Determination of Customer Switching Using Logistic Regression: Case Studyof Barclays Bank, Ghana
| dc.contributor.author | Agyei Addai, Vincent | |
| dc.date.accessioned | 2012-06-14T09:47:46Z | |
| dc.date.accessioned | 2023-04-21T07:05:50Z | |
| dc.date.available | 2012-06-14T09:47:46Z | |
| dc.date.available | 2023-04-21T07:05:50Z | |
| dc.date.issued | 2011-09-14 | |
| dc.description | A Thesis submitted to the Department of Mathematics, Kwame Nkrumah University of Science and Technology, Kumasi, in partial fulfillment of the requirement for the degree of Master of Science, 2011 | en_US |
| dc.description.abstract | The research is to construct a statistical model of customer switching intentions. It uses a binary logistic regression to model the impact of customer satisfaction, customer demographics on customer switching in Barclays Bank Ghana, and to predict and classify customer data. The model predicted that 18.97% of customers are likely to switch from the bank. logit(P)(switching ) = -0.10AGE Results suggest that the most significant customer satisfaction constructs were Quality of staff, Efficiency of customer service, Electronic transactions and pricing. There was also evidence that customers’ age groups and level of education contributed to explaining respondents' propensity to stay with their current banks. | en_US |
| dc.description.sponsorship | KNUST | en_US |
| dc.identifier.uri | https://ir.knust.edu.gh/handle/123456789/3922 | |
| dc.language.iso | en | en_US |
| dc.title | Determination of Customer Switching Using Logistic Regression: Case Studyof Barclays Bank, Ghana | en_US |
| dc.type | Thesis | en_US |
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