MODELLING ONLINE RETAILING REPURCHASE AND SWITCHING BEHAVIOUR OF NIGERIA MILLENNIALS USING CONTINUOUS TIME MARKOV CHAIN (CTMC)

  • A. G. Adekoya Faculty of Management Sciences, University of Lagos, Lagos, Nigeria
  • E. O. Oyatoye Department of Business Administration, Faculty of Management Sciences, University of Lagos. Nigeria
Keywords: Behavioural Intentions, Consumers, Continuous Time Markov Chain, Online Retailing, Repurchase, Switching

Abstract

Despite increasing online retailing momentum in Nigeria understanding and predicting online retailing consumers repurchasing and switching behaviour has continuously been a subject of interest among scholars and practitioners. This study applies the Continuous Time Markov Chain (CTMC) to model millennials’ repurchasing and switching behavioural intentions. The study was conducted among millennials and a sample of 380 online retailing consumers among millennials were drawn using cross-sectional research design and multi-stage sampling technique. Data generated were analyzed systematically by adopting statistical tools and first-order CTMC with the aid of SPSS IBM version 20 and Microsoft Excel 2010 softwares. The Steady State of the CTMC model revealed that approximately 39 percent of millennials would repurchase or switch to preferred online outlets in their next shopping endeavour. While approximately 30 percent of millennials would repurchase or switch to other online outlets in their next shopping endeavour and approximately 31 percent of Millennial online retailing consumers would repurchase or switch to offline retailing outlets in their next shopping endeavour. Based on the findings, the study concludes that CTMC has been successfully applied to understand and predict millennials' online retailing repurchase and switching behaviour that will assist online retailing service providers to formulate appropriate competitive survival strategies. Hence, operators in the online retailing industry are encouraged to make use of this model in understanding, analysing, and predicting online retailing consumers' behavioural intentions decision for sustainable competitive advantage.

Published
2021-05-09