[AISWorld] Final CFP - ECIS 2022 - Track Business Analytics and Big Data

[Barbara Dinter]

30th European Conference on Information Systems (ECIS 2021) June 18 - 24, 2022



- Timisoara, Romania -



Track: Business Analytics and Big Data

(https://ecis2022.eu/tracks-description/)



*Track Description*



Recent global challenges, such as the COVID 19 crisis, have more than ever revealed the need for united societies overcoming national egoisms and inequalities. In order to achieve this vision, big data and the manifold opportunities to gain insights and generate value by sharing, enriching and analyzing this data constitute an indispensable enabler. The application of business analytics allows us to integrate, analyze, visualize, and ultimately understand and improve the complex processes that make up our digitized world. Such approaches foster the transformation of societies and organizations. With the enthusiasm around business analytics comes responsibility, as analytics can amplify digital divides, trigger affronts to human dignity, and be used to incite distrust rather than unify in solidarity.



This track aims to promote multidisciplinary contributions dealing with organizational, technological, cultural, ethical and societal perspectives and challenges of business analytics. We call for submissions based on quantitative and qualitative work as well as theoretical, design, action, or behavioral research. Furthermore, we encourage papers demonstrating the organizational impact of business analytics and big data in terms of competitive performance, innovativeness, as well as inclusion and community building. Papers solely dealing with AI and machine learning are not the focus of this track.



Suggested topics include, but are not limited to:

- The role of business intelligence, business analytics, and big data for new horizons in digitally united societies

- Business analytics for social good

- Strategic and change management issues stemming from business analytics and big data

- Business value of business analytics and big data

- Adoption, routinization, maturity, use, and innovative applications of business analytics and big data

- Data humanism, data harm and societal implications of datafication

- Data privacy, data quality, and data governance

- Opportunities and challenges of sharing data and of open data

- Data-driven business model innovation, data entrepreneurship, and the digital ecosystem big data

- Data visualization, visual analytics

- Process mining and the benefits of robotic process automation





*Track Chairs*



Patrick Mikalef, Norwegian University of Science and Technology, Norway, patrick.mikalef at ntnu.no<mailto:patrick.mikalef at ntnu.no> (Contact)

Barbara Dinter, Chemnitz University of Technology, Germany, barbara.dinter at wirtschaft.tu-chemnitz.de<mailto:barbara.dinter at wirtschaft.tu-chemnitz.de>

Christian Janiesch, TU Dortmund University, Germany, christian.janiesch at tu-dortmund.de<mailto:christian.janiesch at tu-dortmund.de>

Olgerta Tona, University of Gothenburg, Sweden, olgerta.tona at ait.gu.se<mailto:olgerta.tona at ait.gu.se>



*Associate Editors*



Stephan Aier, University of St. Gallen, Switzerland; Henning Baars, University of Stuttgart, Germany; Sule Balkan, Ameriprise Information Management, USA; Imad  Bani-Hani, Linnaeus University, Sweden; Ivo Blohm, University of St. Gallen, Switzerland;  Maria Boura, Athens University of Economics and Business, Greece; Tobias Brandt, Erasmus University Rotterdam, Netherlands; Jessica Braojos, IQS School of Management, Spain; Patrick Delfmann, University of Koblenz, Germany; Christian Dremel, Norwegian University of Science and Technology, Norway; Rameshwar Dubey, Liverpool John Moores University, UK;  Adir Even, Ben-Gurion University of the Negev, Israel; Christoph Flath, University of Würzburg, Germany; Caddie Gao, Monash University, Australia; Michail Giannakos, Norwegian University of Science and Technology, Norway; Manjul Gupta, Florida International University, USA; Kai Heinrich, University of Magdeburg, Germany; Konstantin Hopf, University of Bamberg, Germany; Oyku Isik, Vlerick Business School, Belgium; Najmul Islam, Lappeenranta-Lahti University of Technology LUT, Finland; Arpan Kar, Indian Institute of Technology, IIT Delhi, India; Natalia Kliewer, Freie Universität Berlin, Germany; John Krogstie, Norwegian University of Science and Technology, Norway; Markus Lahtinen, Lund University, Sweden; Nuno Laranjeiro, University of Coimbra, Portugal; Alexander Mädche, Karlsruhe Institute of Technology, Germany; Vasili Mankevich, University of Gothenburg, Sweden; Olivera Marjanovic, University of Technology Sydney, Australia; Roland Müller, Berlin School of Economics and Law, Germany; Oliver Müller, University of Paderborn, Germany; John Otieno Oredo, University of Nairobi, Kenia; Elisabetta Raguseo, Polytechnic of Torino, Italy; Gregory Richards, University of Ottawa, Canada; Laura Ruiz, University of Granada, Spain; Tiilikainen Sanna , Aalto University, Finland; Thomas Setzer, Catholic University of Eichstätt-Ingolstadt, Germany; Ramesh Sharda, University of Oklahoma, USA; Arisa Shollo, Copenhagen Business School; Konstantina Spanaki, Audencia Business School, France; Cristina               Trocin, Norwegian University of Science and Technology, Norway; Rogier van de Wetering, Open Universitat, Netherlands; William Yeoh, Deakin University, Australia; Patrick Zschech, Friedrich-Alexander University Erlangen-Nuremberg, Germany;



*Important Dates*



17 November 2021: Submission deadline

28 February 2022: Notification of conditional acceptance

22-24 June 2022: ECIS 2022 main conference



We are looking forward to your submissions and seeing you _physically_ in Timisoara!



Kind regards

Patrick , Barbara, Christian, and Olgerta


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Prof. Dr. Barbara Dinter

Chemnitz University of Technology

Faculty of Economics and Business Administration

Business Information Systems Group



Thueringer Weg 7, 09126 Chemnitz, Germany

Barbara.Dinter at wirtschaft.tu-chemnitz.de<mailto:Barbara.Dinter at wirtschaft.tu-chemnitz.de>

http://www.tu-chemnitz.de/wirtschaft/wi1