Date

2022-12-23

Author

MADEN BİLGİÇ, BURCU

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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This research aims to investigate the potential impact of recommendation systems on consumers' different perceptions, such as perceived value, privacy concern, confidence in decision, and purchase intention. As recommendation systems, five different filtering techniques were analyzed; content-based filtering, item-based and user-based collaborative filtering, and friend-based and influenced-based social recommendation systems. To test hypotheses proposed, survey data were collected from 743 consumers in general public and analyzed using exploratory factor analysis, bivariate correlation, reliability analysis, one-way ANOVA, and multiple regression analysis. Based on the results, the perceived value was the most crucial perception of consumers' purchase intention in all recommendation systems. Although privacy concern had a negative impact on consumers' purchase intention, its effect was low. Confidence in decision did not differentiate in different recommendation systems, but it moderately impacted consumers' purchase intention. The influenced-based recommendation system had the most substantial impact on consumers' purchase intention. The overall results showed that new recommendation systems would be used in e-commerce to provide more benefits to consumers and increase the sales of e-commerce platforms. Consequently, the present study provides several insightful results regarding new recommendation systems and the impact of recommendation systems on consumer behavior.

Subject Keywords

Recommendation System, Perceived Value, Confidence in Decision, Purchase Intention, Privacy Concern

URI

https://hdl.handle.net/11511/101237

Collections

Graduate School of Social Sciences, Thesis