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Delivery models for optimizing the order volume estimation in the e-commerce industry

Andrea Buttazzoni

Delivery models for optimizing the order volume estimation in the e-commerce industry.

Rel. Giulio Mangano. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Gestionale, 2021


Our society is subject to constant changes manly due to globalization. Over the years, markets are becoming more volatile and erratic. Indeed, 21st-century businesses give a particular example of innovation and adaptation to new trends. This phenomenon can be perceived in one industry in particular, electronic commerce, also called e-commerce, which refers to the exchange of products and services through internet. In the last decades, e-commerce has been one of the fastest-growing industry. My studies are focused on understanding the strategies that e-commerce businesses have implemented to their logistic systems and will be presented the project I developed to optimize the routing systems used in this industry. To compete in the globalized e-commerce environment, companies have to consider many factors that can impact customers to define the best logistic system and, consequently, a successful business. The dissertation will discuss the main supply chain and routing models used in the e-commerce industry. Furthermore, it will present the shortcomings of the above-mentioned models and identify exemplary strategies implemented in this field to ensure companies’ business success. This thesis is organized into five chapters, which will be presented the structure of the e-commerce business, its logistic system and the results obtained from the deployment of my project. The first chapter gives an overview of the e-commerce business whereas the second and third chapter present the supply chain and routing models used in this industry. The fourth chapter presents the project that I have been working on, and the last chapter provides conclusions and benefits for the topics studied.

Relators: Giulio Mangano
Academic year: 2020/21
Publication type: Electronic
Number of Pages: 60
Additional Information: Tesi secretata. Fulltext non presente
Corso di laurea: Corso di laurea magistrale in Ingegneria Gestionale
Classe di laurea: New organization > Master science > LM-31 - MANAGEMENT ENGINEERING
Aziende collaboratrici: Amazon UK Services ltd
URI: http://webthesis.biblio.polito.it/id/eprint/17783
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