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How and When Does Big Data Analytics Capability Boost Innovation Performance?

Author

Listed:
  • Hua Zhang

    (Sunwah International Business School, Faculty of Economics, Liaoning University, Shenyang 110000, China)

  • Shaofeng Yuan

    (Business School, Faculty of Economics, Liaoning University, Shenyang 110000, China)

Abstract

The diffusion of big data in recent years has stimulated many companies to develop big data analytics capability (BDAC) to boost innovation performance. However, research regarding how and when BDAC can increase innovation performance is still scant. This study aims to test how (i.e., the mediating role of strategic flexibility and strategic innovation) and when (i.e., the moderating role of environmental uncertainty) BDAC can boost a firm’s innovation performance drawing on resource-based theory. Through a survey of 421 Chinese managers and employees who are engaged in the field of big data analytics, this study reveals that (1) BDAC has a positive effect on innovation performance, (2) strategic flexibility and strategic innovation play a significant serial mediating role in this relationship, and (3) the positive effect of BDAC on innovation performance is more significant under high (vs. low) environmental uncertainty conditions. This study contributes to the extant literature by verifying how BDAC can increase a firm’s innovation performance through the serial mediating role of strategic flexibility and strategic innovation. It also confirms a contingent factor (i.e., environmental uncertainty) regarding the positive effect of BDAC on innovation performance.

Suggested Citation

  • Hua Zhang & Shaofeng Yuan, 2023. "How and When Does Big Data Analytics Capability Boost Innovation Performance?," Sustainability, MDPI, vol. 15(5), pages 1-19, February.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:5:p:4036-:d:1077436
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    References listed on IDEAS

    as
    1. Kawasaki, Tomoya & Wakashima, Hisayuki & Shibasaki, Ryuichi, 2022. "The use of e-commerce and the COVID-19 outbreak: A panel data analysis in Japan," Transport Policy, Elsevier, vol. 115(C), pages 88-100.
    2. Amankwah-Amoah, Joseph & Khan, Zaheer & Wood, Geoffrey & Knight, Gary, 2021. "COVID-19 and digitalization: The great acceleration," Journal of Business Research, Elsevier, vol. 136(C), pages 602-611.
    3. Sam Tavassoli & Lars Bengtsson, 2018. "The Role Of Business Model Innovation For Product Innovation Performance," International Journal of Innovation Management (ijim), World Scientific Publishing Co. Pte. Ltd., vol. 22(07), pages 1-28, October.
    4. Shengbin Hao & Haili Zhang & Michael Song, 2019. "Big Data, Big Data Analytics Capability, and Sustainable Innovation Performance," Sustainability, MDPI, vol. 11(24), pages 1-15, December.
    5. Erevelles, Sunil & Fukawa, Nobuyuki & Swayne, Linda, 2016. "Big Data consumer analytics and the transformation of marketing," Journal of Business Research, Elsevier, vol. 69(2), pages 897-904.
    6. Vinicius Luiz Ferraz Minatogawa & Matheus Munhoz Vieira Franco & Izabela Simon Rampasso & Rosley Anholon & Ruy Quadros & Orlando Durán & Antonio Batocchio, 2019. "Operationalizing Business Model Innovation through Big Data Analytics for Sustainable Organizations," Sustainability, MDPI, vol. 12(1), pages 1-29, December.
    7. Ghasemaghaei, Maryam & Calic, Goran, 2020. "Assessing the impact of big data on firm innovation performance: Big data is not always better data," Journal of Business Research, Elsevier, vol. 108(C), pages 147-162.
    8. Tauno Kekale & Petra De Weerd-Nederhof & Klaasjan Visscher & Ger Bos, 2010. "Achieving sustained innovation performance through strategic flexibility of new product development," International Journal of Innovation and Learning, Inderscience Enterprises Ltd, vol. 7(4), pages 377-393.
    9. Kevin Zheng Zhou & Fang Wu, 2010. "Technological capability, strategic flexibility, and product innovation," Strategic Management Journal, Wiley Blackwell, vol. 31(5), pages 547-561, May.
    10. Thomas Niebel & Fabienne Rasel & Steffen Viete, 2019. "BIG data – BIG gains? Understanding the link between big data analytics and innovation," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 28(3), pages 296-316, April.
    11. Angel L. Meroño-Cerdán & Carolina López-Nicolás & Francisco J. Molina-Castillo, 2018. "Risk aversion, innovation and performance in family firms," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 27(2), pages 189-203, February.
    12. Abdul Majid & Muhammad Yasir & Muhammad Yasir & Zahid Yousaf, 2021. "Network capability and strategic performance in SMEs: the role of strategic flexibility and organizational ambidexterity," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 11(4), pages 587-610, December.
    13. Jinyong Chen & Xiaochi Wang & Wan Shen & Yanyan Tan & Liviu Marian Matac & Sarminah Samad, 2022. "Environmental Uncertainty, Environmental Regulation and Enterprises’ Green Technological Innovation," IJERPH, MDPI, vol. 19(16), pages 1-28, August.
    14. Olabode, Oluwaseun E. & Boso, Nathaniel & Hultman, Magnus & Leonidou, Constantinos N., 2022. "Big data analytics capability and market performance: The roles of disruptive business models and competitive intensity," Journal of Business Research, Elsevier, vol. 139(C), pages 1218-1230.
    15. Pereira, Vijay & Budhwar, Pawan & Temouri, Yama & Malik, Ashish & Tarba, Shlomo, 2021. "Investigating Investments in agility strategies in overcoming the global financial crisis - The case of Indian IT/BPO offshoring firms," Journal of International Management, Elsevier, vol. 27(1).
    16. Sarah Cheah & Shenghui Wang, 2017. "Big data-driven business model innovation by traditional industries in the Chinese economy," Journal of Chinese Economic and Foreign Trade Studies, Emerald Group Publishing Limited, vol. 10(3), pages 229-251, October.
    17. Miroshnychenko, Ivan & Strobl, Andreas & Matzler, Kurt & De Massis, Alfredo, 2021. "Absorptive capacity, strategic flexibility, and business model innovation: Empirical evidence from Italian SMEs," Journal of Business Research, Elsevier, vol. 130(C), pages 670-682.
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