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DC Field | Value | Language |
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dc.contributor.author | Tikoria, Jyoti | - |
dc.date.accessioned | 2023-05-08T06:28:31Z | - |
dc.date.available | 2023-05-08T06:28:31Z | - |
dc.date.issued | 2021 | - |
dc.identifier.uri | https://www.inderscience.com/info/ingeneral/forthcoming.php?jcode=ijbis | - |
dc.identifier.uri | http://dspace.bits-pilani.ac.in:8080/xmlui/handle/123456789/10683 | - |
dc.description.abstract | While there have been studies for development and evaluation of maturity models for measuring business intelligence and analytics (BI&A) capability maturity of organisations, there has been no empirical study done solely for assessing the BI&A capability maturity of organisations. The purpose of this paper is to measure the BI&A capability maturity in organisations. This has been done through an empirical study with a sample of 145 organisations from different industry sectors in India. BI&A capability maturity has been assessed using six influencing factors. Analysis has been done based on industry sectors and segments, where findings have indicated some distinct industry segments with varying BI&A capability maturity. Organisations have also been grouped based on the maturity of six factors using K-means clustering technique. Each cluster was found to be representing a different level of maturity. The clusters have been reorganised to bring out interesting insights about BI&A capability maturity. The study presents important managerial implications. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Inder Science | en_US |
dc.subject | Management | en_US |
dc.subject | Business Intelligence | en_US |
dc.subject | Business analytics | en_US |
dc.subject | Capability maturity | en_US |
dc.subject | K-means clustering | en_US |
dc.subject | Elbow method | en_US |
dc.subject | Factor analysis | en_US |
dc.title | Measuring Business Intelligence & Analytics capability maturity: A study of organizations in India | en_US |
dc.type | Article | en_US |
Appears in Collections: | Department of Management |
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