Architectural Requirements for Supply Chain Management (SCM) Systems in a Circular Economy

Global transition toward circular economy (CE) has fundamentally changed the operation requirements of Supply Chain Management (SCM) systems and the architecture requirements to enable such transition are still largely under-explored. The traditional SCM structure is fundamentally unsuitable to deal with the bidirectional logistics, multi-lifecycles use of resources, and multi-stakeholder collaboration that circular logistics require. Although there are a number of studies that have focused on a single enabling technology like Blockchain, the Internet of Things (IoT), Building Information Modelling (BIM), and Artificial Intelligence (AI), a comprehensive integrated architectural framework that covers the technical, organizational and governance aspects have not yet been developed. The purpose of this study is thus to identify and validate the fundamental architectural needs for SCM systems to fulfill the principles of the circular economy. By applying a Model-Based Systems Engineering (MBSE) methodology, the research consolidates 102 peer-reviewed papers found in Scopus, IEEE Xplore, SpringerLink and ScienceDirect that were relevant to Industry 4.0, digital construction and sustainable logistics between 2016 and 2025. Each requirement identified is confirmed through structured requirement, structured block definition, and structured activity diagrams through mapping to the literature that has been used as a source for the requirement and to the architectural components that support it. These core, interdependent needs traceability and provenance, lifecycle visibility and resource reuse, interoperability and standards, and security and trust are identified in the analysis and integrated solutions, as opposed to individual solutions, are required to achieve operational benefits. The study moves away from the focus on individual technologies and offers a conceptual blueprint for designing resilient, transparent, and sustainable circular supply chain systems; it recognizes that the framework is conceptually rather than empirically validated.

Circular Economy, Supply Chain Management, Architectural Frameworks, Internet of Things (IoT), Building Information Modelling (BIM)

1. Alhamami, A, Petri, I., & Y. Rezgui. (2018). Use-case analysis for assessing the role of Building Information Modeling in energy efficiency. CRC Press EBooks, 31–38. https://doi.org/10.1201/9780429506215-4 [Google Scholar] [Crossref]

2. Alhamami, A., Petri, I., Rezgui, Y., & Kubicki, S. (2020). Promoting Energy Efficiency in the Built Environment through Adapted BIM Training and Education. Energies, 13(9), 2308. https://doi.org/10.3390/en13092308 [Google Scholar] [Crossref]

3. Alhamami A., et al. (2018). Role of BIM in energy efficiency. ECPPM 2018. [Google Scholar] [Crossref]

4. Ali, A. K., & Badinelli, R. (2016). Novel Integration of Sustainable and Construction Decisions into the Design Bid Build Project Delivery Method Using BPMN. Procedia Engineering, 145, 164–171. https://doi.org/10.1016/j.proeng.2016.04.038 [Google Scholar] [Crossref]

5. Amiri, A. (2025). Requirements validation of event-driven supply chains using MBSE. In Proceedings of the 2025 International Conference on Systems Science and Engineering (SSE 2025). IEEE. [Google Scholar] [Crossref]

6. Azevedo, P., Ferreira, J., & Leitão, J. (2023). Supply chain traceability using blockchain: A systematic literature review. Operations Management Research, 16, 1415-1436. https://doi.org/10.1007/s12063-023-00371-5 [Google Scholar] [Crossref]

7. Baskaran, V., & Nguyen, D. (2025). RFID integration in medical device logistics: A human factors approach. Applied Human Factors and Ergonomics International. [Google Scholar] [Crossref]

8. Baskaran, V., & Nguyen, D. (2025). Architectural analysis of RFID integration in medical device logistics: A healthcare information systems study. Human Interaction and Emerging Technologies (IHIET-FS 2025), 196, 105–114. https://doi.org/10.54941/ahfe1005959 [Google Scholar] [Crossref]

9. Banerjee, A., & Nayaka, R. R. (2021). A comprehensive overview on BIM-integrated cyber physical system architectures and practices in the architecture, engineering and construction industry. Construction Innovation, ahead-of-print(ahead-of-print). https://doi.org/10.1108/ci-02-2021-0029 [Google Scholar] [Crossref]

10. Bryman, A. (2016). Social research methods (5th ed.). Oxford University Press. [Google Scholar] [Crossref]

11. Chen, Q., García de Soto, B., & Adey, B. T. (2020). Using look-ahead plans to improve material flow processes on construction projects. Construction Innovation, 20(1), 87-111. https://doi.org/10.1108/CI-11-2018-0093 [Google Scholar] [Crossref]

