A CONSTRUCT FOR RECOMMENDING STRATEGIC MOBILE NETWORK PROMOS FOR IMPROVED SERVICE DELIVERY BASED ON PREVALENT REGIONAL NETWORK SERVICE REQUEST
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| Natura: | Recurso digital |
| Lingua: | inglese |
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Zenodo
2025
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| _version_ | 1866901899301617664 |
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| author | Journal of Theoretical and Applied Information Technology |
| author_facet | Journal of Theoretical and Applied Information Technology |
| contents | <p><span>Mobile network providers make use of promos to attract more clients or consolidate on existing ones. Network service request of voice and Internet differ across locations and pre-knowledge of prevalent network service request for a given location will determine the promo type and subsequently impact positively on the network providers. This paper proposes a construct for identifying the prevalent network service of different regions of coverage. To test the construct, three quarters of telecommunication data obtained from the Nigerian Bureau of Statistics for the four major mobile network providers (Mtn, Globacom, Airtel and 9-Mobile) in 2021 were used. Clustering models such as K-Means, Agglomerative and Affinity propagation were compared to determine the most suitable. The affinity propagation model gave the best results in terms of Silhouette score, Davies-Bouldin Index and Calinski-Harabasz Index metric tests Subsequently, the Affinity propagation model was used to cluster and determine the prevalent network service of voice and Internet for the states and for each network provider. A mean-based linguistic classification identified Airtel and Glo mobile network providers as having equal subscription of voice and Internet across the states while Mtn and 9-Mobile had variable subscriptions. Suitable voice and Internet subscription promos and tariff bundles were thus recommended based on the classification</span></p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_18062504 |
| institution | Zenodo |
| language | eng |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | A CONSTRUCT FOR RECOMMENDING STRATEGIC MOBILE NETWORK PROMOS FOR IMPROVED SERVICE DELIVERY BASED ON PREVALENT REGIONAL NETWORK SERVICE REQUEST Journal of Theoretical and Applied Information Technology Mobile Network, Clustering, Machine-Learning, Subscription Rate, Promos, Tariff Bundles <p><span>Mobile network providers make use of promos to attract more clients or consolidate on existing ones. Network service request of voice and Internet differ across locations and pre-knowledge of prevalent network service request for a given location will determine the promo type and subsequently impact positively on the network providers. This paper proposes a construct for identifying the prevalent network service of different regions of coverage. To test the construct, three quarters of telecommunication data obtained from the Nigerian Bureau of Statistics for the four major mobile network providers (Mtn, Globacom, Airtel and 9-Mobile) in 2021 were used. Clustering models such as K-Means, Agglomerative and Affinity propagation were compared to determine the most suitable. The affinity propagation model gave the best results in terms of Silhouette score, Davies-Bouldin Index and Calinski-Harabasz Index metric tests Subsequently, the Affinity propagation model was used to cluster and determine the prevalent network service of voice and Internet for the states and for each network provider. A mean-based linguistic classification identified Airtel and Glo mobile network providers as having equal subscription of voice and Internet across the states while Mtn and 9-Mobile had variable subscriptions. Suitable voice and Internet subscription promos and tariff bundles were thus recommended based on the classification</span></p> |
| title | A CONSTRUCT FOR RECOMMENDING STRATEGIC MOBILE NETWORK PROMOS FOR IMPROVED SERVICE DELIVERY BASED ON PREVALENT REGIONAL NETWORK SERVICE REQUEST |
| topic | Mobile Network, Clustering, Machine-Learning, Subscription Rate, Promos, Tariff Bundles |
| url | https://doi.org/10.5281/zenodo.18062504 |