Perception of consumers regarding the use of data in the sharing economy
Notice bibliographique
Résumé
Abstract Title Perception of consumers regarding the use of data in the sharing economy. Authors Laval Maeva & Noiraut Alexian Level Bachelor thesis, 15 ECTS credit Supervisor Venilton Reinert Examiner Hélène Laurell Keywords sharing economy, Y generation, consumers’ perception, and data Background As link between consumption of collaborative economy and perception of data had not yet been investigated; a more indepth analysis of consumer perception of data use by companies is needed. Purpose The purpose of this study is to understand the consumers’ perception about the use of their data by companies of the sharing economy. The goal is to see if they are aware of this phenomenon and if it would modify their behavior regarding the use of these online platforms. Research Question How does the generation Y perceive the fact that companies use their data in Sharing Economy businesses? Method A quantitative, qualitative research has been done for this study to understand generation Y's perception of the sharing economy regarding the use of data by companies. With this research, we focused on a survey but also on four focus groups composed of five persons: French students aged from 18 to 25 years old who travel often for both studies and leisure. We took people from different social backgrounds and have chosen different studies. We emphasize this research with previous theories about the consumer behavior with the buyer decision process in the sharing economy, the selfperception and the price-perception. Theoretical framework: Theories regarding perception on several aspects, from the individual values, to benefit going through price have been included as a basis of discussion in order to analyze our empirical findings. Findings and conclusion Through our research study, we have seen that the Y generation uses the sharing economy essentially for the economy benefit and the time saved but also for its social character and its environmental aspect. Data protection is a really concerning matter for Y generation but they don’t do much about it. Internet use is essential for young people so they accept, when they are aware, to give their data against the free usage of the platform. In addition, we have noticed that the main marketing application of data collection, customized advertising, are misconducted by companies and doesn’t reach users. Despite the awareness of users regarding the protection of data, this generation thinks that collaborative platforms are not so intrusive in their privacy regarding personal information request.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,005 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».