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Barriers to SMEs Adoption of Big Data Analytics for Competitive Advantage

Willetts, Matthew, ATKINS, Anthony and STANIER, Clare (2020) Barriers to SMEs Adoption of Big Data Analytics for Competitive Advantage. In: 2020 Fourth International Conference On Intelligent Computing in Data Sciences (ICDS). IEEE, pp. 1-8. ISBN 978-1-7281-8085-4

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Abstract or description

Small and medium-sized enterprises (SMEs) (which includes micro companies employing <; 10) make a significant contribution to the UK economy accounting for 99.9% of all businesses, employing 60% of the work ,orce and generates £2,168 billion; this represents 52% of the turnover of all businesses in the UK 11]. Big Data Analytics is rapidly being utilised by large companies on a global scale to gain competitive advantage which is well documented in the literature. However, the evidence from the literature indicates that SMEs are underutilising this technology for a variety of reasons, for example lack for expertise and cost implications. The intention of this paper is to identify barriers to the adoption of Big Data Analytics by SMEs to help them overcome the challenges and to exploit the benefits of Big Data Analytics to improve their competitive advantage which will benefit the wealth of the country particularly in the aftermath of Covid-19.

Item Type: Book Chapter, Section or Conference Proceeding
Additional Information: “© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.”
Uncontrolled Keywords: Big Data, Big Data Analytics, SMEs, Barriers to Big Data Analytics Adoption, Competitive Advantage, Covid-19
Faculty: School of Digital, Technologies and Arts > Augmented and Virtual Realities
Event Title: 4th International Conference on Intelligent Computing in Data Sciences, ICDS 2020. IEEE
Event Location: Fez, Morocco
Event Dates: 21-23/10/2020
Depositing User: Anthony ATKINS
Date Deposited: 19 Nov 2021 15:28
Last Modified: 19 Nov 2021 15:28
URI: http://eprints.staffs.ac.uk/id/eprint/7082

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