Markov Analysis for Assessing Consumers’ Brand Switching Behavior:
Abstract
The aim of this paper is to explain how to use markov analysis to evaluate consumers' brand switching behavior in the telecommunication sector. Markov chain has been used for accessing the brand switching tendencies of consumers from one to another, which could help to take right strategies for improving the brand quality of different service providing organization and to capture high market share by reducing the brand switching behavior of the consumers. Also, the logistic regression model has been used to determine the importance of the factors that influence consumers' decision to move from one telecommunication brand to another. Findings of Markov chain highlight that a consumer will move from GP to Banglalink, GP to GP, GP to Robi and GP to Teletalk, whereas the consumers will move from BL to BL, BL to GP, BL to Robi and BL to Teletalk, Lastly, the likelihood that the consumer will move from Robi to Airtel, Airtel to Robi, Robi to Teletalk, and Teletalk to Robi. Moreover, the results of a binary logistic regression model reveal that strong advertising has a major impact on brand switching. Furthermore, buyers who have a favorable view of the package being offered are more likely to switch brands than those who do not. Age, the use of multiple SIM cards, occupation, and perceptions of the current SIM's total attributes rating are all factors that have a vital effect on brand switching behavior in the perspectives of telecommunication sector. Consumers’ solid knowledge and experiences about the products or services and their long-term observation and intentions have played an important role in a service sector. Therefore, consumers’ brand switching behavior in our country can easily be measured with the observations or using various types of model. The implications of these findings can be extended to the growth of many telecommunication service providers' competitive positions in the industry.