Exploring the relationship between big data and firm performance
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Low-Choy, Samantha
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Abstract
Big data offers great potential to improve organizational performance and generate competitive advantages. In this sense, knowing this phenomenon is relevant and this study aims to explore the role of big data on firm performance through a process of synthesis of several studies that have been published in recent years in different organizational contexts. This study adopts a mixed-methods approach. Initially, a systematic literature review is performed to characterize the studies that adopt structural equation modeling to determine the relationship between big data and firm performance. Additionally, a meta-analysis method is used to quantify the association between these two phenomena. The findings reveal a moderate positive relationship between the adoption of big data in the firm performance. This ratio is estimated at 0.38 with a confidence interval between 0.32 and 0.44 for a significance level of 0.05. The results of this study also allow us to conclude that the performance of organizations is also determined by other factors such as human capital, the data-driven organizational culture, or the learning capacity of the organization. This study offers mainly implications for companies that intend to invest in big data to know the potential value of this technology in organizational performance.
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Management Research and Practice
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13
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3
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© 2021 Research Centre in Public Administration and Public Services, Bucharest University of Economic Studies. The attached file is reproduced here in accordance with the copyright policy of the publisher. Please refer to the journal's website for access to the definitive, published version.
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Data management and data science
Statistical data science
Applied statistics
Building information modelling and management
Social Sciences
Management
Business & Economics
big data capabilities
performance
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Almeida, F; Low-Choy, S, Exploring the relationship between big data and firm performance, Management Research and Practice, 2021, 13 (3), pp. 43-57