-------- Forwarded Message -------- Subject: [AISWorld] CfP AMCIS2021 - Big Data for Business and Societal Transformation Date: Sat, 13 Feb 2021 18:08:26 +0000 From: Ilias Pappas ilias.pappas@uia.no To: aisworld@lists.aisnet.org aisworld@lists.aisnet.org
AMCIS2021 Mini Track on Big Data for Business and Societal Transformationhttps://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.nomailto:ilias.pappas@uia.no Patrick Mikalef, NTNU, Norway, patrick.mikalef@ntnu.nomailto:patrick.mikalef@ntnu.no Paul Pavlou, Bauer College of Business, University of Houston, USA, pavlou@bauer.uh.edumailto: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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