Open AccessTHE APPLICABILITY OF FINITE HOMOGENEOUS MARKOV PROCESSES IN THE STUDY OF CONSUMER LOYALTY
Author(s) -
Dr Swapna Datta Khan
Publication year - 2021
Publication title -
epra international journal of research and development
Language(s) - English
Resource type - Journals
ISSN - 2455-7838
DOI - 10.36713/epra6787
Subject(s) - markov chain , markov process , homogeneous , event (particle physics) , loyalty , computer science , markov model , markov property , mathematics , business , econometrics , marketing , statistics , combinatorics , machine learning , physics , quantum mechanics
Markov Processes are sequential events that are related to each other stochastically. Such events, also known as states, may be such that the probability of an event occurring depends only on the previous event and not on any event prior to that. This is known as the memoryless property of Markov Processes. Certain dynamic market conditions especially with respect to the Fast-Moving Consumer Goods Sector, the Telecommunications Sector may enable the use of finite and time-homogeneous Markov Processes to study the brand switching tendency of the consumer, and thus predict consumer loyalty. In this conceptual paper, we shall study how to predict brand switching tendencies using finite, time-homogeneous Markov Processes.KEYWORDS: Markov Process, Brand Switching, Time-Homogeneous, Consumer Loyalty, Transition Matrix