that the incentives provided by public payment schemes (such as AECS and eco-schemes) are seen as insufficient by all farmers in the sample. Improving these schemes could increase their acceptance and effectiveness. Overall, the findings demonstrate that farmers have diverse views on soil health incentives. A single contract solution will not meet the needs of all farmers. Tailored approaches that reflect different beliefs, production systems, and market conditions are essential for designing effective and inclusive strategies. 5.4 Italy: Italian consumers (UNIFE, UNIPI) The findings of the mixed logit model offer significant insights into the preferences of Italian consumers regarding conservation agricultural initiatives. The payment per 116 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 hectare signifies substantial price sensitivity, indicating that participants are less inclined to support programs requiring greater payments. This aligns with established economic behaviour and past findings that individuals generally prefer lower-cost options when contributing to environmental programs (Blasch & Farsi, 2014). Research revealed that a significant number of consumers are willing to pay a little premium price for ecological products; however, their willingness to pay declines as the premium rises (Biswas, 2016; Kucher et al., 2019). Like many European customers, Italians seem to be willing to support environmental initiatives, but only to a certain extent, particularly when the cost is viewed as excessive or unjustified. Besides, there is a considerable possibility for greater consumer awareness and vendor promotional activities due to the low level of consumer awareness of ecological agriculture products (Hao et al., 2022). Similarly, the contract duration shows a clear aversion to long-term commitments, suggesting that longer program durations reduce the likelihood of program selection. The negative effect of program duration suggests a public preference for shorter commitments, likely due to risk aversion or uncertainty about long-term obligations. In a comprehensive analysis of attributes utilized in discrete choice experiments (DCE) for agri-environmental contracts, Raina et al. (2021) discovered that contract duration was a significant component in 17 of the 34 selected studies. On the other hand, attributes that demonstrate environmental effectiveness have a favourable effect on decision-making. An increase in soil organic matter has a large positive impact, suggesting that consumers value tangible environmental benefits highly. This aligns with global soil health initiatives that prioritise organic matter as a key indicator of soil functionality. Soil organic matter is not only a key indicator of fertility and productivity, but it also plays a critical role in carbon sequestration, water retention, and biodiversity (Celestina et al., 2019; EIP-AGRI, 2015). People accord priority to ecological agriculture because it has numerous positive effects on the environment, such as improved soil-building techniques that support soil flora and fauna, long-term sustainability of agro-ecosystems, enhanced biodiversity, better water infiltration, and a lower risk of groundwater pollution (Manco, 2023). For payment type, the result indicates that respondents show a stronger preference for performance-based or mixed payment schemes rather than fixed-rate. The previous research stated that flexible and adaptive contractual solutions are favoured over a fixed payment type of contract. The best contract design under the Common Agricultural Policy (CAP) Pillar 2 measures combines action-based and result-based components in a medium-term agreement (Kelemen et al., 2023). Traditional actionorientated agri-environmental schemes have faced extensive criticism for various reasons, including ineffective targeting, insufficient payment differentiation, shortterm focus, and inadequate monitoring (Moxey & White, 2014). In contrast, result- 117 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 orientated schemes are advocated primarily for their potential to enhance outcomes and reduce costs by permitting greater flexibility and innovation compared to actionorientated schemes (Simpson et al., 2023). The values of marginal willingness to pay (MWTP) highlight these findings. Consumers are prepared to spend roughly €120.37 more per hectare for initiatives that improve soil organic matter. The World Economic Forum (2023) mentioned that at least 65% of customers wish to spend wisely to have more sustainable and healthful lives. In response to this, many food manufacturers are implementing several measures to guarantee environmental sustainability and meet the growing demands of consumers. For instance, Nestlé has partnered with 500,000 farmers to hasten the shift to regenerative farming methods, which improve soil quality, restore natural water cycles, and absorb carbon (World Economic Forum, 2023). Consumers are also showing their willingness to pay €29.36 more per hectare for result-based payments. This result suggests that consumers value performance-linked incentives that reward actual environmental outcomes. Hybrid agri-environmental payment schemes seem to provide the optimal payment solution, considering both fiscal limitations and the necessity for programs to engage significant farmer participation to achieve environmental efficiency (OECD, 2022). The potential of result-orientated agrienvironmental schemes is garnering heightened interest in Europe; researchers generally believe that result-orientated strategies will yield superior ecological, economic, and social outcomes compared to action-orientated approaches (Burton & Schwarz, 2013). While MWTP for contract duration indicates that consumers are unwilling to pay more for longer program