Cloud-related resources, supply chain ambidexterity and supply chain performance: evidence from a cross-national empirical investigation
Bui Thanh KhoaPurpose
This study aims to examine the influence of cloud-related resource dimensions on supply chain performance through ambidexterity mechanisms.
Design/methodology/approach
Grounded in the extended resource-based view (ERBV) and supply chain ambidexterity theory, this study develops a conceptual model in which three cloud-related resource dimensions affect supply chain performance through the mediating roles of supply chain exploration and exploitation and tests whether these two orientations also moderate the direct cloud resource–performance relationships. Survey data were collected from 142 enterprises across four geographic regions and analysed using partial least squares structural equation modelling (PLS-SEM), supported by a post-hoc power analysis, Harman’s single-factor test, a non-response bias assessment, a confirmatory factor analysis of construct distinctiveness and a multigroup analysis of cross-regional invariance.
Findings
Supply chain exploration and exploitation partially mediate the relationship between cloud-related resources and supply chain performance. Eight of the twelve hypothesised paths are supported; four paths involving channel-network- and cloud-synergy-based mechanisms are not statistically supported and are interpreted with caution as directions for replication. The moderation effects, although statistically significant for infrastructure- and channel-based interactions, are small in magnitude and are discussed accordingly in the following sections.
Originality/value
Anchored in the ERBV complemented by ambidexterity theory, this study introduces supply chain ambidexterity as both a mediating mechanism and a contextual moderator in cloud-enabled supply chains. It provides one of the first empirical tests integrating dual mediation and dual moderation to explain how disaggregated cloud resources enhance supply chain performance and verifies the cross-regional stability of these relationships through measurement invariance testing.