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Narula, Sanjiv, Kumar, Anil, Prakash, Surya, Dwivedy, Maheshwar, Puppala, Harish and Talwar, Vishal (2021) Modeling and analysis of challenges for industry 4.0 implementation in medical device industry to post COVID-19 scenario. International Journal of Supply and Operations Management, 10 (2). pp. 117-135. ISSN 2383-1359
Today, the health care and medical sector is adopting digital technologies aggressively. However, this adoption also has significant challenges, especially during COVID-19. This research aims to identify and categorize the significant challenges related with application of Industry 4.0 (I4.0) technologies in the medical device industry. An expert-based survey is carried to capture the perception of medical device industry leaders about the challenges associated with the implementation of digital technologies. Further, interpretive structural modeling (ISM) method was used for an empirical investigation of the hierarchy and interdependencies of identified challenges. The authors have proposed a mind map and conceptual model of hierarchy and interdependencies of challenges associated with the digital transformation of the medical device industry towards I4.0. Industry leaders and policymakers worldwide are defying challenges while the digital transformation of the organizations post COVID-19. The I4.0 implementation challenges identified and categorized in this research may aid as a guide for medical device manufacturing organizations while designing a strategy for I4.0 transformation and to make sure that they start on the right -footing. Most of the existing work is focused on the advantages of I4.0 for managing the organization's post-COVID-19, lacks thoroughness and testing. Owing to the identified gap, this study intends to empirically identify the critical challenges associated with applying I4.0 technologies in the medical device manufacturing sector. This study is a pioneer in identifying and categorizing the vital challenges needed to deal with this critical situation. A potential area of future research can be the validation of the identified challenges with a larger sample size.
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