How do AI startups build trust in their smart service systems?


Bachelor Thesis, 2017

43 Pages, Grade: 1,3


Excerpt


Contents

List of abbreviations

List of figures

1 Introduction

2 Theoretical Background
2.1 Trust
2.1.1 Definition and conceptualization
2.1.2 Initial trust and continuous trust
2.2 Why AI startups have a hard time building trust in their smart service systems
2.2.1 Service Systems
2.2.2 Smart Service Systems
2.3 Strategic spheres of activity and hypotheses
2.3.1 “Transparency”
2.3.2 “Recognition by third parties”
2.3.3 “Points of contact”

3 Method & Data
3.1 Method: An abductive approach drawing on QCA
3.2 Framework
3.3 Coding
3.4 Sample

4 Discussion of results
4.1 Description of results
4.2 Discussion of hypotheses
4.3 Additional findings
4.4 Limitations

5 Conclusion and outlook

6 References

Appendix A

Affidavit (Eidesstattliche Erklärung)

Excerpt out of 43 pages

Details

Title
How do AI startups build trust in their smart service systems?
College
Free University of Berlin  (Fachbereich Wirtschaftswissenschaft)
Course
Wirtschaftsinformatik
Grade
1,3
Author
Year
2017
Pages
43
Catalog Number
V450622
ISBN (eBook)
9783668846227
ISBN (Book)
9783668846234
Language
English
Keywords
AI, Trust, smart service system, startup, start-up, service system, QCA, qualitative comparative analysis, SaaS, B2B, marketing, service-dominant, SDL, MIS, service-dominant logic
Quote paper
Lobosch Pannewitz (Author), 2017, How do AI startups build trust in their smart service systems?, Munich, GRIN Verlag, https://www.grin.com/document/450622

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