[AISWorld] Call for Papers: Data-Driven Knowledge Management –(DDKM 2019) within the 10th Conference on Professional Knowledge Management

Wed Oct 10 07:49:10 EDT 2018

Call for Papers: Data-Driven Knowledge Management –(DDKM 2019) within the 10th Conference on Professional Knowledge Management:

Workshop Website: http://wm2019.fh-potsdam.de/workshops/data-driven-knowledge-management.html

Conference: http://wm2019.fh-potsdam.de/index-en.html

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Scope

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Data-driven technologies are changing and shaping organizational processes, supply chains and business models. This also affects the way how knowledge can be is managed at the individual, organizational and inter-organizational level.
Data-driven technologies offer new opportunities to explicate information and knowledge from organization members, provide personalized decision support, provide learning material during the execution of business processes, or find suitable partners for joint knowledge creation and knowledge sharing. Data-driven technologies also entail the risk of increased knowledge leakage or other knowledge-related risks, which could implicate that an organization loses its competitive edge. Hence, both knowledge protection and an improved (knowledge) risk management become crucial activities of an integrated knowledge management in connected supply chains that are characterized by massive data exchange and collaboration among diverse market actors.

The scope of this workshop is to discuss how data-driven technologies impact the way how organizations manage knowledge to develop and maintain competitive advantage, to develop new knowledge-based business models or to renew existing business models. Additionally, methods and approaches to address the above-mentioned risks shall be discussed.

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Topics of Interest

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Submissions from all areas contributing to the development and application of Data-Driven Knowledge Management are welcome. We explicitly encourage paper submissions from all kinds of disciplines such as computer science, social sciences, mathematics, management and economics in order to obtain an interdisciplinary view on the subject.

Topics of interest include but are not limited to:

  *   Data-driven knowledge management for improved decision making
  *   Application of data-driven knowledge management in industry
  *   Knowledge codification supported by data analytics
  *   Data-driven technology-enhanced learning and unlearning
  *   Knowledge-based business models
  *   Knowledge protection in connected supply chains
  *   Knowledge risk management in data-driven environments
  *   New (alternative) governance mechanisms for data-driven knowledge management

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Submission Guideline

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All papers are to be submitted via the EasyChair system: https://easychair.org/cfp/DDKM2019

Papers should be preferably in English and must be in the LNI format (for templates see http://wm2019.fh-potsdam.de/index-en.html#workshops

(http://wm2019.fh-potsdam.de/index-en.html#workshops)). Author’s instructions, along with LaTeX and Word macro files, are available at Springer’s website.

Submissions should be original papers that have not already been published elsewhere. However, papers may include previously published results that support a new theme, as long as all past publications are fully referenced.

We accept two types of submissions: Full papers (up to 16 pages), Short papers (up to six pages) and position papers (2 pages). Full papers are for mature work, requiring elaborate explanations of the conceptual background, methodology and data as well as an analysis. Short papers present work in progress, new, yet underdeveloped ideas worth discussing in the workshop. Position paper poses a problem or question and a possible answer or (technical) solution to be discussed at the workshop.

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Important dates

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Submission deadline for workshop contributions: 17 December 2018

Notification of acceptance of the papers: 14 January 2019

Camera-ready copy of the papers: 16 February 2019

Workshop at WM2019 in Potsdam: 18-20 March 2019

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Organizing committee

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  *   Stefan Thalmann, Karl-Franzens University, Graz, Austria
  *   Daniel Bachlechner, Fraunhofer Institut für System- und Innovationsforschung, Karlsruhe, Germany
  *   Susanne Durst, School of Business, University of Skövde, Skövde, Schweden

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Univ.-Prof. Dr. Stefan Thalmann
University of Graz
School of Business, Economics and Social Sciences

Elisabethstraße 50b
8010 Graz, Austria

Tel. +43 (0) 316 380 7215
E-Mail: stefan.thalmann at uni-graz.at<mailto:stefan.thalmann at uni-graz.at>