A Sugeno ANFIS Model Based on Fuzzy Factor Analysis for IS/IT Project Portfolio Risk Prediction

Risk inherence jeopardises Information System (IS) and Information Technology (IT) Project Portfolio Management (PPM) to realise the strategic objectives. Previous studies have mainly provided Artificial Intelligence (AI) and statistical models to predict the overall risk of IS/IT project portfolio,...

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Main Authors: Zaidouni, Anass, Idrissi, Mohammed Abdou Janati, Bellabdaoui, Adil
Format: Article
Language:English
Published: Universiti Utara Malaysia Press 2024
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Online Access:https://repo.uum.edu.my/id/eprint/31267/1/JICT%2023%2002%202024%20139-176.pdf
https://doi.org/10.32890/jict2024.23.2.1
https://repo.uum.edu.my/id/eprint/31267/
https://e-journal.uum.edu.my/index.php/jict/article/view/19784
https://doi.org/10.32890/jict2024.23.2.1
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spelling my.uum.repo.312672024-08-14T06:35:00Z https://repo.uum.edu.my/id/eprint/31267/ A Sugeno ANFIS Model Based on Fuzzy Factor Analysis for IS/IT Project Portfolio Risk Prediction Zaidouni, Anass Idrissi, Mohammed Abdou Janati Bellabdaoui, Adil T Technology (General) Risk inherence jeopardises Information System (IS) and Information Technology (IT) Project Portfolio Management (PPM) to realise the strategic objectives. Previous studies have mainly provided Artificial Intelligence (AI) and statistical models to predict the overall risk of IS/IT project portfolio, whereas neuro-fuzzy models were rarely used. This paper proposes a Sugeno Adaptive Neuro-Fuzzy Inference System (ANFIS) model based on Fuzzy Factor Analysis (FFA) named ANFIS-OPR to predict the overall risk of IS/IT project portfolio from historical IS/IT project risk data. The ANFIS-OPR inputs are the relevant factor loadings resulting from the FFA application on the IS/IT projects risks set to cope with the curse of dimensionality. Then, the Sugeno ANFIS model is adopted to give strategic interpretability to the predicted IS/IT project portfolio overall risk by implementing the IS/IT Project Management Office (PMO) expert knowledge, represented by fuzzy rules, on the relationship between IS/IT project portfolio strategic alignment and the IS/IT projects risks. The ANFISOPR outputs are the predicted Overall Portfolio Risk (OPR) and Root Mean Square Error (RMSE). The paper also presents an IS/ IT PMO case study that shows the proposed ANFIS-OPR efficacy, which predicted the OPR values closely to the OPR estimates with an accepted RMSE of 0.108. The proposed ANFIS-OPR is a novel intelligent decision-making tool that enables the IS/IT PMO to monitor the OPR, considering its linkage with strategic alignment; thus, contingency plans can be carried out appropriately while ensuring that the IS/IT project portfolio is strategically aligned Universiti Utara Malaysia Press 2024 Article PeerReviewed application/pdf en cc4_by https://repo.uum.edu.my/id/eprint/31267/1/JICT%2023%2002%202024%20139-176.pdf Zaidouni, Anass and Idrissi, Mohammed Abdou Janati and Bellabdaoui, Adil (2024) A Sugeno ANFIS Model Based on Fuzzy Factor Analysis for IS/IT Project Portfolio Risk Prediction. Journal of ICT, 23 (2). pp. 139-176. ISSN 1675-414X https://e-journal.uum.edu.my/index.php/jict/article/view/19784 https://doi.org/10.32890/jict2024.23.2.1 https://doi.org/10.32890/jict2024.23.2.1
institution Universiti Utara Malaysia
building UUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Utara Malaysia
content_source UUM Institutional Repository
url_provider http://repo.uum.edu.my/
language English
topic T Technology (General)
spellingShingle T Technology (General)
Zaidouni, Anass
Idrissi, Mohammed Abdou Janati
Bellabdaoui, Adil
A Sugeno ANFIS Model Based on Fuzzy Factor Analysis for IS/IT Project Portfolio Risk Prediction
description Risk inherence jeopardises Information System (IS) and Information Technology (IT) Project Portfolio Management (PPM) to realise the strategic objectives. Previous studies have mainly provided Artificial Intelligence (AI) and statistical models to predict the overall risk of IS/IT project portfolio, whereas neuro-fuzzy models were rarely used. This paper proposes a Sugeno Adaptive Neuro-Fuzzy Inference System (ANFIS) model based on Fuzzy Factor Analysis (FFA) named ANFIS-OPR to predict the overall risk of IS/IT project portfolio from historical IS/IT project risk data. The ANFIS-OPR inputs are the relevant factor loadings resulting from the FFA application on the IS/IT projects risks set to cope with the curse of dimensionality. Then, the Sugeno ANFIS model is adopted to give strategic interpretability to the predicted IS/IT project portfolio overall risk by implementing the IS/IT Project Management Office (PMO) expert knowledge, represented by fuzzy rules, on the relationship between IS/IT project portfolio strategic alignment and the IS/IT projects risks. The ANFISOPR outputs are the predicted Overall Portfolio Risk (OPR) and Root Mean Square Error (RMSE). The paper also presents an IS/ IT PMO case study that shows the proposed ANFIS-OPR efficacy, which predicted the OPR values closely to the OPR estimates with an accepted RMSE of 0.108. The proposed ANFIS-OPR is a novel intelligent decision-making tool that enables the IS/IT PMO to monitor the OPR, considering its linkage with strategic alignment; thus, contingency plans can be carried out appropriately while ensuring that the IS/IT project portfolio is strategically aligned
format Article
author Zaidouni, Anass
Idrissi, Mohammed Abdou Janati
Bellabdaoui, Adil
author_facet Zaidouni, Anass
Idrissi, Mohammed Abdou Janati
Bellabdaoui, Adil
author_sort Zaidouni, Anass
title A Sugeno ANFIS Model Based on Fuzzy Factor Analysis for IS/IT Project Portfolio Risk Prediction
title_short A Sugeno ANFIS Model Based on Fuzzy Factor Analysis for IS/IT Project Portfolio Risk Prediction
title_full A Sugeno ANFIS Model Based on Fuzzy Factor Analysis for IS/IT Project Portfolio Risk Prediction
title_fullStr A Sugeno ANFIS Model Based on Fuzzy Factor Analysis for IS/IT Project Portfolio Risk Prediction
title_full_unstemmed A Sugeno ANFIS Model Based on Fuzzy Factor Analysis for IS/IT Project Portfolio Risk Prediction
title_sort sugeno anfis model based on fuzzy factor analysis for is/it project portfolio risk prediction
publisher Universiti Utara Malaysia Press
publishDate 2024
url https://repo.uum.edu.my/id/eprint/31267/1/JICT%2023%2002%202024%20139-176.pdf
https://doi.org/10.32890/jict2024.23.2.1
https://repo.uum.edu.my/id/eprint/31267/
https://e-journal.uum.edu.my/index.php/jict/article/view/19784
https://doi.org/10.32890/jict2024.23.2.1
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score 13.211869