The DOI matches its Crossref record; 96 of the 101 references it cites were found in a registry or an index.
Digital innovation ecosystems in agri-food: design principles and organizational framework
Open accessAbstract
Digital technologies nowadays play a major role in innovation within the agri-food domain. The evolution of IT systems has currently arrived at a level that involves complex systems integration and business ecosystems in which many stakeholders in different roles are involved. A new paradigm for digital innovation is needed that copes with this increased complexity. This paper presents an empirically informed framework for analysing and designing viable, sustainable digital innovation ecosystems in the agri-food domain. The research is based on a series of European large-scale public-private innovation projects from 2011 to 2021 with a total budget of 73 M€. They involved hundreds of stakeholders that were developing a large number of digital solutions through which a digital innovation ecosystem for agri-food was formed. In a longitudinal study, a conceptual framework was used to analyse these projects and describe how the digital innovation ecosystem has developed. Lessons learnt are translated into a number of design principles and an organizational approach to foster digital innovation ecosystems in agri-food. The conceptual framework consists of 6 key concepts: (i) innovation strategy, (ii) innovation organization, (iii) innovation network that contains (iv) the innovation process and (v) the innovation object and finally (vi) an innovation infrastructure. Along these 6 concepts, lessons learnt and in total 21 design principles are derived from analysing the projects forming a basis for the organizational framework. At the core of this framework is a lean multi-actor approach to trials and use case development interacting with a set of multidisciplinary activities: (i) developing a common technical collaboration infrastructure, (ii) identifying value streams with user engagement, (iii) engaging the right partners and stakeholders at the right time supported by strategic project planning and dynamic management. The most important conclusion is that effective, successful and quick use of appropriate IT in agri-food requires that actors should not be analysed in isolation from both their technological and business environment. Another consequence is that a ‘minimal viable ecosystem’ only emerges after considerable time, resources and ingenuity is invested and may require outside (government) intervention. Results from this paper can be used both by public and private stakeholders to diagnose and improve digital innovation projects and develop viable, sustainable digital innovation ecosystems in agri-food.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“food design operates across all stages of the food production process—from cultivation to consumption and disposal—to overcome bottlenecks, spark innovation, and add value via a human-centered approach (Wolfert et al., 2023).”
From Microalgae biotechnology and its role in sustainable and healthy food design (2025) · cites this paper as Wolfert et al., 2023
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Building Theories from Case Study Research
Eisenhardt, K. M. (1989) · The Academy of Management Review · doi:10.2307/258557 · Cited by 17,455
Design Science in Information Systems Research1
Hevner, A. R., March, S. T., Park, J., & Ram, S. (2004) · MIS Quarterly · doi:10.2307/25148625 · Cited by 10,707 · cited 1×
“Design-oriented research focuses on building purposeful artefacts that address heretofore unsolved problems and which are evaluated with respect to the utility provided in solving those problems (Hevner et al., 2004; March and Smith, 1995).”
BackgroundProcess innovation: reengineering work through information technology
(1993) · Choice Reviews Online · doi:10.5860/choice.30-4486 · Cited by 4,390
Big Data in Smart Farming – A review
Wolfert, J., Ge, L., Verdouw, C. N., & Bogaardt, M. J. (2017) · Agricultural Systems · doi:10.1016/j.agsy.2017.01.023 · Cited by 4,196
Self-citationOrganizations in Action: Social Science Bases of Administrative Theory.
Udy, S. H., & Thompson, J. D. (1968) · American Sociological Review · doi:10.2307/2092248 · Cited by 4,130
Design and natural science research on information technology
March, S. T., & Smith, G. F. (1995) · Decision Support Systems · doi:10.1016/0167-9236(94)00041-2 · Cited by 3,871
(2011) · Cited by 3,330
(1993) · PubMed · Cited by 3,302
Developing a framework for responsible innovation
Stilgoe, J., Owen, R., & Macnaghten, P. (2013) · Research Policy · doi:10.1016/j.respol.2013.05.008 · Cited by 3,184
Digital Transformation Strategies
Matt, C., Heß, T., & Benlian, A. (2015) · Business & Information Systems Engineering · doi:10.1007/s12599-015-0401-5 · Cited by 3,172
Research works printed but not linked: 3
- Adner, 2017, Ecosystem as structure: an actionable construct for strategy, J. Manag., 43, 39
- Rijswijk, 2019, Enacting digitalisation in AKIS: how New Zealand agricultural knowledge providers understand and respond to digital agriculture, NJAS-Wagen. J. Life Sci., 90
- Yin, 2003, Case study research design and methods third edition, 5
Cited by
Sorted by citations
Digital innovations for sustainable and resilient agricultural systems
Finger, R. (2023) · European Review of Agricultural Economics · doi:10.1093/erae/jbad021 · Cited by 402
Toader, D.-C., Rădulescu, C., & Toader, C. (2024) · Agriculture · doi:10.3390/agriculture14040614 · Cited by 61
Šestak, M., & Copot, D. (2023) · Sustainability · doi:10.3390/su151813746 · Cited by 55
Klerkx, L., & Villalobos, P. (2023) · Global Food Security · doi:10.1016/j.gfs.2023.100726 · Cited by 57
Self-citationLiao, H., Pan, C.-L., & Wu, Z. (2024) · International Journal of Innovation Studies · doi:10.1016/j.ijis.2024.04.003 · Cited by 38
Metadata
- Authors
- Wolfert, S., Verdouw, C., van Wassenaer, L., Dolfsma, W., & Klerkx, L.
- Affiliations
- Wageningen University & Research (NL)
- Universidad de Talca (CL)
- Venue
- Agricultural Systems
- Publisher
- Elsevier BV
- Published
- 2023-01
- Volume
- 204
- Pages
- 103558
- ISSN
- 0308-521X (ISSN-L)
- OpenAlex
- W4308174942
- Cited by
- 137
- References
- 101
- Citations by year
- 2026: 40 · 2025: 48 · 2024: 34 · 2023: 15
- FWCI
- 18.11
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Agricultural Systems (publishedVersion, cc-by)
- Socio-Environmental Systems Modeling (submittedVersion, cc-by)
- RePEc: Research Papers in Economics (submittedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion, cc-by)
- Funders
- European Commission (285326, 632861, HORIZON2020, 604123, 632874, 731884, 632857)
- Topics
- Social Sciences › Business, Management and Accounting › Strategy and Management › Digitalization and Economic Development in Agriculture
- Life Sciences › Agricultural and Biological Sciences › Plant Science › Smart Agriculture and AI
- Social Sciences › Business, Management and Accounting › Management of Technology and Innovation › Innovative Approaches in Technology and Social Development
- Keywords
- digital innovation ecosystems, agri-food, design principles, organizational framework, innovation strategy, innovation organization, innovation networks, innovation process, innovation infrastructure, stakeholder engagement, value stream, user engagement, multi-actor collaboration, state intervention, sustainable innovation
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review