* Apologies for cross-posting *

 

=== 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

Stefan Smolnik, University of Hagen, Germany. Email: Stefan.Smolnik@FernUni-Hagen.de

Stefan Thalmann, University of Graz, Austria. Email: stefan.thalmann@uni-graz.at

 

 

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Univ.-Prof. Dr. Stefan Thalmann

Karl-Franzens-Universität Graz

Sozial- und Wirtschaftswissenschaftliche Fakultät

 

Elisabethstraße 50b

8010 Graz

 

Telefon +43 (0) 316 380 7215

E-Mail: stefan.thalmann@uni-graz.at