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Bibtex
Cite as text
@Select Types{,
Journal = "Band-1",
Title= "Business Strategies for Data Monetization: Deriving Insights from Practice",
Author= "Julius Baecker, Martin Engert, Matthias Pfaff and Helmut Krcmar",
Doi= "https://doi.org/10.30844/wi_2020_j3-baecker",
Abstract= "Although increases in available data have inspired companies’ interest in creating and extracting value from it, many lack the insight and guidance to assess the potential data offer. To address this issue, we conduct a systematic literature review to create a universe of 102 real-world cases from diverse industries with regard to the use of data. Based on an analysis of these cases, this paper provides a set of 12 generic strategies for monetizing data, ranging from sole asset sale to strategically opening data and guaranteeing control. This study supports business practice by aggregating the wide range of established approaches of data monetization from practice for operational purposes. It advances theoretical understanding of value capturing from data and suggests important avenues for future work in this emerging field of research.
",
Keywords= "Data monetization, data-driven business models, big data, datadriven decision making",
}
Julius Baecker, Martin Engert, Matthias Pfaff and Helmut Krcmar: Business Strategies for Data Monetization: Deriving Insights from Practice. Online: https://doi.org/10.30844/wi_2020_j3-baecker (Abgerufen 17.04.24)
Open Access
Abstract
Abstract
Although increases in available data have inspired companies’ interest in creating and extracting value from it, many lack the insight and guidance to assess the potential data offer. To address this issue, we conduct a systematic literature review to create a universe of 102 real-world cases from diverse industries with regard to the use of data. Based on an analysis of these cases, this paper provides a set of 12 generic strategies for monetizing data, ranging from sole asset sale to strategically opening data and guaranteeing control. This study supports business practice by aggregating the wide range of established approaches of data monetization from practice for operational purposes. It advances theoretical understanding of value capturing from data and suggests important avenues for future work in this emerging field of research.
Keywords
Schlüsselwörter
Data monetization, data-driven business models, big data, datadriven decision making
References
Referenzen
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