Track Chairs

Barbara Dinter, Professor, Chemnitz University of Technology, Germany. Email: barbara.dinter@wirtschaft.tu-chemnitz.de

Patrick Mikalef, Research Fellow, Norwegian University of Science and Technology, Norway. Email: patrick.mikalef@ntnu.no

Paul A. Pavlou, Professor, Fox School of Business, Temple University, USA. Email: pavlou@temple.edu

Aleš Popovič, Associate Professor, University of Ljubljana, Slovenia. Email: ales.popovic@ef.uni-lj.si

Track Description

Business Analytics and Big Data

The transformation into a Sharing Society is reshaping the nature of information systems. Thereby, haring data, information, and knowledge constitutes the foundation for the “datafication of society”.  Consequently, novel and advanced approaches for collecting, storing, managing, and analysing data are required and challenge practitioners and academia as more and more data (big data) becomes available. This trend, as well as digitalisation in general, foster the assimilation and further development of business intelligence and business analytics (BI&A) approaches within organisations and across various industries. The Sharing Society has a boosting effect on the already unprecedented pace of data growth and complexity, with movements such as that of sharing and open data promising to generate sustainable value. In addition, governments and non-profit organisations can benefit from the new opportunities raised by BI&A applications and technologies.

Many scholars are now emphasising the importance of BI&A and big data approaches as well as information assets for efficient and effective decision support, management, and leadership. BI&A is essential for an organisations’ daily business, directly influencing firm performance and business development in a global world. It is not limited to a traditional and isolated organisational focus. The application of BI&A and big data approaches enables us to integrate, analyse, visualise, and ultimately understand and improve the complex processes that make up our digitised world. Such approaches are enablers for knowledge discovery benefitting societies, organisations, and individuals leading to smart technologies. Improved communication, more sustainable processes, as well as new business models are examples for the innovative use of disparate data sources (such as mobile, the Internet of Things, streaming data or social media data). Furthermore, the availability of seemingly endless computing and cheaper storage capabilities available through cloud computing enables new opportunities in providing a global gateway to information as a service and to a Sharing Society.

Over the past few years, there has much enthusiasm around big data analytics as organizations explore how they can leverage their data to create and maintain a competitive advantage. As such, today's companies try to collect and process as much data as possible, with the aim of improving their decision-making processes (Sharma et al., 2014). Nevertheless, while there is some empirical evidence that big data analytics can create value, the thesis that it leads to performance gains requires deeper analysis. To date, there is limited understanding of how organizations need to change to embrace these technological innovations, and the business shifts they entail (McAfee et al., 2012). As big data tools and applications diffuse into the organizational fabric, they will inevitably change longstanding ideas about decision making, management practices, and most importantly competitive strategy formulation (Kalinikos & Constantiou, 2015).

Motivated by the explosion of interest in these emerging fields, the present track aims to promote multidisciplinary contributions dealing with socio-economic, organizational, technological, cultural and societal perspectives. Furthermore, outcomes that demonstrate critical success factors on the organizational impact of big data and BI&A in terms of competitive performance, innovativeness, increased agility, and market capitalizing competence are encouraged. We welcome submissions based on quantitative and qualitative work, theoretical research, design research, action research, or behavioural research

Suggested topics include, but are not limited to:

• The role of BI&A and big data in a Sharing Society

• Emerging concepts and methodologies of BI&A

• Use cases and innovative applications of BI&A

• BI&A in and for the Sharing economy, BI&A in the cloud, BI&A as a service,

• Data, text and process mining for business analytics

• Social media analytics for business

• Data visualisation, visual analytics

• Real-time analytics and operational BI, event-driven BA

• BI&A and big data’s new frontiers in, e.g., social (media), sports, education, healthcare

• Big Data

• Strategic and change management issues stemming from BI&A and big data

• Business value and success of BI&A and big data

• Data-driven competitive advantage

• Adoption, routinisation, maturity, and use of BI&A and big data

• Big data management

• Big data driven business model innovation

• Digital ecosystem big data

• Data privacy, data quality, and data governance

• Digital manufacturing and the Internet of Things

• Human resource management in the data-driven enterprise

• Opportunities and challenges of sharing data and of open data

References

McAfee, A., Brynjolfsson, E., Davenport, T. H., Patil, D. J., & Barton, D. (2012). Big data. The management revolution. Harvard Business Review, 90(10), 61-67.

Kallinikos, J., & Constantiou, I. D. (2015). Big data revisited: a rejoinder. Journal of Information Technology, 30(1), 70-74.

Sharma, R., Mithas, S., & Kankanhalli, A. (2014). Transforming decision-making processes: a research agenda for understanding the impact of business analytics on organisations. European Journal of Information Systems, 23(4), 433-441.

Track Associate Editors

1. Henning Baars, University of Stuttgart, Germany

2. Sule Balkan, Portland State University, USA

3. Ivo Blohm, University of St. Gallen, Switzerland

4. Tobias Brandt, Erasmus University Rotterdam, Netherlands

5. Mauro Castelli, NOVA IMS, Portugal

6. Joseph Clark, University of Maine, USA

7. Patrick Delfmann, University of Koblenz, Germany

8. Adir Even, Ben-Gurion University of the Negev, Israel

9. Caddie Gao, Monash University, Australia

10.Michail Giannakos, Norwegian University of Science and Technology, Norway

11. Roland Holten, University of Frankfurt, Germany

12. Öykü Işık, Vlerick Business School, Belgium

13. Christian Janiesch, Julius-Maximilians-Universität Würzburg, Germany

14. Björn Johansson, Lund University, Sweden

15. Arpan Kar, Indian Institute of Technology, IIT Delhi, India

16. Ralf Knackstedt, University of Hildesheim, Germany

17. Marek Kowalkiewicz, Queensland University of Technology, Australia

18. John Krogstie, Norwegian University of Science and Technology, Norway

19. Uday Kulkarni, Arizona State University, USA

20. Caroline Lancelot Miltgen, AUDENCIA Business School, France

21. Nuno Laranjeiro, University of Coimbra, Portugal

22. George Lekakos, Athens University of Economics and Business, Greece

23. Olivera Marjanovic, University of Technology Sydney, Australia

24. Tobias Mettler, University of Lausanne, Switzerland

25.  Tiago Oliveira, ISEGI, Universidade Nova de Lisboa, Portugal

26. Ilias Pappas, Norwegian University of Science and Technology, Norway

27. Gregory Richards, University of Ottawa, Canada

28. Nripendra Rana, Swansea University, UK

29. Soumya Sen, University of Minnesota, USA

30. Ramesh Sharda, University of Oklahoma, USA

31.Konstantina Spanaki, Loughborough University, UK

32. Ida Asadi Someh, University of Queensland, Australia

33. Luka Tomat, University of Ljubljana, Slovenia

34. Olgerta Tona, Lund University, Sweden

35. Ozgur Turetken, Ryerson University, Canada

36. Rogier van de Wetering, Open University, the Netherlands

37. Johan Versendaal, HU University of Applied Sciences Utrecht, the Netherlands

38. William Yeoh, Deakin University, Australia

39. Bin Zhang, The University of Arizona, USA

40. Frederico Cruz, Universidade Nova de Lisboa, Portugal