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Adaptive model to support business process reengineering
The one constant in the world is change. The changing dynamics of business environment enforces the organizations to re-design or reengineer their business processes. The main objective of such reengineering processes is to provide services or produce products with the possible lowest cost, shortest...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8093952/ https://www.ncbi.nlm.nih.gov/pubmed/33987460 http://dx.doi.org/10.7717/peerj-cs.505 |
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author | Ahmed Bayomy, Noha E. Khedr, Ayman Abd-Elmegid, Laila A. |
author_facet | Ahmed Bayomy, Noha E. Khedr, Ayman Abd-Elmegid, Laila A. |
author_sort | Ahmed Bayomy, Noha |
collection | PubMed |
description | The one constant in the world is change. The changing dynamics of business environment enforces the organizations to re-design or reengineer their business processes. The main objective of such reengineering processes is to provide services or produce products with the possible lowest cost, shortest time, and best quality. Accordingly, Business Process Re-engineering (BPR) provides a roadmap of how to efficiently achieve the operational goals in terms of enhanced flexibility and productivity, reduced cost, and improved quality of service or product. In this article, we propose an efficient model for BPR. The model specifies where the breakdowns occur in BPR implementation, justifies why such breakdowns occur, and proposes techniques to prevent their occurrence again. The proposed model has been built based on two main sections. The first section focuses on integrating Critical Success Factors (CSFs) and the performance of business processes during the reengineering processes. Additionally, it implements the association rule mining technique to investigate the relationship between CSFs and different business processes. The second section aims to measure the performance of business processes (intended success of BPR) by process time, cycle time, quality and cost before and after reengineering processes. A case study of the Egyptian Tax Authority (ETA) is used to test the efficiency of the proposed model. |
format | Online Article Text |
id | pubmed-8093952 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | PeerJ Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-80939522021-05-12 Adaptive model to support business process reengineering Ahmed Bayomy, Noha E. Khedr, Ayman Abd-Elmegid, Laila A. PeerJ Comput Sci Adaptive and Self-Organizing Systems The one constant in the world is change. The changing dynamics of business environment enforces the organizations to re-design or reengineer their business processes. The main objective of such reengineering processes is to provide services or produce products with the possible lowest cost, shortest time, and best quality. Accordingly, Business Process Re-engineering (BPR) provides a roadmap of how to efficiently achieve the operational goals in terms of enhanced flexibility and productivity, reduced cost, and improved quality of service or product. In this article, we propose an efficient model for BPR. The model specifies where the breakdowns occur in BPR implementation, justifies why such breakdowns occur, and proposes techniques to prevent their occurrence again. The proposed model has been built based on two main sections. The first section focuses on integrating Critical Success Factors (CSFs) and the performance of business processes during the reengineering processes. Additionally, it implements the association rule mining technique to investigate the relationship between CSFs and different business processes. The second section aims to measure the performance of business processes (intended success of BPR) by process time, cycle time, quality and cost before and after reengineering processes. A case study of the Egyptian Tax Authority (ETA) is used to test the efficiency of the proposed model. PeerJ Inc. 2021-04-29 /pmc/articles/PMC8093952/ /pubmed/33987460 http://dx.doi.org/10.7717/peerj-cs.505 Text en © 2021 Ahmed Bayomy et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Computer Science) and either DOI or URL of the article must be cited. |
spellingShingle | Adaptive and Self-Organizing Systems Ahmed Bayomy, Noha E. Khedr, Ayman Abd-Elmegid, Laila A. Adaptive model to support business process reengineering |
title | Adaptive model to support business process reengineering |
title_full | Adaptive model to support business process reengineering |
title_fullStr | Adaptive model to support business process reengineering |
title_full_unstemmed | Adaptive model to support business process reengineering |
title_short | Adaptive model to support business process reengineering |
title_sort | adaptive model to support business process reengineering |
topic | Adaptive and Self-Organizing Systems |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8093952/ https://www.ncbi.nlm.nih.gov/pubmed/33987460 http://dx.doi.org/10.7717/peerj-cs.505 |
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