Integrating smart technologies into circular supply chain management: A framework for sustainable, transparent, and data-driven operations

Authors

https://doi.org/10.22105/sci.v2i2.35

Abstract

The Circular Economy (CE) is gaining momentum as businesses and governments worldwide recognize the need to reduce waste, minimize environmental impacts, and unlock new economic opportunities. Supply chain management, which needs to change to meet circularity principles, is at the center of this shift. This study examines how smart technologies support Circular Supply Chain Management (CSCM), emphasizing how they can change conventional methods into more adaptable, efficient, and sustainable systems. The potential for improving efficiency, sustainability, and resilience has led to a great deal of interest in the integration of smart technologies in supply chain management. In the framework of CSCM, which attempts to reduce waste and maximize resource use throughout the product lifecycle, this article investigates the deployment of smart technology. This study identifies several smart technologies, including the Internet of Things (IoT), blockchain, Artificial Intelligence (AI), and big data analytics, and investigates their roles in supporting CSCM practices through a thorough analysis of the available literature. This paper also addresses the advantages, difficulties, and potential applications of smart technology adoption in CSCM. The results add to our understanding of how businesses might use smart technology to make it more sustainable.

Keywords:

Smart technologies, Circular supply chain management, Internet of things, Blockchain, Artificial intelligence, Big data analytics, Sustainability