durations, they would pay €11.59 less for each additional year of contract duration. It is well documented in behavioural environmental research, which indicates that uncertainty regarding future rewards or costs diminishes the willingness to engage in long-term programs (Buttenheim et al., 2023). These estimations emphasize the importance of environmental results and program design in influencing public support. Empirical evidence indicates that Italian consumers are inclined to support conservation agriculture, contingent upon the initiatives being cost-effective, flexible, and outcome focused. Their preferences favour short-term, quantifiable activities that distinctly exhibit environmental impact, especially enhancements in soil organic matter. These findings could have significant implications for the formulation of future agri-environmental policies. Integrating consumer-desired attributes, such as performance-based incentives and shorter contracts, can improve the acceptance and effectiveness of soil conservation initiatives. 118 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 5.5 Estonia: Seed centre (METK) The findings of this study shed light on Estonian farmers’ willingness to pay for carbonlabelled and environmentally labelled seeds, revealing a mix of economic, behavioural, and systemic influences. While policy momentum from initiatives like the European Green Deal (European Commission, 2020) and Estonia’s CAP Strategic Plan 2023-2027 (RT I, 27.03.2025) highlight the importance of sustainable practices in agriculture, price remains the dominant factor guiding farmers’ seed purchasing decisions. The challenge, therefore, lies in aligning environmental goals with farmers’ financial realities and practical needs. Market incentives and price sensitivity Farmers in this study were most willing to pay more for carbon-labelled seeds when those seeds conferred a clear market advantage or price premium. This underscores that sustainability alone is not a sufficient incentive – unless tied directly to improved revenue, reputation, or reduced risk. Introducing environmental labelling into the seed sector must therefore be accompanied by mechanisms that translate sustainability into tangible business benefits, such as access to premium markets or preferential treatment in procurement schemes. This aligns with broader literature on sustainable agriculture that emphasizes the importance of value-added strategies for incentivizing sustainable input use (e.g., Singh et al., 2013). Adding a sustainability label may also enhance the company’s ESG value, potentially improving conditions for investment and stakeholder confidence (Sandberg et. al, 2023). Yet, price sensitivity remains a core barrier. While consumers and downstream actors increasingly demand green products (CBI, 2022), farmers face tight margins. This is especially true in Estonia, where climate risks and farm size diversity make investment decisions cautious. Behavioural dimensions: values, beliefs, and the value-action gap This study confirms the presence of a value-action gap: respondents who strongly agreed that farmers should support sustainable seed producers were, paradoxically, less likely to pay more themselves. This phenomenon reflects a tension between normative environmental values and individual economic behaviour – widely observed in environmental psychology and behavioural economics. Similarly, respondents who believed that technology alone can solve environmental problems – without requiring lifestyle or practice change – were less likely to pay more for carbonlabelled seed. This reflects what Abson et al. (2017) term “shallow leverage points,” where optimism about innovation replaces the need for immediate behavioural change. The observed gender differences add nuance to the discussion: male respondents were more likely to pay a premium when market benefits were present 119 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 but less inclined when motivations involved indirect environmental gains, such as ESG improvements or carbon credit compensation. These results suggest that sustainability messaging must be targeted by gender, education level, and farm type. Structural barriers and business model challenges There are several fundamental challenges in transitioning seed production to soilsustainable practices. These include questions around how to introduce new soil management technologies – such as reduced tillage, cover crops, or organic amendments – that ensure soils maintain their ecological functions, such as carbon storage, biodiversity support, and water regulation (Bender et al., 1999; Abawi & Widmer, 2000). Moreover, farmers must also secure financing to make these transitions viable. The design of future business models must consider both seed quality and productivity alongside soil health. This requires integrating local soil data, weather information, and crop requirements into decision-making and aligning them with consumer and market expectations. The entire supply chain – from production to marketing – should be considered to ensure a functioning system where soil-health benefits translate into product value. Although innovative cultivation technologies (e.g. direct drilling, catch crops) and their impacts on seed productivity and soil functions have been studied (Singh et al., 2013), there is limited integration of these findings into business modelling in seed systems. More research is needed to identify which technologies provide both agronomic and ecological value in specific contexts. Policy landscape and research gaps The Estonian CAP Strategic Plan 2023-2027 provides several direct and indirect measures for soil protection. These include permanent grasslands on slopes to mitigate erosion, peatland protection, crop rotation, legume cultivation, winter