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Business intelligence model empowering SMEs to make better decisions and enhance their competitive advantage
Small and medium-sized businesses (SMEs) typically steer clear of implementing business intelligence (BI) systems because they feel that this sort of modeling is complicated and costly. But the market for business intelligence (BI) has evolved quickly. New opportunities like cloud computing have gre...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9901379/ http://dx.doi.org/10.1007/s44257-022-00002-3 |
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author | Ragazou, Konstantina Passas, Ioannis Garefalakis, Alexandros Zopounidis, Constantin |
author_facet | Ragazou, Konstantina Passas, Ioannis Garefalakis, Alexandros Zopounidis, Constantin |
author_sort | Ragazou, Konstantina |
collection | PubMed |
description | Small and medium-sized businesses (SMEs) typically steer clear of implementing business intelligence (BI) systems because they feel that this sort of modeling is complicated and costly. But the market for business intelligence (BI) has evolved quickly. New opportunities like cloud computing have greatly lowered prices and eventually made it possible to design integrated solutions that are only intended for SMEs. In addition to highlighting the research trends in the sector under investigation, this paper explores the function of business intelligence in enhancing the decision-making process and competitive advantage of SMEs. The research subject has been approached using bibliometric analysis using the R package. The display of the results was done with the aid of Biblioshiny and VOSviewer's bibliometric tools. The study highlighted that SMEs have started integrating Business Intelligence systems. However, a new business model that will combine business analytics and will ensure to SMEs that emerging technologies will not affect them negatively is crucial. Thus, this research proposes the development of a new business model that will be based on Business Intelligence and Technology–organization–environment framework (TOE) framework, which helps SMEs to feel safe with emerging technologies. |
format | Online Article Text |
id | pubmed-9901379 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-99013792023-02-07 Business intelligence model empowering SMEs to make better decisions and enhance their competitive advantage Ragazou, Konstantina Passas, Ioannis Garefalakis, Alexandros Zopounidis, Constantin Discov Anal Review Small and medium-sized businesses (SMEs) typically steer clear of implementing business intelligence (BI) systems because they feel that this sort of modeling is complicated and costly. But the market for business intelligence (BI) has evolved quickly. New opportunities like cloud computing have greatly lowered prices and eventually made it possible to design integrated solutions that are only intended for SMEs. In addition to highlighting the research trends in the sector under investigation, this paper explores the function of business intelligence in enhancing the decision-making process and competitive advantage of SMEs. The research subject has been approached using bibliometric analysis using the R package. The display of the results was done with the aid of Biblioshiny and VOSviewer's bibliometric tools. The study highlighted that SMEs have started integrating Business Intelligence systems. However, a new business model that will combine business analytics and will ensure to SMEs that emerging technologies will not affect them negatively is crucial. Thus, this research proposes the development of a new business model that will be based on Business Intelligence and Technology–organization–environment framework (TOE) framework, which helps SMEs to feel safe with emerging technologies. Springer International Publishing 2023-02-06 2023 /pmc/articles/PMC9901379/ http://dx.doi.org/10.1007/s44257-022-00002-3 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Review Ragazou, Konstantina Passas, Ioannis Garefalakis, Alexandros Zopounidis, Constantin Business intelligence model empowering SMEs to make better decisions and enhance their competitive advantage |
title | Business intelligence model empowering SMEs to make better decisions and enhance their competitive advantage |
title_full | Business intelligence model empowering SMEs to make better decisions and enhance their competitive advantage |
title_fullStr | Business intelligence model empowering SMEs to make better decisions and enhance their competitive advantage |
title_full_unstemmed | Business intelligence model empowering SMEs to make better decisions and enhance their competitive advantage |
title_short | Business intelligence model empowering SMEs to make better decisions and enhance their competitive advantage |
title_sort | business intelligence model empowering smes to make better decisions and enhance their competitive advantage |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9901379/ http://dx.doi.org/10.1007/s44257-022-00002-3 |
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