A three-level view of readiness models: Statistical and managerial insights on industry 4.0

Vincenzo Basile, Marco Tregua and Massimiliano Giacalone

Technology in Society, 2024, vol. 77, issue C

Abstract: Over the past ten years, business intelligence (BI) and data analytics (DA) have consistently increased their impact on information management and firms' strategies, as evidenced in decision-making processes. Moreover, using new tools in so-called digitalization has become a core element, and while it may help firms sustain their competitive advantage, it could also have multiple side effects. Therefore, this paper adopts a service ecosystem perspective and focuses on firms’ level of digitalization to observe the effects of technologies regarded as actors, as well as deriving outlooks beyond the firm level. Additionally, a multilevel view is aligned with the digital service ecosystem and supports the analysis of Industry 4.0 as sociotechnical factors in smart manufacturing technologies. Using principal component analysis (PCA), an analysis of industries was conducted to identify where the modernization of manufacturing and the contribution of digitalization show lower levels of readiness. Furthermore, the purpose of the analysis is to alert firms about opportunities to gain the most from digitalization or to enhance their level of implementation of such technologies. A three-level view emerges because novel technology implementation ranges from companies to industries to regions; therefore, a general process of digitalization may also increase competitiveness at a wider level.

Keywords: Big data; Digitalization; Small and medium enterprises; Business intelligence; Digital service ecosystem; Industry 4.0 (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:teinso:v:77:y:2024:i:c:s0160791x24000769

DOI: 10.1016/j.techsoc.2024.102528

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