Do Agricultural Knowledge and Innovation Systems Have the Dynamic Capabilities to Guide the Digital Transition of Short Food Supply Chains?

Do Agricultural Knowledge and Innovation Systems Have the Dynamic Capabilities to Guide the Digital Transition of Short Food Supply Chains? 1 2 3 4 * Information 2024 , 15 (1), 22; https://doi.org/10.3390/info15010022 (registering DOI) Abstract : 1. Introduction 2. Agricultural Knowledge and Innovation Systems in a Digitalized World: The Role of Dynamic Capabilities 3. Methods 4. Results 4.1. The Greek AKIS 4.1.1. Sensing Capacity “Big companies offering advisory services don’t even see farmers using short food supply chains to sell their products. They are not their target group. If you ask me whether they can search for opportunities, the answer is: definitely yes. Nevertheless, the right question here is: who can afford the cost of exploiting these opportunities?” (Antonis, Freelancer advisor). 4.1.2. Seizing Capacity and Transformational Capability “I’m not sure at all that they [advisors] can really help. They try to get rid of you by giving instructions that rarely work. Then, you have to contact the company that sells those things, hoping to find a solution.” 4.2. The Italian AKIS 4.2.1. Sensing Capacity “I did not even know about the existence of public consultants to support my activity. Is it really true that public advisors can help us?” (Alessandro, farmer). “Farmers need user-friendly digital solutions, which, at the same time, should take into account the heterogeneity of the farming sector. A possibly suitable digital solution for a certain farm may not fit well with other farms.” 4.2.2. Seizing Capacity and Transformational Capability 5. Discussion and Conclusions Author Contributions Funding Institutional Review Board Statement Informed Consent Statement Data Availability Statement Acknowledgments Conflicts of Interest References Charatsari, C.; Michailidis, A.; Lioutas, E.D.; Bournaris, T.; Loizou, E.; Paltaki, A.; Lazaridou, D. Competencies needed for guiding the digital transition of agriculture: Are future advisors well-equipped? Sustainability 2023 , 15, 15815. [Google Scholar] Musa, S.F.P.D.; Basir, K.H. Smart farming: Towards a sustainable agri-food system. Br. Food J. 2021 , 123, 3085–3099. [Google Scholar] [CrossRef] Walter, A.; Finger, R.; Huber, R.; Buchmann, N. Smart farming is key to developing sustainable agriculture. Proc. Natl. Acad. Sci. USA 2017 , 114, 6148–6150. [Google Scholar] [CrossRef] [PubMed] Bourgeois, L.J., III; Eisenhardt, K.M. Strategic decision processes in high velocity environments: Four cases in the microcomputer industry. Manag. Sci. 1988 , 34, 816–835. [Google Scholar] [CrossRef] Charania, I.; Li, X. Smart farming: Agriculture’s shift from a labor intensive to technology native industry. Internet Things 2020 , 9, 100142. [Google Scholar] [CrossRef] Klerkx, L.; Jakku, E.; Labarthe, P. A review of social science on digital agriculture, smart farming and agriculture 4.0: New contributions and a future research agenda. NJAS—Wagening. J. Life Sci. 2019 , 90, 100315. [Google Scholar] [CrossRef] Precedence Research. Digital Agriculture Market Size is Expanding to USD 52.3 BN by 2030. 