Food, land, and water systems face daunting challenges in the future, and the body of research exploring these challenges is growing rapidly. This note is part of aseriesdeveloped by theCGIAR Foresight Initiativeto summarize what we know today about the future of various aspects of food systems. The goal of these notes is to serve as a quick reference, point to further information, and help guide future research and decisions.
By Daniel Mason-D’Croz, Mario Herrero, Cody Kugler, Rosaline Remans, Philip Thornton, and Heather Zornetzer
Key messages
- Innovations have been and will continue to be critical drivers of food systems and societal change.
- Predicting “game-changing” technology ahead of time is not possible and silver bullets do not exist.
- Novel innovations can alleviate some challenges, but unintended consequences always arise.
- Foresight research can help to identify undesirable outcomes early on and align investments and incentives with social and environmental objectives.
Recent trends and challenges
Innovations have been critical to shaping the food systems we know today, contributing to many historical food system transitions as new technologies, practices, and food products have redefined humanity’s connection to food and food production (Herrero et al. 2020, 2021; Loboguerrero et al. 2020). Food systems innovation, industrialization, and infrastructure have been intertwined and self-reinforcing, with increasing agricultural productivity acting as an important driver of past transformational sociopolitical and economic change (Gollin, Parente, and Rogerson 2002).
Agricultural productivity growth has been critical to allow food systems to respond to the growing global population while increasing food availability and affordability, as the risk of hunger despite recent increases has been falling for decades (Barrett et al. 2020, 2022). Nevertheless, sustained productivity growth is challenged, with evidence suggesting that agricultural productivity growth is slowing (Fuglie 2018b) and that it is getting harder to develop groundbreaking innovations (Bloom et al. 2020; Chu and Evans 2021; Park, Leahey, and Funk 2023), while climate change is eroding past gains (Mbow, Rosenzweig, et al. 2019).
All innovations, revolutionary or incremental, come with unintended consequences (Merton 1936; Baert 1991), which can be both positive and negative. The industrialization of food systems has been accompanied by many undesired consequences, including unbalanced and unhealthy diets and unsustainable environmental practices (IPBES 2019; IPCC 2019; Swinburn et al. 2019; Willett et al. 2019).
Innovations are needed to help respond to these undesired outcomes, including development of more climate-resilient agriculture, as well as a shift toward more holistic approaches to food systems that consider the social, environmental, and health consequences of innovation. The call for a “Great Food System Transformation” (Vermeulen et al. 2020; Béné 2022) highlights the need for more responsible or mission-oriented innovation in food systems, to more systematically consider power dynamics and potential unintended consequences to better assess potential winners and losers. Reviews of historical food system innovations have highlighted that successful adoption of innovations requires a range of social processes, such as establishing permission, developing a fostering enabling environment, and enacting active and adaptive policies in the face of unintended consequences (Thornton et al. 2024). This suggests that future innovation will need to more intentionally embed social processes in the technological development process to contribute to more sustainable food systems (Barrett et al. 2022). Figure 1 highlights a framework for accelerating more responsible innovation that identified 10 accelerators and enablers for food systems innovation.
Figure 1: Accelerators and enablers of innovation
Source: Mason-D’Croz et al. (2023), adapted from Herrero et al. (2020, 2021).
Recent policy shifts toward more activist industrial policy (Aiginger and Rodrik 2020) offer new potential opportunities for more mission-oriented research and development (R&D). However, without an intentional approach to innovation policy and a rebalancing of the food system to align incentives with desired environmental, social, and health outcomes—for example, True Costing of Food (Baker et al. 2020; FAO 2023; Kennedy et al. 2023)—increased public sector involvement in the innovation process will not ensure that future innovation contributes to healthier and more sustainable food systems.
What is the latest foresight research on food systems innovations?
Food systems innovation is a complex sociotechnical process. Foresight research focusing on food systems innovation seeks to better understand how these processes function and could be improved, as well as how their outcomes can contribute to positive and/or negative change. Much of the research assessing the potential of food systems innovation focuses on assessing specific technologies (or combinations of technologies) or the consequences of novel policies. Additionally, a growing body of literature considers how sociocultural changes can alter consumer preferences as well as paradigms of what is valued by society. Figure 2 summarizes some of the broad areas of foresight research focused on food systems innovation.
Figure 2: Examples of food systems innovation foresight research
Selection of sources:
- Baker and Shittu 2008; Dietrich et al. 2014; Hong et al. 2014.
- Rosegrant et al. 2017; Mason-D’Croz et al. 2019; Sulser et al. 2021.
- Nordmann 2014; Hall and Dijkman 2019; Conti et al. 2024.
- Gerhardt et al. 2020; Humpenöder, Bodirsky, et al. 2022; Mason-D’Croz et al. 2022; Kozicka et al. 2023; UNEP 2023.
