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

A. Leal-Millán, J. Guadix-Martín and F. Criado García-Legaz

Technological Forecasting and Social Change, 2023, vol. 192, issue C

Abstract: 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.

Keywords: Green image; Green supply chain management practices; Relationship learning; Networking orientation; PLS-SEM (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:192:y:2023:i:c:s0040162523002548

DOI: 10.1016/j.techfore.2023.122569

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