Abstract
COVID-19 is a major health, economic, and social crisis in the modern age. Even before the COVID-19 pandemic, digitization had changed the consumer behavior and habits, regulations, supply-side factors, demand-side factors, and costs of information structure and coordination. We have been experiencing shifts from physical interactions to digital interactions and transitioning from physical, predictable, and slow world into digital, virtual, fast, and agile world. COVID-19 will likely accelerate the digitization but will also force corporations to refine and possibly redefine their digital business strategies. Corporations have to address many questions about how to deal with the crisis in digital age and refine their digital business strategy while going through some transformations already. The main question is how corporations could navigate through this crisis when traditional economy and even digital economy assumptions and approaches do not necessarily apply. In this paper, we study how corporations could characterize the digital business strategy during crisis and devise a framework for how they could model and evaluate various strategic options. Due to so many complex dynamics involved and many uncertainties, we argue a layered intelligence framework that supports qualitative analysis that should be used to model the digital business strategy during crisis.
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Yucel, S. (2021). Modeling Digital Business Strategy During Crisis. In: Arabnia, H.R., et al. Advances in Parallel & Distributed Processing, and Applications. Transactions on Computational Science and Computational Intelligence. Springer, Cham. https://doi.org/10.1007/978-3-030-69984-0_69
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DOI: https://doi.org/10.1007/978-3-030-69984-0_69
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