2023. Available online: https://finance.yahoo.com/news/digital-agriculture-market-size-expanding-200000031.html?guccounter=1&guce_referrer=aHR0cHM6Ly93d3cuZ29vZ2xlLmNvbS8&guce_referrer_sig=AQAAAHSRGKO34APeE1LKfA1vNKBgStb47xfuM7DjuyJvdS_whb005mwWbiEMr1AnNN_eUb727PQYl_5e122CwMFwqCHyCQaxfE1x1P0yzycisVrmA2pLlTu-b14lmTDl05EX_iHHfp32qvjvoAWOxd3stcf6Xno4FrB5qJaL2QxC_dBo (accessed on 28 October 2023). Forney, J.; Dwiartama, A. The project, the everyday, and reflexivity in sociotechnical agri-food assemblages: Proposing a conceptual model of digitalisation. Agric. Hum. Values 2023 , 40, 441–454. [Google Scholar] [CrossRef] [PubMed] Lioutas, E.D.; Charatsari, C. Innovating digitally: The new texture of practices in agriculture 4.0. Sociol. Rural 2022 , 62, 250–278. [Google Scholar] [CrossRef] Lioutas, E.D.; Charatsari, C.; De Rosa, M. Digitalization of agriculture: A way to solve the food problem or a trolley dilemma? Technol. Soc. 2021 , 67, 101744. [Google Scholar] [CrossRef] Visser, O.; Sippel, S.R.; Thiemann, L. Imprecision farming? Examining the (in) accuracy and risks of digital agriculture. J. Rural Stud. 2021 , 86, 623–632. [Google Scholar] [CrossRef] Regan, Á. ‘Smart farming’ in Ireland: A risk perception study with key governance actors. NJAS Wagening. J. Life Sci. 2019 , 90–91, 100292. [Google Scholar] [CrossRef] Charatsari, C.; Lioutas, E.D.; Papadaki-Klavdianou, A.; Michailidis, A.; Partalidou, M. Farm advisors amid the transition to Agriculture 4.0: Professional identity, conceptions of the future and future-specific competencies. Sociol. Rural. 2022 , 62, 335–362. [Google Scholar] [CrossRef] Ingram, J.; Maye, D.; Bailye, C.; Barnes, A.; Bear, C.; Bell, M.; Cutress, D.; Davies, L.; de Boon, A.; Dinnie, L.; et al. What are the priority research questions for digital agriculture? Land Use Policy 2022 , 114, 105962. [Google Scholar] [CrossRef] Lajoie-O’Malley, A.; Bronson, K.; van der Burg, S.; Klerkx, L. The future (s) of digital agriculture and sustainable food systems: An analysis of high-level policy documents. Ecosyst. Serv. 2020 , 45, 101183. [Google Scholar] [CrossRef] Fielke, S.J.; Garrard, R.; Jakku, E.; Fleming, A.; Wiseman, L.; Taylor, B.M. Conceptualising the DAIS: Implications of the ‘Digitalisation of Agricultural Innovation Systems’ on technology and policy at multiple levels. NJAS Wagening. J. Life Sci. 2019 , 90, 102763. [Google Scholar] [CrossRef] Cook, S.; Jackson, E.L.; Fisher, M.J.; Baker, D.; Diepeveen, D. Embedding digital agriculture into sustainable Australian food systems: Pathways and pitfalls to value creation. Int. J. Agric. Sustain. 2022 , 20, 346–367. [Google Scholar] [CrossRef] Frankelius, P.; Norrman, C.; Johansen, K. Agricultural innovation and the role of institutions: Lessons from the game of drones. J. Agric. Environ. Ethics 2019 , 32, 681–707. [Google Scholar] [CrossRef] Eastwood, C.; Ayre, M.; Nettle, R.; Rue, B.D. Making sense in the cloud: Farm advisory services in a smart farming future. NJAS Wagening. J. Life Sci. 2019 , 90, 100298. [Google Scholar] [CrossRef] Teece, D.J. Explicating dynamic capabilities: The nature and microfoundations of (sustainable) enterprise performance. Strateg. Manag. J. 2007 , 28, 1319–1350. [Google Scholar] [CrossRef] Teece, D.J. Technological innovation and the theory of the firm: The role of enterprise-level knowledge, complementarities, and (dynamic) capabilities. In Handbook of the Economics of Innovation; Rosenberg, N., Hall, B., Eds.; North-Holland: Amsterdam, The Netherlands, 2010; Volume 1, pp. 679–730. [Google Scholar] Fischer, T.; Gebauer, H.; Gregory, M.; Ren, G.; Fleisch, E. Exploitation or exploration in service business development? Insights from a dynamic capabilities perspective. J. Serv. Manag. 