Publicação
Tokenomics models for a multi company loyalty programs: a Monte Carlo method approach - regulatory implications in the Eu
| datacite.subject.fos | Ciências Sociais::Economia e Gestão | pt_PT |
| dc.contributor.advisor | Zejnilovic, Leid | |
| dc.contributor.advisor | Mestrinho, Lénia | |
| dc.contributor.author | Croce, Martina | |
| dc.date.accessioned | 2025-03-24T10:25:39Z | |
| dc.date.available | 2025-03-24T10:25:39Z | |
| dc.date.issued | 2024-01-18 | |
| dc.date.submitted | 2024-01-18 | |
| dc.description.abstract | The research aims to provide Celfocus with a comprehensive comparative analysis of tokenomics models for multi-company loyalty programs, highlighting their strengths and weaknesses to aid informed decision-making. This involves an in-depth analysis of current loyalty schemes, assessing the impact of tokenization in the digital economy, and exploring how blockchain and gamification can transform customer loyalty experiences. The study includes the development of three unique token-based loyalty programs, designed to optimize benefits for both partner companies and customers. It also addresses challenges and regulatory considerations, with a particular focus on GDPR compliance. The effectiveness of these models was validated through a Monte Carlo analysis, which involved simulating various scenarios to identify critical elements and evaluating key performance indicators for a more profound understanding. | pt_PT |
| dc.identifier.tid | 203867289 | pt_PT |
| dc.identifier.uri | http://hdl.handle.net/10362/181164 | |
| dc.language.iso | eng | pt_PT |
| dc.relation | UID/ECO/00124/2013 | pt_PT |
| dc.subject | Blockchain | pt_PT |
| dc.subject | Loyalty program | pt_PT |
| dc.subject | Marketing | pt_PT |
| dc.subject | Technology | pt_PT |
| dc.subject | Monte Carlo simulation | pt_PT |
| dc.subject | Gamification | pt_PT |
| dc.subject | Tokenomics | pt_PT |
| dc.title | Tokenomics models for a multi company loyalty programs: a Monte Carlo method approach - regulatory implications in the Eu | pt_PT |
| dc.type | master thesis | |
| dspace.entity.type | Publication | |
| rcaap.rights | openAccess | pt_PT |
| rcaap.type | masterThesis | pt_PT |
| thesis.degree.name | A Work Project, presented as part of the requirements for the Award of a Master Degree in Business Analytics from the NOVA – School of Business and Economics | pt_PT |