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Big data analytics capabilities and organizational performance: the mediating effect of dual innovations

Xiaofeng Su (College of Business Administration, Fujian Business University, Fuzhou, China)
Weipeng Zeng (College of Economics and Management, Fujian Agriculture and Forestry University, Fuzhou, China)
Manhua Zheng (College of Economics and Management, Fujian Agriculture and Forestry University, Fuzhou, China)
Xiaoli Jiang (College of Economics and Management, Fujian Agriculture and Forestry University, Fuzhou, China)
Wenhe Lin (College of Economics and Management, Fujian Agriculture and Forestry University, Fuzhou, China)
Anxin Xu (College of Economics and Management, Fujian Agriculture and Forestry University, Fuzhou, China)

European Journal of Innovation Management

ISSN: 1460-1060

Article publication date: 12 April 2021

Issue publication date: 23 June 2022

2941

Abstract

Purpose

Following the rapid expansion of data volume, velocity and variety, techniques and technologies, big data analytics have achieved substantial development and a surge of companies make investments in big data. Academics and practitioners have been considering the mechanism through which big data analytics capabilities can transform into their improved organizational performance. This paper aims to examine how big data analytics capabilities influence organizational performance through the mediating role of dual innovations.

Design/methodology/approach

Drawing on the resource-based view and recent literature on big data analytics, this paper aims to examine the direct effects of big data analytics capabilities (BDAC) on organizational performance, as well as the mediating role of dual innovations on the relationship between (BDAC) and organizational performance. The study extends existing research by making a distinction of BDACs' effect on their outcomes and proposing that BDACs help organizations to generate insights that can help strengthen their dual innovations, which in turn have a positive impact on organizational performance. To test our proposed research model, this study conducts empirical analysis based on questionnaire-base survey data collected from 309 respondents working in Chinese manufacturing firms.

Findings

The results support the proposed hypotheses regarding the direct and indirect effect that BDACs have on organizational performance. Specifically, this paper finds that dual innovations positively mediate BDACs' effect on organizational performance.

Originality/value

The conclusions on the relationship between big data analytics capabilities and organizational performance in previous research are controversial due to lack of theoretical foundation and empirical testing. This study resolves the issue by provides empirical analysis, which makes the research conclusions more scientific and credible. In addition, previous literature mainly focused on BDACs' direct impact on organizational performance without making a distinction of BDAC's three dimensions. This study contributes to the literature by thoroughly introducing the notions of BDAC's three core constituents and fully analyzing their relationships with organizational performance. What's more, empirical research on the mechanism of big data analytics' influence on organizational performance is still at a rudimentary stage. The authors address this critical gap by exploring the mediation of dual innovations in the relationship through survey-based research. The research conclusions of this paper provide new perspective for understanding the impact of big data analytics capabilities on organizational performance, and enrich the theoretical research connotation of big data analysis capabilities and dual innovation behavior.

Keywords

Acknowledgements

Funding: This study is supported by Fujian Science and Technology Planning Project “A Research on the Performance Evaluation of Participants in the Rural-Business Interconnection Model in Fujian Province” (Grant 2020R0034), the think tank special project of the Ecological Civilization Research Center (Grant KXJD1840A), the first batch of cooperative education project of industry university cooperation of the Ministry of Education in 2020 (Grant 202002168035) and the 2020 annual project of the 13th five-year plan of educational science of Fujian (Grant FJJKCG20-244).

Conflicts of Interest: There are no conflicts of interest among authors.

Citation

Su, X., Zeng, W., Zheng, M., Jiang, X., Lin, W. and Xu, A. (2022), "Big data analytics capabilities and organizational performance: the mediating effect of dual innovations", European Journal of Innovation Management, Vol. 25 No. 4, pp. 1142-1160. https://doi.org/10.1108/EJIM-10-2020-0431

Publisher

:

Emerald Publishing Limited

Copyright © 2021, Emerald Publishing Limited

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