TY - CHAP

T1 - How does Enterprise Architecture support the Design and Realization of Data-Driven Business Models?

T2 - 16th International Conference on Business Information Systems Engineering - WI 2021

AU - Rashed, Faisal

AU - Drews, Paul

N1 - Conference code: 16

PY - 2021/1/1

Y1 - 2021/1/1

N2 - As part of the data evolution, data-driven business models (DDBMs) have emerged as a phenomenon in great demand for academia and practice. Latest technological advancements such as cloud, internet of things, big data, and machine learning have contributed to the rise of DDBM, along with novel opportunities to monetize data. While enterprise architecture (EA) management and modeling have proven its value for IT-related projects, the support of EA for DDBM is a rather new and unexplored field. Building upon a grounded theory research approach, we shed light on the support of EA for DDBM in practice. We derived four approaches for DDBM design and realization and relate them to the support of EA modeling and management. Our study draws on 16 semi-structured interviews with experts from consulting and industry firms. Our results contribute to a still sparsely researched area with empirical findings and new research avenues. Practitioners gain insights into reference cases and find opportunities to apply EA artifacts in DDBM projects.

AB - As part of the data evolution, data-driven business models (DDBMs) have emerged as a phenomenon in great demand for academia and practice. Latest technological advancements such as cloud, internet of things, big data, and machine learning have contributed to the rise of DDBM, along with novel opportunities to monetize data. While enterprise architecture (EA) management and modeling have proven its value for IT-related projects, the support of EA for DDBM is a rather new and unexplored field. Building upon a grounded theory research approach, we shed light on the support of EA for DDBM in practice. We derived four approaches for DDBM design and realization and relate them to the support of EA modeling and management. Our study draws on 16 semi-structured interviews with experts from consulting and industry firms. Our results contribute to a still sparsely researched area with empirical findings and new research avenues. Practitioners gain insights into reference cases and find opportunities to apply EA artifacts in DDBM projects.

KW - Business informatics

KW - Data-driven

KW - Business model

KW - enterprise architecture

KW - Informatics

UR - https://aisel.aisnet.org/wi2021/EManagementofdigitalprocesses20/Track20/3/

UR - http://www.scopus.com/inward/record.url?scp=85119336159&partnerID=8YFLogxK

UR - https://www.mendeley.com/catalogue/e3e584de-d1bc-33d3-9841-a6fe691cab59/

U2 - 10.1007/978-3-030-86800-0_45

DO - 10.1007/978-3-030-86800-0_45

M3 - Article in conference proceedings

SN - 978-3-030-86799-7

T3 - Lecture Notes in Information Systems and Organisation

SP - 662

EP - 677

BT - Innovation Through Information Systems - Volume III

A2 - Ahlemann, Frederik

A2 - Schütte, Reinhard

A2 - Stieglitz, Stefan

PB - Springer Nature Switzerland AG

CY - Cham

Y2 - 9 March 2021 through 11 March 2021

ER -