ArticleF1000Research2024
Impact of Green Supply Chain Management on Sustainable Performance: A Dual Mediated-moderated Analysis of Green Technology Innovation And Big Data Analytics Capability Powered by Artificial Intelligence.
Article in F1000Research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: This study aims to empirically test a comprehensive interrelationship between green supply chain management (GSCM), green technology innovation (GTI), waste management (WM), big data analytics capability powered by artificial intelligence (BDAC-AI), and their collective impact on sustainable performance (SP) in organizational contexts. Methods: This study was conducted in Pakistan's food processing sector. The respondents included 495 managers working in the food processing industry. A structural equation modelling (SEM) approach is used to examine direct and indirect relationships between the variables. The originality of this study lies in integration of the technology acceptance model (TAM) and dynamic capability theory (DCT) to understand sustainable practices in the context of the provided model. Results: This study highlights that GSCM, GTI, WM, and BDAC-AI have positive, strong, and direct impacts on SP. Furthermore, GTI and WM only partially mediate the link between GSCM and SP, whereas the two moderate the link. In addition, BDAC-AI had a moderating effect on the relationship between GTI and SP. This study has managerial implications, including strategies that involve the use of theoretical frameworks for technological acceptance and dynamic capabilities to support sustainable initiatives. However, it is worth noting that the findings provide a practical contingency for managers and businesses interested in implementing green studies effectively, improving technologies, and strengthening sustainable performance capabilities. Conclusions: The study extends the literature by establishing a model for operationalizing GSCM in the food processing sector. Furthermore, it adds value in that it first integrates TAM and DCT to explain sustainable operations and their impact on organizations. Furthermore, it extends the existing literature by establishing a relationship between GSCM and SC. It offers a model through which GSCM can be operationalized in the context of the FS sector.
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Registered trials
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