soil cover, and soil sampling (RT I, 27.03.2025). However, carbon certification and carbonlabelled seeds are not yet common practice in Estonia’s seed production sector, as confirmed by this study’s survey data. Policy should focus on incentivizing participation in carbon programs, encouraging adoption of soil-friendly practices through subsidies, and integrating carbon and biodiversity metrics into existing CAP measures. As Liu et al. (2016) suggest, long-term effects of carbon labelling and behavioural barriers among conventional tillage users must also be addressed through tailored outreach and support. Despite green thinking becoming more widespread – including among processors and consumers – the market still signals that price is the deciding factor in seed purchasing (CBI, 2022). Therefore, a sustainability label cannot stand alone; it must be embedded in a larger system of business value and social trust. 120 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 The way forward: Differentiated strategies and soil-centred innovation In conclusion, our findings suggest that soil-health-promoting measures must be embedded into all agricultural sectors, including seed production. These measures should not be introduced uniformly but rather tailored to the production characteristics of different crops, regions, and farm types. Not all sustainable practices are equally effective in every context, and the most suitable technologies for seed production – ones that balance seed quality, soil conservation, and economic feasibility – should be a priority for future research. The vision is to develop business models where seeds produced with sustainable soil management practices offer added value, allowing producers to earn additional income while also improving ecological outcomes. This strategy has the potential to create a win-win situation: enhancing soil health and biodiversity while increasing the economic resilience of farms. 5.6 Bulgaria: Agrotourism (NBU) The results presented in the matrix highlight the market potential of BG CS, which is primarily linked to its strong focus on agro-ecological wine production practices that protect soil from erosion. This potential is evident across several key areas. In terms of channels, there are opportunities to expand the popularity of such wines through wine tourism and related activities, including tastings, restaurants, and hotel partnerships, while also targeting niche markets that value sustainable production. Strengthening customer relationships can be achieved by certifying wines that guarantee soil protection practices, as well as by fostering collective initiatives such as associations of wineries producing comparable quantities of wine. From a cost structure perspective, participation in joint procurement of materials and supplies offers the chance to optimize expenses and increase efficiency. Among the most important key resources is the certification of both grapes and wine produced under soil erosion protection standards, which serves as a mark of quality and sustainability. Finally, the policy framework supports the implementation of inter-row grassing, alongside investments in new technologies and experimental approaches, in order to further enhance and establish effective soil erosion protection practices. Together, these elements explain the indicated market potential and position BG CS as a promising example of how ecological practices can create both environmental and economic value. 121 This project has received funding from the European Union’s HORIZON-AG - HORIZON Action Grant Budget-Based research and innovation programme under grant agreement GA 101091268 5.7 Denmark: Soil health label (UCPH) Results suggest that soil health labels on food products can increase consumers’ utility when combined with organic labels. Labelling food products with only the soil health label leads to relatively small utility differentiation compared to conventional products without labels. The utility of dual-labelled food products – those carrying both soil health and organic labels – is also reflected in their cross-utility effects, as they are less frequently purchased together with other product versions in the same category. The market potential of soil health labels depends on changes in both their own and other products’ prices. Overall, food products carrying soil health labels, whether combined with organic labels or not, have negative own-price elasticities, indicating that price increases reduce demand for such products. However, when the price of dual-labelled products rises, demand is likely to shift toward conventional products and, to a lesser extent, organic-labelled products. This suggests that while duallabelled products are highly preferred and competitive at the current prices considered in the study, further price increases would reduce their market share. The results carry several implications. Soil health labels can play a role in soil health business models, but their success requires integration with established labels that are already well recognized and accepted by consumers. In our case, pairing soil health labels with organic labels enhances consumer utility. Such integrated labelling could also have significant market potential in the food sector if supported by appropriate pricing strategies or policy mechanisms. For example, subsidizing farmers to adopt soil health-enhancing practices could reduce food production costs, prevent price increases for soil health-labelled products, and in turn encourage consumer adoption through increased purchases. Moreover, our findings imply that policymakers should carefully consider the price sensitivity of food products before introducing taxes on agricultural practices. 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