Closing the Loop in Supply Chains: Supplier Commitment and Green Motivation as Drivers of Circular Logistics Adoption via Identity Mechanisms
Замыкание цикла в цепочках поставок: приверженность поставщиков и экологическая мотивация как факторы внедрения циркулярной логистики через механизмы идентичности
2026-06-15
SCID: 54.1/8wubj4tn
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PLS-SEMcircular logisticscircular logistics adoptioncircular supply chain identitycircular supply chain motivationdigital traceability capabilitypartial least squares structural equation modelingsupplier sustainability commitment
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Abstract (AI)
Background: Circular logistics translates circular economy principles into practical supply chain processes, but its adoption varies across firms because organizations differ in sustainability commitment, circular supply chain motivation, shared circular identity, and digital traceability capability. This study examines how supplier sustainability commitment and circular supply chain motivation influence circular logistics adoption through circular supply chain identity, while also testing the moderating role of digital traceability capability. Methods: Data were collected from 350 supply chain professionals in Saudi Arabia and analyzed using partial least squares structural equation modeling (PLS-SEM). Results: Supplier sustainability commitment and circular supply chain motivation positively influenced both circular logistics adoption and circular supply chain identity. Circular supply chain identity also positively affected circular logistics adoption and partially mediated the effects of both antecedents. Digital traceability capability acted as a selective moderator: it weakened the circular supply chain motivation–identity relationship, did not significantly moderate the supplier sustainability commitment–adoption relationship, but strengthened the circular supply chain identity–adoption relationship. It also moderated the indirect effect of circular supply chain motivation on circular logistics adoption through circular supply chain identity. Conclusions: Circular logistics adoption is driven not only by commitment and motivation, but also by shared circular identity and digitally enabled traceability.
Key Findings
1
Circular supply chain identity positively affects circular logistics adoption and partially mediates effects of commitment and motivation.
2
Circular supply chain motivation positively influences circular logistics adoption.
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Circular supply chain motivation positively influences circular supply chain identity.
4
Digital traceability capability does not significantly moderate the supplier sustainability commitment→adoption relationship.
5
Digital traceability capability moderates the indirect effect of circular supply chain motivation on adoption via circular supply chain identity.
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Digital traceability capability selectively moderates relationships: it weakens the motivation→identity link.
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Digital traceability capability strengthens the circular supply chain identity→circular logistics adoption relationship.
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Overall, adoption of circular logistics is driven by supplier commitment, circular motivation, shared circular identity, and digital traceability.
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Supplier sustainability commitment positively influences circular logistics adoption.
10
Supplier sustainability commitment positively influences circular supply chain identity.
Research Object
Adoption of circular logistics in supply chains
Research Subject
Effects of supplier sustainability commitment, circular supply chain motivation, circular supply chain identity, and digital traceability capability on circular logistics adoption (including mediation by identity and moderation by digital traceability)
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2026-06-15
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References available in scid.ai5
Common method biases in behavioral research: A critical review of the literature and recommended remedies.2003
A new criterion for assessing discriminant validity in variance-based structural equation modeling2014
Back-Translation for Cross-Cultural Research1970
Partial Least Squares Structural Equation Modeling (PLS-SEM) Using R2021
Reverse logistics and closed-loop supply chain: A comprehensive review to explore the future2014