AI-Driven Recommendation: Impact on Consumer Engagement and Purchasing Decisions in Toledo City.
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| Title: | AI-Driven Recommendation: Impact on Consumer Engagement and Purchasing Decisions in Toledo City. |
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| Authors: | Macapaz, Johnreill Kleint M.1 johnreillmacapz@gmail.com, Repollo, Marly1, Forniza, Dhanna Quell1, Poloyapoy, Cassandra A.1, Mala-ay, Francis Veron B.1, Barabat, Rose Marie M.1, Lumaino, Ade Rose D.1, Broncano, Junpray A.1, Adorable, Cirilo A.1, Perater, Renna1, Botanas, Stella Marie D.1, Alqueza, Jessalyn M.1 |
| Source: | Psychology & Education: A Multidisciplinary Journal. 2026, Vol. 58 Issue 5, p678-685. 8p. |
| Subject Terms: | Recommender systems, Consumer behavior, Stimulus & response (Psychology), Consumers, Regression analysis, Internet marketing |
| Geographic Terms: | Toledo (Ohio) |
| Abstract: | This study examined the impact of AI-driven personalized recommendations on consumer engagement and purchasing decisions among consumers in Toledo City. Guided by the Stimulus-Organism-Response (S-O-R) Model, the study considered AI-driven personalized recommendations as the stimulus influencing consumer engagement and purchasing behavior. A descriptive-correlational research design was used, with data collected from 150 local consumers through a researcher-developed questionnaire. Descriptive statistics, Pearson's correlation coefficient, and regression analysis were applied to analyze the data. The findings revealed that consumers generally showed positive perceptions toward AI-driven personalized recommendations, consumer engagement, and purchasing decisions. Results also indicated a significant positive relationship between AI-driven personalized recommendations, consumer engagement, and purchasing decisions. Regression analysis further showed that AI-driven personalized recommendations significantly influence how consumers interact with digital platforms and make purchasing choices. The study concludes that effective AI-driven personalization enhances consumer engagement and positively affects purchasing decisions. These findings provide valuable insights for local businesses and marketers in improving digital marketing strategies through personalized and data-driven approaches. [ABSTRACT FROM AUTHOR] |
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| Database: | Education Research Complete |
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