2010 , 21, 591–624. [Google Scholar] [CrossRef] Žabko, O.; Tisenkopfs, T. New entrants need tailored farm advice. EuroChoices 2022 , 21, 63–69. [Google Scholar] [CrossRef] Chiaverina, P.; Drogué, S.; Jacquet, F. Do farmers participating in short food supply chains use less pesticides? Evidence from France. Ecol. Econ. 2024 , 216, 108034. [Google Scholar] [CrossRef] Charatsari, C.; Kitsios, F.; Lioutas, E.D. Short food supply chains: The link between participation and farmers’ competencies. Renew. Agric. Food Syst. 2020 , 35, 643–652. [Google Scholar] [CrossRef] Renting, H.; Marsden, T.K.; Banks, J. Understanding alternative food networks: Exploring the role of short food supply chains in rural development. Environ. Plan. A 2003 , 35, 393–411. [Google Scholar] [CrossRef] Charatsari, C.; Lioutas, E.D.; Michailidis, A.; Aidonis, D.; De Rosa, M.; Partalidou, M.; Achillas, C.; Nastis, S.; Camanzi, L. Facets of value emerging through the operation of short food supply chains. NJAS Wagening. J. Life Sci. 2023 , 95, 2236961. [Google Scholar] [CrossRef] Reina-Usuga, L.; Parra-López, C.; de Haro-Giménez, T.; Carmona-Torres, C. Sustainability assessment of territorial short food supply chains versus large-scale food distribution: The case of Colombia and Spain. Land Use Policy 2023 , 126, 106529. [Google Scholar] [CrossRef] EU SCAR. Agricultural Knowledge and Innovation Systems towards the Future—A Foresight Paper; Standing Committee on Agricultural Research (SCAR), Collaborative Working Group AKIS: Luxembourg, Brussels, 2016. [Google Scholar] Potters, J.; Collins, K.; Schoorlemmer, H.; Stræte, E.P.; Kilis, E.; Lane, A.; Leloup, H. Living labs as an approach to strengthen agricultural knowledge and innovation systems. EuroChoices 2022 , 21, 23–29. [Google Scholar] [CrossRef] Mirra, L.; Caputo, N.; Gandolfi, F.; Menna, C. The Agricultural Knowledge and Innovation System (AKIS) in Campania Region: The challenges facing the first implementation of experimental model. J. Agric. Policy 2020 , 3, 35–44. [Google Scholar] [CrossRef] Hermans, F.; Klerkx, L.; Roep, D. Structural Conditions for Dynamic Innovation Networks: A Review of Eight European Agricultural Knowledge and Innovation Systems. In Proceedings of the 10th European IFSA Symposium, Aarhus, Denmark, 1–4 July 2012. [Google Scholar] Hermans, F.; Klerkx, L.; Roep, D. Structural conditions for collaboration and learning in innovation networks: Using an innovation system performance lens to analyse agricultural knowledge systems. J. Agric. Educ. Ext. 2015 , 21, 35–54. [Google Scholar] [CrossRef] Hidalgo, F.; Quiñones-Ruiz, X.F.; Birkenberg, A.; Daum, T.; Bosch, C.; Hirsch, P.; Birner, R. Digitalization, sustainability, and coffee. Opportunities and challenges for agricultural development. Agric. Syst. 2023 , 208, 103660. [Google Scholar] [CrossRef] Schnebelin, É.; Labarthe, P.; Touzard, J.M. How digitalisation interacts with ecologisation? Perspectives from actors of the French Agricultural Innovation System. J. Rural Stud. 2021 , 86, 599–610. [Google Scholar] [CrossRef] Dahesh, M.B.; Tabarsa, G.; Zandieh, M.; Hamidizadeh, M. Reviewing the intellectual structure and evolution of the innovation systems approach: A social network analysis. Technol. Soc. 2020 , 63, 101399. [Google Scholar] [CrossRef] Eidelson, R.J. Complex adaptive systems in the behavioral and social sciences. Rev. Gen. Psychol. 