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@article{208162,
        author = {Dr. Amruta Shyam kumar},
        title = {How Indian Online Shoppers Perceive Personalized Product Recommendations: An Exploratory Look at Online Purchase Intention -Dr. Amruta Shyam Kumar},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {4},
        pages = {570-576},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=208162},
        abstract = {Personalized product suggestions now appear on almost every shopping app and website a consumer visits, yet not every shopper reacts to them the same way. How a person responds seems to hinge on whether a given suggestion feels relevant to what they actually want, whether it is genuinely useful, whether it looks tailored to them individually, and whether the platform delivering it can be trusted. This exploratory study looks at these four perception dimensions and how each relates to online purchase intention among Indian online shoppers. Data were gathered using a structured Google Forms survey made up of 25 statements rated on a Likert scale together with a short demographic section; 27 usable responses were retained for analysis. Internal consistency was checked with Cronbach's alpha, associations were tested with Pearson correlation, and a multiple regression model was run as an exploratory check on the combined effect of all four predictors. All five measurement scales performed well, returning alpha values between 0.860 and 0.945. Recommendation relevance had the strongest bivariate relationship with purchase intention (r = 0.772), with recommendation trust (r = 0.684), perceived personalization (r = 0.670) and perceived usefulness (r = 0.654) following behind. When entered together, the four predictors explained 69.3% of the variance in purchase intention, although recommendation relevance was the lone variable that stayed significant at the 5% level once the others were controlled for. Because the sample is small and was not drawn using probability methods, these results are offered as early-stage evidence rather than conclusions that generalize to the wider population, and the study is intended mainly as a template that later work with a bigger Indian sample can refine.},
        keywords = {E-commerce, Indian consumers, personalization, purchase intention, recommendation relevance, trust, usefulness.},
        month = {September},
        }