Unraveling the transformation: the three-wave time-lagged study on big data analytics, green innovation and their impact on economic and environmental performance in manufacturing SMEs
| dc.contributor.author | Alshibani, Safiya Mukhtar | |
| dc.contributor.author | Mehmood, Khalid | |
| dc.contributor.author | Jabeen, Fauzia | |
| dc.contributor.author | ETAL.. | |
| dc.date.accessioned | 2026-01-12T09:48:57Z | |
| dc.date.available | 2026-01-12T09:48:57Z | |
| dc.date.issued | 2025 | |
| dc.description | The utilization of contemporary technologies by corporations has led to an abundance of data, raising challenges related to sustainability and capabilities (Aydiner et al., 2019). The strategies employed by these firms in extracting valuable insights from this extensive data are pivotal in establishing their competitive edge and innovation capabilities (Su et al., 2022). Scholars and practitioners advocate for the adoption of big data analytics (BDA) as a means to enhance the dynamic capabilities of firms, thereby bolstering their operational sustainability at the business process level (Nižetić et al., 2019; Mehmood et al., 2023f). | |
| dc.description.abstract | Purpose The firms’ adoption and improvement of big data analytics capabilities to improve economic and environmental performance have recently increased. This makes it important to discover the underlying mechanism influencing the association between big data analytics (BDA) and economic and environmental performance, which is missing in the existing literature. The present study discovers the indirect effect of green innovation (GI) and the moderating role of corporate green image (CgI) on the impact of BDA capabilities, including big data management capability (MC) and big data talent capability (TC), on economic and environmental performance. Design/methodology/approach A time-lagged design was employed to collect data from 417 manufacturing firms, and study hypotheses were evaluated using Mplus. Findings The empirical outcomes indicate that both BDA capabilities of firms significantly influence green innovation (GI), which significantly mediates the relationship between BDA and economic and environmental performance. Our findings also revealed that CgI strengthened the effect of GI on economic and environmental performance. The empirical evidence provides important theoretical and practical repercussions for manufacturing SMEs and policymakers. Originality/value This study contributes to the literature on BDA by empirically exploring the effects of MC and TC on improving the EcP and EnP of manufacturing firms. It does so through the indirect impact of GIs and the moderating effect of CgI, thereby extending the Dynamic capabilities view (DCV) paradigm. keywords: Big data analytics, Corporate green image, Dynamic capabilities view, Economic performance, Environmental performance, Green innovation, Manufacturing SMEs | |
| dc.identifier.citation | Mehmood, K., Jabeen, F., Rashid, M., Alshibani, S. M., Lanteri, A., & Santoro, G. (2025). Unraveling the transformation: the three-wave time-lagged study on big data analytics, green innovation and their impact on economic and environmental performance in manufacturing SMEs. European Journal of Innovation Management, 28(6), 2189-2216. | |
| dc.identifier.doi | https://doi.org/10.1108/EJIM-10-2023-0903 | |
| dc.identifier.uri | https://repository.adu.ac.ae/handle/1/7952 | |
| dc.language.iso | en | |
| dc.publisher | Emerald Publishing | |
| dc.title | Unraveling the transformation: the three-wave time-lagged study on big data analytics, green innovation and their impact on economic and environmental performance in manufacturing SMEs | |
| dc.type | Article |