12. Das, L., Nag, A., & Alsamhi, S. H. (2023). Convergence of AR & VR with IoT. In M. Alam & A. Malik (Eds.), Handbook of Augmented and Virtual Reality (pp. 1-24). Springer. https://doi.org/10.1007/978-3-030-97044-9_1 [Google Scholar] [Crossref]

13. Dave, B., Kubler, S., Främling, K., & Koskela, L. (2016). Opportunities for enhanced lean construction management using Internet of Things standards. Automation in Construction, 61, 86-97. https://doi.org/10.1016/j.autcon.2015.10.009 [Google Scholar] [Crossref]

14. Erbel, J., Wittek, S., Grabowski, J., & Rausch, A. (2020). Dynamic Management of Multi-level-simulation Workflows in the Cloud. Communications in Computer and Information Science, 21–38. https://doi.org/10.1007/978-3-030-45718-1_2 [Google Scholar] [Crossref]

15. Farooque, M., Zhang, A., Thürer, M., Qu, T., & Huisingh, D. (2019). Circular Supply Chain management: a Definition and Structured Literature Review. Journal of Cleaner Production, 228(228), 882–900. [Google Scholar] [Crossref]

16. Geissdoerfer, M., Morioka, S. N., de Carvalho, M. M., & Evans, S. (2018). Business models and supply chains for the circular economy. Journal of Cleaner Production, 190(1), 712–721. https://doi.org/10.1016/j.jclepro.2018.04.159 [Google Scholar] [Crossref]

17. Gupta, P. K. (2025). Intent-based networking architecture: A deep dive into its components and workflow. Journal of Computer Science and Technology Studies, 7(4), 586–597. https://doi.org/10.32996/jcsts.2025.7.4.69 [Google Scholar] [Crossref]

18. Khedr, A. M., & Sheeja , R. S. (2024). Enhancing Supply Chain Management with Deep Learning and Machine Learning Techniques: A Review. Journal of Open Innovation Technology Market and Complexity, 10(4), 100379–100379. Sciencedirect. https://www.sciencedirect.com/science/article/pii/S2199853124001732 [Google Scholar] [Crossref]

19. Kitchenham, B., & Charters, S. (2007). Guidelines for performing systematic literature reviews in software engineering (EBSE Technical Report EBSE-2007-01). Keele University and University of Durham. [Google Scholar] [Crossref]

20. Kizgin, U. V., & Vietor, T. (2025). A scalable framework for demand-oriented model-based systems engineering application: The MBSE cube. Proceedings of the Design Society. https://doi.org/10.1017/pds.2025.10040 [Google Scholar] [Crossref]

21. Lahane, S., Kant, R., & Shankar, R. (2020). Circular supply chain management: A state-of-the-art review and future opportunities. Journal of Cleaner Production, 258, 120859. https://doi.org/10.1016/j.jclepro.2020.120859 [Google Scholar] [Crossref]

22. Landis, J. R., & Koch, G. G. (1977). The measurement of observer agreement for categorical data. Biometrics, 33(1), 159–174. https://doi.org/10.2307/2529310 [Google Scholar] [Crossref]

23. Moher, D., Liberati, A., Tetzlaff, J., & Altman, D. G. (2009). Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. PLoS Medicine, 6(7), e1000097. https://doi.org/10.1371/journal.pmed.1000097 [Google Scholar] [Crossref]

24. Nascimento, D. L. M., Alencastro, V., Quelhas, O. L. G., Caiado, R. G. G., Garza-Reyes, J. A., Rocha-Lona, L., & Tortorella, G. (2019). Exploring Industry 4.0 technologies to enable circular economy practices in a manufacturing context. Journal of Manufacturing Technology Management, 30(3), 607–627. https://doi.org/10.1108/JMTM-03-2018-0071 [Google Scholar] [Crossref]

25. Perau, Martin & Gaillard, Antoine & Berninger, Stefanie & Caspari, Phil & Urboneit, Justus & Spindeldreier, Svenja & Byl, Achim & Winkler, Maximilian & Welsh, Dominic & Schröer, Tobias & Boos, Wolfgang. (2025). Enterprise Architecture Model for Digitally Enabled Reverse Logistics. 10.1007/978-3-032-03538-7_37. [Google Scholar] [Crossref]

