A logistic regression model of customer satisfaction of airline
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Date
2012
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Publisher
Macrothink Institute
Abstract
Evaluation of customer satisfaction differs from one study to another. Studies have been differing with their focus and coverage. Most of studies focused on evaluating factors influencing customer satisfaction or associate customer satisfaction and quality of services. This paper used logistic regression to develop customer satisfaction model for Precision Air. Five dimensions or variables have been considered: on time performance; aircraft safety; schedule integrity; on board services; and customer service. Data used in this paper were collected from four major regions with many flights. These include Dar es Salaam, Mwanza, Arusha and Kilimanjaro. A sample size of 272 passengers was selected. Convenience sampling was used to select the respondents. Primary data were collected in the field through questionnaire. Findings showed that out of the five independent variables only one variable is negatively related with satisfaction of airline passengers (customer services). In contrast, on time performance was satisfactory variable by most of passengers compared to the rest of explanatory variables. Airline safety, schedule integrity and on board services are positively related with passengers satisfaction. Relationship between customer services and satisfaction are negatively related which implies that, there is a need of finding strategies to improve customer services to customers. The paper recommends that the airline should maintain and improve on time performance as this is crucial variable for passenger’s satisfaction but other variables need more improvement.
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Full Text Article
Also available at: http://dx.doi.org/10.5296/ijhrs.v2i4.2868
Keywords
Logistic, Logit, Dimension, Aircraft safety, Schedule integrity, On Board Services, Customer service, Airline operations, Customer satisfaction, Precision air
Citation
Josephat, P., & Ismail, A. (2012). A logistic regression model of customer satisfaction of airline. International Journal of Human Resource Studies, 2(4), 197.