References

  1. [1] Geissdoerfer, M., Savaget, P., Bocken, N. M. P., & Hultink, E. J. (2017). The circular economy – A new sustainability paradigm? Journal of cleaner production, 143, 757–768. https://doi.org/10.1016/j.jclepro.2016.12.048
  2. [2] Genovese, A., Acquaye, A. A., Figueroa, A., & Koh, S. C. L. (2017). Sustainable supply chain management and the transition towards a circular economy: Evidence and some applications. Omega, 66, 344–357. https://doi.org/10.1016/j.omega.2015.05.015
  3. [3] De Sousa Jabbour, A. B. L., Luiz, J. V. R., Luiz, O. R., Jabbour, C. J. C., Ndubisi, N. O., De Oliveira, J. H. C., & Junior, F. H. (2019). Circular economy business models and operations management. Journal of cleaner production, 235, 1525–1539. https://doi.org/10.1016/j.jclepro.2019.06.349
  4. [4] Khan, S. A. R., Razzaq, A., Yu, Z., & Miller, S. (2021). Retracted: Industry 4.0 and circular economy practices: A new era business strategies for environmental sustainability. Business strategy and the environment, 30(8), 4001–4014. https://doi.org/10.1002/bse.2853
  5. [5] Tseng, M. L., Islam, M. S., Karia, N., Fauzi, F. A., & Afrin, S. (2019). A literature review on green supply chain management: Trends and future challenges. Resources, conservation and recycling, 141, 145–162. https://doi.org/10.1016/j.resconrec.2018.10.009
  6. [6] Rajput, S., & Singh, S. P. (2019). Connecting circular economy and industry 4.0. International journal of information management, 49, 98–113. https://doi.org/10.1016/j.ijinfomgt.2019.03.002
  7. [7] Awan, U., Shamim, S., Khan, Z., Zia, N. U., Shariq, S. M., & Khan, M. N. (2021). Big data analytics capability and decision-making: The role of data-driven insight on circular economy performance. Technological forecasting and social change, 168, 120766. https://doi.org/10.1016/j.techfore.2021.120766
  8. [8] de Sousa Jabbour, A. B., Jabbour, C. J. C., Godinho Filho, M., & Roubaud, D. (2018). Industry 4.0 and the circular economy: A proposed research agenda and original roadmap for sustainable operations. Annals of operations research, 270(1), 273–286. https://doi.org/10.1007/s10479-018-2772-8
  9. [9] Queiroz, M. M., Telles, R., & Bonilla, S. H. (2020). Blockchain and supply chain management integration: A systematic review of the literature. Supply chain management, 25(2), 241–254. https://doi.org/10.1108/SCM-03-2018-0143
  10. [10] Fořt, J., Vejmelková, E., Koňáková, D., Alblová, N., Čáchová, M., Keppert, M., ... & Černý, R. (2018). Application of waste brick powder in alkali activated aluminosilicates: Functional and environmental aspects. Journal of cleaner production, 194, 714–725. https://doi.org/10.1016/j.jclepro.2018.05.181
  11. [11] Govindan, K., & Hasanagic, M. (2018). A systematic review on drivers, barriers, and practices towards circular economy: A supply chain perspective. International journal of production research, 56(1–2), 278–311. https://doi.org/10.1080/00207543.2017.1402141
  12. [12] Rosa, P., Sassanelli, C., & Terzi, S. (2019). Towards circular business models: A systematic literature review on classification frameworks and archetypes. Journal of cleaner production, 236, 117696. https://doi.org/10.1016/j.jclepro.2019.117696
  13. [13] Saidani, M., Yannou, B., Leroy, Y., Cluzel, F., & Kendall, A. (2019). A taxonomy of circular economy indicators. Journal of cleaner production, 207, 542–559. https://doi.org/10.1016/j.jclepro.2018.10.014
  14. [14] Kirchherr, J., Reike, D., & Hekkert, M. (2017). Conceptualizing the circular economy: An analysis of 114 definitions. Resources, conservation and recycling, 127, 221–232. https://doi.org/10.1016/j.resconrec.2017.09.005
  15. [15] Bressanelli, G., Adrodegari, F., Perona, M., & Saccani, N. (2018). The role of digital technologies to overcome circular economy challenges in PSS business models: An exploratory case study. Procedia cirp, 73, 216–221. https://doi.org/10.1016/j.procir.2018.03.322
  16. [16] Lombardi, D. R., & Laybourn, P. (2012). Redefining industrial symbiosis: Crossing academic--practitioner boundaries. Journal of industrial ecology, 16(1), 28–37. https://doi.org/10.1111/j.1530-9290.2011.00444.x
  17. [17] Paquin, R. L., & Howard-Grenville, J. (2012). The evolution of facilitated industrial symbiosis. Journal of industrial ecology, 16(1), 83–93. https://doi.org/10.1111/j.1530-9290.2011.00437.x
  18. [18] Theobald, T. F. H., Schipper, M., & Kern, J. (2016). Phosphorus flows in Berlin-Brandenburg, a regional flow analysis. Resources, conservation and recycling, 112, 1–14. https://doi.org/10.1016/j.resconrec.2016.04.008
  19. [19] Stupak, N., Sanders, J., & Heinrich, B. (2019). The role of farmers’ understanding of nature in shaping their uptake of nature protection measures. Ecological economics, 157, 301–311. https://doi.org/10.1016/j.ecolecon.2018.11.022
