Enterprise resources planning implementation success factors of steel industry

In order to survive in a rapidly changing business environment, organizations must improve their business practices and procedures.A steel industry has to undergo various procedures before embark on the production phase.Hence, enterprise resource planning (ERP) can be considered as the most importan...

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Bibliographic Details
Main Authors: Maarop, Nurazean, Ayazia, Erfan, Mohd Sam, Suriani, Mohd Yusop, Othman, Azmi, Azrina Hani, Alia, Rosmah
Format: Conference or Workshop Item
Language:English
Published: 2016
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Online Access:http://repo.uum.edu.my/23404/1/ICT4T2016%20114%20118.pdf
http://repo.uum.edu.my/23404/
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Institution: Universiti Utara Malaysia
Language: English
Description
Summary:In order to survive in a rapidly changing business environment, organizations must improve their business practices and procedures.A steel industry has to undergo various procedures before embark on the production phase.Hence, enterprise resource planning (ERP) can be considered as the most important systems in this type of organization as it serves as the organization business operation backbone handling all the bulky procedures and processes efficiently.The difficulties and high failure rate in implementing ERP systems have been widely discussed in the literature. However, factors affecting ERP implementation are complex and abundant thus should be investigated contextually.The objective of this paper is to explore the key issues that possibly influence ERP systems implementation in one of the enterprise steel industry organizations.Several factors deduced from literature were used to further investigate concerning the relevancy of the factors in the context of the study.The factors were further validated through expert reviews with five ERP consultants using semi-structured interviews.Consequently, seven from eight deduced factors were found to be critical to be considered in the next phases of study which may involve model understanding and validation after the primary data collection.