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An empirical investigation on how big data analytics influence China SMEs performance: do product and process innovation matter?

Author

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  • Hamza Saleem
  • Yongjun Li
  • Zulqurnain Ali
  • Aqsa Mehreen
  • Muhammad Salman Mansoor

Abstract

Globalization and a keen interest in big data have directed the firms to develop and utilize big data analytics (BDA) to bring technological innovation (TI) and enhance firm productivity. Using resource-based view theory (RBVT), we intend to predict TI and SMEs’ performance through BDA. Therefore, we recruited 312 Chinese SMEs’ officials using survey methods. The proposed model and structural associations were examined in AMOS. The findings suggest that BDA (predictive-and-prescriptive) is positively related to TI (product-and-process) and SMEs’ performance. Moreover, TI (product-and-process) mediates the relationship between BDA and SMEs performance. Finally, the study discussion and implications are recorded.

Suggested Citation

  • Hamza Saleem & Yongjun Li & Zulqurnain Ali & Aqsa Mehreen & Muhammad Salman Mansoor, 2020. "An empirical investigation on how big data analytics influence China SMEs performance: do product and process innovation matter?," Asia Pacific Business Review, Taylor & Francis Journals, vol. 26(5), pages 537-562, October.
    • Handle: RePEc:taf:apbizr:v:26:y:2020:i:5:p:537-562
    DOI: 10.1080/13602381.2020.1759300
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    Citations

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    Cited by:

    1. Showimy Aldossari & Umi Asma’ Mokhtar & Ahmad Tarmizi Abdul Ghani, 2023. "Factor Influencing the Adoption of Big Data Analytics: A Systematic Literature and Experts Review," SAGE Open, , vol. 13(4), pages 21582440231, December.
    2. Radicic, Dragana & Petković, Saša, 2023. "Impact of digitalization on technological innovations in small and medium-sized enterprises (SMEs)," Technological Forecasting and Social Change, Elsevier, vol. 191(C).
    3. Edmund Mallinguh & Christopher Wasike & Zeman Zoltan, 2020. "Technology Acquisition and SMEs Performance, the Role of Innovation, Export and the Perception of Owner-Managers," JRFM, MDPI, vol. 13(11), pages 1-19, October.
    4. Jaroslava Kádárová & Laura Lachvajderová & Dominika Sukopová, 2023. "Impact of Digitalization on SME Performance of the EU27: Panel Data Analysis," Sustainability, MDPI, vol. 15(13), pages 1-19, June.
    5. Qinghua Fu & Muhammad Safdar Sial & Muhammad Zulqarnain Arshad & Ubaldo Comite & Phung Anh Thu & József Popp, 2021. "The Inter-Relationship between Innovation Capability and SME Performance: The Moderating Role of the External Environment," Sustainability, MDPI, vol. 13(16), pages 1-14, August.
    6. Oesterreich, Thuy Duong & Anton, Eduard & Teuteberg, Frank & Dwivedi, Yogesh K, 2022. "The role of the social and technical factors in creating business value from big data analytics: A meta-analysis," Journal of Business Research, Elsevier, vol. 153(C), pages 128-149.
    7. Yasheng Chen & Mohammad Islam Biswas, 2021. "Turning Crisis into Opportunities: How a Firm Can Enrich Its Business Operations Using Artificial Intelligence and Big Data during COVID-19," Sustainability, MDPI, vol. 13(22), pages 1-17, November.
    8. Mariani, Marcello M. & Machado, Isa & Nambisan, Satish, 2023. "Types of innovation and artificial intelligence: A systematic quantitative literature review and research agenda," Journal of Business Research, Elsevier, vol. 155(PB).

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