Bibliographic Metadata

Title
How artificial intelligence (AI) innovators profit from innovation in digital platform ecosystems : an explorative business model study / Slobodanka Dana Kathrin Tomic, PhD
AuthorTomic, Slobodanka Dana Kathrin
CensorGruber, Marc
PublishedWien, 2018
DescriptionVIII, 78 Seiten : Illustrationen
Institutional NoteTechnische Universität Wien, Masterarbeit, 2018
Institutional NoteWirtschaftsuniversität Wien, Masterarbeit, 2018
Annotation
Literaturverzeichnis: Seite 61-71
LanguageEnglish
Document typeMaster Thesis
Keywords (DE)Artificial Intelligence / AI / AI technology solutions / digital platform / business model / innovation
Keywords (EN)Artificial Intelligence / AI / AI technology solutions / digital platform / business model / innovation
URNurn:nbn:at:at-ubtuw:1-115188 Persistent Identifier (URN)
Restriction-Information
 The work is publicly available
Files
How artificial intelligence (AI) innovators profit from innovation in digital platform ecosystems [1.06 mb]
Links
Reference
Classification
Abstract (English)

The topic of this thesis is the relationship between the business models (BMs) of the firms which create artificial intelligence (AI) solutions in complex digital platform ecosystems and their success in profiting from innovation. The AI technology endows machines and processes with human-like communication and perception abilities, and with the capacity to learn from data and optimize at scale not accessible to humans. The AI technology solutions depend on the underlying digital solutions for access to data and computation resources. An AI solution is a digital product offered over a complex platformbased architecture that combines internal innovation with complementary assets some of which are controlled by other companies. According to theory, external complementary assets have substantial impact on how much a firm can profit from innovation. How key assets are allocated and controlled is part of a firms business model. The aim of the thesis is to systematize BMs of AI innovators into a typology of patterns and to analyze how AI innovators of different types profit from their innovation. The thesis adopts the qualitative content analysis of the information acquired in e-research. The particular focus of this study is on the AI innovators who are registered in the CrunchBase database, and who were acquired by other companies. The BM information is extracted from the websites of firms and the information about the acquisition. The hypotheses are: H1) Based on the collected data, a small number of distinct patterns can be identified; H2) The motivation for acquisition is to improve not only operational capabilities but also higher-order transformative capabilities, H3) The existing theory can be applied to BM patterns to reason about the emergence of the dominant design. The result of the thesis is a typology of BM patterns and the underpinning analysis framework. The research prospects include verifying the typology and the analysis framework in both case studies and a larger sample of companies and conducting quantitative studies based on surveys and interviews with experts and managers to verify the findings.

Stats
The PDF-Document has been downloaded 25 times.