Please use this identifier to cite or link to this item: http://irepo.futminna.edu.ng:8080/jspui/handle/123456789/32028
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dc.contributor.authorADETUTU, OLAYIWOLA MATTHEW-
dc.date.accessioned2026-10-15T20:41:21Z-
dc.date.available2026-10-15T20:41:21Z-
dc.date.issued2026-03-18-
dc.identifier.citationAdetutu, O. M. (2026). On Retention and Growth Patterns of Abuja Electricity Distribution Company Metered Customers through Times Series Forecasting. Benin Journal of Statistics, Vol.9, pp. 1-16en_US
dc.identifier.issnISSN 2682-5767-
dc.identifier.urihttp://irepo.futminna.edu.ng:8080/jspui/handle/123456789/32028-
dc.descriptionhe study examines the retention and growth patterns of metered customers of the Abuja Electricity Distribution Company (AEDC) from 2015 to the first quarter of 2024 using descriptive statistics, trend analysis, and time series forecasting. The results reveal a sustained increase in metered customers, with the linear trend model showing a significant positive growth rate of 4,946.69 customers per time period and a strong explanatory power of 94%. Among the ARIMA models evaluated, ARIMA (1,1,1) was identified as the most suitable forecasting model based on its information criteria and prediction error measures. The model projects continued growth in metered customers from 2024 to 2028, while its Ljung–Box test result indicates no evidence of residual autocorrelation. The study concludes that the findings provide a reliable statistical foundation for AEDC's future metering investment, operational planning, and electricity service expansion strategies.en_US
dc.description.abstractThis study investigates the long term growth dynamics of metered customers within the Abuja Electricity Distribution Company (AEDC) from 2015 to the first quarter of 2024, using descriptive analytics, trend modelling, and time series forecasting. The descriptive analysis shows a sustained upward trajectory in metering coverage, characterized by policy driven surges during key roll out periods. A linear trend model reveals a highly significant positive slope β = 4, 946.69 and strong explanatory power (R2 = 0.94), confirming that time is a dominant driver of metering expansion. Annual retention rates further highlight substantial growth in several years, with values exceeding 110% during intensive metering campaigns. In order to forecast future metering performance, multiple ARIMA models were compared, and ARIMA (1, 1, 1) emerged as the optimal specification based on lowest AIC, BIC, RMSE, and MAPE values. The model’s Ljung-Box p-value of 1 indicates that residual autocorrelation is fully addressed which validate its suitability for forecasting. Projections for 2024–2028 indicate continued growth under current operational and policy conditions. Overall, the findings demonstrate strong historical progress and provide a statistically sound basis for future planning and metering investment strategies within AEDC.en_US
dc.description.sponsorshipSelf sponsorshipen_US
dc.language.isoenen_US
dc.publisherBenin Journal of Statisticsen_US
dc.subjectForecastingen_US
dc.subjectGrowthen_US
dc.subjectMetereden_US
dc.subjectRetention rateen_US
dc.titleOn Retention and Growth Patterns of Abuja Electricity Distribution Company Metered Customers through Times Series Forecasting.en_US
dc.typeArticleen_US
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