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Big Data, Big Data Analytics Capability, and Sustainable Innovation Performance

Author

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  • Shengbin Hao

    (School of Management, Harbin Institute of Technology, Harbin 150001, China)

  • Haili Zhang

    (School of Economics and Management, Xi’an Technological University, Xi’an 720021, China)

  • Michael Song

    (School of Economics and Management, Xi’an Technological University, Xi’an 720021, China)

Abstract

Literature suggests that big data is a new competitive advantage and that it enhance organizational performance. Yet, previous empirical research has provided conflicting results. Building on the resource-based view and the organizational inertia theory, we develop a model to investigate how big data and big data analytics capability affect innovation success. We show that there is a trade-off between big data and big data analytics capability and that optimal balance of big data depends upon levels of big data analytics capability. We conduct a four-year empirical research project to secure empirical data on 1109 data-driven innovation projects from the United States and China. This research is the first time reporting the empirical results. The study findings reveal several surprising results that challenge traditional views of the importance of big data in innovation. For U.S. innovation projects, big data has an inverted U-shaped relationship with sales growth. Big data analytics capability exerts a positive moderating effect, that is, the stronger this capability is, the greater the impact of big data on sales growth and gross margin. For Chinese innovation projects, when big data resource is low, promoting big data analytics capability increases sales growth and gross margin up to a certain point; developing big data analytics capability beyond that point may actually inhibit innovation performance. Our findings provide guidance to firms on making strategic decisions regarding resource allocations for big data and big data analytics capability.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:24:p:7145-:d:297587
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    References listed on IDEAS

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    1. Feng Hu & Wei Liu & Sang-Bing Tsai & Junbin Gao & Ning Bin & Quan Chen, 2018. "An Empirical Study on Visualizing the Intellectual Structure and Hotspots of Big Data Research from a Sustainable Perspective," Sustainability, MDPI, vol. 10(3), pages 1-19, March.
    2. Patrick Mikalef & Ilias O. Pappas & John Krogstie & Michail Giannakos, 2018. "Big data analytics capabilities: a systematic literature review and research agenda," Information Systems and e-Business Management, Springer, vol. 16(3), pages 547-578, August.
    3. Akter, Shahriar & Wamba, Samuel Fosso & Gunasekaran, Angappa & Dubey, Rameshwar & Childe, Stephen J., 2016. "How to improve firm performance using big data analytics capability and business strategy alignment?," International Journal of Production Economics, Elsevier, vol. 182(C), pages 113-131.
    4. Miltiades D. Lytras & Anna Visvizi, 2019. "Big Data and Their Social Impact: Preliminary Study," Sustainability, MDPI, vol. 11(18), pages 1-18, September.
    5. Y. Lisa Zhao & Michael Song & Gregory L. Storm, 2013. "Founding Team Capabilities and New Venture Performance: The Mediating Role of Strategic Positional Advantages," Entrepreneurship Theory and Practice, , vol. 37(4), pages 789-814, July.
    6. Lei Xu & Runpeng Gao & Yu Xie & Peng Du, 2019. "To Be or Not to Be? Big Data Business Investment Decision-Making in the Supply Chain," Sustainability, MDPI, vol. 11(8), pages 1-14, April.
    7. Chunjia Hu & Haili Zhang & Michael Song & Dapeng Liang, 2019. "Past Performance, Organizational Aspiration, and Organizational Performance: The Moderating Effect of Environmental Jolts," Sustainability, MDPI, vol. 11(15), pages 1-16, August.
    8. Sunghae Jun, 2019. "Bayesian Structural Time Series and Regression Modeling for Sustainable Technology Management," Sustainability, MDPI, vol. 11(18), pages 1-12, September.
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    Cited by:

