Data science, i.e., making sense and deriving insights from data has been at the heart of scientific endeavor for centuries. However, very recently significant new questions and opportunities have arisen due to the advent of big data and advancements in data storage and analytics. This has not only stimulated new research in data science by information systems (IS) scholars, but also had a fundamental impact on traditional core fields, such as Business Intelligence and Decision Support Systems. In this track, we welcome the full variety of IS research on data science and Business Analytics (BA). This ranges from the generation, collection and representation of (big) data, over advancements in statistical & machine learning techniques to applications of predictive and prescriptive analytics in various business contexts. In addition, the track invites submissions in the areas of Business Intelligence, data warehousing and Decision Support Systems, also in the context of big data. We encourage the submission of relevant and novel contributions in the area of data science & business analytics while embracing the methodological breadth of the field, including quantitative and qualitative papers as well as design science oriented papers.

Mögliche Themen

• Big data collection, storage and integration
• (Big) data management, such as data quality management, metadata management and data governance
• The role of open data and data marketplaces
• Predictive analytics and prescriptive analytics
• Statistical & machine learning methods for big data, including web analytics, network analytics, streaming analytics and text mining, as well as their applications
• Visualisation of big data and visual analytics
• Business value and strategic implications of big data, including data driven innovation
• Business Intelligence, data warehousing and in-memory analytics
• Decision Support Systems
• BA organisational use and impact

Track chairs

Contact Track Chairs

Associate Editors

Henning Baars, Universität Stuttgart
Ivo Blohm, Universität St.Gallen
Tobias Brandt, Albert-Ludwigs-Universität Freiburg
Ralf Buschermöhle, Hochschule Osnabrück / Fakultät Management, Kultur und Technik
Verena Dorner, KIT
Jan Fabian Ehmke , Freie Universität Berlin
Carsten Felden, TU Bergakademie Freiberg
Stefan Feuerriegel, Universität Freiburg
Christoph Flath, Universität Würzburg
Gilbert Fridgen, Universität Bayreuth
Burkhardt Funk, Universität Lüneburg
Michaela Geierhos, Universität Paderborn
Peter Gluchowski, Technische Universität Chemnitz
Gundula Heinatz Bürki, Mobiliar / Leiterin Mobiliar Lab für Analytik der ETH
Andreas Hilbert, Technische Universität Dresden
Christian Janiesch, Universität Würzburg
Hans-Georg Kemper, Universität Stuttgart
Ralf Knackstedt, Stiftung Universität Hildesheim
Stefan Lessmann, HU Berlin
Marco Meier, Universität Augsburg
Oliver Müller, IT University of Denmark, Kopenhagen, Dänemark
Torsten Priebe, Simplity
Bodo Rieger, Universität Osnabrück
Michael Scholz, Universität Passau
Thomas Setzer, KIT
Mariya Sodenkamp, Otto-Friedrich Universität Bamberg
Steffen Stock, Europäische Fachhochschule
Leena Suhl, Universität Paderborn
Jochen Wulf, IWI, Universität St.Gallen

Data Science & Business Analytics

13.02.2017, 11:00-12:30, Raum: 01-011

Session Chair: Barbara Dinter

Jens Passlick; Benedikt Lebek; Michael H. Breitner: A Self-Service Supporting Business Intelligence and Big Data Analytics Architecture

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Christian Dremel; Sven Overhage; Sebastian Schlauderer; Jochen Wulf: Towards a Capability Model for Big Data Analytics

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Mateusz Dolata; Falk Uebernickel; Gerhard Schwabe: The power of words: Towards a methodology for progress monitoring in design thinking projects

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13.02.2017, 13:30-15:00, Raum: 01-011

Session Chair: Michael Scholz

Marcel Rhyn; Ivo Blohm: A Machine Learning Approach for Classifying Textual Data in Crowdsourcing

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Marc Egger; Gloria Volkmann; Detlef Schoder: Erhebung und Diagnostik von Markenassoziationsnetzwerken auf Grundlage nutzergenerierter Inhalte

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Matthias Hauser; Sebastian Günther; Christoph Flath; Frédéric Thiesse: Leveraging RFID Data Analytics for the Design of an Automated Checkout System

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13.02.2017, 15:30-17:00, Raum: 01-011

Session Chair: Christoph Flath

Christoph Gleue; Dennis Eilers; Hans-Jörg von Mettenheim; Michael H. Breitner: Decision Support for the Automotive Industry: Forecasting Residual Values using Artificial Neural Networks

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Christopher Kohl; Dalia Mostafa; Markus Böhm; Helmut Krcmar: Disruption of Individual Mobility Ahead? A Longitudinal Study of Risk and Benefit Perceptions of Self-Driving Cars on Twitter

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Mariya Sodenkamp; Ilya Kozlovskiy; Konstantin Hopf; Thorsten Staake: Smart Meter Data Analytics for Enhanced Energy Efficiency in the Residential Sector

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14.02.2017, 11:00-12:30, Raum: 01-102

Session Chair: Jan Krämer

Dominikus Kleindienst; Daniela Waldmann: Dead or Alive? A Formal Decision Model for Deciding on Customer Recovery Investments

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Christof Naumzik; Dirk Neumann; Stefan Feuerriegel: Understanding Consumer Behavior in Electronic Commerce with Image Sentiment

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Darius Schlangenotto; Dennis Kundisch: Over-Paid Search: When Bricks-and-Mortar Retailers Should Not Use Paid Search *Best Paper Nominee*

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