TY - JOUR
T1 - The dark side of data ecosystems
T2 - A longitudinal study of the DAMD project
AU - Aaen, Jon
AU - Nielsen, Jeppe Agger
AU - Carugati, Andrea
PY - 2022
Y1 - 2022
N2 - Data are often vividly depicted as strategic assets that organisations can (re)use to create value for myriad purposes. However, the same qualities that make data so appreciated—that is, their volume, their value for a plurality of stakeholders and their indefinite reuse capacity—also have a dark side: data reuse can lead to deviant data use that undermines the legitimacy of data analytics initiatives. To investigate this dynamic, we build on the notion of data ecosystems and provide empirical evidence from a longitudinal, 15-year case study of the emergence, expansion and eventual collapse of a large-scale data analytics project—called DAMD—in the Danish health care sector. We demonstrate that data reuse in the evolving data ecosystem elicited a data reuse dark side that was so dominant that it eventually resulted in the project’s demise. We conceptualize the reuse dark side’s three major mechanisms as function creep, stakeholder creep and data creep. Based on these insights, we develop an empirically grounded Data Analytics Ecosystem Model that extends the current understanding of data ecosystems and provides a view of these ecosystems as having both a bright and a dark side.
AB - Data are often vividly depicted as strategic assets that organisations can (re)use to create value for myriad purposes. However, the same qualities that make data so appreciated—that is, their volume, their value for a plurality of stakeholders and their indefinite reuse capacity—also have a dark side: data reuse can lead to deviant data use that undermines the legitimacy of data analytics initiatives. To investigate this dynamic, we build on the notion of data ecosystems and provide empirical evidence from a longitudinal, 15-year case study of the emergence, expansion and eventual collapse of a large-scale data analytics project—called DAMD—in the Danish health care sector. We demonstrate that data reuse in the evolving data ecosystem elicited a data reuse dark side that was so dominant that it eventually resulted in the project’s demise. We conceptualize the reuse dark side’s three major mechanisms as function creep, stakeholder creep and data creep. Based on these insights, we develop an empirically grounded Data Analytics Ecosystem Model that extends the current understanding of data ecosystems and provides a view of these ecosystems as having both a bright and a dark side.
KW - Data analytics
KW - Patrick Mikalef, Aleš Popovic, Jenny Eriksson Lundström and Kieran Conboy
KW - dark side
KW - data ecosystems
KW - data reuse
KW - longitudinal case study
UR - http://www.scopus.com/inward/record.url?scp=85110897955&partnerID=8YFLogxK
U2 - 10.1080/0960085X.2021.1947753
DO - 10.1080/0960085X.2021.1947753
M3 - Journal article
SN - 0960-085X
VL - 31
SP - 288
EP - 312
JO - European Journal of Information Systems
JF - European Journal of Information Systems
IS - 3
ER -