Role of institutional pressures and resources in the adoption of big data analytics powered artificial intelligence, sustainable manufacturing practices and circular economy capabilities

Surajit Bag, Jan Ham Christiaan Pretorius, Shivam Gupta and Yogesh K. Dwivedi

Technological Forecasting and Social Change, 2021, vol. 163, issue C

Abstract: The significance of big data analytics-powered artificial intelligence has grown in recent years. The literature indicates that big data analytics-powered artificial intelligence has the ability to enhance supply chain performance, but there is limited research concerning the reasons for which firms engaging in manufacturing activities adopt big data analytics-powered artificial intelligence. To address this gap, our study employs institutional theory and resource-based view theory to elucidate the way in which automotive firms configure tangible resources and workforce skills to drive technological enablement and improve sustainable manufacturing practices and furthermore develop circular economy capabilities. We tested the research hypothesis using primary data collected from 219 automotive and allied manufacturing companies operating in South Africa. The contribution of this work lies in the statistical validation of the theoretical framework, which provides insight regarding the role of institutional pressures on resources and their effects on the adoption of big data analytics-powered artificial intelligence, and how this affects sustainable manufacturing and circular economy capabilities under the moderating effects of organizational flexibility and industry dynamism.

Keywords: Big data; Artificial intelligence; Industry 4.0; Circular economy; Sustainable manufacturing (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (79)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:163:y:2021:i:c:s0040162520312464

DOI: 10.1016/j.techfore.2020.120420

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