Pathways of Data-driven Business Model Design and Realization: A Qualitative Research Study
Publikation: Beiträge in Sammelwerken › Aufsätze in Konferenzbänden › Forschung › begutachtet
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Pathways of Data-driven Business Model Design and Realization : A Qualitative Research Study . / Rashed, Faisal; Drews, Paul.
Proceedings of the 54th Annual Hawaii International Conference on System Sciences, HICSS 2021. Hrsg. / Tung X. Bui. Honolulu : University of Hawaiʻi at Mānoa, 2021. S. 5676-5685 (Proceedings of the Annual Hawaii International Conference on System Sciences; Band 2020-January).Publikation: Beiträge in Sammelwerken › Aufsätze in Konferenzbänden › Forschung › begutachtet
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TY - CHAP
T1 - Pathways of Data-driven Business Model Design and Realization
T2 - 54th Hawaii International Conference on System Sciences - HICSS 2021
AU - Rashed, Faisal
AU - Drews, Paul
N1 - Conference code: 54
PY - 2021
Y1 - 2021
N2 - Maximizing the value from data has become a key challenge for companies as it helps improve operations and decision making, enhances products and services, and ultimately, leads to new business models (BMs). Aiming to achieve the latter, companies take different pathways. Building on a grounded theory research approach, we identified four pathways for designing and realizing data-driven business models (DDBMs). To achieve this goal, we conducted 16 semi-structured interviews with experts from consulting and industry firms. The results fill the gap in the literature on the design and realization of DDBMs and act as a guide for companies.
AB - Maximizing the value from data has become a key challenge for companies as it helps improve operations and decision making, enhances products and services, and ultimately, leads to new business models (BMs). Aiming to achieve the latter, companies take different pathways. Building on a grounded theory research approach, we identified four pathways for designing and realizing data-driven business models (DDBMs). To achieve this goal, we conducted 16 semi-structured interviews with experts from consulting and industry firms. The results fill the gap in the literature on the design and realization of DDBMs and act as a guide for companies.
KW - Business informatics
KW - Business Intelligence
KW - business analytics and big data
KW - innovation
KW - deployment
KW - management business model
UR - http://www.scopus.com/inward/record.url?scp=85108329847&partnerID=8YFLogxK
UR - https://hdl.handle.net/10125/70871
UR - https://www.mendeley.com/catalogue/b2a391e2-a1e1-3cef-b5ff-0bb58cfd4ea4/
U2 - 10.24251/HICSS.2021.689
DO - 10.24251/HICSS.2021.689
M3 - Article in conference proceedings
SN - 978-0-9981331-4-0
T3 - Proceedings of the Annual Hawaii International Conference on System Sciences
SP - 5676
EP - 5685
BT - Proceedings of the 54th Annual Hawaii International Conference on System Sciences, HICSS 2021
A2 - Bui, Tung X.
PB - University of Hawaiʻi at Mānoa
CY - Honolulu
Y2 - 4 January 2021 through 8 January 2021
ER -