Willetts, Matthew and ATKINS, Anthony (2024) Big Data Analytics Maturity Model for SMEs. International Journal of Information Technology and Computer Science, 16 (2). pp. 1-15. ISSN 2074-9007
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Abstract or description
Small and medium-sized enterprises (SMEs) are the backbone of the global economy, constituting 90% of all businesses. Despite being widely adopted by large businesses who have reported numerous benefits including increased profitability and increased efficiency and a survey in 2017 of 50 Fortune 1000 and leading firms’ executives indicated that 48.4% of respondents confirmed they are achieving measurable results from their Big Data investments, with 80.7% confirming that they have generated business. Big Data Analytics is adopted by only 10% of SMEs. The paper outlines a review of Big Data Maturity Models and discusses their positive features and limitations. Previous research has analysed the barriers to adoption of Big Data Analytics in SMEs and a scoring tool has been developed to help SMEs adopt Big Data Analytics. The paper demonstrates that the scoring tool could be translated and compared to a Maturity Model to provide a visual representation of Big Data Analytics maturity and help SMEs to understand where they are on the journey. The paper outlines a case study to show a comparison to provide intuitive visual model to assist top management to improve their competitive advantage.
Item Type: | Article |
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Uncontrolled Keywords: | Big Data Analytics, Maturity Model, SMEs, Scoring Tool |
Faculty: | School of Digital, Technologies and Arts > Computer Science, AI and Robotics |
Depositing User: | Anthony ATKINS |
Date Deposited: | 06 Dec 2024 15:50 |
Last Modified: | 06 Dec 2024 15:50 |
URI: | https://eprints.staffs.ac.uk/id/eprint/8568 |