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Workforce resilience in the post-COVID-19 era: differences based on manufacturing–service orientation and firm size

Soomro, Mansoor Ahmed; Ali, Mohd Helmi; Tan, Kim Hua; Kumar, Ajay; Sinniah, Suguna


Mansoor Ahmed Soomro

Mohd Helmi Ali

Professor of Operations and Innovation Management

Ajay Kumar

Suguna Sinniah


The devastating impact of COVID-19 on businesses has led to the redefinition of workforce resilience. This study hence explores workforce resilience factors that will be important in the post-COVID-19 era. It investigates whether these factors perform differently in the manufacturing vs. the service sector and in small and medium enterprises (SMEs) vs. large firms. Sixty-five firms were studied in Malaysia and analyzed through Rasch modelling. The results indicate that three workforce resilience factors (positive thinking, sense of responsibility, and emotional control) are difficult to overcome in the manufacturing sector. Regarding the SMEs and large firm contexts, six workforce resilience factors (positive thinking, differentiation, degree of involvement, sense of responsibility, cognitive processes, and innovation) are complicated for SMEs. In comparison, two workforce resilience factors (work–life balance and decision-making) are difficult for large firms. Capitalizing on these findings, managers in various organizations (manufacturing vs. service and SMEs vs. large firms) can adopt different strategies to leverage workforce resilience post-COVID. Moreover, government agencies can use these findings for policy-making when leading post-COVID-19 projects and initiatives.


Soomro, M. A., Ali, M. H., Tan, K. H., Kumar, A., & Sinniah, S. (2022). Workforce resilience in the post-COVID-19 era: differences based on manufacturing–service orientation and firm size. Production Planning and Control, 1-13.

Journal Article Type Article
Acceptance Date Jul 12, 2022
Online Publication Date Aug 12, 2022
Publication Date Aug 12, 2022
Deposit Date Sep 8, 2022
Publicly Available Date Aug 13, 2023
Journal Production Planning and Control
Print ISSN 0953-7287
Electronic ISSN 1366-5871
Publisher Taylor & Francis Open
Peer Reviewed Peer Reviewed
Pages 1-13
Keywords Industrial and Manufacturing Engineering; Management Science and Operations Research; Strategy and Management; Computer Science Applications
Public URL
Publisher URL
Additional Information This is an Accepted Manuscript of an article published by Taylor & Francis in Production Planning and Control on 12 August 2022, available at: