A Mathematical Model for Estimating the Quality of Service of Mobile Cellular Network Provider in Nigeria

Abstract

The liberalization of telecommunication sector in Nigeria led to serious competition among the cellular mobile network service providers. In spite of the big financial commitment by these companies into their particular communication technologies, users ultimately make purchasing decisions based on their identified quality of service (QoS). To meet the expectation of subscribers on quality service delivery and gain a sustainable competitive edge in the market, network providers have to understand and characterize customer’s view of the quality of service provided by their given technologies. In this study, the factors that influence the quality of service of mobile network operators in Nigeria were assessed through a cross-sectional survey design. A total of 100 experts from telecommunication industry and 300 subscribers of the four major network operators (MTN, Glo, Airtel, 9 Mobile) aged between 18 and 65 years living in the South East (Imo State, Ebonyi State, Anambra State, Abia State and Enugu State) of Nigeria were enrolled into the study using a random sampling technique. The quantitative approach used was regression analysis. In order to manage the large volume of data gathered, statistical package for social sciences [SPSS] software window version 18.0 was employed. It was observed that the factors that influence the quality of service of mobile cellular network providers in Nigeria are: Customer care (L2), Network coverage/ Availability of service (L5), Price of service (L4), Call quality (L3), Diversity of bundle option of service (L1) and Promotion/Offering of Incentive (L6). When considered together, all the factors significantly affect the quality of services of the mobile network service provider with 0.000 significant level of confidence. A model of the relationship between the Quality of service (dependent variable) and the Quality of service factors (independent variables) was derived as: Y=3.731 + 0.565L5 + 0.440L3 + 0.221L2 + 0.189L4 + 0.165L1 + 0.097L6. It is suggested that telecommunication industries invest more on radio infrastructural development to guarantee a very wide coverage area and boost Call quality.