How to Successfully Orchestrate Content for Digital Agriecosystems

Maximilian Treiber (), Theresa Theunissen (), Simon Grebner, Jan Witting and Heinz Bernhardt
Additional contact information
Maximilian Treiber: Agricultural Systems Engineering, Technical University of Munich, Duernast 10, 85354 Freising, Germany
Theresa Theunissen: Agricultural Systems Engineering, Technical University of Munich, Duernast 10, 85354 Freising, Germany
Simon Grebner: Agricultural Systems Engineering, Technical University of Munich, Duernast 10, 85354 Freising, Germany
Jan Witting: Agricultural Systems Engineering, Technical University of Munich, Duernast 10, 85354 Freising, Germany
Heinz Bernhardt: Agricultural Systems Engineering, Technical University of Munich, Duernast 10, 85354 Freising, Germany

Agriculture, 2023, vol. 13, issue 5, 1-11

Abstract: Since the 2000s, digital ecosystems have been affecting markets—Facebook and Uber being prominent examples. Looking at the agrisector, however, there is not yet a winner-takes-all solution in place. Instead, numerous digital agriplatforms have emerged, many of which have already failed. In the context of this study, it was revealed that reasons for such failures can be manifold, with one key challenge being the orchestration of platform content. Because, however, publicly available knowledge on this regard is limited, we decided to introduce a methodology for the evaluation of digital agriecosystem services, enabling providers to optimize their existing offering and to prioritize new services prior to implementation. By deploying our methodology to digital agriecosystems with two different application focuses (DairyChainEnergy—data agriecosystem on energy management for dairy farmers, and NEVONEX—IoT agriecosystem comprising digital services for agrimachinery), its applicability was proven. Providers of digital agriecosystems will benefit from applying this new methodology because they receive a structured decision-making process, which takes the most relevant success criteria (e.g., customer benefit, technical feasibility, and resilience) into account. Hence, a resulting prioritization of digital agriservices will guide providers in making the right implementation choices in order to successfully generate network effects on their digital agriecosystems.

Keywords: agriecosystem; DairyChainEnergy; methodology; NEVONEX; platform; root-cause analysis (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/2077-0472/13/5/1003/pdf (application/pdf)
https://www.mdpi.com/2077-0472/13/5/1003/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jagris:v:13:y:2023:i:5:p:1003-:d:1137997

Access Statistics for this article

Agriculture is currently edited by Ms. Leda Xuan

More articles in Agriculture from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().