Repository logo

Development of an Analytics and Collaborations Integrated Supply Chain Risk Management Capability Measurement Instrument Based on the Information Processing Theory and the Relational View

aut.relation.endpage24
aut.relation.issue2
aut.relation.journalSri Lankan Journal of Applied Statistics
aut.relation.startpage1
aut.relation.volume27
dc.contributor.authorSilva, Chathurani
dc.contributor.authorFernando, MACSS
dc.contributor.authorJayatilake, AC
dc.date.accessioned2026-09-14T04:06:38Z
dc.date.issued2026-08-31
dc.description.abstractSupply chain risk management (SCRM) plays a vital role in any business entity, comprising activities that aim to prevent, detect, respond to, and recover organizations from the impacts of disruptive events. Both analyzing supply chain (SC) data and collaborating with SC partners help firms manage risks effectively during disruptions. Although supply chain analytics (SCA) is an integral element of SCRM, the existing measurement instruments for SCRM do not fully integrate SCA as it is used in the Sri Lankan manufacturing context. However, SC collaborations (SCC) are invariably included in these measurement instruments. Hence, the primary objective of the study was to develop a new measurement instrument for the analytics-and collaboration-integrated SCRM capability of Sri Lankan industrial product manufacturing sector using Organizational Information Processing Theory (OIPT) and the Relational View (RV) as theoretical lens. The study employed an exploratory quantitative research design. The items were generated from both the literature on related measurement instruments and the results of a previously conducted qualitative study. Then, the finalized items were used in an online survey administered to 205 randomly selected SC managers from industrial product manufacturing organizations in Sri Lanka that engaged in global business. Initially, an exploratory factor analysis was conducted to identify the factors representing the firms’ analytics collaboration-based SCRM capabilities. The study proposed a novel four-dimensional measurement instrument for evaluating analytics and collaboration-based SCRM, and it includes: (1) analytics-based risk assessment, (2) information sharing-based risk mitigation, (3) analytics-based risk identification and monitoring, and (4) collaboration-based strategic risk mitigation. Subsequently, a confirmatory factor analysis was conducted to validate the measurement instrument for the identified factors. Given the increasing importance of collaboration and analytics-based SCRM, the validated measurement instrument introduced in this study would be a valuable tool for advancing future research on SCRM.
dc.identifier.citationSri Lankan Journal of Applied Statistics, ISSN: 1391-4987 (Print); 2424-6271 (Online), Sri Lanka Journals Online, 27(2), 1-24. doi: 10.4038/sljas.v27i2.8254
dc.identifier.doi10.4038/sljas.v27i2.8254
dc.identifier.issn1391-4987
dc.identifier.issn2424-6271
dc.identifier.urihttp://hdl.handle.net/10292/21970
dc.publisherSri Lanka Journals Online
dc.relation.urihttps://sljastats.sljol.info/articles/10.4038/sljas.v27i2.8254
dc.rights© 2026 Institute of Applied Statistics, Sri Lanka. This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 license (unless stated otherwise) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
dc.rights.accessrightsOpenAccess
dc.rights.licenseCreative Commons Attribution License
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subject35 Commerce, Management, Tourism and Services
dc.subject3507 Strategy, Management and Organisational Behaviour
dc.subject3509 Transportation, Logistics and Supply Chains
dc.subject46 Information and Computing Sciences
dc.subject4609 Information Systems
dc.subjectGeneric health relevance
dc.subject9 Industry, Innovation and Infrastructure
dc.subjectConfirmatory factor analysis
dc.subjectExploratory factor analysis
dc.subjectMeasurement instrument
dc.subjectSupply chain analytics
dc.subjectSupply chain collaboration
dc.subjectSupply chain risk management
dc.titleDevelopment of an Analytics and Collaborations Integrated Supply Chain Risk Management Capability Measurement Instrument Based on the Information Processing Theory and the Relational View
dc.typeJournal Article
pubs.elements-id773783

Files

Original bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
6a952405bfa47.pdf
Size:
434.48 KB
Format:
Adobe Portable Document Format
Description:
Journal article

License bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
license.txt
Size:
1.37 KB
Format:
Plain Text
Description: