The impact of big data acceptance and analysis on company performance

Elham Nikmanesh et al.

International Journal of Knowledge-Based Development2025https://doi.org/10.1504/ijkbd.2025.151403article
AJG 1
Weight
0.50

What the paper says

This study investigates the strategic impact of big data adoption and analytics on organisational performance, with a specific focus on the telecommunications sector in a developing economy. Addressing a key gap in the extant literature, it proposes an integrated framework assessing how big data technologies influence financial and operational outcomes, as well as exploratory and exploitative innovation (EPI) capabilities. A quantitative research design was employed, using structured questionnaires distributed among senior and mid-level managers of telecommunications firms actively engaged in analytics. Structural equation modelling (SEM) was used to empirically validate the conceptual model. Results indicate that big data analytics (BDA) significantly enhance decision-making and forecasting, which subsequently improve financial and operational performance. Big data adoption fosters exploratory and EPI, explaining the variance in organisational performance. Innovation and decision-making emerge as critical mediators in translating data capabilities into competitive advantage. Practical implications emphasise continued investment in analytics infrastructure and human capital development.

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https://doi.org/https://doi.org/10.1504/ijkbd.2025.151403

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@article{elham2025,
  title        = {{The impact of big data acceptance and analysis on company performance}},
  author       = {Elham Nikmanesh et al.},
  journal      = {International Journal of Knowledge-Based Development},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1504/ijkbd.2025.151403},
}

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.