    1. Huynh, Minh-Tay & Nippa, Michael & Aichner, Thomas, 2023. "Big data analytics capabilities: Patchwork or progress? A systematic review of the status quo and implications for future research," Technological Forecasting and Social Change, Elsevier, vol. 197(C).
    2. Zhengang Zhang & Yu Shang & Linyuan Cheng & Antao Hu, 2022. "Big Data Capability and Sustainable Competitive Advantage: The Mediating Role of Ambidextrous Innovation Strategy," Sustainability, MDPI, vol. 14(14), pages 1-17, July.
    3. Haili Zhang & Michael Song & Huanhuan He, 2020. "Achieving the Success of Sustainability Development Projects through Big Data Analytics and Artificial Intelligence Capability," Sustainability, MDPI, vol. 12(3), pages 1-23, January.
    4. S. M. F. D. Syed Mustapha, 2022. "The UAE Employees’ Perceptions towards Factors for Sustaining Big Data Implementation and Continuous Impact on Their Organization’s Performance," Sustainability, MDPI, vol. 14(22), pages 1-19, November.
    5. 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.
    6. Meng Zhang & Yong Qi, 2023. "Vertical Network Relationships, Technological Capabilities, and Innovation Performance: The Moderating Role of Strategic Flexibility," Sustainability, MDPI, vol. 15(14), pages 1-15, July.
    7. JAHAN Sakila Akter & SAZU Mesbaul Haque, 2022. "Innovation Management: Is Big Data Necessarily Better Data?," Management of Sustainable Development, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, vol. 14(2), pages 27-33, December.
    8. Yufan Wang & Haili Zhang, 2020. "Achieving Sustainable New Product Development by Implementing Big Data-Embedded New Product Development Process," Sustainability, MDPI, vol. 12(11), pages 1-20, June.
    9. Miloš Arsić & Zoran Jovanović & Radoljub Tomić & Nena Tomović & Siniša Arsić & Ištvan Bodolo, 2020. "Impact of Logistics Capacity on Economic Sustainability of SMEs," Sustainability, MDPI, vol. 12(5), pages 1-30, March.
    10. Xiaoli Wang & Ying Gu & Mahmood Ahmad & Chaokai Xue, 2022. "The Impact of Digital Capability on Manufacturing Company Performance," Sustainability, MDPI, vol. 14(10), pages 1-24, May.
    11. Mihai BOGDAN & Anca BORZA, 2020. "Big Data Analytics And Firm Performance: A Text Mining Approach," Proceedings of the INTERNATIONAL MANAGEMENT CONFERENCE, Faculty of Management, Academy of Economic Studies, Bucharest, Romania, vol. 14(1), pages 549-560, November.
    12. Qidi Dong & Jun Cai & Shuo Chen & Pengman He & Xuli Chen, 2022. "Spatiotemporal Analysis of Urban Green Spatial Vitality and the Corresponding Influencing Factors: A Case Study of Chengdu, China," Land, MDPI, vol. 11(10), pages 1-17, October.
    13. Weihong Xie & Qian Zhang & Yuyao Lin & Zhong Wang & Zhongshun Li, 2024. "The Effect of Big Data Capability on Organizational Innovation: a Resource Orchestration Perspective," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(1), pages 3767-3791, March.
    14. Haili Zhang & Yufan Wang & Michael Song, 2019. "Does Competitive Intensity Moderate the Relationships between Sustainable Capabilities and Sustainable Organizational Performance in New Ventures?," Sustainability, MDPI, vol. 12(1), pages 1-18, December.
    15. Guixiang Cao & Xintong Fang & Ying Chen & Jinghuai She, 2023. "Regional Big Data Application Capability and Firm Green Technology Innovation," Sustainability, MDPI, vol. 15(17), pages 1-29, August.
    16. Irina Bogdana Pugna & Dana Maria Boldeanu & Mirela Gheorghe & Gabriel Cozgarea & Adrian Nicolae Cozgarea, 2022. "Management Perspectives towards the Data-Driven Organization in the Energy Sector," Energies, MDPI, vol. 15(16), pages 1-20, August.
    17. Michael Song & Haili Zhang & Jinjin Heng, 2020. "Creating Sustainable Innovativeness through Big Data and Big Data Analytics Capability: From the Perspective of the Information Processing Theory," Sustainability, MDPI, vol. 12(5), pages 1-23, March.
    18. Okharedia Goodheart Akhimien & Simon Ayo Adekunle, 2023. "Technological environment and sustainable performance of oil and gas firms: a structural equation modelling approach," Future Business Journal, Springer, vol. 9(1), pages 1-11, December.
    19. Philipp Korherr & Dominik Kanbach, 2023. "Human-related capabilities in big data analytics: a taxonomy of human factors with impact on firm performance," Review of Managerial Science, Springer, vol. 17(6), pages 1943-1970, August.

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