  20. [20] Li, D., Zuo, Q., Wu, Q., Li, Q., & Ma, J. (2021). Achieving the tradeoffs between pollutant discharge and economic benefit of the Henan section of the South-to-North water diversion project through water resources-environment system management under uncertainty. Journal of cleaner production, 321, 128857. https://doi.org/10.1016/j.jclepro.2021.128857
  21. [21] Adomavicius, G., & Tuzhilin, A. (2005). Toward the next generation of recommender systems: A survey of the state-of-the-art and possible extensions. IEEE transactions on knowledge and data engineering, 17(6), 734–749. https://doi.org/10.1109/TKDE.2005.99
  22. [22] Stang, S., Khalkhali, M., Petrik, M., Palace, M., Lu, Z., & Mo, W. (2021). Spatially optimized distribution of household rainwater harvesting and greywater recycling systems. Journal of cleaner production, 312, 127736. https://doi.org/10.1016/j.jclepro.2021.127736
  23. [23] Dhamal, S., Ben-Ameur, W., Chahed, T., & Altman, E. (2020). A two phase investment game for competitive opinion dynamics in social networks. Information processing & management, 57(2), 102064. https://doi.org/10.1016/j.ipm.2019.102064
  24. [24] Tintarev, N., & Masthoff, J. (2015). Explaining recommendations: Design and evaluation. In Recommender systems handbook (pp. 353–382). Springer. https://doi.org/10.1007/978-1-4899-7637-6_10
  25. [25] Kalloori, S., & Ricci, F. (2017). Improving cold start recommendation by mapping feature-based preferences to item comparisons [presentation]. Proceedings of the 25th conference on user modeling, adaptation and personalization (pp. 289–293). https://doi.org/10.1145/3079628.3079696
  26. [26] Kamble, S. S., Gunasekaran, A., & Sharma, R. (2020). Modeling the blockchain enabled traceability in agriculture supply chain. International journal of information management, 52, 101967. https://doi.org/10.1016/j.ijinfomgt.2019.05.023
  27. [27] Ben-Daya, M., Hassini, E., & Bahroun, Z. (2019). Internet of things and supply chain management: A literature review. International journal of production research, 57(15–16), 4719–4742. https://doi.org/10.1080/00207543.2017.1402140
  28. [28] Saberi, S., Kouhizadeh, M., Sarkis, J., & Shen, L. (2019). Blockchain technology and its relationships to sustainable supply chain management. International journal of production research, 57(7), 2117–2135. https://doi.org/10.1080/00207543.2018.1533261
  29. [29] Dubey, R., Gunasekaran, A., Childe, S. J., Papadopoulos, T., Luo, Z., Wamba, S. F., & Roubaud, D. (2019). Can big data and predictive analytics improve social and environmental sustainability? Technological forecasting and social change, 144, 534–545. https://doi.org/10.1016/j.techfore.2017.06.020
  30. [30] Boakye, D. J., Tingbani, I., Ahinful, G. S., & Nsor-Ambala, R. (2021). The relationship between environmental management performance and financial performance of firms listed in the Alternative Investment Market (AIM) in the UK. Journal of cleaner production, 278, 124034. https://doi.org/10.1016/j.jclepro.2020.124034
  31. [31] Zhong, R. Y., Xu, C., Chen, C., & Huang, G. Q. (2017). Big data analytics for physical internet-based intelligent manufacturing shop floors. International journal of production research, 55(9), 2610–2621. https://doi.org/10.1080/00207543.2015.1086037
  32. [32] Francisco, K., & Swanson, D. (2018). The supply chain has no clothes: Technology adoption of blockchain for supply chain transparency. Logistics, 2(1), 2. https://doi.org/10.3390/logistics2010002
  33. [33] Sassanelli, C., Rosa, P., Rocca, R., & Terzi, S. (2019). Circular economy performance assessment methods: A systematic literature review. Journal of cleaner production, 229, 440–453. https://doi.org/10.1016/j.jclepro.2019.05.019
  34. [34] Garza-Reyes, J. A. (2015). Lean and green--a systematic review of the state of the art literature. Journal of cleaner production, 102, 18–29. https://doi.org/10.1016/j.jclepro.2015.04.064
  35. [35] Singh, A., Quinn, N. W. T., Benes, S. E., & Cassel, F. (2020). Policy-driven sustainable saline drainage disposal and forage production in the Western San Joaquin Valley of California. Sustainability, 12(16), 6362. https://doi.org/10.3390/su12166362
  36. [36] Asadi, N., Jackson, M., & Fundin, A. (2019). Implications of realizing mix flexibility in assembly systems for product modularity—A case study. Journal of manufacturing systems, 52, 13–22. https://doi.org/10.1016/j.jmsy.2019.04.010

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Published

2025-06-20

Issue

Vol. 2 No. 2 (2025): Smart City Insights

Section

Articles

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How to Cite

Ghandehari, M., Najafi, S. E., & Alijani, H. (2025). Integrating smart technologies into circular supply chain management: A framework for sustainable, transparent, and data-driven operations. Smart City Insights, 2(2), 68-76. https://doi.org/10.22105/sci.v2i2.35