Abstract
This study explores how digital technologies and data analytics can transform urban waste management in smart cities by addressing systemic inefficiencies. Integrating perspectives from the Resource-Based View, Socio-Technical Systems Theory, Circular Economy Theory, and Institutional Theory, the research examines sustainability, operational efficiency, and resilience in extended supply chains. A case study of Company A and its demand-side supply chain with Retailer B highlights key drivers of waste, including overstocking, inventory mismanagement, and inefficiencies in transportation and promotional activities. Using a mixed-methods approach, the study combines quantitative analysis of operational data with advanced statistical techniques and machine learning models. Key data sources include inventory records, sales forecasts, promotional activities, waste logs, and IoT sensor data collected over a two-year period. Machine learning techniques were employed to uncover complex, non-linear relationships between waste drivers and waste generation. A waste-type-specific emissions framework was used to assess environmental impacts, while IoT-enabled optimization algorithms helped improve logistics efficiency and reduce waste collection costs. Our findings indicate that the adoption of IoT and AI technologies significantly reduced waste by enhancing inventory control, optimizing transportation, and improving supply chain coordination. These digital innovations also align with circular economy principles by minimizing resource consumption and emissions, contributing to broader sustainability and resilience goals in urban environments. The study underscores the importance of integrating digital solutions into waste management strategies to foster more sustainable and efficient urban supply chains. While the research is particularly relevant to the food production and retail sectors, it also provides valuable insights for policymakers, urban planners, and supply chain stakeholders. By bridging theoretical frameworks with practical applications, this study demonstrates the potential of digital technologies to drive sustainability and resilience in smart cities.
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Divisions: | Leeds Business School School of Built Environment, Engineering and Computing |
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Identification Number: | https://doi.org/10.3390/su17051996 |
Status: | Published |
Refereed: | Yes |
Publisher: | MDPI AG |
Additional Information: | © 2025 by the authors |
Uncontrolled Keywords: | 12 Built Environment and Design |
SWORD Depositor: | Symplectic |
Depositing User (symplectic) | Deposited by Mann, Elizabeth |
Date Deposited: | 06 Mar 2025 16:52 |
Last Modified: | 01 Apr 2025 00:18 |
Item Type: | Article |
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Read more research from the author(s):
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H Fatorachian
ORCID: 0000-0002-2569-7882
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H Kazemi
ORCID: 0000-0001-5982-2605
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K Pawar
ORCID: 0000-0001-8830-1024