1997 , 1, 42–71. [Google Scholar] [CrossRef] Helfat, C.E.; Finkelstein, S.; Mitchell, W.; Peteraf, M.; Singh, H.; Teece, D.; Winter, S.G. Dynamic Capabilities: Understanding Strategic Change in Organizations; John Wiley & Sons: New Jersey, NJ, USA, 2007. [Google Scholar] Eisenhardt, K.M.; Martin, J.A. Dynamic capabilities: What are they? Strateg. Manag. J. 2000 , 21, 1105–1121. [Google Scholar] [CrossRef] Kierser, A.; Beck, N.; Tainio, R. Rules and organizational learning: The behavioral theory approach. In Handbook of Organizational Learning & Knowledge; Dierkes, M., Antal, A.B., Child, J., Nonaka, I., Eds.; Oxford University Press: Oxford, UK, 2003; pp. 598–623. [Google Scholar] Yi, S.; Knudsen, T.; Becker, M.C. Inertia in routines: A hidden source of organizational variation. Org. Sci. 2016 , 27, 782–800. [Google Scholar] [CrossRef] Godkin, L.; Allcorn, S. Overcoming organizational inertia: A tripartite model for achieving strategic organizational change. J. Appl. Bus. Econ. 2008 , 8, 82. [Google Scholar] Kelly, D.; Amburgey, T.L. Organizational inertia and momentum: A dynamic model of strategic change. Acad. Manag. J. 1991 , 34, 591–612. [Google Scholar] [CrossRef] Hanif, S.; Ahsan, A.; Wise, G. Icebergs of expertise-based leadership: The role of expert leaders in public administration. Sustainability 2020 , 12, 4544. [Google Scholar] [CrossRef] Colombo, M.G.; Delmastro, M. The determinants of organizational change and structural inertia: Technological and organizational factors. J. Econ. Manag. Strategy 2002 , 11, 595–635. [Google Scholar] [CrossRef] Hannan, M.T.; Freeman, J. Structural inertia and organizational change. Am. Sociol. Rev. 1984 , 49, 149–164. [Google Scholar] [CrossRef] Miller, D.; Friesen, P.H. Momentum and revolution in organizational adaptation. Acad. Manag. J. 1980 , 23, 591–614. [Google Scholar] [CrossRef] Haveman, H.A. Between a rock and a hard place: Organizational change and performance under conditions of fundamental environmental transformation. Adm. Sci. Q. 1992 , 37, 48–75. [Google Scholar] [CrossRef] Bellon-Maurel, V.; Lutton, E.; Bisquert, P.; Brossard, L.; Chambaron-Ginhac, S.; Labarthe, P.; Lagacherie, P.; Martignac, F.; Molenat, J.; Parisey, N.; et al. Digital revolution for the agroecological transition of food systems: A responsible research and innovation perspective. Agric. Syst. 2022 , 203, 103524. [Google Scholar] [CrossRef] Lioutas, E.D.; Charatsari, C. Smart farming and short food supply chains: Are they compatible? Land Use Policy 2020 , 94, 104541. [Google Scholar] [CrossRef] Rose, D.C.; Sutherland, W.J.; Parker, C.; Lobley, M.; Winter, M.; Morris, C.; Twining, S.; Ffoulkes, C.; Amano, T.; Dicks, L.V. Decision support tools for agriculture: Towards effective design and delivery. Agric. Syst. 2016 , 149, 165–174. [Google Scholar] [CrossRef] Zscheischler, J.; Brunsch, R.; Rogga, S.; Scholz, R.W. Perceived risks and vulnerabilities of employing digitalization and digital data in agriculture—Socially robust orientations from a transdisciplinary process. J. Clean. Prod. 2022 , 358, 132034. [Google Scholar] [CrossRef] da Silveira, F.; da Silva, S.L.C.; Machado, F.M.; Barbedo, J.G.A.; Amaral, F.G. Farmers’ perception of barriers that difficult the implementation of agriculture 4.0. Agric. Syst. 2023 , 208, 103656. [Google Scholar] [CrossRef] Lieder, S.; Schröter-Schlaack, C. Smart farming technologies in arable farming: Towards a holistic assessment of opportunities and risks. Sustainability 2021 , 13, 6783. [Google Scholar] [CrossRef] Barreto, L.; Amaral, A. Smart Farming: Cyber Security Challenges. In Proceedings of the 2018 International Conference on Intelligent Systems (IS), Funchal, Portugal, 25–27 September 2018; Jardim-Gonçalves, R., Mendonça, J.P., Jotsov, V., Marques, M., Martins, J., Bierwolf, R., Eds.; pp. 870–876. [Google Scholar] Clapp, J.; Ruder, S.