Combining Big Data and Artificial Intelligence for Managing Collective Knowledge in Unpredictable Environment—Insights from the Chinese Case in Facing COVID-19

Francesca Iandolo, Francesca Loia (), Irene Fulco (), Chiara Nespoli () and Francesco Caputo ()
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Francesca Loia: University of Naples ‘Federico II’
Irene Fulco: University of Tuscia of Viterbo
Chiara Nespoli: University of Campania ‘L. Vanvitelli’
Francesco Caputo: University of Naples ‘Federico II’

Journal of the Knowledge Economy, 2021, vol. 12, issue 4, No 21, 1982-1996

Abstract: Abstract The increasing fluidity of social and business configurations made possible by the opportunities provided by the World Wide Web and the new technologies is questioning the validity of consolidated business models and managerial approaches. New rules are emerging and multiple changes are required to both individuals and organizations engaged in dynamic and unpredictable paths. In such a scenario, the paper aims at describing the potential role of big data and artificial intelligence in the path toward a collective approach to knowledge management. Thanks to the interpretative lens provided by systems thinking, a framework able to explain human-machine interaction is depicted and its contribution to the definition of a collective approach to knowledge management in unpredictable environment is traced. Reflections herein are briefly discussed with reference to the Chinese governmental approach for managing COVID-19 spread to emphasise the support that a technology-based collective approach to knowledge management can provide to decision-making processes in unpredictable environments.

Keywords: Knowledge management; Collective knowledge; Big data; Artificial intelligence; Viable systems approach; COVID-19 (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (6)

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DOI: 10.1007/s13132-020-00703-8

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