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Identifying Organizational Factors for Successful Business Intelligence Implementation

Identifying Organizational Factors for Successful Business Intelligence Implementation

Md Shaheb Ali, Shah J. Miah
Copyright: © 2018 |Volume: 9 |Issue: 2 |Pages: 17
ISSN: 1947-3591|EISSN: 1947-3605|EISBN13: 9781522545415|DOI: 10.4018/IJBIR.2018070103
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MLA

Ali, Md Shaheb, and Shah J. Miah. "Identifying Organizational Factors for Successful Business Intelligence Implementation." IJBIR vol.9, no.2 2018: pp.47-63. http://doi.org/10.4018/IJBIR.2018070103

APA

Ali, M. S. & Miah, S. J. (2018). Identifying Organizational Factors for Successful Business Intelligence Implementation. International Journal of Business Intelligence Research (IJBIR), 9(2), 47-63. http://doi.org/10.4018/IJBIR.2018070103

Chicago

Ali, Md Shaheb, and Shah J. Miah. "Identifying Organizational Factors for Successful Business Intelligence Implementation," International Journal of Business Intelligence Research (IJBIR) 9, no.2: 47-63. http://doi.org/10.4018/IJBIR.2018070103

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Abstract

Business intelligence (BI) has proliferated due to its growing application for business decision support. Research on organizational factors may offer significant use in BI implementation. However, a limited number of studies focus on organizational factors for revealing adverse impacts on effective decision support. The aim of this theoretical study is to conduct a literature analysis to identify organizational factors relevant to BI implementation. Through a systematic literature review, a qualitative content analysis on 49 relevant sample articles for generating themes inductively is adopted to reveal organizational factors. Findings suggest two contexts: information management that integrates factors such as technological capability and personnel capability and organizational context that integrates factors such as organizational capability, managerial decision, and organizational culture for facilitating embedding information management capability for BI implementation in businesses. It is hoped that these contextual understanding can be useful for further BI implementations.

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