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Managing in a Post-COVID-19 World: A Stakeholder Network Perspective
- Source :
- IEEE Engineering Management Review. 49:63-71
- Publication Year :
- 2021
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2021.
-
Abstract
- This article argues that technical leaders in a post-COVID-19 world should adopt stakeholder-oriented management techniques tailored to complex, chaotic, and disordered domains. In part, this is because the unprecedented breadth of the novel coronavirus's impact has required organizations to strengthen their stakeholder orientation, given the second-order, network effects of management decisions during a global pandemic on unseen, unknown constituencies. In part, this is because even our causal models and modes of group sense-making have been affected by the suffering and uncertainty caused by the pandemic. This article draws from ongoing research on complex stakeholder networks, applying recent advances in graph theory to establish that organizations with more resilient, more efficient, more globally connected stakeholder networks better satisfy the claims of their stakeholders, across an array of financial and environmental, social and governance metrics. This research can be extended into postcrisis, chaotic, and disordered domains by adapting the Cynefin framework, from the Welsh word for “habitat,” and applying it to the stakeholder theory literature. This stakeholder network perspective yields surprisingly simple and relevant tools for managers, as shown by a case study of the real-world performance of large US firms during the period of COVID-19’s initial diffusion and impact.
- Subjects :
- Knowledge management
business.industry
Strategy and Management
Corporate governance
05 social sciences
Perspective (graphical)
Stakeholder
Graph theory
language.human_language
Welsh
Management of Technology and Innovation
Taxonomy (general)
0502 economics and business
language
Business
Electrical and Electronic Engineering
Stakeholder theory
050203 business & management
Causal model
Subjects
Details
- ISSN :
- 19374178 and 03608581
- Volume :
- 49
- Database :
- OpenAIRE
- Journal :
- IEEE Engineering Management Review
- Accession number :
- edsair.doi...........22e71bfa2698f806961344396f3430a0
- Full Text :
- https://doi.org/10.1109/emr.2021.3057306