-------- Weitergeleitete Nachricht -------- Betreff: [AISWorld] Final CfP ECIS 2017 T05. Business Analytics and Data Science for Business Performance Datum: Tue, 29 Nov 2016 21:52:24 +0100 Von: Aleš Popovič ales.popovic@ef.uni-lj.si An: aisworld@lists.aisnet.org

=== FINAL CALL FOR PAPERS ===

European Conference on Information Systems (ECIS 2017)

Track 05: Business Analytics and Data Science for Business Performance

June 5th-10th 2017 / Guimarães, Portugal

Deadline for paper submissions: December 3, 2016

=== TRACK CHAIRS ===

Aleš Popovič University of Ljubljana, Slovenia ales.popovic@ef.uni-lj.si [ales.popovic@ef.uni-lj.si]

Barbara Dinter Chemnitz University of Technology, Germany barbara.dinter@wirtschaft.tu-chemnitz.de [barbara.dinter@wirtschaft.tu-chemnitz.de]

Christian Janiesch University of Würzburg, Germany christian.janiesch@uni-wuerzburg.de [christian.janiesch@uni-wuerzburg.de]

=== TRACK DESCRIPTION === (full version: http://www.ecis2017.eu/wp-content/uploads/2016/05/ECIS2017-T05.pdf [http://www.ecis2017.eu/wp-content/uploads/2016/05/ECIS2017-T05.pdf] )

ECIS 2017 CfP: Business Analytics and Data Science Track

Business Analytics is not limited to a traditional and isolated organizational focus. The Application of Business Analytics and Data Science approaches enables us to integrate, analyze, visualize, and ultimately understand and improve the complex processes that make up our digitized world. Such approaches are, therefore, great enablers for knowledge discovery benefitting people, organizations, societies, while leading to the smart technologies. Improved communication, more sustainable processes as well as new business models are examples for the innovative usage of disparate data sources (such as mobile, Internet of Things/ wearables/ streaming data, social media data.). This changes the nature of interaction and use of information exchange technologies along with the information is consumed at the individual, team, and organizational level, or even in global settings. Motivated by the explosion of interest in these emerging fields, the Business Analytics and Data Science for Business Performance track aims to promote multidisciplinary contributions dealing with managerial, economic, methodological, cultural, and technological perspectives. Submissions based on theoretical research, design research, action research, or behavioural research are encouraged. We welcome full research papers, research in progress papers, and prototype papers.

The track’s topics of interest include, but are not limited to:

Business Intelligence and Analytics (BI&A) * Strategic and change management issues stemming from BI&A * Adoption, implementation, routinization and use of BI&A * Organizational issues in BI&A implementation and success * Descriptive BI, predictive and prescriptive analytics for operational process improvement * Real time data warehousing and operational BI, event-driven BA, business activity monitoring * BI&A’s new frontiers: e.g. social (media) BI&A, BI&A in the cloud, BI&A as a service * Applications (e.g. CRM, HRM) and success of BI&A * BI&A for decision support; visual analytics; in-memory analytics

Data Science * Big data driven business model innovation and applications * Adoption and utilization of big data analytics for improving process and firm performance * Big data in Internet of Things, people, organizations, and markets * Architectures, technical and organizational approaches to facilitate the handling of big data * Applications of various analytics approaches in healthcare, sports, education, habitat planning, smart cities, etc. * Applications using wearables and the Internet of Things.

We are looking forward to seeing you in Portugal 2017! _______________________________________________ AISWorld mailing list AISWorld@lists.aisnet.org