Authors:
Wendel Barbosa, Tulio Augusto, Yohany Jimenez
Graduate Certificate in Logistics and Supply Chain Management (GCLOG)
Summary:
Given Colombia’s fragmented, heterogeneous, and diesel-powered road freight sector, this project uses data-driven clustering to identify operational emissions profiles. By applying an exploratory quantitative methodology using unsupervised learning (k-prototype) on extensive primary data from the industry, it confirms that carbon emissions can be segmented and are mainly influenced by strategic and operational context. Statistical evidence confirms that vehicle technology leverages urban efficiency, meanwhile load factor and fuel type influence long-haul performance, thus decarbonization strategies should combine collaborative logistics and urban consolidation centers with hybrid and gas technologies.
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