Enterprise modelling for decision-making in the software ecosystem

Even with the availability of modelling languages such as 4EM and ArchiMate, a noticeable uncertainty persists among professionals regarding the efficient development of process models in the software ecosystem. While current enterprise modelling frameworks and guidelines provide valuable perspectives on essential quality aspects, they are usually more abstract to apply in real-world scenarios directly. This study compares the features of 4EM and ArchiMate, underlining their distinct characteristics for a specific context of software outsourcing. Further, this paper demonstrates a choice of appropriate views of these two modelling languages to model a decision-making scenario for software vendor analysis and selection. Thus, this research supports software enterprises to understand their business processes related explicitly to outsourcing and benefits company personnel involved in decision-making. In addition to model development, 4EM and ArchiMate are tested for the extent they fit for modelling the given decision-making context in the software ecosystem. It is observed that ArchiMate is better suited to the given context. Afterwards, the models are validated using the SEQUAL framework which resulted in identification and incorporation of a new process activity in 'As-Is' scenario. This further provided means for digital innovation for 'To-Be' scenario of enterprise business process. However, the models developed in this study are premature since they are validated with a theoretical framework only, and the involvement of experts is limited. Thus, more validation studies are required in actual settings with more experts to improve the models further.

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Publication Details

Journal
Scientific Reports
Published
2025-04-01
DOI
https://doi.org/10.1038/s41598-025-90916-1
Citations
3
Primary Topic
Business Process Modeling and Analysis
Type
article
Field-Weighted Citation Impact
6.85

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article

Enterprise modelling for decision-making in the software ecosystem

Anshul Rani, Deepti Mishra, Aida Omerovic
3 citations
Scientific Reports
Business Process Modeling and Analysis
6.85
article

Enterprise modelling for decision-making in the software ecosystem

Anshul Rani, Deepti Mishra, Aida Omerovic
article en
3 citations

Abstract

Even with the availability of modelling languages such as 4EM and ArchiMate, a noticeable uncertainty persists among professionals regarding the efficient development of process models in the software ecosystem. While current enterprise modelling frameworks and guidelines provide valuable perspectives on essential quality aspects, they are usually more abstract to apply in real-world scenarios directly. This study compares the features of 4EM and ArchiMate, underlining their distinct characteristics for a specific context of software outsourcing. Further, this paper demonstrates a choice of appropriate views of these two modelling languages to model a decision-making scenario for software vendor analysis and selection. Thus, this research supports software enterprises to understand their business processes related explicitly to outsourcing and benefits company personnel involved in decision-making. In addition to model development, 4EM and ArchiMate are tested for the extent they fit for modelling the given decision-making context in the software ecosystem. It is observed that ArchiMate is better suited to the given context. Afterwards, the models are validated using the SEQUAL framework which resulted in identification and incorporation of a new process activity in 'As-Is' scenario. This further provided means for digital innovation for 'To-Be' scenario of enterprise business process. However, the models developed in this study are premature since they are validated with a theoretical framework only, and the involvement of experts is limited. Thus, more validation studies are required in actual settings with more experts to improve the models further.

Scientific ReportsVol. 15(1)
SINTEF (NO), Norwegian University of Science and Technology (NO), SINTEF Digital
Norges Teknisk-Naturvitenskapelige Universitet, St. Olavs Hospital Universitetssykehuset i Trondheim
Industry, innovation and infrastructure
Openalex Percentile: Top 4%
Business Process Modeling and Analysis
6.85
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