4.8 Article

From networking orientation to green image: A sequential journey through relationship learning capability and green supply chain management practices. Evidence from the automotive industry

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Publisher

ELSEVIER SCIENCE INC
DOI: 10.1016/j.techfore.2023.122569

Keywords

Green image; Green supply chain management practices; Relationship learning; Networking orientation; PLS-SEM

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Drawing on the RBV and resources and capabilities theory, this study develops a model that extends our understanding of the mechanisms through which strategic assets, capabilities, and GSCMP contribute to GI. The model includes two new antecedents of GSCMP: RL and NO, and explores their impacts on firms' GI. Empirical data from 106 Spanish firms in the automotive industry were collected and analyzed to study the proposed relationships. The results suggest that NO, RL capability, and GSCMP positively affect GI through a sequential mediation relationship, highlighting the importance of ordinary capabilities in improving the green image.
Drawing on the resource-based view of the firm (RBV) and resources and capabilities theory, this study develops a model that extends our understanding of the mechanisms through which strategic assets, capabilities, and green supply chain management practices (GSCMP) contribute to green image (GI). The model comprises (i) two new antecedents of GSCMP: relationship learning capability (RL) and strategic networking orientation (NO), and (ii) the direct and mediated impacts of GSCMP and their antecedents on firms' GI. To empirically study the proposed relationships, data were collected from 106 Spanish firms in the automotive industry and analyzed using partial least squares structural equation modelling (PLS-SEM). The results indicate that NO, RL capability, and GSCMP positively affect GI through a sequential mediation relationship. An important implication is the identification of a stream of research proposing that GSCMP act similarly to a lower-order capability and that it is the interaction with other ordinary capabilities that can contribute to improving the green image.

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