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AMCIS2021
Mini Track on Big Data for Business and Societal
Transformation
<https://amcis2021.aisconferences.org/track-descriptions/#toggle-id-6>
https://amcis2021.aisconferences.org
Deadline: March 1, 2021
Mini track Chairs
Ilias Pappas, University of Agder, Norway,
ilias.pappas@uia.no<mailto:ilias.pappas@uia.no>
Patrick Mikalef, NTNU, Norway,
patrick.mikalef@ntnu.no<mailto:patrick.mikalef@ntnu.no>
Paul Pavlou, Bauer College of Business, University of Houston,
USA,
pavlou@bauer.uh.edu<mailto:pavlou@bauer.uh.edu>
The minitrack aims to explore the business and societal
transformations big data entail, and how they enable innovative
ways of conducting business supporting rapid decision making with
external stakeholders such as business partners, customers, public
authorities, and citizens. To understand how big data can be of
value requires an examination of the interplay between various
factors (e.g., social, technical, economical, environmental), as
well as the interrelation between different actors in a big data
ecosystem (e.g., academia, private and public organisations, civil
society, and individuals).
Emphasis will be placed on interdisciplinary papers that bridge
the domains of organizational science, information systems
strategic management, information science, marketing, and computer
science. Despite the hype surrounding big data, the aforementioned
predicaments still remain largely unexplored, severely hampering
the business and societal benefits of big data analytics. This
mini track aims to add in this direction and therefore welcomes
quantitative, qualitative, and mixed methods papers, as well as
reviews, conceptual papers, and theory development papers. Topics
of interest include but are not limited to the following:
Big data and management
• Data-driven competitive advantage
• Big data enabled organizational capabilities
• Big data strategic alignment
• Organizational learning and innovation from big data analytics
• Big data and its impact on business strategy-formulation
• Leveraging big data for social innovation and entrepreneurship
• Human resource management in the data-driven enterprise
• How big data shapes strategy and decision making
• Big data digital business models
• Big data and the dynamics of societal change
• Big data for social good
• The role of big data in social innovation
• Proactive strategy formulation from big data analytics
• Data and text mining for business analytics
• Behavioural and Recommender Systems Analytics
• Big data analytics for strategic value
• Data quality improvement for business analytics
• Application of big data to address societal challenges
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