Factor Influencing the Adoption of Big Data Analytics: A Systematic Literature and Experts Review

被引:4
|
作者
Aldossari, Showimy [1 ,2 ]
Mokhtar, Umi Asma' [1 ]
Ghani, Ahmad Tarmizi Abdul [1 ]
机构
[1] Univ Kebangsaan Malaysia, Bangi, Selangor, Malaysia
[2] Univ Kebangsaan Malaysia, Fac Informat Sci & Technol, Bangi 43600, Selangor, Malaysia
来源
SAGE OPEN | 2023年 / 13卷 / 04期
关键词
big data analytics; systematic literature review; technology adoption; experts rank; factors extraction; small and medium-sized enterprises; BUSINESS INTELLIGENCE BI; SUPPLY CHAIN MANAGEMENT; DECISION-MAKING; PREDICTIVE ANALYTICS; DATA TECHNOLOGIES; PERFORMANCE; IMPLEMENTATION; FUTURE; MODEL; ERP;
D O I
10.1177/21582440231217902
中图分类号
C [社会科学总论];
学科分类号
03 ; 0303 ;
摘要
In the current market landscape, enterprises face tremendous pressure to remain competitive and innovative to extend their businesses globally. Thus, a need exists for a new data analysis technique and a tool known as Big Data Analytics (BDA), which refers to massive data sets in light of their volume, velocity, variety, and veracity. Small and Medium Enterprises (SMEs) face challenges in obtaining and utilizing the knowledge derived from big data to make informed decisions regarding market selection and adopting appropriate internationalization strategies. These enterprises encounter resource limitations that hinder their ability to effectively acquire and implement big data insights for strategic decision-making in these areas. This systematic literature review aims to investigate the state of research on adopting big data analytics in SMEs. The study focuses on identifying key factors that influence the adoption of BDA. The study extracted 13 significant factors that are the highest influencers for BDA in SMEs. Those factors are top management support, training, relative advantage, it infrastructure, security, compatibility, complexity, adaptability, government it policies, competency, collaboration, digital transformation tools, and decision quality. The findings of this review are useful for practitioners, researchers, and decision-makers in understanding the factors that influence the adoption of big data analytics and the potential benefits and challenges associated with its implementation. Findings will shed light on the interplay between data governance and other factors influencing adoption, providing valuable insights for organizations seeking to establish robust data governance frameworks that support successful BDA initiatives. Key Factors in Adopting Big Data Analytics: Insights from Literature and Expert ReviewsPurpose: The purpose of our study is to investigate the adoption of Big Data Analytics (BDA) in Small and Medium Enterprises (SMEs) and identify the key factors influencing its implementation. Methods: To achieve our research objective, we conducted a systematic literature review to gather and critically evaluate relevant studies on BDA adoption in SMEs. This approach allowed us to synthesize and analyze a wide range of existing research to gain comprehensive insights. Conclusions: Our study revealed 13 significant factors that have a strong influence on BDA adoption in SMEs. These factors include top management support, training, relative advantage, IT infrastructure, security, compatibility, complexity, adaptability, government IT policies, competency, collaboration, digital transformation tools, and decision quality. Implications: The findings of our research have practical implications for SMEs, researchers, and decision-makers. Understanding these key factors can help SMEs develop effective strategies to successfully implement BDA and gain a competitive advantage in the global market. For researchers, our study contributes to the body of knowledge on BDA adoption in SMEs, paving the way for further investigations and academic discussions in this area. Limitations: Despite the valuable insights gained from the systematic literature review, our study has certain limitations. The focus on SMEs may restrict the generalizability of the findings to larger enterprises. Additionally, while we strived to encompass a wide range of studies, there might be some relevant research that was not included in our analysis. These limitations should be considered when interpreting the results and applying them to specific contexts.
引用
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页数:25
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