- Sulser et al. 2010; Rosegrant et al. 2014; Ignaciuk, Mason-D’Croz, and Islam 2015; Robinson et al. 2015; Islam et al. 2016.
- Havlík et al. 2014; Frank et al. 2017, 2018.
- Parodi et al. 2018; Selm et al. 2022.
- Springmann et al. 2017; Springmann, Mason-D’Croz, et al. 2018; Laborde et al. 2021; Springmann and Freund 2022.
- Siriwardana, Meng, and McNeill 2017; Bellora and Fontagné 2020; Janssens et al. 2022.
- Cohn et al. 2014; Dixon et al. 2016; Tabeau et al. 2017; Henderson et al. 2018; Roe et al. 2021; Humpenöder, Popp, et al. 2022.
- Debucquet et al. 2016; Chichaibelu et al. 2021.
- Stehfest et al. 2009; Springmann et al. 2016; Searchinger et al. 2018; Springmann, Clark, et al. 2018; Eker, Reese, and Obersteiner 2019; Willett et al. 2019; Humpenöder et al. 2024.
- Bodirsky et al. 2022; Li et al. 2023.
The spatial scale of foresight analysis can range from the individual/firm level to the global level. More microanalysis has tended to focus primarily on private benefits and costs and the adoption process, exploring questions of how and why individuals and firms choose to adopt new technologies and practices. Various methods are applied in this area including agent-based (for example, Bell 2017; Giabbanelli and Crutzen 2017; Kaaronen and Strelkovskii 2020; Marvuglia et al. 2022) and system dynamic models (for example, Dizyee, Baker, and Rich 2017; Francesca Varia et al. 2017; Dizyee et al. 2021). More macro studies tend to explore somewhat different questions, focusing on questions of R&D investment (for example, Mason-D’Croz et al. 2019) or policies to encourage more innovation (for example, Sodano 2019; Moberg et al. 2021). Some studies explore the role of various actors in the innovation ecosystem (for example, National Agricultural Research Systems (NARS) vs CGIAR), often with a goal of better understanding the process of technology diffusion (for example, Aghion and Jaravel 2015; Fuglie 2018a). This work often implicitly frames technology in terms of Pareto efficiency (that is, adopted innovations move the technological frontier out, or help to move us closer to the frontier), and that knowledge generation occurs in core countries nearest the technological frontier, with catchup and diffusion assumed for peripheral countries farther from this frontier. National and global studies also assess potential unintended consequences of adoption at scale, particularly with respect to negative environmental or social consequences (for example, UNEP 2023).
The scope of innovation foresight research can be sector-specific or economywide. Economywide analysis allows for assessing potential spillover effects from one sector to another, spurring economic growth more broadly, but the wider scope of analysis tends to come with more stylized representation of innovations.
What are key gaps, questions, and opportunities for further foresight research on this topic?
Predicting future groundbreaking innovations is impossible (King and Baatartogtokh 2015; Fink et al. 2017; Hall and Dijkman 2019; FAO 2022; Thornton et al. 2024), but growing calls for a food system transformation (Webb et al. 2020) and the need for responsible (Nordmann 2014; Brier et al. 2020) and mission-oriented innovation (Klerkx and Begemann 2020) highlight a critical role for foresight research. Such research will be fundamental to helping better orient the application of science to solving critical environmental, economic, and human wellbeing challenges, while emphasizing the potential undesired consequences of transformation.
While improvements in modeling capability and data collection on innovation (including how to apply artificial intelligence approaches) are critical to improve our understanding of the process of innovation as well as its consequences, we focus our key gaps on research and scenario design. To date, much of foresight analysis on food systems innovation has focused on “What If” questions to consider the impacts of the wide-scale adoption of an innovation, for example: What if alternative proteins displaced conventional meat?; What if investments in R&D increased?; or What if a paradigm shift led to healthy diets? This valuable first step helps to highlight potential innovations worthy of consideration and investment, but leaves several key questions unanswered, as follows.
- How do innovations compete with and complement each other? The innovation ecosystem is highly dynamic and volatile. Yet most foresight studies explore individual innovations as one-offs or, if in a bundle, in a very stylized way. Relatively limited exploration exists of how innovations coevolve, and what these implications might mean for designing bundles of innovations and appropriate policies.
- What is the theory of change? Relatively few foresight studies have explored in detail innovation and transition roadmaps, instead focusing more on the ends than the means. However, historical experience reveals that the impacts of innovations are path-dependent, and the sociotechnical interface of adoption and obsolescence largely determines the winners and losers of innovation. Exploring such roadmaps will require greater engagement with multiscale and multidisciplinary research to better understand how innovation processes scale and diffuse. It also will require developing or adapting new modelling tools to simulating plausible pathways across relevant time and spatial scales.