-L. Precision Technologies for Agriculture: Digital Farming, Gene-Edited Crops, and the Politics of Sustainability. Glob. Environ. Politics 2020 , 20, 49–69. [Google Scholar] [CrossRef] Hansen, B.G.; Bugge, C.T.; Skibrek, P.K. Automatic milking systems and farmer wellbeing—Exploring the effects of automation and digitalization in dairy farming. J. Rural Stud. 2020 , 80, 469–480. [Google Scholar] [CrossRef] Kvam, G.T.; Hårstad, R.M.B.; Stræte, E.P. The role of farmers’ microAKIS at different stages of uptake of digital technology. J. Agric. Educ. Ext. 2022 , 28, 671–688. [Google Scholar] [CrossRef] Ingram, J.; Maye, D. What are the implications of digitalisation for agricultural knowledge? Front. Sustain. Food Syst. 2020 , 4, 66. [Google Scholar] [CrossRef] Charatsari, C.; Lioutas, E.D.; De Rosa, M.; Papadaki-Klavdianou, A. Extension and advisory organizations on the road to the digitalization of animal farming: An organizational learning perspective. Animals 2020 , 10, 2056. [Google Scholar] [CrossRef] [PubMed] Fielke, S.; Taylor, B.; Jakku, E. Digitalisation of agricultural knowledge and advice networks: A state-of-the-art review. Agric. Syst. 2020 , 180, 102763. [Google Scholar] [CrossRef] Brown, C.; Regan, Á.; van der Burg, S. Farming futures: Perspectives of Irish agricultural stakeholders on data sharing and data governance. Agric. Hum. Values 2023 , 40, 565–580. [Google Scholar] [CrossRef] Koutsouris, A. AKIS and Advisory Services in Greece. Report for the AKIS Inventory (WP3) of the PRO AKIS Project; Agricultural University of Athens: Athens, Greece, 2014. [Google Scholar] Birke, F.M.; Bae, S.; Schober, A.; Wolf, S.; Gerster-Bentaya, M.; Knierim, A. AKIS in European Countries: Cross Analysis of AKIS Country Reports from the i2connect Project. 2022. Available online: https://i2connect-h2020.eu/wp-content/uploads/2022/12/2022-12-02-AKIS-cross-analysis_updated.pdf (accessed on 26 October 2023). Sutherland, L.A.; Adamsone-Fiskovica, A.; Elzen, B.; Koutsouris, A.; Laurent, C.; Stræte, E.P.; Labarthe, P. Advancing AKIS with assemblage thinking. J. Rural Stud. 2023 , 97, 57–69. [Google Scholar] [CrossRef] Proietti, P.; Cristiano, S. Innovation support services: An evidence-based exploration of their strategic roles in the Italian AKIS. J. Agric. Educ. Ext. 2023 , 29, 351–371. [Google Scholar] [CrossRef] Lioutas, E.D.; Charatsari, C.; Černič Istenič, M.; La Rocca, G.; De Rosa, M. The challenges of setting up the evaluation of extension systems by using a systems approach: The case of Greece, Italy and Slovenia. J. Agric. Educ. Ext. 2019 , 25, 139–160. [Google Scholar] [CrossRef] Braun, V.; Clarke, V. Using thematic analysis in psychology. Qual. Res. Psychol. 