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=== CALL FOR PAPERS ===
European Conference on Information Systems (ECIS 2019)
Track "Knowledge Management & Artificial Intelligence"
June 8-14, 2019, Stockholm, Sweden (
http://ecis2019.eu/)
Deadline for paper submissions: November 27th, 2018
=== TRACK DESCRIPTION ===
Full version:
http://ecis2019.eu/programme/research-tracks/knowledge-managament-and-ai/knowledge-management-and-ai-1.393835
Knowledge management (KM) scholars have emphasized the importance
of (big) data, information, and knowledge assets for decision
support, management, and leadership, thereby clearly indicating
the relation between human beings and technology. However, various
powerful digital technologies have led to substantial changes in
knowledge sharing practices. In this regard, the rise of
artificial intelligence (AI) is of special importance and creates
new opportunities on the interface between KM & AI.
This track raises the questions whether and how digitization in
general and AI in particular change the socio-technical aspects
related to knowledge sharing. With respect to the increasing
influence of digital technologies, AI, machine learning and the
importance of KM for organizations' daily business, we believe
that this research topic has the potential for valuable
contributions to both theory and practice. In addition, with
respect to AI, the question is how AI approaches can support
knowledge creation and especially help to externalize implicit
knowledge. Further, AI seems promising in context detection and,
thus, in the delivery of suitable training artefacts and in
connecting people.
Main goal of the track is to gather current research with an
emphasis on KM & AI as an integral part of a changing business
and social environment focusing on emerging trends such as sharing
society and economy. KM has become an interdisciplinary research
field - the traditional gap between researcher from a
technology-oriented versus a human-oriented angle has been bridged
by holistic, socio-technical approaches. We currently see strong
developments towards research on AI, changing digital tools (such
as the use of social software or machine learning for business and
private purposes) as well as towards entire digital business
models (such as multi-sided online platforms or networks and
online communities) fostering knowledge sharing across
organizations.
What needs to be addressed additionally are developments
complementary to digitization and AI, for instance geographical
dispersion, knowledge sharing across time zones, or
national/cultural influence factors. Due to the usage of AI in
collaborative technologies such as social software, organizational
and national boundaries become more blurred and knowledge can be
diffused much easier. Openness and inter-organizational
collaboration build the digital pathway of rich, contextualized
and sustainable knowledge sharing activities among networked
persons within and beyond organizational boundaries. Besides
benefits of the increased sharing also risks of losing competitive
advantage arise. Hence, organizations should carefully balance
their activities to promote and control knowledge sharing, to
protect their competitive knowledge.
Obviously, such developments have to be assessed carefully. One
might think of negative outcomes such as a limited work-life
balance or unwanted knowledge spill-overs. Furthermore, applying
AI in the context of KM raises also questions about ownership of
knowledge, control about data and ethical issues. All this takes
place in digital environments and leads to enormous changes of
KM-related socio-technical aspects which are rather
under-researched, so far.
This track aims to promote multi-disciplinary contributions
dealing with a managerial, an economic, a methodological, a
cultural or a socio-technical perspective. Submissions based on
theoretical research, design research, action research, or
behavioral research are encouraged. We welcome both full research
papers and research-in-progress papers.
Topics of interest include, but are not limited to:
* Application of AI in KM (e.g. blockchain)
* AI for knowledge creation (e.g. deep learning)
* KM in a sharing society
* Balancing knowledge sharing and knowledge protection for
inter-organizational collaboration
* From technology-oriented towards human-oriented KM in digital
environments
* Social and behavioral issues in the context of KM and AI
* KM and technology enhanced learning
* AI for technology-mediated social collaboration
* Knowledge life cycle and data-driven decision support
* Cross-organizational, cross-border and cross-cultural KM enabled
by AI
* AI to capture and share knowledge in social networks and
distributed contexts
* Support for mature KM solutions: KM governance, KM strategies,
KM maturity models, and KM performance
* KM and risk management
* KM for digital competency development
=== TRACK CHAIRS ===
Markus Bick, ESCP Europe Business School, Information &
Operations management, France, Germany, United Kingdom, Italy,
Spain, Poland. Email:
mbick@escpeurope.eu<mailto:mbick@escpeurope.eu>
Stefan Smolnik, University of Hagen, Germany. Email:
Stefan.Smolnik@FernUni-Hagen.de<mailto:Stefan.Smolnik@FernUni-Hagen.de>
Stefan Thalmann, University of Graz, Austria. Email:
stefan.thalmann@uni-graz.at<mailto:stefan.thalmann@uni-graz.at>
----------------------------------
Univ.-Prof. Dr. Stefan Thalmann
University of Graz
School of Business, Economics and Social Sciences
Elisabethstrasse 50b
8010 Graz, Austria
Tel. +43316 380 7215
E-Mail:
stefan.thalmann@uni-graz.at<mailto:stefan.thalmann@uni-graz.at>
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