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How the Variance of Hotel Dominance Attribute Affects the Consumer Recommendation Rate: An Empirical Study with the Data from Ctrip.com

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11068))

Abstract

The influence of consumer reviews on hotel reservation has been addressed in both practical and theoretical fields. Most previous studies focus on the volume and score of reviews, little about the score of hotel attributes. This paper focuses on that how the variance of the hotel dominance attribute ratings affects the consumer recommendation rate to economy hotels and luxury hotels respectively. Research model has been developed based on Elaboration Likelihood Model and tested with the data from Ctrip.com in China. The results show that the variance of economy hotels has positive effect on the consumer recommendation rate, while that of luxury hotels has negative effect. Furthermore, results also indicate that the volume and score of reviews have different moderating effect.

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References

  1. Yin, D., Bond, S.D.: Anxious or angry effects of discrete emotions on the perceived helpfulness of online reviews. MIS Q. 38, 539–560 (2013)

    Article  Google Scholar 

  2. Ye, Q., Law, R.: The impact of online user reviews on hotel room sales. Int. J. Hosp. Manag. 28(1), 180–182 (2009)

    Article  Google Scholar 

  3. Wang, M., Lu, Q.: How word-of-mouth moderates room price and hotel stars for online hotel booking an empirical investigation with expedia data. J. Electron. Commer. Res. 16(1), 72–80 (2015)

    MathSciNet  Google Scholar 

  4. Provencher, J.F.: Quantifying ingested debris in marine megafauna: a review and recommendations for standardization. Anal. Methods 9(9), 1454–1469 (2017)

    Article  Google Scholar 

  5. Sun, M.: How does the variance of product ratings matter. Manag. Sci. 58(4), 696–707 (2012)

    Article  Google Scholar 

  6. Huang, A.H., Chen, K.: A study of factors that contribute to online review helpfulness. Comput. Hum. Behav. 48(C), 17–27 (2015)

    Article  Google Scholar 

  7. Liu, Z.W., Sangwon, P.: What makes a useful online review? Implication for travel product websites. Tourism Manag. 47(47), 140–151 (2015)

    Article  Google Scholar 

  8. Li, Z.: A survey of link recommendation for social networks: methods, theoretical foundations, and future research directions. ACM Trans. Manag. Inf. Syst. 9(1) (2018)

    Article  Google Scholar 

  9. Liu, Y.: Recommendation in a changing world: exploiting temporal dynamics in ratings and reviews. ACM Trans. Web 12(1), 3 (2018)

    Google Scholar 

  10. Petty, R.E., Cacioppo, J.T.: The elaboration likelihood model of persuasion. Adv. Consum. Res. 19(4), 123–205 (1986)

    Google Scholar 

  11. Cheung, M.Y., Sia, C.L.: Is this review believable? A study of factors affecting the credibility of online consumer reviews from an ELM perspective. J. Assoc. Inf. Syst. 13(8), 618–635 (2012)

    Google Scholar 

  12. Liu, S.W., Law, R.: Analyzing changes in hotel customers’ expectations by trip mode. Int. J. Hosp. Manag. 34(1), 359–371 (2013)

    Article  Google Scholar 

  13. Kim, D., Perdue, R.R.: The effects of cognitive, affective, and sensory attributes on hotel choice. Int. J. Hosp. Manag. 35, 246–257 (2013)

    Article  Google Scholar 

  14. Mao, M.: Multirelational social recommendations via multigraph ranking. IEEE Trans. Cybern. 47(12), 4049–4061 (2017)

    Article  Google Scholar 

  15. Duan, W., Gu, B.: Do online reviews matter? An empirical investigation of panel data. Decis. Support Syst. 45(4), 1007–1016 (2008)

    Article  Google Scholar 

  16. Zhu, F., Zhang, X.M.: Impact of online consumer reviews on sales: the moderating role of product and consumer characteristics. J. Market. 74(2), 133–148 (2010)

    Article  Google Scholar 

  17. Sparks, B.A., Browning, V.: The impact of online reviews on hotel booking intentions and perception of trust. Tourism Manag. 32(6), 1310–1323 (2011)

    Article  Google Scholar 

  18. Baka, V.: The becoming of user-generated reviews: looking at the past to understand the future of managing reputation in the travel sector. Tourism Manag. 53, 148–162 (2016)

    Article  Google Scholar 

  19. Duan, W., Gu, B.: The dynamics of online word-of-mouth and product sales—an empirical investigation of the movie industry. J. Retail. 84(2), 233–242 (2008)

    Article  Google Scholar 

  20. Flanagan, A.J., Metzger, M.J.: Trusting expert- versus user-generated ratings online: the role of information volume, valence, and consumer characteristics. Comput. Hum. Behav. 29(4), 1626–1634 (2013)

    Article  Google Scholar 

  21. Park, D.H., Lee, J.: eWOM overload and its effect on consumer behavioral intention depending on consumer involvement. Electron. Commer. Res. Appl. 7(4), 386–398 (2008)

    Article  Google Scholar 

  22. Zhang, S.: The recommendation system of micro-blog topic based on user clustering. Mob. Netw. Appl. 22(2), 228–239 (2017)

    Article  Google Scholar 

  23. Park, J.Y., Jang, S.C.: Confused by too many choices? Choice overload in tourism. Tourism Manag. 35(4), 1–12 (2013)

    Article  Google Scholar 

Download references

Acknowledgments

This research was supported by the National Social Science Foundation of China (No. 14AGL023) and the Plan of Ten Thousand Tourism Excellence launched by National Tourism Administration (No. WMYC20171080). We would like to thank all the reviewers for their kind suggestions to this work.

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Correspondence to Shasha Liu .

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Shao, B., Liu, S., Gao, Y., Lyu, X., Cheng, Z. (2018). How the Variance of Hotel Dominance Attribute Affects the Consumer Recommendation Rate: An Empirical Study with the Data from Ctrip.com. In: Sun, X., Pan, Z., Bertino, E. (eds) Cloud Computing and Security. ICCCS 2018. Lecture Notes in Computer Science(), vol 11068. Springer, Cham. https://doi.org/10.1007/978-3-030-00021-9_49

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  • DOI: https://doi.org/10.1007/978-3-030-00021-9_49

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-00020-2

  • Online ISBN: 978-3-030-00021-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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