Information Technology Reference
The high score for discretions of alignment staff members can be related to
unawareness of the technical geoICT possibilities of strategic staff members in these
three partnerships. In contrast, in all these three cases, the alignment staff mem-
bers are in active contact with the technical experts in this field (such as private
IT companies or universities). This active contact provides them the opportunity
to maneuver around or even outside higher-level coordination requirements. One
theory that could explain this behavior is social network theory, for example, which
emphasizes that the networks in which individual staff members are active are
influential and have the capability to make organizations opt for certain solutions.
The scores for the aspect of “personal tasks simplification” reveal that in two
cases, Dataland and Sabimos, it was the dominant justification to bypass the coor-
dination requirements. In both these cases, the task simplification actions consisted
of avoiding constructing geoICT interoperability (with other existing geoICT
systems). This finding has be put in context with the fact that the Dataland and
Sabimos cases are different from the AHN and the Cadastral cases in both the
amount of partners and resources available to construct interoperable database,
workflow, and IT system models. With fewer resources, tackling interoperability
constraints is possible through making tasks simpler. Instead, they opt to either
maintain two parallel systems or utilize one of these systems at their convenience.
In contrast, for the staff members in the AHN and the Cadastral cases, interoper-
ability of systems is so crucial that simplification of tasks is not an issue.
Comparing the scores on “client interests” reveals that only in the Cadastral
case did discretions emerge with client interests in mind. In all other cases, this
aspect scores low, implying that practitioners in these cases are less willing to adapt
the requirements of specific geoICT coordination in favor of requirements of par-
ticular clients. An obvious difference between the cases is that the client base for
the Cadastral case is much more confined to a particular domain than the client
base for all other cases. Clients from the Cadastral data are primarily actors in the
land and property sector, whereas clients in all other cases are from a larger variety
of sectors (AHN data are used by actors in both water and environment; Dataland
data are used by small- and medium-sized enterprises; Sabimos data are used by
government, citizens, and transport companies). Adhering to needs of a specific
client is thus easier in the Cadastral case as compared to all other cases.
9.7 interpretation of Discretion Findings with theory
The comparison of scores reveals that discretions vary with the context of indi-
vidual staff members and with the justification that staff members utilize to reach
to discretions. The comparison of the discretion aspect scores across the cases can
be further explained using a number of theoretical frameworks.
The similar values of “cognitive filter to the environment” reflect a practice
of mimicking or isomorphism across the geoICT domain. The mimicking can