- What role can low- and middle-income countries (LMICs) play in spurring innovation? Technology development and diffusion is represented too simplistically (that is, core-periphery and Pareto efficiency), with novel technologies developed predominantly in advanced economies and then spread to the rest of the world. Foresight research needs to consider more pluralistic futures (Mangnus et al. 2019), reexamining what is meant by progress in varying regional and cultural contexts (Ritzer 2003; Pereira et al. 2021). It should explore how innovation processes can be started in LMICs and potentially spread to high-income countries (for example, frugal innovation is needed (Hossain, Simula, and Halme 2016)).
- Can we build consensus on desirable futures? Food systems are complex and fractal. Micro and macro analyses highlight the fundamental complexity and unknowability of the whole system. Nevertheless, foresight approaches can help to highlight different stakeholder perspectives and facilitate dialogue across alternative and potentially competing visions of the future (for example, group-based model building (Gerritsen et al. 2020; Anastasiou et al. 2023) or participatory scenarios (Chaudhury et al. 2013; Mason-D’Croz et al. 2016; Aguiar et al. 2020)), a critical first step for collective action.
Answering these questions requires developing more nuanced scenarios that simulate the innovation process in a less linear fashion. Greater application of foresight methods such as backcasting (Holmberg and Robert 2000; Robinson 2003) and 3-horizons (Sharpe et al. 2016) could help enrich scenario development that feeds into quantitative analyses of food systems innovation. This will provide not just a quantification of an endpoint, but of the pathway between the present and an alternative future. It should also incorporate growing literature on innovation readiness and scaling (Herrero et al. 2020; Sartas et al. 2020; List 2022; Woltering et al. 2024). Achieving this will require broader and larger scenario sets and a wider range of foresight models to better capture key relationships and feedbacks, learning and expanding on previous multimodel efforts not only to understand model uncertainty (Nelson et al. 2014), but to allow representation of a wider range of behaviors described in these more pluralistic scenarios. Failing to do this will reduce the applicability of future foresight research to inform strategic decision-making, such as in the design of innovation bundles (that is, prioritization and investment).
This note was prepared by Daniel Mason-D’Croz, Senior Research Associate, Cornell Global Development, and PhD candidate with Agricultural Economics and Rural Policy Group, Wageningen University and Research; Mario Herrero, Professor, Cornell Atkinson Scholar, and Nancy and Peter Meinig Family Investigator in the Life Sciences, Department of Global Development, Cornell University; Cody Kugler, Independent consultant, formerly agri-food innovations project manager for Food Systems & Global Change research group, Cornell University; Rosaline Remans, Honorary Research Fellow, The Alliance of Bioversity International and the International Center for Tropical Agriculture (CIAT); Philip Thornton, Emeritus Fellow, International Livestock Research Institute (ILRI), Research and Innovation Strategist with Clim-Eat, and an Honorary Professor in the School of Geosciences, University of Edinburgh; Heather Zornetzer, Coordinator of the Innovative Food System Solutions (IFSS) Portal, The Alliance of Bioversity International and CIAT.
If you have any feedback or questions about this note, please contact Daniel Mason-D’Croz (dem286@cornell.edu).
References
Aghion, P. and Jaravel, X. (2015) ‘Knowledge Spillovers, Innovation and Growth’, The Economic Journal, 125(583), pp. 533–573. Available at: https://doi.org/10.1111/ecoj.12199.
Aguiar, A.P.D. et al. (2020) ‘Co-designing global target-seeking scenarios: A cross-scale participatory process for capturing multiple perspectives on pathways to sustainability’, Global Environmental Change, 65, p. 102198. Available at: https://doi.org/10.1016/j.gloenvcha.2020.102198.
Aiginger, K. and Rodrik, D. (2020) ‘Rebirth of Industrial Policy and an Agenda for the Twenty-First Century’, Journal of Industry, Competition and Trade, 20(2), pp. 189–207. Available at: https://doi.org/10.1007/s10842-019-00322-3.
Anastasiou, K. et al. (2023) ‘Conceptualising the drivers of ultra-processed food production and consumption and their environmental impacts: A group model-building exercise’, Global Food Security, 37, p. 100688. Available at: https://doi.org/10.1016/j.gfs.2023.100688.
Baert, P. (1991) ‘Unintended Consequences: A Typology and Examples’, International Sociology, 6(2), pp. 201–210. Available at: https://doi.org/10.1177/026858091006002006.
Baker, E. and Shittu, E. (2008) ‘Uncertainty and endogenous technical change in climate policy models’, Energy Economics, 30(6), pp. 2817–2828. Available at: https://doi.org/10.1016/j.eneco.2007.10.001.
