Abstract
As the new form of online reviews, supplemental reviews have attracted the attention of many scholars. Considering current studies do not take full consideration on the content of reviews, the study goes better maturely and thoroughly on all information in supplemental reviews. In detail, sentiments of supplemental reviews in terms of different features corresponding to product, service and logistics are quantitatively analyzed. Except for the sentiments of reviews, other important factors including the volume of supplemental reviews, price, and ratings are introduced into the designed log-linear regression model for estimation. To explore the impact of supplemental reviews on product sales, an empirical study is conducted. The selected product with high involvement is mobile phone covering 32 products. The related sales as well as initial reviews and supplemental reviews are crawled from tmall.com for experiments. The period of data is from July 5, 2018 to July 24, 2018. By regression analysis, the results show that the sentiments of product features in both initial reviews and supplemental reviews and the sentiments of logistics features in supplemental reviews have significant positive impact on product sales. The volume of supplemental reviews has a negative impact on product sales. Compared with initial reviews, the impact of sentiments of product features on sales in supplemental reviews is greater.
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References
Shi, W., Gong, X., Zhang, Q., Wang, L.: A comparative study on the first-time online reviews and appended online reviews. J. Manag. Sci. 29(04), 45–58 (2016). (in Chinese)
Wang, C., He, S., Wang, K.: Research on how additional review affects perceived review usefulness. J. Manag. Sci. 28(3), 102–114 (2015). (in Chinese)
Shi, W., Wang, L., Sheng, N., Cai, J.: A comparative study into the impact of initial and follow-on online comments on sales. Manag. Rev. 30(01), 144–153 (2018). (in Chinese)
Li, L., An, S.: The effect of additional difference on product sales. In: 19th China Management Science Academic Conference, vol. 25 (2017). (in Chinese)
Chatterjee, P.: Online reviews: do consumers use them? Adv. Consum. Res. 28, 129–134 (2001)
Park, D.H., Kim, S.: The effects of consumer knowledge on message processing of electronic word-of mouth via online consumer reviews. Electron. Commer. Res. Appl. 7(4), 399–410 (2008)
Clemons, E., Gao, G., Hitt, L.: When online reviews meet hyper differentiation: a study of the craft beer industry. J. Manag. Inf. Syst. 23(2), 149–171 (2006)
Chevalier, J., Mayzlin, D.: The effect of word of mouth on sales: online book reviews. Nber Work. Pap.43(3), 345–354 (2006)
Liu, Y.: Word of mouth for movies: Its dynamics and impact on box office revenue. J. Mark. 70(3), 74–89 (2006)
Zhu, F., Zhang, X.: Impact of online consumer reviews on sales: the moderating role of product and consumer characteristics. J. Mark. 74(2), 133–148 (2010)
Gong, S., Liu, X., Zhao, P.: How do online consumer reviews impact sales? An empirical research based on online book reviews. China Soft Sci. 6, 171–183 (2013). (in Chinese)
Luan, Y., Jackie, Y., Neslin, S.: The Development and Impact of Consumer Word of Mouth in New Product Diffusion. Social Science Electronic Publishing (2009)
Li, Z., Liu, R., Zhang, Y., Guan, H.: Statistical characteristics study on the Taobao’s appended online review group based on complex networks. Soft Sci. 28(08), 103–106 (2014). (in Chinese)
Li, Q., Ren, X.: Research on how conflictive additional reviews affect perceived helpfulness. J. Manag. Sci. 30(04), 139–150 (2017). (in Chinese)
Archak, N., Ghose, A., Ipeirotis, G.P.: Deriving the pricing power of product features by mining consumer reviews. Manag. Sci. 57(8), 1485–1509 (2011)
Wang, W., Wang, H.: The impact of feature opinions on purchase decision: sentiment analysis method of online reviews. Syst. Eng. Theory Pract. 36(1), 63–76 (2016). (in Chinese)
Sun, Y., Dong, X., McIntyre, S.: Motivation of user-generated content: social connectedness moderates the effects of monetary rewards. Mark. Sci. 36(3), 329–337 (2017)
Hu, M., Liu, B.: Mining opinion features in customer reviews. In: National Conference on Artificial Intelligence, vol. 69, pp. 755–760 (2004)
Ghani, R., Probst, K., Liu, Y., Krema, M., Fano, A.: Text mining for product attribute extraction. ACM SIGKDD Explor. Newsl. 8(1), 41–48 (2006)
Yang, X., Yang, G., Wu, J.: Integrating rich and heterogeneous information to design a ranking system for multiple products. Decis. Support Syst. 84, 117–133 (2016)
Pee, L.G.: Negative online consumer reviews: can the impact be mitigated? Int. J. Mark. Res. 58(4), 545–568 (2016)
Song, X., Sun, X.: Review of consumer adoption of online reviews. J. Mod. Inf. 35(01), 164–169 (2015). (in Chinese)
Acknowledgements
We thank Tmall for providing plenty of products reviews. We also thank the project supported by Scientific and Technological Innovation Foundation of Dalian (2018J11CY009).
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Liu, H., Wu, J., Yang, X., Li, X. (2018). The Impact of Online Reviews on Product Sales: What’s Role of Supplemental Reviews. In: Chen, J., Yamada, Y., Ryoke, M., Tang, X. (eds) Knowledge and Systems Sciences. KSS 2018. Communications in Computer and Information Science, vol 949. Springer, Singapore. https://doi.org/10.1007/978-981-13-3149-7_12
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DOI: https://doi.org/10.1007/978-981-13-3149-7_12
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