Artificial Intelligence, Content Recommendation, Biases, and Consumer Behavior: An Analysis of the Impact of Artificial Intelligence on Consumer Behavior - Sanghamitra Das, Ankit Garg, Neha Verma, Deepak Jha, Ritesh Kumar Singhal, Manupriya Gaur, Rahul Singhal (International Journal of Intelligent Systems and Applications in Engineering, 2024)
Purpose: Information plays very important role in decision making. Awareness of brand, price, discounts, post sales activities like guarantee, warrantee, and maintenance must be advertised to influence the buying behaviour. But what if this information creates a bias. Does any type of bias generated by this information, in the form of advertisement, influence the buying behaviour? The present research is exploring the fact that how artificial intelligence-based advertisement suggestions and content recommendations create certain type of bias and how it affects the buying behaviour. This research is based upon a survey of consumers. Design/methodology/approach: The methodology emphasised to eliminate the errors in measurement. Respondents were approached twice, in a gap of 30 days for collecting data. They were asked to retake the survey and data in both the attempts have been examined for any major deviation. The average of scores have been consolidated as final data of the research analysis. Findings: The linear regression equation coefficients for the various model variables. The "B" values are the coefficients for each variable. In model 04 we could predict buying behaviour as BB (y) = 0.589 + .403 Anchoring bias + .284 Conformity Bias + .259 Heuristic Bias+ .233 FOMO. Originality: Researchers have emphasis on exploring a new set of influencing factors for consumer behaviour rather following the key factors in systematic review of previous works. Thus, the work ensures the originality in research.