Baker, L. et al. (2020) ‘Prospects for the true cost accounting of food systems’, Nature Food, 1(12), pp. 765–767. Available at: https://doi.org/10.1038/s43016-020-00193-6.
Barrett, C.B. et al. (2020) ‘Bundling innovations to transform agri-food systems’, Nature Sustainability, 3(12), pp. 974–976. Available at: https://doi.org/10.1038/s41893-020-00661-8.
Barrett, C.B. et al. (2022) Socio-Technical Innovation Bundles for Agri-Food Systems Transformation. Cham: Springer International Publishing. Available at: https://doi.org/10.1007/978-3-030-88802-2.
Bell, A.R. (2017) ‘Informing decisions in agent-based models — A mobile update’, Environmental Modelling & Software, 93, pp. 310–321. Available at: https://doi.org/10.1016/j.envsoft.2017.03.028.
Bellora, C. and Fontagné, L. (2020) Carbon Border Adjustment and Alternatives. CEPII.
Béné, C. (2022) ‘Why the Great Food Transformation may not happen – A deep-dive into our food systems’ political economy, controversies and politics of evidence’, World Development, 154, p. 105881. Available at: https://doi.org/10.1016/j.worlddev.2022.105881.
Bloom, N. et al. (2020) ‘Are Ideas Getting Harder to Find?’, American Economic Review, 110(4), pp. 1104–1144. Available at: https://doi.org/10.1257/aer.20180338.
Bodirsky, B.L. et al. (2022) ‘Integrating degrowth and efficiency perspectives enables an emission-neutral food system by 2100’, Nature Food, 3(5), pp. 341–348. Available at: https://doi.org/10.1038/s43016-022-00500-3.
Brier, D. et al. (2020) ‘Foresighting for Responsible Innovation Using a Delphi Approach: A Case Study of Virtual Fencing Innovation in Cattle Farming’, Journal of Agricultural and Environmental Ethics, 33(3–6), pp. 549–569. Available at: https://doi.org/10.1007/s10806-020-09838-9.
Chaudhury, M. et al. (2013) ‘Participatory scenarios as a tool to link science and policy on food security under climate change in East Africa’, Regional Environmental Change, 13(2), pp. 389–398. Available at: https://doi.org/10.1007/s10113-012-0350-1.
Chichaibelu, B.B. et al. (2021) ‘The global cost of reaching a world without hunger: Investment costs and policy action opportunities’, Food Policy, 104, p. 102151. Available at: https://doi.org/10.1016/j.foodpol.2021.102151.
Chu, J.S.G. and Evans, J.A. (2021) ‘Slowed canonical progress in large fields of science’, Proceedings of the National Academy of Sciences, 118(41), p. e2021636118. Available at: https://doi.org/10.1073/pnas.2021636118.
Cohn, A.S. et al. (2014) ‘Cattle ranching intensification in Brazil can reduce global greenhouse gas emissions by sparing land from deforestation’, Proceedings of the National Academy of Sciences, 111(20), pp. 7236–7241. Available at: https://doi.org/10.1073/pnas.1307163111.
Conti, C. et al. (2024) ‘What does the agri-food systems transformation agenda mean for agricultural research organisations? Exploring organisational prototypes for uncertain futures’, Global Food Security, 40, p. 100733. Available at: https://doi.org/10.1016/j.gfs.2023.100733.
Debucquet, D.L. et al. (2016) Ending hunger: What would it cost? International Institute for Sustainable Development. Available at: http://ebrary.ifpri.org/cdm/singleitem/collection/p15738coll5/id/5532/rec/17.
Dietrich, J.P. et al. (2014) ‘Forecasting technological change in agriculture—An endogenous implementation in a global land use model’, Technological Forecasting and Social Change, 81, pp. 236–249. Available at: https://doi.org/10.1016/j.techfore.2013.02.003.
Dixon, P.B. et al. (2016) ‘RED versus REDD: Biofuel policy versus forest conservation’, Economic Modelling, 52, pp. 366–374. Available at: https://doi.org/10.1016/j.econmod.2015.09.014.
Dizyee, K. et al. (2021) Regional integrated livestock value chain simulation model for economic, equity, and environment policy assessment. ILRI Research Report 93. Nairobi, Kenya: ILRI. Available at: https://cgspace.cgiar.org/server/api/core/bitstreams/38a5e353-d20b-45f1-b7c9-6084647ff034/content (Accessed: 16 July 2024).
Dizyee, K., Baker, D. and Rich, K.M. (2017) ‘A quantitative value chain analysis of policy options for the beef sector in Botswana’, Agricultural Systems, 156, pp. 13–24. Available at: https://doi.org/10.1016/j.agsy.2017.05.007.
Eker, S., Reese, G. and Obersteiner, M. (2019) ‘Modelling the drivers of a widespread shift to sustainable diets’, Nature Sustainability [Preprint]. Available at: https://doi.org/10.1038/s41893-019-0331-1.
