Big Data Analytics Capability Ecosystem Model for SMEs

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.

Appropriate Means to Vulgarize the Human Cytogenetics

“…Moreover, data represents information collected during the conduct of a research project. Their analysis and interpretation is a phase which essentially includes operations of classification, comparison, on each of the information collected in order to find its meaning and to draw conclusions [28] [29] [30]. In the area of research, there is a need for additional support in the management and analysis of large datasets as there seems to be a lack of knowledge about tools and resources for data management.…”

“…In the area of research, there is a need for additional support in the management and analysis of large datasets as there seems to be a lack of knowledge about tools and resources for data management. Barriers to acquiring currently available tools are most often related to the financial burdens of small labs and unmet expectations for institutional support [28] [29] [30].…”

“…Institutions should facilitate the training of researchers in management strategies for conducting preserved data themselves, using for example secure networks and data encryption by user authentication through the password [28] [29] [30].…”

The impact of artificial intelligence (AI) on employees’ skills and well-being in global labor markets: A systematic review

“…While exploring the relevant papers regarding the impact of AI on employees, both the professional dimension (skills related) as well as the personal one (well-being related) were considered. As far as the impact on skills is concerned, the large adoption of AI-related technologies has led to a clear need to upskill the professional profile of employees (the readiness for so-called human-machine competencies (Semaan et al, 2021;Jaiswal et al, 2022) and/or to reskill employees in properly adopting the new job requirements (Li, 2022;Falahat et al, 2023). The need for continuous learning focused on digital skills is clear, through upskilling or reskilling.…”

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“…Talent is crucial for harnessing skills and competencies. Falahat et al [11] articulated that digitalisation requires skilful and talented people. Those with substandard talent would encounter difficulties and must put extra effort into familiarising themselves.…”