The interaction effects of information cascades, word of mouth and recommendation systems on online reading behavior: an empirical investigation
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DOI: 10.1007/s10660-018-9312-0
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Cited by:
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- Jiang Shen & Bang An & Man Xu & Dan Gan & Ting Pan, 2022. "Internal or External Word-of-Mouth (WOM), Why Do Patients Choose Doctors on Online Medical Services (OMSs) Single Platform in China?," IJERPH, MDPI, vol. 19(20), pages 1-14, October.
- Blasco-Arcas, Lorena & Lee, Hsin-Hsuan Meg & Kastanakis, Minas N. & Alcañiz, Mariano & Reyes-Menendez, Ana, 2022. "The role of consumer data in marketing: A research agenda," Journal of Business Research, Elsevier, vol. 146(C), pages 436-452.
- Satish Kumar & Weng Marc Lim & Nitesh Pandey & J. Christopher Westland, 2021. "20 years of Electronic Commerce Research," Electronic Commerce Research, Springer, vol. 21(1), pages 1-40, March.
- Xue Pan & Lei Hou & Kecheng Liu, 2022. "The effect of product distance on the eWOM in recommendation network," Electronic Commerce Research, Springer, vol. 22(3), pages 901-924, September.
- Haoyan Sun & Jianqing Chen & Ming Fan, 2021. "Effect of Live Chat on Traffic‐to‐Sales Conversion: Evidence from an Online Marketplace," Production and Operations Management, Production and Operations Management Society, vol. 30(5), pages 1201-1219, May.
- Supriyo Mandal & Abyayananda Maiti, 2022. "Network promoter score (NePS): An indicator of product sales in E-commerce retailing sector," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(3), pages 1327-1349, September.
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Keywords
Information cascades; Word of mouth; Recommendation systems; Interaction effect; Online reading;All these keywords.
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