A multilayer network model for studying business ecosystems: insights from enterprise architectures in the real estate sector

Olli Vigren & Kent Eriksson

Journal of European Real Estate Research2025https://doi.org/10.1108/jerer-04-2024-0027article
AJG 1ABDC C
Weight
0.48

What the paper says

Purpose This article proposes a Multilayer Network (MLN) model for studying business ecosystems. The model focuses on the flows of products, services and money between buyers and sellers, emphasizing that these flows form both actor-level and emergent system-level ecosystem structures. Design/methodology/approach The article examines two case studies of real estate owners and their suppliers, using financial transaction data to provide a detailed, data-driven view of business ecosystems. Findings The study advances real estate theory by deepening research on the digitalization of real estate owners, especially on their enterprise architectures and supplier networks. Despite size differences, both case firms have similar, complex supplier-network structures. The findings may inform enterprise architecture management and procurement practices in the real estate sector. Originality/value The MLN model defines terminology for ecosystem layers and provides methods for establishing ecosystem boundaries. This aligns with the micro-level critique in management and ecosystems research. We conclude by highlighting that event data, when available, can enhance future business ecosystem analysis by enabling the study of broader ecosystem structures with the MLN model.

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https://doi.org/https://doi.org/10.1108/jerer-04-2024-0027

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@article{olli2025,
  title        = {{A multilayer network model for studying business ecosystems: insights from enterprise architectures in the real estate sector}},
  author       = {Olli Vigren & Kent Eriksson},
  journal      = {Journal of European Real Estate Research},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1108/jerer-04-2024-0027},
}

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Evidence weight

0.48

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.41 × 0.4 = 0.16
M · momentum0.63 × 0.15 = 0.09
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.