推荐展示形式对用户行为意图的影响研究
Research on the Effect of Recommendation Formats on Users’ Behavioral Intentions in Personalized Recommendation System
摘要: 推荐算法和用户界面是推荐系统的重要构成。为揭示推荐展示形式这一用户界面重要因素对用户行为意图的影响及不同推荐展示形式影响的差异,本文构建了基于S-O-R的研究模型,并利用情景实验通过结构方程模型进行了假设检验。结果表明:不同推荐展示形式对用户行为意图的影响不存在显著差异,但在影响机制上存在一定差异;分类目录的推荐展示形式并不通过感知有用性显著提升用户满意;翻页的推荐展示形式并没有通过感知享乐性和感知精确性显著提升用户信任。
Abstract: Recommendation algorithm and user interface are important components of the recommendation system. Based on S-O-R model, a theoretical model is constructed in this paper. It is aimed at re-vealing the influence mechanisms of different recommendation formats on users’ behavioral in-tentions and the differences of these mechanisms. Scenario experiments are taken to test research hypothesis through structural equation model. Results show that there is no significant difference in the effect of different recommendation formats on users’ behavioral intentions. But there are some differences in their influence mechanism. The organization-based recommendation interface does not significantly improve users’ satisfaction through perceived usefulness. The page switching recommendation interface does not significantly help increase users’ trust by affecting perception hedonism and perceived accuracy.
文章引用:陈梅梅, 施驰玮. 推荐展示形式对用户行为意图的影响研究[J]. 管理科学与工程, 2018, 7(4): 330-339. https://doi.org/10.12677/MSE.2018.74040

参考文献

[1] 杨一翁, 王毅, 孙国辉. 消费者视角下的推荐系统研究[J]. 企业经济, 2016(9): 79-85.
[2] Pu, P. and Chen, L. (2006) Trust Building with Explanation Interfaces. Proceedings of the 11th International Conference on Intelligent user Interfaces, Sydney, 29 January-1 February 2006, 93-100.
[Google Scholar] [CrossRef
[3] Hu, R. and Pu, P. (2011) Enhancing Recommendation Diversity with Organiza-tion Interfaces. Proceedings of the 16th International Conference on Intelligent User Interfaces, Palo Alto, 13-16 February 2011, 347-350.
[Google Scholar] [CrossRef
[4] Chen, L. and Pu, P. (2014) Experiments on User Experiences with Recommender Interfaces. Behaviour & Information Technology, 33, 372-394.
[Google Scholar] [CrossRef
[5] Nanou, T., Lekakos, G. and Fouskas, K. (2010) The Effects of Recommendations’ Presentation on Persuasion and Satisfaction in a Movie Recommender System. Multimedia Systems, 16, 219-230.
[Google Scholar] [CrossRef
[6] Chen, L. and Tsoi, H.K. (2011) Users’ Decision Behavior in Recommender Interfaces: Impact of Layout Design. RecSys’11 Workshop on Human Decision Making in Recommender Systems, Chicago, 23-27 October 2011, 21-26.
[7] Knijnenburg, B.P., Willemsen, M.C., Gantner, Z., et al. (2012) Explaining the User Experience of Rec-ommender Systems. User Modeling and User-Adapted Interaction, 22, 441-504.
[Google Scholar] [CrossRef
[8] 陶晓波. 网络环境下消费者信任影响因素研究——以产品类型为调节变量[J]. 技术经济与管理研究, 2011(2): 51-56.
[9] Pu, P., Chen, L. and Hu, R. (2011) A User-Centric Evaluation Framework for Recommender Systems. Proceedings of the Fifth ACM Conference on Recommender Systems, Chicago, 23-27 October 2011, 157-164.
[Google Scholar] [CrossRef
[10] Deng, S.L., Fang, Y.L., Liu, Y., et al. (2015) Understanding the Factors Influ-encing User Experience of Social Question and Answer Services. Information Research, 20, 694.
[11] 陈明亮, 蔡日梅. 电子商务中产品推荐代理对消费者购买决策的影响[J]. 浙江大学学报: 人文社会科学版, 2009, 39(5): 138-148.
[12] Bhattacherjee, A. (2001) Understanding Information Systems Continuance: An Expectation-Confirmation Model. MIS Quarterly, 25, 351-370.
[Google Scholar] [CrossRef