FAO (2022) Introducing the Agrifood Systems Technologies and Innovations Outlook (ATIO). FAO. Available at: https://doi.org/10.4060/cc2506en.
FAO (2023) The State of Food and Agriculture 2023: Revealing the true cost of food to transform agrifood systems. Rome, Italy: FAO (The State of Food and Agriculture (SOFA), 2023). Available at: https://doi.org/10.4060/cc7724en.
Fink, T.M.A. et al. (2017) ‘Serendipity and strategy in rapid innovation’, Nature Communications, 8(1), p. 2002. Available at: https://doi.org/10.1038/s41467-017-02042-w.
Francesca Varia et al. (2017) ‘System dynamics model to design effective policy strategies aiming at fostering the adoption of conservation agriculture practices in sicily’, Chemical Engineering Transactions, 58, pp. 763–768. Available at: https://doi.org/10.3303/CET1758128.
Frank, S. et al. (2017) ‘Reducing greenhouse gas emissions in agriculture without compromising food security?’, Environmental Research Letters, 12(10), p. 105004. Available at: https://doi.org/10.1088/1748-9326/aa8c83.
Frank, S. et al. (2018) ‘Structural change as a key component for agricultural non-CO2 mitigation efforts’, Nature Communications, 9(1), p. 1060. Available at: https://doi.org/10.1038/s41467-018-03489-1.
Fuglie, K. (2018a) ‘R&D Capital, R&D Spillovers, and Productivity Growth in World Agriculture’, Applied Economic Perspectives and Policy, 40(3), pp. 421–444. Available at: https://doi.org/10.1093/aepp/ppx045.
Fuglie, K.O (2018b) ‘Is agricultural productivity slowing?’, Global Food Security, 17, pp. 73–83. Available at: https://doi.org/10.1016/j.gfs.2018.05.001.
Gerhardt, C. et al. (2020) ‘How Will Cultured Meat and Meat Alternatives Disrupt the Agricultural and Food Industry?’, Industrial Biotechnology, 16(5), pp. 262–270. Available at: https://doi.org/10.1089/ind.2020.29227.cge.
Gerritsen, S. et al. (2020) ‘Community Group Model Building as a Method for Engaging Participants and Mobilising Action in Public Health’, International Journal of Environmental Research and Public Health, 17(10), p. 3457. Available at: https://doi.org/10.3390/ijerph17103457.
Giabbanelli, P.J. and Crutzen, R. (2017) ‘Using Agent-Based Models to Develop Public Policy about Food Behaviours: Future Directions and Recommendations’, Computational and Mathematical Methods in Medicine, 2017, pp. 1–12. Available at: https://doi.org/10.1155/2017/5742629.
Gollin, D., Parente, S. and Rogerson, R. (2002) ‘The Role of Agriculture in Development’, American Economic Review, 92(2), pp. 160–164. Available at: https://doi.org/10.1257/000282802320189177.
Hall, A. and Dijkman, J. (2019) Public Agricultural Research in an Era of Transformation: The Challenge of Agri-Food System Innovation. Rome and Canberra: CGIAR ISPC Secretariat and CSIRO, p. 67. Available at: https://iaes.cgiar.org/isdc/publications/public-agricultural-research-era-transformation-challenge-agri-food-system.
Havlík, P. et al. (2014) ‘Climate change mitigation through livestock system transitions’, Proceedings of the National Academy of Sciences, 111(10), pp. 3709–3714. Available at: https://doi.org/10.1073/pnas.1308044111.
Henderson, B. et al. (2018) ‘The power and pain of market-based carbon policies: a global application to greenhouse gases from ruminant livestock production’, Mitigation and Adaptation Strategies for Global Change, 23(3), pp. 349–369. Available at: https://doi.org/10.1007/s11027-017-9737-0.
Herrero, M. et al. (2020) ‘Innovation can accelerate the transition towards a sustainable food system’, Nature Food, 1(5), pp. 266–272. Available at: https://doi.org/10.1038/s43016-020-0074-1.
Herrero, M. et al. (2021) ‘Articulating the effect of food systems innovation on the Sustainable Development Goals’, The Lancet Planetary Health, 5(1), pp. e50–e62. Available at: https://doi.org/10.1016/S2542-5196(20)30277-1.
Holmberg, J. and Robert, K.H. (2000) ‘Backcasting — a framework for strategic planning’, International Journal of Sustainable Development & World Ecology, 7(4), pp. 291–308. Available at: https://doi.org/10.1080/13504500009470049.
Hong, C. et al. (2014) ‘Validation of an R&D-based computable general equilibrium model’, Economic Modelling, 42, pp. 454–463. Available at: https://doi.org/10.1016/j.econmod.2014.07.014.