26. Radivojević, D., Milica, M., & Dražen , P. (2022). Overview of criteria and methods of machine learning for supplier selection. In Proceedings of the 5th Logistics International Conference, Elsevier, 26–27. [Google Scholar] [Crossref]

27. Rangga Primadasa, Tauhida, D., Bellachintya Reira Christata, Imam Abdul Rozaq, Salman Alfarisi, & Ilyas Masudin. (2024). An Investigation of the Interrelationship Among Circular Supply Chain Management Indicators in Small and Medium Enterprises. Supply Chain Analytics, 7, 100068–100068. https://doi.org/10.1016/j.sca.2024.100068 [Google Scholar] [Crossref]

28. Robertshaw, G., Hayes, J., & Lark, R. (2023). Digital asset management on aging port infrastructure: Integration of BIM and IoT for condition monitoring. Australasian Coasts and Ports 2023: Technical Papers, 1176-1182. [Google Scholar] [Crossref]

29. Saberi, S., Kouhizadeh, M., Sarkis, J., & Shen, L. (2020). Blockchain-enabled circular supply chain management: A system architecture for fast fashion. Computers & Industrial Engineering, 147, 106622. https://doi.org/10.1016/j.cie.2020.106622 [Google Scholar] [Crossref]

30. Salzano, F., Ponsiglione, C., Quinto, I., & Zollo, G. (2024). Integrating blockchain technology within an information ecosystem: A focus on the circular economy. Blockchain: Research and Applications, 5(1), 100155. https://doi.org/10.1016/j.bcra.2023.100155 [Google Scholar] [Crossref]

31. Sapra P., et al. (2022). Blockchain and IoT for Auto Leak Unearthing. Lecture Notes on Data Engineering. [Google Scholar] [Crossref]

32. Solanki, R. K., Gupta, S., & Singh, A. (2025). Design paradigms and efficiency trade-offs in blockchain frameworks. EPJ Web of Conferences, 296, 02003. https://doi.org/10.1051/epjconf/202429602003 [Google Scholar] [Crossref]

33. Sundmaeker, H., Guillemin, P., Friess, P., & Woelfflé, S. (2016). Intelligent networked devices for proactive collaboration. In Proceedings of the 2008 22nd International Conference on Engineering, Construction and Architectural Management (ECAM) (pp. 1-12). IEEE. [Google Scholar] [Crossref]

34. Taddei, E., Sassanelli, C., Rosa, P., & Terzi, S. (2024). Circular supply chains theoretical gaps and practical barriers: A model to support approaching firms in the era of industry 4.0. Computers & Industrial Engineering, 190, 110049–110049. https://doi.org/10.1016/j.cie.2024.110049 [Google Scholar] [Crossref]

35. Toland, P. P., & Collery, D. (2023). How Can the Irish Construction Industry Become Less Fragmented and More Productive? European Conference on Knowledge Management, 24(2), 1643–1650. https://doi.org/10.34190/eckm.24.2.1387 [Google Scholar] [Crossref]

36. Tranfield, D., Denyer, D., & Smart, P. (2003). Towards a methodology for developing evidence-informed management knowledge by means of systematic review. British Journal of Management, 14(3), 207–222. https://doi.org/10.1111/1467-8551.00375 [Google Scholar] [Crossref]

37. Wang, B., Luo, W., Zhang, A., Tian, Z., & Li, Z. (2020). Blockchain-enabled circular supply chain management: A system architecture for fast fashion. Computers in Industry, 123, 103324. https://www.sciencedirect.com/science/article/pii/S0166361520305583 [Google Scholar] [Crossref]

• Assessment of the Role of Artificial Intelligence in Repositioning TVET for Economic Development in Nigeria
• Teachers’ Use of Assure Model Instructional Design on Learners’ Problem Solving Efficacy in Secondary Schools in Bungoma County, Kenya
• “E-Booksan Ang Kaalaman”: Development, Validation, and Utilization of Electronic Book in Academic Performance of Grade 9 Students in Social Studies
• Analyzing EFL University Students’ Academic Speaking Skills Through Self-Recorded Video Presentation
• Major Findings of The Study on Total Quality Management in Teachers’ Education Institutions (TEIs) In Assam – An Evaluative Study