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Big Data Analytics Capability Ecosystem Model for SMEs

Author

Listed:
  • Mohammad Falahat

    (Centre for Entrepreneurial Sustainability, Universiti Tunku Abdul Rahman (UTAR), Sungai Long Campus, Bandar Sungai Long 43000, Malaysia)

  • Phaik Kin Cheah

    (Faculty of Arts and Social Science, Universiti Tunku Abdul Rahman (UTAR), Kampar Campus, Kampar 31900, Malaysia)

  • Jayamalathi Jayabalan

    (Centre for Entrepreneurial Sustainability, Universiti Tunku Abdul Rahman (UTAR), Sungai Long Campus, Bandar Sungai Long 43000, Malaysia)

  • Corrinne Mei Jyin Lee

    (Centre for Entrepreneurial Sustainability, Universiti Tunku Abdul Rahman (UTAR), Sungai Long Campus, Bandar Sungai Long 43000, Malaysia)

  • Sia Bik Kai

    (Institute of Strategic Analysis & Policy Research, Kuala Lumpur 50450, Malaysia)

Abstract

The unprecedented COVID-19 pandemic, together with globalization and advanced technologies, has drastically changed the business environment and forced companies to become more innovative and agile in the way they run their business and respond to the needs and wants of customers. Survival highly depends on the adaptability of SMEs to this ever-changing complex dynamic environment by taking steps in implementing Big Data Analytics as the next frontier for innovation, competition, productivity, and value creation. Based on the grounded theory, this study employed a qualitative method via focus group discussion. Focus groups were conducted with 14 government agencies, SMEs associations, business owners, Chief Operating Officers (CEOs), academic and industrial experts and directors of SMEs in Malaysia. The study revealed the challenges of Malaysian SMEs in adopting Big Data Analytics Capability, presents the criticality of Big Data Analytics Capability to overcome the identified challenges, and develops a BDA Capability Ecosystem Model that integrates the internal enablers, external barriers and support to explain the adoption of BDA Capability for value creation and support the decision-making process. This paper is followed by some policy suggestions for companies’ owners, policymakers, government agencies, universities, and SMEs. This study directly impacts Malaysia’s economy as a whole by addressing Malaysia’s Shared Prosperity Vision 2030. This research contributes to industries that are still in the low value added category with low adoption of technology. Furthermore, it will ultimately lead to the realization of SMEs as ‘game changers’ to transition the economy to a high-income nation. This study proposes a model that could help SMEs improve their value creation performance, directly influencing the country’s GDP and employability.

Suggested Citation

  • Mohammad Falahat & Phaik Kin Cheah & Jayamalathi Jayabalan & Corrinne Mei Jyin Lee & Sia Bik Kai, 2022. "Big Data Analytics Capability Ecosystem Model for SMEs," Sustainability, MDPI, vol. 15(1), pages 1-23, December.
    • Handle: RePEc:gam:jsusta:v:15:y:2022:i:1:p:360-:d:1015240
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    References listed on IDEAS

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    1. Cabrera-Sánchez, Juan-Pedro & Villarejo-Ramos, à ngel F., 2020. "Acceptance and use of big data techniques in services companies," Journal of Retailing and Consumer Services, Elsevier, vol. 52(C).
    2. Alberto Bertello & Alberto Ferraris & Stefano Bresciani & Paola Bernardi, 2021. "Big data analytics (BDA) and degree of internationalization: the interplay between governance of BDA infrastructure and BDA capabilities," Journal of Management & Governance, Springer;Accademia Italiana di Economia Aziendale (AIDEA), vol. 25(4), pages 1035-1055, December.
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    Cited by:

    1. Dong Feng & Jiayi Han & Han Jia & Xinyuan Chang & Jiaqi Guo & Pinghua Huang, 2023. "Regional Economic Growth and Environmental Protection in China: The Yellow River Basin Economic Zone as an Example," Sustainability, MDPI, vol. 15(14), pages 1-20, July.

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