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结合大数据与人工智能在不可预测环境中管理集体知识——来自中国应对新冠肺炎案例的见解

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

作者信息

Iandolo Francesca, Loia Francesca, Fulco Irene, Nespoli Chiara, Caputo Francesco

机构信息

Department of Management, Faculty of Economics, University of Rome 'La Sapienza', Via del Castro Laurenziano, 9, 00161 Rome, Italy.

Department of Economics, Management, and Institutions (DEMI), University of Naples 'Federico II', Via Cintia, 21, 80126 Naples, Italy.

出版信息

J Knowl Econ. 2021;12(4):1982-1996. doi: 10.1007/s13132-020-00703-8. Epub 2020 Nov 13.

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.

摘要

万维网和新技术所带来的机遇使社会和商业格局的流动性日益增强,这正在质疑传统商业模式和管理方法的有效性。新规则正在出现,参与动态且不可预测路径的个人和组织都需要进行多重变革。在这种情况下,本文旨在描述大数据和人工智能在迈向知识管理集体方法的道路上的潜在作用。借助系统思维提供的解释视角,描绘了一个能够解释人机交互的框架,并追溯了其对在不可预测环境中定义知识管理集体方法的贡献。本文结合中国政府应对新冠疫情传播的方法简要讨论了相关思考,以强调基于技术的知识管理集体方法能够为不可预测环境中的决策过程提供的支持。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2c3d/7664164/3d390cdee129/13132_2020_703_Fig1_HTML.jpg

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