Are AgriFoodTech start-ups the new drivers of food systems transformation? An overview of the state of the art and a research agenda
Laurens Klerkx, Pablo Villalobos
- 发表年份
- 2023
- 引用次数
- 37
摘要
AgriFoodTech start-ups are coming to be seen as relevant players in the debate around and reality of the transformation of food systems, especially in view of emerging or already-established novel technologies (such as Artifical Intelligence, Sensors, Precision Fermentation, Robotics, Nanotechnologies, Genomics) that constitute Agriculture 4.0 and Food 4.0. However, so far, there have only been limited studies of this phenomena, which are scattered across disciplines, with no comprehensive overview of the state of the art and outlook for future research. In this paper, we argue that AgriFoodTech start-up ecosystems should receive more attention by researchers and policy makers as a relatively new, and potentially transformative, component of agrifood innovation systems, which adopt a narrative of offering a solution to the global challenges of sustainability and food security. To this end we review the extant literature and provide a brief overview of this emerging field of study, in which we sketch what constitutes an AgriFoodTech start-up, the start-up ecosystems from which they often emerge and show the potentials and pitfalls of the contribution of AgriFoodTech start-ups to food security and food systems transformation. In order to spur further research in this area, we outline four main lines for a research agenda: 1) the global geography of AgriFoodTech start-up ecosystems; 2) the role of AgriFoodTech start-ups in different food system transformation pathways and resolving food security challenges; 3) the effect of AgriFoodTech start-ups on agrifood innovation, and; 4) the influence of public policies on AgriFoodTech start-up ecosystems.
关键词
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Fractional Differential Equations
Igor Podlubný
2025
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
Genetic Programming: On the Programming of Computers by Means of Natural Selection
John R. Koza
1992