Digital transformation of supply chain: a study on additive manufacturing practice in medical device in Australia

Chowdhury, MH; Scerri, M; Shahriar, S; Skellern, K

Digital transformation of supply chain: a study on additive manufacturing practice in medical device in Australia

Chowdhury, MH Scerri, M Shahriar, S Skellern, K

Permalink

Publisher:: Emerald
Publication Type:: Journal Article
Citation:: Journal of Enterprise Information Management, ahead-of-print, (ahead-of-print)

Open Access

Copyright Clearance Process

Recently Added
In Progress
Open Access

This item is open access.

Adobe PDF

Download Accepted versionAdobe PDF (601.78 kB)

View on publisher's site

View statistics

Full metadata record

Field	Value	Language
dc.contributor.author	Chowdhury, MH
dc.contributor.author	Scerri, M
dc.contributor.author	Shahriar, S
dc.contributor.author	Skellern, K
dc.date.accessioned	2023-03-09T01:36:45Z
dc.date.available	2023-03-09T01:36:45Z
dc.identifier.citation	Journal of Enterprise Information Management, ahead-of-print, (ahead-of-print)
dc.identifier.issn	1741-0398
dc.identifier.uri	http://hdl.handle.net/10453/166747
dc.description.abstract	<jats:sec><jats:title content-type="abstract-subheading">Purpose</jats:title><jats:p>Drawing on a dynamic capability view, this study develops a decision support model that determines the most suitable configuration of strategies and challenges to adopt additive manufacturing (AM) to expedite digital transformation and performance improvement of the surgical and medical device (SMD) supply chain.</jats:p></jats:sec><jats:sec><jats:title content-type="abstract-subheading">Design/methodology/approach</jats:title><jats:p>To investigate the research objective, a multi-method and multi-study research design was deployed using quality function deployment and fuzzy set qualitative comparative analysis.</jats:p></jats:sec><jats:sec><jats:title content-type="abstract-subheading">Findings</jats:title><jats:p>The study finds that only resilience strategies or negation (i.e. minimisation) of challenges are not enough; instead, a configuration of resilience strategies and negation of challenges is highly significant in enhancing performance.</jats:p></jats:sec><jats:sec><jats:title content-type="abstract-subheading">Practical implications</jats:title><jats:p>SMD supply chain decision-makers will find the decision support model presented in this study as beneficial to be resilient against various challenges in the digital transformation of service delivery process.</jats:p></jats:sec><jats:sec><jats:title content-type="abstract-subheading">Originality/value</jats:title><jats:p>This study builds new knowledge of the adoption of AM technology in the SMD supply chain. The decision support model developed in this study is unique and highly effective for fostering digital transformation and enhancing SMD supply chain performance.</jats:p></jats:sec>
dc.language	en
dc.publisher	Emerald
dc.relation	APICS
dc.relation.ispartof	Journal of Enterprise Information Management
dc.relation.isbasedon	10.1108/jeim-09-2022-0337
dc.rights	info:eu-repo/semantics/openAccess
dc.rights	The version of record is available at https://doi.org/10.1108/jeim-09-2022-0337. The full citation is as follows: [Digital transformation of supply chain: a study on additive manufacturing practice in medical device in Australia. Journal of Enterprise Information (2023) ©2023 Emerald Publishing Limited. This AAM is provided for your own personal use only. It may not be used for resale, reprinting, systematic distribution, emailing, or for any other commercial purpose without the permission of the publisher
dc.subject	0806 Information Systems, 0807 Library and Information Studies, 1503 Business and Management
dc.subject.classification	Business & Management
dc.title	Digital transformation of supply chain: a study on additive manufacturing practice in medical device in Australia
dc.type	Journal Article
utslib.citation.volume	ahead-of-print
utslib.for	0806 Information Systems
utslib.for	0807 Library and Information Studies
utslib.for	1503 Business and Management
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Business
pubs.organisational-group	/University of Technology Sydney/Faculty of Business/Management Discipline
utslib.copyright.status	open_access	*
dc.date.updated	2023-03-09T01:36:44Z
pubs.issue	ahead-of-print
pubs.publication-status	Published online
pubs.volume	ahead-of-print
utslib.citation.issue	ahead-of-print

Abstract:

PurposeDrawing on a dynamic capability view, this study develops a decision support model that determines the most suitable configuration of strategies and challenges to adopt additive manufacturing (AM) to expedite digital transformation and performance improvement of the surgical and medical device (SMD) supply chain.Design/methodology/approachTo investigate the research objective, a multi-method and multi-study research design was deployed using quality function deployment and fuzzy set qualitative comparative analysis.FindingsThe study finds that only resilience strategies or negation (i.e. minimisation) of challenges are not enough; instead, a configuration of resilience strategies and negation of challenges is highly significant in enhancing performance.Practical implicationsSMD supply chain decision-makers will find the decision support model presented in this study as beneficial to be resilient against various challenges in the digital transformation of service delivery process.Originality/valueThis study builds new knowledge of the adoption of AM technology in the SMD supply chain. The decision support model developed in this study is unique and highly effective for fostering digital transformation and enhancing SMD supply chain performance.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/166747