Hossain, M., Simula, H. and Halme, M. (2016) ‘Can frugal go global? Diffusion patterns of frugal innovations’, Technology in Society, 46, pp. 132–139. Available at: https://doi.org/10.1016/j.techsoc.2016.04.005.
Humpenöder, F., Popp, A., et al. (2022) ‘Overcoming global inequality is critical for land-based mitigation in line with the Paris Agreement’, Nature Communications, 13(1), p. 7453. Available at: https://doi.org/10.1038/s41467-022-35114-7.
Humpenöder, F., Bodirsky, B.L., et al. (2022) ‘Projected environmental benefits of replacing beef with microbial protein’, Nature 2022 605:7908, 605(7908), pp. 90–96. Available at: https://doi.org/10.1038/s41586-022-04629-w.
Humpenöder, F. et al. (2024) ‘Food matters: Dietary shifts increase the feasibility of 1.5°C pathways in line with the Paris Agreement’, Science Advances, 10(13), p. eadj3832. Available at: https://doi.org/10.1126/sciadv.adj3832.
Ignaciuk, A., Mason-D’Croz, D. and Islam, S. (2015) ‘Better Drip than Flood: Reaping the Benefits of Efficient Irrigation’, EuroChoices, 14(2), pp. 26–32. Available at: https://doi.org/10.1111/1746-692X.12088.
IPBES (2019) Global assessment report on biodiversity and ecosystem services of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services. Available at: https://doi.org/10.5281/ZENODO.3831673.
IPCC (2019) Climate Change and Land: an IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems. Edited by P.R. Shukla et al. Interngovernmental Panel on Climate Change.
Islam, S. et al. (2016) ‘Structural approaches to modeling the impact of climate change and adaptation technologies on crop yields and food security’, Global Food Security, 10, pp. 63–70. Available at: https://doi.org/10.1016/j.gfs.2016.08.003.
Janssens, C. et al. (2022) ‘A sustainable future for Africa through continental free trade and agricultural development’, Nature Food, 3(8), pp. 608–618. Available at: https://doi.org/10.1038/s43016-022-00572-1.
Kaaronen, R.O. and Strelkovskii, N. (2020) ‘Cultural Evolution of Sustainable Behaviors: Pro-environmental Tipping Points in an Agent-Based Model’, One Earth, 2(1), pp. 85–97. Available at: https://doi.org/10.1016/j.oneear.2020.01.003.
Kennedy, E.T. et al. (2023) ‘Beyond the Food Systems Summit: Linking Recommendations to Action—The True Cost of Food’, Current Developments in Nutrition, 7(5), p. 100028. Available at: https://doi.org/10.1016/j.cdnut.2023.100028.
King, A.A. and Baatartogtokh, B. (2015) ‘How useful is the theory of disruptive innovation?’, MIT Sloan Management Review, 57(1), pp. 77–90. Available at: https://sloanreview.mit.edu/article/how-useful-is-the-theory-of-disruptive-innovation/.
Klerkx, L. and Begemann, S. (2020) ‘Supporting food systems transformation: The what, why, who, where and how of mission-oriented agricultural innovation systems’, Agricultural Systems, 184, p. 102901. Available at: https://doi.org/10.1016/j.agsy.2020.102901.
Kozicka, M. et al. (2023) ‘Feeding climate and biodiversity goals with novel plant-based meat and milk alternatives’, Nature Communications, 14(1), p. 5316. Available at: https://doi.org/10.1038/s41467-023-40899-2.
Laborde, D. et al. (2021) ‘Agricultural subsidies and global greenhouse gas emissions’, Nature Communications, 12(1), p. 2601. Available at: https://doi.org/10.1038/s41467-021-22703-1.
Li, M. et al. (2023) ‘Integrated assessment modelling of degrowth scenarios for Australia’, Economic Systems Research, 0(0), pp. 1–31. Available at: https://doi.org/10.1080/09535314.2023.2245544.
List, J.A. (2022) The Voltage Effect: How to Make Good Ideas Great and Great Ideas Scale. Crown Currency.
Loboguerrero, A.M. et al. (2020) ‘Perspective article: Actions to reconfigure food systems’, Global Food Security, 26, p. 100432. Available at: https://doi.org/10.1016/j.gfs.2020.100432.
Mangnus, A.C. et al. (2019) ‘New pathways for governing food system transformations: a pluralistic practice-based futures approach using visioning, back-casting, and serious gaming’, Ecology and Society, 24(4), p. art2. Available at: https://doi.org/10.5751/ES-11014-240402.
Marvuglia, A. et al. (2022) ‘Agent-based modelling to simulate farmers’ sustainable decisions: Farmers’ interaction and resulting green consciousness evolution’, Journal of Cleaner Production, 332, p. 129847. Available at: https://doi.org/10.1016/j.jclepro.2021.129847.
