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Research on Mobile Marketing Recommendation Method Incorporating Layout Aesthetic Preference for Sustainable m-Commerce

Author

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  • Liang Xiao

    (School of Management and E-Business, Zhejiang Gongshang University, Hangzhou 310018, China
    Modern Business Research Center, Zhejiang Gongshang University, Hangzhou 310018, China)

  • Hangxiao Mao

    (School of Management and E-Business, Zhejiang Gongshang University, Hangzhou 310018, China)

  • Shu Wang

    (School of Management and E-Business, Zhejiang Gongshang University, Hangzhou 310018, China
    Modern Business Research Center, Zhejiang Gongshang University, Hangzhou 310018, China)

Abstract

The strong interactivity and size limitation of the mobile interface calls for the utilization of users’ aesthetic preferences to provide better mobile marketing recommendations in order to promote the sustainable development of m-commerce. Existing studies mostly focus on matching user interests by analyzing marketing content properties. The studies for utilizing the layout information and user aesthetic preferences for the layout of the mobile marketing interface from an aesthetic perspective are insufficient. This paper proposes a mobile marketing recommendation method (LAPR) that incorporates layout aesthetic preferences. Based on the traditional content-based and collaborative filtering recommendation methods, this method introduces users’ aesthetic preferences for interface layout into a mobile marketing recommender. From an aesthetic perspective, a new interface layout design quantification method, a user aesthetic preference similarity measurement model, and a recommendation result ranking method are designed. Experiments show that compared to traditional methods, LAPR is significantly higher in recommendation precision in the task for recommending the same content and outperforms traditional methods in recall, precision, and F-metrics in the common recommendation task. We conclude that incorporating aesthetic preference for layout can improve mobile marketing recommendation quality and promote the sustainable development of m-commerce.

Suggested Citation

  • Liang Xiao & Hangxiao Mao & Shu Wang, 2020. "Research on Mobile Marketing Recommendation Method Incorporating Layout Aesthetic Preference for Sustainable m-Commerce," Sustainability, MDPI, vol. 12(6), pages 1-25, March.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:6:p:2496-:d:335727
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    References listed on IDEAS

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    1. Jun Wu & Xinyu Song & Xiaxia Niu & Li Shi & Lu Gao & Liping Geng & Dan Wang & Dongkui Zhang, 2022. "IT-PMF: A Novel Community E-Commerce Recommendation Method Based on Implicit Trust," Mathematics, MDPI, vol. 10(14), pages 1-16, July.
    2. Chengmin Zhou & Fangfang Yuan & Ting Huang & Yurong Zhang & Jake Kaner, 2022. "The Impact of Interface Design Element Features on Task Performance in Older Adults: Evidence from Eye-Tracking and EEG Signals," IJERPH, MDPI, vol. 19(15), pages 1-24, July.

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