posted on 2023-08-30, 19:39authored byObafemi M. Oyewole
Enterprise resource planning (ERP) systems are a core software program that organisations can use to integrate, manage, and coordinate information. The ERP system supports organisations to manage business processes within a single database. ERP technology is at the core of many organisations in Europe, and it is used in facilitating organisational performance. The Nigeria manufacturing organisations (NMOs) quickly understand the urgent need to adopt ERP technology. However, the industry is yet to realise the precise impact of ERP system adoption. Despite ERP adoption within the Nigeria manufacturing organisations, the sector’s contribution to the country’s Gross Domestic Product (GDP) is still very minimal. Hence, the industry is yet to grasp the efficacy of ERP system. The purpose of this study is to investigate what hinders ERP implementation success and optimising NMOs organisational performance. Mixed research method is used, which involves the qualitative and quantitative research approach. This method contributes immensely towards a comprehensive data collection and analysis. This research shows that some of the main factors that hinder ERP implementation success include improper ERP project management, corrupt practices at different levels, and lack of performance measurement. The conclusion and recommendation suggest a structured lean six-sigma procedure towards ERP implementation projects and effective performance measurement post-implementation. Also, Nigeria manufacturing workers need adequate knowledge transfer, education, and training to implement and navigate such advanced integrated systems. Finally, to tackle corruption, blockchain technology integration into ERP system is examined (B-ERP). This integration has reflected the positive impact of the B-ERP system on an organisation’s performance as seen in the validation study. Further research can look into replicating this integration in other sectors in Nigeria.
History
Institution
Anglia Ruskin University
File version
Accepted version
Language
eng
Thesis name
PhD
Thesis type
Doctoral
Legacy posted date
2022-03-03
Legacy creation date
2022-03-03
Legacy Faculty/School/Department
Theses from Anglia Ruskin University/Faculty of Science and Technology
Note
Accessibility note: If you require a more accessible version of this thesis, please contact us at arro@aru.ac.uk