Mason-D’Croz, D. et al. (2016) ‘Multi-factor, multi-state, multi-model scenarios: Exploring food and climate futures for Southeast Asia’, Environmental Modelling & Software, 83, pp. 255–270. Available at: https://doi.org/10.1016/j.envsoft.2016.05.008.
Mason-D’Croz, D. et al. (2019) ‘Agricultural investments and hunger in Africa modeling potential contributions to SDG2 – Zero Hunger’, World Development, 116, pp. 38–53. Available at: https://doi.org/10.1016/j.worlddev.2018.12.006.
Mason-D’Croz, D. et al. (2022) ‘Ethical and economic implications of the adoption of novel plant-based beef substitutes in the USA: a general equilibrium modelling study’, The Lancet Planetary Health, 6(8), pp. e658–e669. Available at: https://doi.org/10.1016/S2542-5196(22)00169-3.
Mason-D’Croz, D. et al. (2023) Wild Futures – Innovations for Food Systems Transformations: Project Summary Report. Project Report. Ithaca, NY: Cornell Food Systems and Global Change.
Mbow, C., Rosenzweig, C., and et al. (2019) ‘Chapter 5 : Food Security — Special Report on Climate Change and Land’, in Climate Change and Land: An IPCC Special Report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems. Available at: https://www.ipcc.ch/srccl/chapter/chapter-5/ (Accessed: 25 July 2023).
Merton, R.K. (1936) ‘The Unanticipated Consequences of Purposive Social Action’, American Sociological Review, 1(6), p. 894. Available at: https://doi.org/10.2307/2084615.
Moberg, E. et al. (2021) ‘Combined innovations in public policy, the private sector and culture can drive sustainability transitions in food systems’, Nature Food, 2(4), pp. 282–290. Available at: https://doi.org/10.1038/s43016-021-00261-5.
Nelson, G.C. et al. (2014) ‘Climate change effects on agriculture: Economic responses to biophysical shocks’, Proceedings of the National Academy of Sciences, 111(9), pp. 3274–3279. Available at: https://doi.org/10.1073/pnas.1222465110.
Nordmann, A. (2014) ‘Responsible innovation, the art and craft of anticipation’, Journal of Responsible Innovation, 1(1), pp. 87–98. Available at: https://doi.org/10.1080/23299460.2014.882064.
Park, M., Leahey, E. and Funk, R.J. (2023) ‘Papers and patents are becoming less disruptive over time’, Nature, 613(7942), pp. 138–144. Available at: https://doi.org/10.1038/s41586-022-05543-x.
Parodi, A. et al. (2018) ‘The potential of future foods for sustainable and healthy diets’, Nature Sustainability, 1(12), pp. 782–789. Available at: https://doi.org/10.1038/s41893-018-0189-7.
Pereira, L. et al. (2021) ‘Grounding global environmental assessments through bottom-up futures based on local practices and perspectives’, Sustainability Science, 1, pp. 1–16. Available at: https://doi.org/10.1007/s11625-021-01013-x.
Ritzer, G. (2003) ‘Rethinking Globalization: Glocalization/Grobalization and Something/Nothing’, Sociological Theory, 21(3), pp. 193–209. Available at: https://doi.org/10.1111/1467-9558.00185.
Robinson, J. (2003) ‘Future subjunctive: backcasting as social learning’, Futures, 35(8), pp. 839–856. Available at: https://doi.org/10.1016/S0016-3287(03)00039-9.
Robinson, S. et al. (2015) Climate Change Adaptation in Agriculture: Ex Ante Analysis of Promising and Alternative Crop Technologies Using DSSAT and IMPACT. International Food Policy Research Institute.
Roe, S. et al. (2021) ‘Land‐based measures to mitigate climate change: Potential and feasibility by country’, Global Change Biology, 27(23), pp. 6025–6058. Available at: https://doi.org/10.1111/gcb.15873.
Rosegrant, M.W. et al. (2014) Food Security in a World of Natural Resource Scarcity, Monographs of the Society for Research in Child Development. Available at: https://doi.org/10.1111/mono.12084.
Rosegrant, M.W. et al. (2017) Quantitative foresight modeling to inform the CGIAR research portfolio. Available at: http://ebrary.ifpri.org/cdm/singleitem/collection/p15738coll2/id/131144.
Sartas, M. et al. (2020) ‘Scaling Readiness: Science and practice of an approach to enhance impact of research for development’, Agricultural Systems, 183, p. 102874. Available at: https://doi.org/10.1016/j.agsy.2020.102874.
