Assessing Sustainability of E-Commerce Goods Distribution
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Assessing Sustainability of E-Commerce Goods Distribution

Filetype[PDF-1.82 MB]


English
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Details:

  • Creators:
    Pahwa, Anmol
  • Corporate Creators:
    University of California, Davis. Department of Civil and Environmental Engineering
  • Subject/TRT Terms:
  • Resource Type:
    Dissertation
  • Geographical Coverage:
  • Corporate Publisher:
    University of California, Davis
  • Abstract:
    The growth of e-commerce, spurred by the internet, has transformed urban goods flow. What would previously have been a trip to a store is now a hassle-free delivery to the home. With consolidated and optimized delivery tours, e-commerce has the potential to make urban goods flow economically viable, environmentally efficient, and socially equitable. However, as e-retailers compete with increasingly consumer-focused service, urban freight witnesses a significant increase in associated distribution costs and negative externalities including greenhouse gas emissions advancing global climate change, as well as criteria pollutant emissions worsening local air quality and thus affecting those living close to logistics clusters. Thus, considering the potential of e-commerce to render economically viable, environmentally efficient, and socially equitable urban goods flow, it is pertinent to understand the opportunities and challenges associated with urban freight in light of the increasingly consumer-focused e-commerce distribution. To this end, the author develops A) the impact of e-commerce on urban goods distribution, with a simulation framework founded on consumer shopping behavior simulating urban goods flow, B) the impact of key delivery environment parameters on e-commerce goods distribution, with a continuous approximation (CA) framework modeling last-mile distribution operation for an e-retailer, and C) the impact of demand uncertainty on e-commerce goods distribution, with a discrete optimization framework formulating a last-mile network design (LMND) problem as a dynamic-stochastic two-echelon capacitated location routing problem with time-windows (DS-2E-C-LRP-TW), addressed using an adaptive large neighborhood search (ALNS) metaheuristic algorithm.
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