Resource re-orchestration and firm survival in crisis periods: The role of business models of technology MNEs during COVID-19
Rexford Attah-Boakye,
Kweku Adams,
Elvis Hernandez-Perdomo,
Honglan Yu and
Jeaneth Johansson
Technovation, 2023, vol. 125, issue C
Abstract:
Using data from world-leading digital-driven/technology multinational enterprises (DTMNEs), we draw from the resource orchestration theory to investigate the associations between business model (BM) drivers and firm performance during crisis periods. Drawing on data from the COVID-19 pandemic period, we deploy diverse analytical approaches including multivariate linear regressions and aggregated composite index statistical methods in examining how the BMs of our sampled DTMNEs drive firm performance. Our study highlights six methodological approaches that can be utilised by decision-makers in examining which variables in their BM drive better firm performance. Our findings revealed that the principal component analysis and multicriteria decision analysis (PROMETHEE methods) that espouse the use of aggregate composite index can provide significant and consistent predictive results in comparison to the traditional linear methods when examining the association between BM and firm performance during crisis periods. The paper provides policy and managerial implications on how firms and decision-makers can bolster business continuity, resilience, and plasticity by using analytical lenses that identify optimum resource orchestration during crises.
Keywords: Business models; Artificial intelligence; Machine learning; Digitalisation; Agility; Resource orchestrations (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0166497223000809
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:techno:v:125:y:2023:i:c:s0166497223000809
DOI: 10.1016/j.technovation.2023.102769
Access Statistics for this article
Technovation is currently edited by Jonathan Linton
More articles in Technovation from Elsevier
Bibliographic data for series maintained by Catherine Liu ().