Searchinger, T. et al. (2018) Creating a Sustainable Food Future. A Menu of solutions to feed nearly 10 billion people by 2050: Synthesis Report Dec 2018, World Resources Report. World Resources Institute, p. 96. Available at: https://www.wri.org/our-work/project/world-resources-report/publications.
Selm, B. van et al. (2022) ‘Circularity in animal production requires a change in the EAT-Lancet diet in Europe’, Nature Food, 3(1), pp. 66–73. Available at: https://doi.org/10.1038/s43016-021-00425-3.
Sharpe, B. et al. (2016) ‘Three horizons: a pathways practice for transformation’, Ecology and Society, 21(2), p. art47. Available at: https://doi.org/10.5751/ES-08388-210247.
Siriwardana, M., Meng, S. and McNeill, J. (2017) ‘Border adjustments under unilateral carbon pricing: the case of Australian carbon tax’, Journal of Economic Structures, 6(1), p. 34. Available at: https://doi.org/10.1186/s40008-017-0091-x.
Sodano, V. (2019) ‘Innovation Trajectories and Sustainability in the Food System’, Sustainability, 11(5), p. 1271. Available at: https://doi.org/10.3390/su11051271.
Springmann, M. et al. (2016) ‘Global and regional health effects of future food production under climate change: a modelling study’, The Lancet, 387(10031), pp. 1937–1946. Available at: https://doi.org/10.1016/S0140-6736(15)01156-3.
Springmann, M. et al. (2017) ‘Mitigation potential and global health impacts from emissions pricing of food commodities’, Nature Climate Change, 7(1), pp. 69–74. Available at: https://doi.org/10.1038/nclimate3155.
Springmann, M., Mason-D’Croz, D., et al. (2018) ‘Health-motivated taxes on red and processed meat: A modelling study on optimal tax levels and associated health impacts’, PLOS ONE. Edited by B. Shankar, 13(11), p. e0204139. Available at: https://doi.org/10.1371/journal.pone.0204139.
Springmann, M., Clark, M., et al. (2018) ‘Options for keeping the food system within environmental limits’, Nature, 562(7728), pp. 519–525. Available at: https://doi.org/10.1038/s41586-018-0594-0.
Springmann, M. and Freund, F. (2022) ‘Options for reforming agricultural subsidies from health, climate, and economic perspectives’, Nature Communications, 13(1), p. 82. Available at: https://doi.org/10.1038/s41467-021-27645-2.
Stehfest, E. et al. (2009) ‘Climate benefits of changing diet’, Climatic change, 95(1–2), pp. 83–102.
Sulser, T. et al. (2021) Climate Change and hunger: Estimating costs of adaptation in the agrifood system. International Food Policy Research Institute. Available at: https://doi.org/10.2499/9780896294165.
Sulser, T.B. et al. (2010) ‘Green and blue water accounting in the Ganges and Nile basins: Implications for food and agricultural policy’, Journal of Hydrology, 384(3–4), pp. 276–291. Available at: https://doi.org/10.1016/j.jhydrol.2009.10.003.
Swinburn, B.A. et al. (2019) ‘The Global Syndemic of Obesity, Undernutrition, and Climate Change: The Lancet Commission report’, The Lancet, 393(10173), pp. 791–846. Available at: https://doi.org/10.1016/S0140-6736(18)32822-8.
Tabeau, A. et al. (2017) ‘REDD policy impacts on the agri-food sector and food security’, Food Policy, 66, pp. 73–87. Available at: https://doi.org/10.1016/j.foodpol.2016.11.006.
Thornton, P. et al. (2024) ‘Enabling food system innovation: accelerators for change’, Global Food Security, 40, p. 100738. Available at: https://doi.org/10.1016/j.gfs.2023.100738.
UNEP (2023) Frontiers 2023. What’s Cooking? An assessment of the potential impacts of selected novel alternatives to conventional animal products. United Nations Environment Programme. Available at: https://doi.org/10.59117/20.500.11822/44236.
Vermeulen, S.J. et al. (2020) ‘Changing diets and the transformation of the global food system’, Annals of the New York Academy of Sciences, 1478(1), pp. 3–17. Available at: https://doi.org/10.1111/nyas.14446.
Webb, P. et al. (2020) ‘The urgency of food system transformation is now irrefutable’, Nature Food, 1(10), pp. 584–585. Available at: https://doi.org/10.1038/s43016-020-00161-0.
Willett, W. et al. (2019) ‘Food in the Anthropocene: the EAT–Lancet Commission on healthy diets from sustainable food systems’, The Lancet, 393(10170), pp. 447–492. Available at: https://doi.org/10.1016/S0140-6736(18)31788-4.
Woltering, L. et al. (2024) ‘Supporting a systems approach to scaling for all; insights from using the Scaling Scan tool’, Agricultural Systems, 217, p. 103927. Available at: https://doi.org/10.1016/j.agsy.2024.103927
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