2006 , 3, 77–101. [Google Scholar] [CrossRef] De Rosa, M.; Olivieri, G.; Menna, C.; Gandolfi, F.; Del Giudice, T. Multifunctional farm advisory services in promoting change in agricultural systems: The case of Campania region of Italy. AIMS Agric. Food. 2023 , 8, 962–977. [Google Scholar] [CrossRef] Sutherland, L.A.; Labarthe, P. Introducing ‘microAKIS’: A farmer-centric approach to understanding the contribution of advice to agricultural innovation. J. Agric. Educ. Ext. 2022 , 28, 525–547. [Google Scholar] [CrossRef] Kiraly, G.; Vago, S.; Bull, E.; van der Cruyssen, L.; Arbour, T.; Spanoghe, P.; van Dijk, L. Information behaviour of farmers, foresters, and advisors in the context of digitalisation in the EU. Stud. Agric. Econ. 2023 , 125, 1–12. [Google Scholar] Ding, J.; Jia, X.; Zhang, W.; Klerkx, L. The effects of combined digital and human advisory services on reducing nitrogen fertilizer use: Lessons from China’s national research programs on low carbon agriculture. Int. J. Agric. Sustain. 2022 , 20, 1136–1149. [Google Scholar] [CrossRef] Klerkx, L. Digital and virtual spaces as sites of extension and advisory services research: Social media, gaming, and digitally integrated and augmented advice. J. Agric. Educ. Ext. 2021 , 27, 277–286. [Google Scholar] [CrossRef] Ayre, M.; Mc Collum, V.; Waters, W.; Samson, P.; Curro, A.; Nettle, R.; Paschen, J.-A.; King, B.; Reichelt, N. Supporting and practising digital innovation with advisers in smart farming. NJAS -Wagening. J. Life Sci. 2019 , 90, 100302. [Google Scholar] [CrossRef] Pfeiffer, J.; Gabriel, A.; Gandorfer, M. Understanding the public attitudinal acceptance of digital farming technologies: A nationwide survey in Germany. Agric. Hum. Values 2021 , 38, 107–128. [Google Scholar] [CrossRef] Spykman, O.; Emberger-Klein, A.; Gabriel, A.; Gandorfer, M. Society’s view on autonomous agriculture: Does digitalization lead to alienation? Eng. Proc. 2021 , 9, 12. [Google Scholar] Bolfe, É.L.; Jorge, L.A.D.C.; Sanches, I.D.A.; Júnior, A.L.; da Costa, C.C.; Victoria, D.D.C.; Inamasu, R.Y.; Grego, C.R.; Ferreira, V.R.; Ramirez, A. Precision and digital agriculture: Adoption of technologies and perception of Brazilian farmers. Agriculture 2020 , 10, 653. [Google Scholar] [CrossRef] Townsend, L.C.; Noble, C. Variable rate precision farming and advisory services in Scotland: Supporting responsible digital innovation? Sociol. Rural 2022 , 62, 212–230. [Google Scholar] [CrossRef] Giua, C.; Materia, V.C.; Camanzi, L. Smart farming technologies adoption: Which factors play a role in the digital transition? Technol. Soc. 2022 , 68, 101869. [Google Scholar] [CrossRef] Giua, C.; Materia, V.C.; Camanzi, L. Management information system adoption at the farm level: Evidence from the literature. Br. Food J. 2021 , 123, 884–909. [Google Scholar] [CrossRef] Maijanen, P.; Jantunen, A. Dynamics of dynamic capabilities-the case of public broadcasting. Int. J. Bus. Excell. 2016 , 9, 135–155. [Google Scholar] [CrossRef] Valantiejienė, D.; Butkevičienė, J.; Šmakova, V. Dynamic capabilities in social purpose organisation during critical event: Case study analysis. Int. J. Disaster Risk Reduct. 2022 , 78, 103125. [Google Scholar] [CrossRef] Hermelingmeier, V.; von Wirth, T. The nexus of business sustainability and organizational learning: A systematic literature review to identify key learning principles for business transformation. Bus. Strategy Environ. 