Citation

Murugasu, Umapathy Sivan G. (2025) Autonomous adaption of cognitive Telco data for hyper-personalisation of subscriber preferences in business transformation. PhD thesis, Multimedia University.

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Abstract

Customers expect cognitive telecommunications companies (Telco) to provide highvalue digital services. To remain competitive, Telcos must offer products and services matching client’s preferences. This research studied a critical knowledge gap in matching client preferences and developed an artifact for hyper-personalization based on the three cycles approach design science framework: namely, relevance cycle, rigor cycle, and design cycle. A systematic literature review identified the initial hyperpersonalization attributes, based on three major telecommunications providers, that were refined for collective consensus by a team of ten industry experts through a multistage Delphi method. User data collected using Google Forms was used to create a demography database. The proof of concept was built using the Waikato Environment for Knowledge Analysis data analysis software. Artificial intelligence techniques were used to determine the optimum algorithm, Logistic Model Tree for analysis. The model was trained on the client’s digital behavior to classify and predict client preferences. Design parameters with the best-fit statistics for the hyper-personalization procedure were used to assemble the artifact. The artifact was validated by the prediction accuracy of selected clients. The study made a novel theoretical contribution by extending the applicability of Hevner’s Design Science Research framework to AIdriven hyper-personalization in telecommunications by operationalizing the relevance, rigor, and design cycles through predictive analytics. The practical contributions of this research are 1) real-time identification of client requirements; 2) classification of clients for targeted marketing; and 3) ability to offer hyper-personalized products to Telco clients. Collectively, these contributions advance the theoretical and practical understanding of how digital demography can be systematically transformed into actionable hyper-personalization mechanisms, demonstrating artificial intelligence enables Telco organizations to operationalize cognitive business models that deliver competitive client-centric products and services. This research created the artifact named Hypersona. In conclusion, this research demonstrates how artificial intelligence can be systematically embedded in Telco operations to enable a cognitive model that delivers data-driven, hyper-personalized products and services to strengthen competitive advantage.

Item Type:	Thesis (PhD)
Additional Information:	Call No.: TA347.A78 M87 2025
Uncontrolled Keywords:	Artificial intelligence—Industrial applications
Subjects:	T Technology > TA Engineering (General). Civil engineering (General) > TA329-348 Engineering mathematics. Engineering analysis
Divisions:	Faculty of Management (FOM)
Depositing User:	Ms Nurul Iqtiani Ahmad
Date Deposited:	06 Mar 2026 00:48
Last Modified:	06 Mar 2026 01:50
URII:	http://shdl.mmu.edu.my/id/eprint/15452

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