This thesis is backed up by an internship in SIFA' (Società  Italiana Flotte Aziendali). The thesis starts by providing an overview of the automotive market, with a focus on the Italian one, then covering the definition and the particularities of the long-term car rental and the differences with the other main car rental modalities. Then, it is analyzed the specificity of the services and of the companies that provide services, considering the different approaches adopted when constructing the price. After looking into the SIFA' company, its dynamics and processes, it is reported the project done during the internship. The project aim is to help the company by: Analyzing the costs relative to the maintenance and introducing the age of the vehicles as a key data to determine real maintenance costs in time, creating a simple forecast model in order to estimate the above-mentioned costs for the next year. Categorize the different vehicles in their classes of belonging and estimate the cost of every category, in order to help to identify the right tariff to apply in new contracts of the same category. Analyze the cost of claims, and how to retarget the tariffs for the penalties for virtuous customer and high frequency claims customers.

Pricing Evaluations in the Long-Term Car Rental Sector: The Sifà  Case

2020

Abstract

This thesis is backed up by an internship in SIFA' (Società  Italiana Flotte Aziendali). The thesis starts by providing an overview of the automotive market, with a focus on the Italian one, then covering the definition and the particularities of the long-term car rental and the differences with the other main car rental modalities. Then, it is analyzed the specificity of the services and of the companies that provide services, considering the different approaches adopted when constructing the price. After looking into the SIFA' company, its dynamics and processes, it is reported the project done during the internship. The project aim is to help the company by: Analyzing the costs relative to the maintenance and introducing the age of the vehicles as a key data to determine real maintenance costs in time, creating a simple forecast model in order to estimate the above-mentioned costs for the next year. Categorize the different vehicles in their classes of belonging and estimate the cost of every category, in order to help to identify the right tariff to apply in new contracts of the same category. Analyze the cost of claims, and how to retarget the tariffs for the penalties for virtuous customer and high frequency claims customers.
2020
it
Dipartimento di Economia
Università degli Studi di Modena e Reggio Emilia
File in questo prodotto:
File Dimensione Formato  
Tesi_Nicola_Melli_x_Sifa.pdf

accesso solo da BNCF e BNCR

Tipologia: Altro materiale allegato
Licenza: Tutti i diritti riservati
Dimensione 2.76 MB
Formato Adobe PDF
2.76 MB Adobe PDF

I documenti in UNITESI sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14242/301074
Il codice NBN di questa tesi è URN:NBN:IT:UNIMORE-301074