2021 , 30, 1839–1851. [Google Scholar] [CrossRef] Pablo, A.L.; Reay, T.; Dewald, J.R.; Casebeer, A.L. Identifying, enabling and managing dynamic capabilities in the public sector. J. Manag. Stud. 2007 , 44, 687–708. [Google Scholar] [CrossRef] Cawley, A.; Heanue, K.; Hilliard, R.; O’Donoghue, C.; Sheehan, M. How knowledge transfer impact happens at the farm level: Insights from advisers and farmers in the Irish agricultural sector. Sustainability 2023 , 15, 3226. [Google Scholar] [CrossRef] Nikam, V.; Ashok, A.; Kale, R.B. The functionality of agricultural extension and advisory services from a system perspective: A subnational level analysis in India. J. Agric. Educ. Ext. 2023 , 29, 557–581. [Google Scholar] [CrossRef] Lioutas, E.D.; Charatsari, C.; La Rocca, G.; De Rosa, M. Key questions on the use of big data in farming: An activity theory approach. NJAS -Wagening. J. Life Sci. 2019 , 90, 100297. [Google Scholar] [CrossRef] Eriksson, T. Processes, antecedents and outcomes of dynamic capabilities. Scand. J. Manag. 2014 , 30, 65–82. [Google Scholar] [CrossRef] Knierim, A.; Kernecker, M.; Erdle, K.; Kraus, T.; Borges, F.; Wurbs, A. Smart farming technology innovations—Insights and reflections from the German Smart-AKIS hub. NJAS -Wagening. J. Life Sci. 2019 , 90, 100314. [Google Scholar] [CrossRef] Eastwood, C.; Klerkx, L.; Nettle, R. Dynamics and distribution of public and private research and extension roles for technological innovation and diffusion: Case studies of the implementation and adaptation of precision farming technologies. J. Rural Stud. 2017 , 49, 1–12. [Google Scholar] [CrossRef] Warner, K.S.R.; Wäger, M. Building dynamic capabilities for digital transformation: An ongoing process of strategic renewal. Long Range Plan. 2019 , 52, 326–349. [Google Scholar] [CrossRef] Helfat, C.E.; Peteraf, M.A. Managerial cognitive capabilities and the microfoundations of dynamic capabilities. Strat. Manag. J. 2015 , 36, 831–850. [Google Scholar] [CrossRef] Capability Dimensions Sensing Understanding the potential of digitalization Scanning the horizon for technologies that suit the needs of different farmers’ segments Forecasting positive and negative impacts of digitalization on farms, environment, and society Foreseeing the future trajectories of technology development Seizing Leveraging resources to develop new offerings Creating new resources (knowledge, technical infrastructure) Drawing plans to offer high-quality advisory support to farmers Building alliances with actors occupying key positions in the digitalized innovation ecosystems Transforming Altering missions Revamping advisory organizations and the whole AKIS Developing digital applications Redesigning business models Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Share and Cite MDPI and ACS Style
Charatsari, C.; Michailidis, A.; Francescone, M.; De Rosa, M.; Aidonis, D.; Bartoli, L.; La Rocca, G.; Camanzi, L.; Lioutas, E.D.
Do Agricultural Knowledge and Innovation Systems Have the Dynamic Capabilities to Guide the Digital Transition of Short Food Supply Chains? Information 2024 , 15 , 22.
https://doi.org/10.3390/info15010022
AMA Style
Charatsari C, Michailidis A, Francescone M, De Rosa M, Aidonis D, Bartoli L, La Rocca G, Camanzi L, Lioutas ED.
Do Agricultural Knowledge and Innovation Systems Have the Dynamic Capabilities to Guide the Digital Transition of Short Food Supply Chains? Information . 2024; 15(1):22.
https://doi.org/10.3390/info15010022
Chicago/Turabian Style
Charatsari, Chrysanthi, Anastasios Michailidis, Martina Francescone, Marcello De Rosa, Dimitrios Aidonis, Luca Bartoli, Giuseppe La Rocca, Luca Camanzi, and Evagelos D. Lioutas.
2024. “Do Agricultural Knowledge and Innovation Systems Have the Dynamic Capabilities to Guide the Digital Transition of Short Food Supply Chains?” Information 15, no. 1: 22.
https://doi.org/10.3390/info15010022