Key Factors Affecting Consumer Behavior in Thai Digital Marketing: Research Synthesis by Systematic Literature Review and Data-Mining Techniques
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Abstract
This research was conducted using systematic literature review and data-mining techniques to create predictive models of key factors affecting consumer behavior in digital marketing in Thailand. The data analysis is based on 50 synthesized pieces of literature regarding the relationship of digital marketing factors with a systematic review process. Techniques for data-mining relationship rules were employed to create a relationship model and prediction.
The results of the study showed that there were 84 variables from 50 research papers. The top five most frequently studied variables are purchase intentions, customer satisfaction, reliability, attitude, and quality of the product and service. Data from 50 synthetic literature was analyzed using data-mining techniques. Afterward, a predictive model from an association rule was created. The predictive model was able to predict the most variables under the study, which are attitude and purchase intentions or services. The chance that a pair/variable group will be studied in future research is 12.72%. This predictive model can guide researchers and marketers to conduct digital marketing studies, accurately study key factors influencing consumer behaviors, be a guide to find out related variables of consumer behavior, and plan marketing strategies that fit the context of Thailand.
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