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https://hdl.handle.net/10321/2905
Title: | Customer satisfaction analysis of Conlog electricity prepayment meters in KwaZulu-Natal : a customer perspective | Authors: | Gina, Mondli | Issue Date: | 2016 | Abstract: | In the electricity prepayment metering industry the continuous increase in customers’ expectations and technological innovation demand that leading firms in the industry differentiate themselves from the competition by going beyond customers’ present expectations. Thus, organizations which have set their goals on mere customer satisfaction are, from a customers’ perspective, deemed to be of limited value and may subsequently lack the anticipation and preparation essential to meet the demands of the future. Electricity prepayment metering market competition today is forcing organisations to seek the means to gain customer satisfaction, and thus aim to sustain their future in times of economic instability. The study revealed that the most effective way to retain customer satisfaction is consistent service quality that decreases the cost of attracting new customers and raises sales and market share. The quality of service is one of the most effective factors in creating competitive advantages and advance business. Factors that influence customer satisfaction in the electricity prepayment industry were investigated and tested. The study also attempted to identify the critical factors, as identified in the literature, among those investigated: service quality, customer expectations, customer perception and customer retention. Against this background, the study sought to determine the interrelationship between customer satisfaction and the critical factors of customer satisfaction with Conlog Electricity Prepayment Meters in KwaZulu-Natal. The research developed to ascertain subjects’ perceptions of the critical factors of customer satisfaction; determine the interrelationship among the critical factors of customer satisfaction; and explore the relationship between customer satisfaction and the critical factors of customer satisfaction. The research population comprising of Conlog electricity prepayment metering customers in KwaZulu-Natal was selected and interviewed. Questionnaires were distributed through electronic mail and self-administered for data collection and a sample of twelve respondents was selected for interview. Interviews were analysed using conversational analysis and the data collected from the interviews were merged with the questionnaire data, seeking depth as well as breadth. Data collected from respondents was analysed using descriptive and inferential statistical techniques. The tool utilised to analyze data was the Statistical Package for the Social Sciences (SPSS) version 22 (SPSS Inc., Chicago, Illinois, USA). A p value < 0.05 was considered as statistically significant. Conclusions and recommendations were drawn from the literature and the findings of the study. The results of the study revealed that service quality is the most significant critical factor of customer satisfaction. The study recommends that the management of Conlog can use the specific data obtained from the measurement of service quality in their strategies and plans. The study further recommends that Conlog allocates resources to this effect to provide better service to their customers. The results and findings of the study will provide further information concerning customer satisfaction and customer perception in the prepayment metering industry in KwaZulu-Natal. It will also contribute to future industry research, setting the ground for further research in measuring levels of customer satisfaction in the electricity prepayment industry in South Africa. |
Description: | Submitted in fulfillment of the requirement for the Degree of Master of Management Sciences Specialising in Business Administration, Durban University of Technology, Durban, South Africa, 2017. |
URI: | http://hdl.handle.net/10321/2905 | DOI: | https://doi.org/10.51415/10321/2905 |
Appears in Collections: | Theses and dissertations (Management Sciences) |
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File | Description | Size | Format | |
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GINA_M_2016.pdf | 2.23 MB | Adobe PDF | View/Open |
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