Impact of big data analytics on innovation performance: the mediating role of team dynamics

Purpose This study aims to examine the impact of big data analytics (BDA) on innovation performance (IPF) in the IT sector, with a focus on the mediating roles of team innovation culture (TIC), team reflexivity (TR), and team entrepreneurial passion (TEP). Design/methodology/approach A survey was conducted among 422 senior IT professionals in Peru. Data were analyzed using partial least squares structural equation modeling to test both direct and indirect relationships between BDA and IPF, incorporating TIC, TR, and TEP as mediators. Findings Results show that BDA has a significant positive effect on IPF. While BDA also positively impacts TIC and TR, these factors do not significantly mediate the relationship between BDA and IPF. However, TEP emerges as a significant partial mediator, highlighting its role in translating data insights into innovation outcomes. Research limitations/implications The cross-sectional design limits causal inference. Future studies should investigate the longitudinal effects and explore additional mediators, such as organizational readiness and knowledge-sharing practices. Practical implications IT firms should foster entrepreneurial passion within teams and align BDA strategies with innovation goals to drive performance. Originality/value To the best of the authors’ knowledge, this study is among the first to examine TEP as a mediator between BDA and IPF, combining resource-based view and social learning theory to explain how team dynamics shape data-driven innovation.

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Publication Details

Journal
European Business Review
Published
2025-10-14
DOI
https://doi.org/10.1108/ebr-10-2024-0318
Citations
1
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
2.28
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article

Impact of big data analytics on innovation performance: the mediating role of team dynamics

Juan Carlos Sosa Varela, Diego Norena-Chávez
1 citations
European Business Review
Big Data and Business Intelligence
2.28
article

Impact of big data analytics on innovation performance: the mediating role of team dynamics

Juan Carlos Sosa Varela, Diego Norena-Chávez
article en
1 citations

Abstract

Purpose This study aims to examine the impact of big data analytics (BDA) on innovation performance (IPF) in the IT sector, with a focus on the mediating roles of team innovation culture (TIC), team reflexivity (TR), and team entrepreneurial passion (TEP). Design/methodology/approach A survey was conducted among 422 senior IT professionals in Peru. Data were analyzed using partial least squares structural equation modeling to test both direct and indirect relationships between BDA and IPF, incorporating TIC, TR, and TEP as mediators. Findings Results show that BDA has a significant positive effect on IPF. While BDA also positively impacts TIC and TR, these factors do not significantly mediate the relationship between BDA and IPF. However, TEP emerges as a significant partial mediator, highlighting its role in translating data insights into innovation outcomes. Research limitations/implications The cross-sectional design limits causal inference. Future studies should investigate the longitudinal effects and explore additional mediators, such as organizational readiness and knowledge-sharing practices. Practical implications IT firms should foster entrepreneurial passion within teams and align BDA strategies with innovation goals to drive performance. Originality/value To the best of the authors’ knowledge, this study is among the first to examine TEP as a mediator between BDA and IPF, combining resource-based view and social learning theory to explain how team dynamics shape data-driven innovation.

European Business ReviewVol. 37(6)
Universidad de Lima (PE), Ana G. Mendez University System (PR)
Openalex Percentile: Top 9%
Big Data and Business Intelligence
2.28
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Impact of big data analytics on innovation performance: the mediating role of team dynamics — Juan Carlos Sosa Varela, Diego Norena-Chávez · European Business Review (2025) | TGRS Research Map | TGRS