Business intelligence effectiveness and corporate performance management: an empirical analysis
Business intelligence (BI) technologies have received much attention from both academics and practitioners, and the emerging field of business analytics (BA) is beginning to generate academic research. However, the impact of BI and the relative importance of BA on corporate performance management (C...
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| Format: | Article |
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Taylor & Francis
2017
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| Online Access: | https://eprints.nottingham.ac.uk/51904/ |
| _version_ | 1848798600183676928 |
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| author | Richards, Gregory Yeoh, William Chong, Alain Yee Loong Popovič, Aleš |
| author_facet | Richards, Gregory Yeoh, William Chong, Alain Yee Loong Popovič, Aleš |
| author_sort | Richards, Gregory |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | Business intelligence (BI) technologies have received much attention from both academics and practitioners, and the emerging field of business analytics (BA) is beginning to generate academic research. However, the impact of BI and the relative importance of BA on corporate performance management (CPM) have not yet been investigated. To address this gap, we modeled a CPM framework based on the Integrative model of IT business value and on information processing theory. Data were collected from a global survey of senior managers in 337 companies. Findings suggest that the more effective the BI implementation, the more effective the CPM-related planning and analytic practices. BI effectiveness is strongly related to BA, planning and to measurement. In contrast, BA effectiveness is strongly related to planning but less so to measurement. The study suggests that although both BI and BA contribute to corporate management practices, the information needs are different based on the level of uncertainty versus ambiguity characteristic of the management practice. |
| first_indexed | 2025-11-14T20:22:21Z |
| format | Article |
| id | nottingham-51904 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T20:22:21Z |
| publishDate | 2017 |
| publisher | Taylor & Francis |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-519042020-05-04T18:58:02Z https://eprints.nottingham.ac.uk/51904/ Business intelligence effectiveness and corporate performance management: an empirical analysis Richards, Gregory Yeoh, William Chong, Alain Yee Loong Popovič, Aleš Business intelligence (BI) technologies have received much attention from both academics and practitioners, and the emerging field of business analytics (BA) is beginning to generate academic research. However, the impact of BI and the relative importance of BA on corporate performance management (CPM) have not yet been investigated. To address this gap, we modeled a CPM framework based on the Integrative model of IT business value and on information processing theory. Data were collected from a global survey of senior managers in 337 companies. Findings suggest that the more effective the BI implementation, the more effective the CPM-related planning and analytic practices. BI effectiveness is strongly related to BA, planning and to measurement. In contrast, BA effectiveness is strongly related to planning but less so to measurement. The study suggests that although both BI and BA contribute to corporate management practices, the information needs are different based on the level of uncertainty versus ambiguity characteristic of the management practice. Taylor & Francis 2017-07-31 Article PeerReviewed Richards, Gregory, Yeoh, William, Chong, Alain Yee Loong and Popovič, Aleš (2017) Business intelligence effectiveness and corporate performance management: an empirical analysis. Journal of Computer Information Systems . ISSN 0887-4417 Business intelligence; corporate performance management; empirical study https://www.tandfonline.com/doi/figure/10.1080/08874417.2017.1334244?scroll=top&needAccess=true doi:10.1080/08874417.2017.1334244 doi:10.1080/08874417.2017.1334244 |
| spellingShingle | Business intelligence; corporate performance management; empirical study Richards, Gregory Yeoh, William Chong, Alain Yee Loong Popovič, Aleš Business intelligence effectiveness and corporate performance management: an empirical analysis |
| title | Business intelligence effectiveness and corporate performance management: an empirical analysis |
| title_full | Business intelligence effectiveness and corporate performance management: an empirical analysis |
| title_fullStr | Business intelligence effectiveness and corporate performance management: an empirical analysis |
| title_full_unstemmed | Business intelligence effectiveness and corporate performance management: an empirical analysis |
| title_short | Business intelligence effectiveness and corporate performance management: an empirical analysis |
| title_sort | business intelligence effectiveness and corporate performance management: an empirical analysis |
| topic | Business intelligence; corporate performance management; empirical study |
| url | https://eprints.nottingham.ac.uk/51904/ https://eprints.nottingham.ac.uk/51904/ https://eprints.nottingham.ac.uk/51904/ |