dc.contributor.advisor |
Albarelli, Andrea |
it_IT |
dc.contributor.author |
Galassi, Rebecca <1999> |
it_IT |
dc.date.accessioned |
2023-09-30 |
it_IT |
dc.date.accessioned |
2024-02-21T12:17:15Z |
|
dc.date.issued |
2023-11-03 |
it_IT |
dc.identifier.uri |
http://hdl.handle.net/10579/25364 |
|
dc.description.abstract |
In recent years, pricing optimization algorithms have grown in popularity in the B2B sector. These algorithms make price adjustments based on variables like market demand and supply chain expenses.
Offering optimal prices for their goods and services enables businesses to maximize their earnings, and help organizations stay competitive leading to increasing margins.
As the global economy becomes increasingly competitive and complex, organizations are recognizing the need to adopt more sophisticated pricing strategies to maximize their profitability and maintain a competitive edge. In this thesis, we will delve into the realm of pricing optimization in B2B firms, exploring its significance, challenges, and potential benefits.
This study will adopt a mixed-methods approach. At first, a comprehensive literature review will be conducted to gather insights from existing research and industry practices related to pricing optimization in B2B firms, outlining the background, significance, and impact on the digital world.
Subsequent chapters will delve into exploring the development of a practical case study based on real business data in collaboration with a consultancy firm which will not be displayed as in reference to the company providing the data for privacy reasons.
In addition, since the area of belonging of this company is the metalworking sector, a brief overview of the Italian metalworking context is included.
The practical part of the project is composed of three main parts; first, a more exploratory analysis, then the application of demand forecasting techniques which will be the basis for the last part dedicated to the optimization of prices to verify the possibility of obtaining a higher margin. |
it_IT |
dc.language.iso |
en |
it_IT |
dc.publisher |
Università Ca' Foscari Venezia |
it_IT |
dc.rights |
© Rebecca Galassi, 2023 |
it_IT |
dc.title |
Pricing optimization in B2B firms |
it_IT |
dc.title.alternative |
Pricing Optimization in B2B firms |
it_IT |
dc.type |
Master's Degree Thesis |
it_IT |
dc.degree.name |
Data analytics for business and society |
it_IT |
dc.degree.level |
Laurea magistrale |
it_IT |
dc.degree.grantor |
Dipartimento di Economia |
it_IT |
dc.description.academicyear |
LM_2022/2023_sessione-autunnale |
it_IT |
dc.rights.accessrights |
closedAccess |
it_IT |
dc.thesis.matricno |
873347 |
it_IT |
dc.subject.miur |
ING-INF/05 SISTEMI DI ELABORAZIONE DELLE INFORMAZIONI |
it_IT |
dc.description.note |
|
it_IT |
dc.degree.discipline |
|
it_IT |
dc.contributor.co-advisor |
|
it_IT |
dc.date.embargoend |
10000-01-01 |
|
dc.provenance.upload |
Rebecca Galassi (873347@stud.unive.it), 2023-09-30 |
it_IT |
dc.provenance.plagiarycheck |
Andrea Albarelli (albarelli@unive.it), 2023-10-16 |
it_IT |