FACTORS AFFECT THE BEHAVIOR OF USING CASHBACK PROGRAMS: BAYESIAN ALGORITHM

Abstract

The paper explored factors that affect the behavior of using cashback programs by applying the Bayesian algorithm. The payback model is an international commercial strategy that encourages shopping. The US and the UK are where the "cashback" business model first appeared. It is now used in many other nations, including Vietnam. There are four factors behavior of using cashback programs Ease of Use (EU), Perceived Risk (PR), Using Intention of Cashback (UIC), and Personal Capacity (PC). The paper uses quantitative and qualitative methods. With the qualitative method, we implement the group discussion method to discuss with the group members about the survey questionnaire before launching the official survey. After discussing and discussing, the members kept the questionnaire. Quantitative methods were applied and the design of the study was descriptive and explained for this research model. The data collection method is by questionnaire, a survey designed on Google Form Tool, and sending surveys through social networks Facebook and Zalo. The survey is conducted in Ho Chi Minh City, Vietnam in 2023. Bayesian Algorithm for the Using Behavior of Cashback (UBC) revealed that there is one independent factor. Personal Capacity (PC) has a positive influence on the Using Behavior of Cashback (UBC). Therefore, the implication given to businesses of the cashback program is to put prestige first, implementing policies on customer information security to create a trust for customers. Since this is a financial-related market, reputation is a factor that customers care about, so reputable businesses will attract more customers.