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Information and communication technologies (ICT)-enabled severe moral communities and how the (Covid19) pandemic might bring new ones

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  • Parra, Carlos M.
  • Gupta, Manjul
  • Mikalef, Patrick

Abstract

In this study we present an autopoietic social systems model based on Collectively Prevalent Interpretants (CPIs). We adapt this model to represent and exemplify how Information and Communication Technologies (ICTs) may enable the emergence of severe moral communities. In particular, we argue that ICTs may help severe moral communities promote increasingly polarized, radicalized and even extremist viewpoints. We also discuss our propositions in the context of the current pandemic (caused by Covid19) and warn about the possible emergence of new and related severe moral communities. In an effort to help understand and manage the enabling role of ICTs, the study also presents recommendations for theory and practice, which may prove useful in advancing digital resiliency (by empowering individuals and communities to recognize when this may be occurring).

Suggested Citation

  • Parra, Carlos M. & Gupta, Manjul & Mikalef, Patrick, 2021. "Information and communication technologies (ICT)-enabled severe moral communities and how the (Covid19) pandemic might bring new ones," International Journal of Information Management, Elsevier, vol. 57(C).
    • Handle: RePEc:eee:ininma:v:57:y:2021:i:c:s0268401220314705
    DOI: 10.1016/j.ijinfomgt.2020.102271
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    Citations

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    Cited by:

    1. Salih Tutun & Marina E. Johnson & Abdulaziz Ahmed & Abdullah Albizri & Sedat Irgil & Ilker Yesilkaya & Esma Nur Ucar & Tanalp Sengun & Antoine Harfouche, 2023. "An AI-based Decision Support System for Predicting Mental Health Disorders," Information Systems Frontiers, Springer, vol. 25(3), pages 1261-1276, June.
    2. Danish, & Khan, Salahuddin & Haneklaus, Nils, 2023. "Sustainable economic development across globe: The dynamics between technology, digital trade and economic performance," Technology in Society, Elsevier, vol. 72(C).
    3. Manjul Gupta & Amin Shoja & Patrick Mikalef, 2022. "Toward the understanding of national culture in the success of non‐pharmaceutical technological interventions in mitigating COVID-19 pandemic," Annals of Operations Research, Springer, vol. 319(1), pages 1433-1450, December.
    4. Han, Zhongya & Tang, Zhongjun & He, Bo, 2022. "Improved Bass model for predicting the popularity of product information posted on microblogs," Technological Forecasting and Social Change, Elsevier, vol. 176(C).

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