dc.contributor |
Universitat Politècnica de Catalunya. Departament d'Organització d'Empreses |
dc.contributor |
Fernández Alarcón, Vicenç |
dc.contributor |
Buzzacchi, Luigi |
dc.contributor.author |
Reho, Pietro |
dc.date |
2016-07 |
dc.identifier.citation |
205-845 |
dc.identifier.uri |
http://hdl.handle.net/2117/174173 |
dc.language.iso |
eng |
dc.publisher |
Universitat Politècnica de Catalunya |
dc.rights |
info:eu-repo/semantics/openAccess |
dc.subject |
Àrees temàtiques de la UPC::Economia i organització d'empreses |
dc.subject |
Big data |
dc.subject |
Technological innovations |
dc.subject |
Dades massives |
dc.subject |
Empreses -- Direcció i administració -- Sistemes d'informació |
dc.subject |
Innovacions tecnològiques |
dc.title |
Study of Big data and emerging technologies impact over pricing competition: new tools to approach first-degree price discrimination |
dc.type |
info:eu-repo/semantics/masterThesis |
dc.description.abstract |
The master thesis has the objective to describe and analyse the impact of technologies drastic improvements over firm’s strategical behaviour. First-degree price discrimination has been considered for centuries as a mirage to apply in competitive markets, due to consumer’s differentiated tastes and preferences over goods. On the other hand, the last decades have led to an exponential growth in machine learning performance and computer technologies. Such unexpected evolution permits firms to manipulate an increasing amount of data, and enlarge their perspectives on customer’s reservation price knowledge. Here lies one of the greatest challenges of the new era: how could emerging technologies change the way firms set their price to consumers? The proposed master thesis aims to explore this uncovered topic, and present a global overview of pricing policies consumers are about to face with the Big data revolution. |
dc.description.abstract |
The master thesis has the objective to describe and analyse the impact of technologies drastic improvements over firm’s strategical behaviour. First-degree price discrimination has been considered for centuries as a mirage to apply in competitive markets, due to consumer’s differentiated tastes and preferences over goods. On the other hand, the last decades have led to an exponential growth in machine learning performance and computer technologies. Such unexpected evolution permits firms to manipulate an increasing amount of data, and enlarge their perspectives on customer’s reservation price knowledge. Here lies one of the greatest challenges of the new era: how could emerging technologies change the way firms set their price to consumers? The proposed master thesis aims to explore this uncovered topic, and present a global overview of pricing policies consumers are about to face with the Big data revolution. |