The matching algorithm presents the main
contribution of this study. The foundations are closely
based on MST and the proposed results are evaluated
through interviews. The algorithm allows for an
adaption for varieties of technological solutions, e.g.
management systems with discussion sections, due to
its high level of abstraction and with generalizability.
Future research could focus on matching
technological solutions with the needs of certain
professional fields, e.g. for researchers or legal
consultants, as we did not specify the requirements of
certain professions. We assessed the insights of the
evaluation cautiously because of the following weak
points. The number of interviewed experts was
relatively small and thus provides only indicative
results. Insights by expert interviews are known to
tend to rather validate whatever is assumed
beforehand (Kromrey, Roose and Strübing, 2016).
Subsequent studies could provide further insights for
enhancing the matching algorithm, also including
longitude studies analyzing changes of technology
use over time (DeSanctis and Poole, 1994) or
focusing on specific industries or requirements by
diverse user groups. The proposed results of the
matching algorithm can serve virtual teams by
optimizing their technology choice and support future
decisions in technology design.
The current revival of “the three Ds” - the trends
and visions of new work - manifests in deploying
virtual teams, and it is enabled through new
technology and requested by the current and future
workforce. Scientific research is encouraged to
further develop an understanding and moreover
provide guidance for these and upcoming trends and
visions of new work.
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