This single explorative case study investigated the causes of churn in the telecommunication industry in Kenya, narrowed down to include only the capital city of Nairobi. The question of this dissertation was split into three sub-questions. The first sub-question investigated the behavioral patterns of customers causing churn. The second sub-question investigated the economic patterns causing churn, and the third sub-question investigated the policies and regulations that cause churn.
Data was gathered from carrier websites and publications from all the four carriers, Safaricom, Airtel, Orange, and YuMobile. Face-to-face interviews with one manager from each carrier were conducted. Field research was gathered from 29 customers who used multiple SIM cards or have changed their carrier.
Findings of this dissertation confirmed findings of most previous literature. Causes of churn differed based on the perspectives. Carriers thought they were mainly in control of churn, whereas customer causes reflected multiple behavioral and economic factors that were not related to the carriers. Findings also indicated that it not possible to investigate a single cause of churn without taking into consideration the effect of all other linked causes. Recommendations for telecommunication leaders have been provided, and a model illustrating the procedure that was followed to solve the problem was also provided. The first step that leaders must take is to identify the true causes of any problem from all the different perspectives before attempting to solve the problem. Future quantitative research is required to investigate the links between causes of churn. Results from this dissertation together with the quantitative research could be used to make customized churn prediction software to accurately predict churning customer.
|School:||University of Phoenix|
|School Location:||United States -- Arizona|
|Source:||DAI-A 77/07(E), Dissertation Abstracts International|
|Subjects:||Behavioral psychology, Management, Information science|
|Keywords:||Causes of churn, Churn prediction, Churn software, Customer retention, Kenya, Nairobi, Telecommunications|
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