Abstract
The goal of the master thesis is to identify factors influencing customers willingness to share private data. The reason behind this is the growing trend of digitalization and the vast number of information customers are sharing and retailers collecting. Relevant papers are screened while nonrelevant removed. Consequently, the remaining papers are evaluated by applying a qualitative content analysis resulting in important information to be structured and utilized which are utilized to create a catalogue of factors as the result of the master thesis. Similar factors are grouped into categories offering a comprehensive overview of the most influence aspects. Each factor is explained in detailed and provide insight as to how the customer behaves depending on the factor. As a result, a catalogue of 28 identified factors structured into 9 categories is created providing information and explanation on how each factor influences customers willingness. The result shows that some factors are more significant than others while unsignificant factors gain importance depending on other contexts and the relation between each factor. For instance, demographic factors like age and gender play an important role in customers willingness to share private data while privacy concerns drastically decrease it. However, this can be counterbalanced by rewards or a better company-customer relationship.
| Originalsprache | Englisch |
|---|---|
| Betreuung / Begutachtung |
|
| Publikationsstatus | Veröffentlicht - 2023 |
Wissenschaftszweige
- 303026 Public Health
- 305909 Stressforschung
- 102 Informatik
- 102006 Computer Supported Cooperative Work (CSCW)
- 102015 Informationssysteme
- 102016 IT-Sicherheit
- 502007 E-Commerce
- 502014 Innovationsforschung
- 502030 Projektmanagement
- 509026 Digitalisierungsforschung
- 501016 Pädagogische Psychologie
- 602036 Neurolinguistik
- 501030 Kognitionswissenschaft
- 502032 Qualitätsmanagement
- 502043 Unternehmensberatung
- 502044 Unternehmensführung
- 502050 Wirtschaftsinformatik
- 502058 Digitale Transformation
- 503008 E-Learning
- 509004 Evaluationsforschung
- 301407 Neurophysiologie
- 301401 Hirnforschung
JKU-Schwerpunkte
- Digital Transformation
Dieses zitieren
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver