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Successful enterprise resource planning implementation: taxonomy of critical factors

Shahin Dezdar (Faculty of Business and Accountancy, University of Malaya, Kuala Lumpur, Malaysia)
Ainin Sulaiman (Faculty of Business and Accountancy, University of Malaya, Kuala Lumpur, Malaysia)

Industrial Management & Data Systems

ISSN: 0263-5577

Article publication date: 25 September 2009

6454

Abstract

Purpose

The purpose of this paper is to investigate the current literature base of critical success factors (CSFs) of enterprise resource planning (ERP) implementations, provide a systematic compilation of CSFs, and present a new comprehensive taxonomy of CSFs for ERP system implementation.

Design/methodology/approach

This paper compiles literature that highlighted possible references to CSFs for ERP implementation projects. Given that the purpose of this paper is to achieve a depth of understanding of the various CSFs already identified by other researchers, “content analysis” is used. Four stages of content analysis are adopted to collect and analyse the literature, i.e. data collection, open coding, axial coding, and selective coding.

Findings

By analyzing all CFSs mentioned in literature during the last ten years (1999‐2008), taxonomy of ERP CSFs implementation was formulated. In total 17 CSFs were identified, which is then categorized into five main categories.

Research limitations/implications

Literature is collected from selected databases and journals from 1999 to 2008.

Practical implications

This paper is significant because taxonomy helps us organize the knowledge. Taxonomy can help the researchers to make their search easier by assigning CSFs to a category and defining relationships between those categories.

Originality/value

The output of this paper will help future researchers to increase identification of related studies in the literature review phase of their work.

Keywords

Citation

Dezdar, S. and Sulaiman, A. (2009), "Successful enterprise resource planning implementation: taxonomy of critical factors", Industrial Management & Data Systems, Vol. 109 No. 8, pp. 1037-1052. https://doi.org/10.1108/02635570910991283

Publisher

:

Emerald Group Publishing Limited

Copyright © 2009, Emerald Group Publishing Limited

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