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   <dc:title>Ecommerce distribution: defining a new cost model</dc:title>
   <dc:creator>Tell Conchan, Gerard</dc:creator>
   <dc:contributor>Universitat Politècnica de Catalunya. Departament d'Enginyeria Civil i Ambiental</dc:contributor>
   <dc:contributor>Campos Cacheda, Jose Magin</dc:contributor>
   <dc:subject>Àrees temàtiques de la UPC::Enginyeria civil</dc:subject>
   <dc:subject>Electronic commerce</dc:subject>
   <dc:subject>Business planning</dc:subject>
   <dc:subject>Comerç electrònic</dc:subject>
   <dc:subject>Empreses -- Planificació</dc:subject>
   <dc:description>This project introduces a novel approach for defining a cost model for ecommerce shipment&#xd;
distribution. The key objective is to determine the functionality of the advanced model, in order to&#xd;
obtain the cost of distributing ecommerce shipments to customers and enable the assessment of the&#xd;
cost impact for different business decisions.&#xd;
The cost model is based on the process costing models and the allocation criteria is determined for&#xd;
each specific process. In this regard, process costing is utilized as it is an organic full cost model&#xd;
reflecting all the costs of the production process, which in turn reflects the structure and organization&#xd;
of the different processes involved in the distribution. The model advanced in this project is built on&#xd;
the data gathered from publicly available information on sortation, labor and vehicle cost.&#xd;
Four different distribution ecommerce business decisions have been analyzed utilizing the model&#xd;
proposed: direct injection skipping intermediate hubs to reach the delivery unit, offer of different&#xd;
delivery windows to customers, impact of increasing pickup point’s adoption rate and enabling&#xd;
mailbox delivery.&#xd;
For direct injection, results show that there is no cost saving from skipping intermediate hubs for all&#xd;
delivery units, but there is for the units which concentrate the highest demand. Direct injection cost&#xd;
impact requires an individual analysis lane by lane as cost variation depends on fill rate, distance,&#xd;
vehicle cost, and sortations skipped for each specific case. For scheduled deliveries, the cost increases&#xd;
observed in the last mile versus a full day window are as follows: 30% for 4 hours windows, 60% for 3&#xd;
hours, 80% for 2 hours and reaching up to 110% for 1 hour window. On the other side, increasing the&#xd;
adoption rate of pickup points or mailbox delivery increases the driver productivity and reduces last&#xd;
mile cost. Finally, by enabling mailbox delivery instead of door step delivery a 6% reduction in the total&#xd;
cost has been observed.&#xd;
By applying the model advanced in this project, we could further analyze the cost impact of different&#xd;
business decisions and compare the results with other metrics such as: sales uplift, customer&#xd;
experience and time from click to delivery.</dc:description>
   <dc:date>2017-06-14</dc:date>
   <dc:type>Master thesis</dc:type>
   <dc:identifier>https://hdl.handle.net/2117/117572</dc:identifier>
   <dc:identifier>PRISMA-125402</dc:identifier>
   <dc:language>eng</dc:language>
   <dc:rights>Restricted access - author's decision</dc:rights>
   <dc:format>application/pdf</dc:format>
   <dc:publisher>Universitat Politècnica de Catalunya</dc:publisher>
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