Grimmel, P., Niemeyer, J. F., Tan, C. F., Sun, Y., Zhao, Y., Schöling, N., Yeo, Z., Mennenga, M., Carlow, V. M., & Herrmann, C. (2025). Urban–industrial symbiosis recommendation platform for urban factories: Leveraging historical exchange patterns through feature analysis for real‐world applications. Journal of Industrial Ecology, 29(3), 656–669. Portico. https://doi.org/10.1111/jiec.70015
Abstract:
Abstract
Since the beginning of industrialization, the economic viability of manufacturing companies relied on the exploitation of natural resources. From 2000 to 2019, the global consumption of raw materials surged by 65%, with 70% of these materials being non‐renewable. Addressing this unsustainable trajectory, the United Nations emphasizes “Responsible consumption and production” as a sustainable development goal (SDG 12), advocating for resource efficiency, circularity, and dematerialization of economic growth. In that context, industrial symbiosis (IS) emerges as a key strategy for sustainable industrial development. IS networks have demonstrated substantial environmental and economic benefits in supply chains. Urban areas, such as the Braunschweig region in Germany or Singapore, characterized by its diverse industries in close geographical proximity, present unique opportunities for IS. In parallel, there is a special demand to enhance the circular economy due to the high density of resource flows and the high dependency on external material supply and disposal. Against this background, this research introduces an IS recommendation system that relies on a knowledge database containing reported material exchange data from various industries. This system incorporates a knowledge‐based matching methodology, which identifies potential symbiotic relationships by evaluating the suitability of different waste stream patterns. Additionally, a hierarchical matching method is developed to suggest potential IS partners based on multicriteria decision support. The proposed method is implemented, tested, and validated through a case study in Braunschweig and Singapore. Finally, recommendations for action are derived, and the methodology is critically reviewed for its effectiveness and applicability.
License type:
Attribution 4.0 International (CC BY 4.0)
Funding Info:
This research / project is supported by the A*STAR - Central Research Fund for Applied & Translational Research
Grant Reference no. :