ERP Institutionalisation- A Quantitative Data Analysis Using The Integrative Framework of IS Theories
DOI:
https://doi.org/10.3127/ajis.v18i3.1089Keywords:
Enterprise Resource Planning, ERP, Institutionalisation, Information Systems Theories, Critical Success FactorsAbstract
There is a wide agreement that IT projects have disappointing success rates and often generate less value than originally promised. In the context of ERP systems, the same statistical reports exist which demonstrate an overwhelming number of failures in ERP implementations. A thorough review of IS literature, however, leads us to believe that organisations that broadly deploy and routinise IT (in particular, ERPs) into their day-to-day work procedures realise the greatest productivity benefit and business values, and in return perceive to be more successful. The stage wherein ERP is fully assimilated, widely accepted and routinised is also referred to as institutionalised ERP in the extant IS literature of institutional theory. As a result, the authors of this paper believe that studying the influence of various social, environmental, technological and organisational factors on ERP institutionalisation has significant potential in improving the chance of successful ERP projects. In doing so, this paper introduces an integrative framework of IS theories based on an in-depth review of IS literature. The survey instrument is developed to gather data on possible impacts of factors derived from each theory on ERP institutionalisation. The gathered data is then analysed using quantitative data analysis methods to shape the final hypothetical inferences. Finally, based on the data analysis results, this paper proposed valuable suggestions to business and IT managers to improve the chance of ERP success in their organisations.Downloads
Published
2014-11-01
How to Cite
Pishdad, A., Koronios, A., Reich, B. H., & Geursen, G. (2014). ERP Institutionalisation- A Quantitative Data Analysis Using The Integrative Framework of IS Theories. Australasian Journal of Information Systems, 18(3). https://doi.org/10.3127/ajis.v18i3.1089
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Section
Selected Papers from the Australasian Conference on Information Systems (ACIS)
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