Suiting Ding
Leiden University| Leiden University | |
| Leiden, Netherlands | |
| Member ID | 4250 |
|---|---|
| Member since | Apr 25, 2024 |
| Status | Active |
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About
I am a Ph.D. candidate at Institute of Environmental Science (CML) at Leiden University (2020-2024). From December 2020 to March 2024, I examined the environmental opportunities and challenges posed by Internet of Things (IoT) technologies in sustainable supply chain operations, from an industrial to product perspective. In this work, I utilized literature review, grey correlation and forecasting modeling, hybrid agent-based and system dynamics modeling, and ex-ante life cycle assessment to explore the impact of IoT/RFID technologies on industrial logistics from the triple bottom line dimensions. Additionally, I investigated the environmental benefits and costs of emerging IoT systems and its role in stimulating Li-ion battery supply chain operations.Details
List of peer-reviewed publications:1. Ding, S., Tukker, A., Ward, H. Opportunities and risks of Internet of Things (IoT) technologies for circular business models: A literature review. Journal of Environmental Management 336, 117662 (2023).
2. Ding, S., Ward, H., Tukker, A. How Internet of Things can influence the sustainability performance of logistics industries – A Chinese case study. Cleaner Logistics and Supply Chain 6, 100094 (2023).
3. Ding, S., Ward, H., Cucurachi, S., Tukker, A. Revealing the hidden potentials of Internet of Things (IoT) - An integrated approach using agent-based modelling and system dynamics to assess sustainable supply chain performance. Journal of Cleaner Production 421, 138558 (2023).
4. Ding, S., Cucurachi, S., Ward, H. The environmental benefits and costs of RFID systems in Li-ion battery supply chains – An ex-ante LCA approach. (Submitted to Resource, conservation & recycling)
Additional publications:
5. Ding, S., Zhang, M., Song, Y. Exploring China's carbon emissions peak for different carbon tax scenarios. Energy Policy 129, 1245-1252 (2019).
6. Zhang, M., Ding, S., Pang, J., Wang, W. The effect of indirect household energy consumption on PM 2.5 emission in China: An analysis based on CLA method. Journal of Environmental Management 279, 111531 (2021).