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The European Journal of Information Systems

Call for Papers | Dark Side of Analytics and Artificial Intelligence | Deadline: March 31st 2020

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European Journal of Information Systems

The European Journal of Information Systems (EJIS) provides a distinctive European perspective on the theory and practice of IS for a global audience. We encourage first rate articles that provide a critical view on IT - its effects, development, implementation, strategy, management and policy.

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Important dates
Initial paper submission deadline: March 31st, 2020
First round authors notification: May 31st, 2020
Invited revisions deadline: July 15th, 2020
Second round authors notification: August 31st, 2020
Final revision deadline: October 15th, 2020
Final authors notification: December 15th, 2020
Projected publication: Spring 2021

We are living in an age of data deluge. Everywhere we go, everything we say, everything we buy leaves a digital footprint that
is recorded and stored (Vidgen, Shaw, & Grant, 2017). Combining big data, analytics and artificial intelligence (AI) have
signaled a revolution in the way data can be processed and the types of insights that can be generated (Kersting & Meyer,
2018). Mainstream information systems research generally celebrates the proliferation of analytics and AI for its economic
and business potential, and its capacity to create novel ways of working, organizing and developing new products and
services. In contrast, critical research has highlighted some of the negative consequences of such technologies, where the
emergence of big data analytics and AI threaten individual rights of organisational members, and hinder business value.
From a macro perspective, the potential of such technologies coupled with the immense data that large organisations now
manage to control, may cause a power imbalance and unwanted authority of certain businesses (Zuboff, 2015). The
concentrated control of data in a small number of organisations threaten to create a stark imbalance, and there is a pressing
need to address the question of power and authority with the widest possible frame. Clearly, there are many aspects
concerning the moral, social, and psychological implications for our everyday lives (O’Neil, 2015).

With this call for papers, we aim to extend the critical reflection on the impact and unintended consequences of big data
analytics and AI. Specifically, we aim to attract submissions that delve into the many misplaced assumptions and potential
dangers that AI might introduce in the organizational setting. Such negative implications tend to be often overlooked by
empirical research studies and their consequence seldom discussed. We invite the submission of original manuscripts that
advance empirical, theoretical, and conceptual understanding of the consequences and effects of how big data analytics and
AI drive digital business strategy. Manuscripts must have substantial implications for theory and practice, and we welcome
both empirical papers and conceptual theory development papers, as well as other genres. We are particularly interested in
manuscripts that address the challenges and changes that these technological innovations bring to strategic management
theories, and how such technologies may change the way we think about how organisations operate and compete. The
special issue is designed to embrace a variety of perspectives on emerging technological innovations, information systems,
and digital business strategy research. Purely computer science papers are not within the scope of this special issue.

Topics of interest

  • Critical perspectives on analytics and AI
  • The impact of analytics and AI on stress and loss of autonomy
  • Ethical implications of analytics and AI
  • Unexpected and un- or under-explored aspects of business analytic and AI
  • Implications of analytics and AI on work and workers, e.g. automation, the changing nature of work
  • Organisational learning and innovation from analytics and AI
  • Analytics and AI and their impact on business strategy formulation
  • Digital business strategy and value destruction using analytics and AI
  • The changing and/or automated nature of business decision-making in the age of analytics and AI
  • Governance challenges of digital business strategy in analytics and AI projects
  • Inertial forces, path-dependencies and hindrances of digital capabilities in analytics and AI projects
  • Business value and unanticipated consequences of analytics and AI in the organisational context
  • Micro-foundations of digital business strategy in the age of analytics and AI
  • Managerial issues concerning the implementation of analytics and AI projects
  • Business model reconfiguration in the age of analytics and AI
  • Data-driven competitive advantage in changing competitive markets
  • Organisational structure, skills, management thinking, algorithmic management, strategic decision-making and
    leadership in the age of analytics and AI

Guest Editors

Patrick Mikalef, Department of Computer Science, Norwegian University of Science and Technology (NTNU)

Aleš Popovič, School of Economics and Business, Universito Ljubljana, Slovenia

Jenny Eriksson Lundström, Department of Informatics and Media, Uppsala University, Sweden

Kieran Conboy, J.E. Cairnes School of Business & Economics, National University of Ireland Galway, Ireland


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Kersting, K., & Meyer, U. (2018). From Big Data to Big Artificial Intelligence? Algorithmic Challenges and Opportunities of Big Data, 32(1), 3-8.

Vidgen, R., Shaw, S., & Grant, D. B. (2017). Management challenges in creating value from business analytics. European Journal of Operational Research, 261(2), 626-639.

Zuboff, S. (2015). Big other: surveillance capitalism and the prospects of an information civilization. Journal of Information Technology, 30(1), 75-89