Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
Skip to main content
Springer Nature Link
Log in

A group consensus-based travel destination evaluation method with online reviews

  • Published:
Applied Intelligence Aims and scope Submit manuscript

Abstract

With the help of the massive online information, non-expert decision-making problems (such as travel destination selection) can be solved. Online reviews provide decision-making opinions and weight information for tourists who have never been to the alternative travel destinations. To deal with the increasing tourism products and group tourists, this study proposes a novel group consensus-based travel destination evaluation method with online reviews, which considers the missing preference estimating and group consensus reaching process. Firstly, decision opinions are represented through the sentiment matrix with the percentage distribution. Secondly, to obtain the weight vector of attributes, the incomplete complementary matrices with the preference of attributes are given by group users. Subsequently, the missing preference values in the matrix are estimated. Thirdly, all users are required to reach group consensus based on the minimum adjustment cost feedback mechanism. Finally, the sentiment matrix with the percentage distribution can be aggregated by the weight vectors. So that the ranking of alternatives can be obtained. In this study, an example of travel destination evaluation based on the online reviews of Dazhong.com and Ctrip.com is given to illustrate the use of the proposed method.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

Explore related subjects

Discover the latest articles, news and stories from top researchers in related subjects.

References

  1. Zhang HY, Ji P, Wang JQ, Chen XH (2017) A novel decision support model for satisfactory restaurants utilizing social information: A case study of TripAdvisor.com. Tour Manag 59:281–297

    Article  Google Scholar 

  2. Sun XY, Han MX, Feng J (2019) Helpfulness of online reviews: Examining review informativeness and classification thresholds by search products and experience products. Decis Support Syst:124

  3. Yu SM, Wang J, Wang JQ, Li L (2018) A multi-criteria decision-making model for hotel selection with linguistic distribution assessments. Appl Soft Comput 67:741–755

    Article  Google Scholar 

  4. Li CC, Gao Y, Dong YC (2020) Managing ignorance elements and personalized individual semantics under incomplete linguistic distribution context in group decision making. Group Decision and Negotiation

  5. Zhang HJ, Xiao J, Dong YC (2019) Integrating a consensus-reaching mechanism with bounded confidences into failure mode and effect analysis under incomplete context. Knowl-Based Syst 183:1–20

    Google Scholar 

  6. Dong YC, Zha QB, Zhang HJ, Herrera F (2020) Consensus reaching and strategic manipulation in group decision making with trust relationships. IEEE Transactions on systems, Man, and Cybernetics: Systems, pp 1–15

  7. Zha QB, Dong YC, Zhang HJ, Chiclana F, Herrera-Viedmac E (2019) A personalized feedback mechanism based on bounded confidence learning to support consensus reaching in group decision making, IEEE Transactions on Systems, Man, and Cybernetics: Systems, pp 1–11

  8. Cao MS, Wu J, Chiclana F, Ureña R, Herrera-Viedma E (2020) A personalized feedback mechanism based on maximum harmony degree. IEEE Transactions on Systems, Man, and Cybernetics: Systems, pp 1–13

  9. Gai TT, Cao MS, Cao QW, Wu J, Yu GF, Zhou M (2020) A joint feedback strategy for consensus in large-scale group decision making under social network. Comput Indust Eng:147

  10. Dong YC, Chen X, Herrera F (2015) Minimizing adjusted simple terms in the consensus reaching process with hesitant linguistic assessments in group decision making. Inf Sci 297:95–117

    Article  MathSciNet  Google Scholar 

  11. Lu YL, Xu YJ, Herrera-Viedma E, Han YF (2021) Consensus of large-scale group decision making in social network: The minimum cost model based on robust optimization. Inf Sci 547:910–930

    Article  MathSciNet  Google Scholar 

  12. Wu J, Zhao ZW, Sun Q, Fujita H (2021) A maximum self-esteem degree based feedback mechanism for group consensus reaching with the distributed linguistic trust propagation in social network. Inf Fusion 67:80–93

    Article  Google Scholar 

  13. Wu J, Sun Q, Fujita H, Chiclana F (2019) An attitudinal consensus degree to control the feedback mechanism in group decision making with different adjustment cost. Knowl-Based Syst 164:265–273

    Article  Google Scholar 

  14. Dong YC, Zha QB, Zhang HJ, Kou G, Fujita H, Chiclana F, Herrera-Viedma E (2018) Consensus reaching in social network group decision making: Research paradigms and challenges. Knowl-Based Syst 3-13:162

    Google Scholar 

  15. Chiclana F, Herrera-Viedma E, Alonso S, Herrera F (2018) A note on the estimation of missing pairwise preference values: A uninorm consistency based method. Int J Uncert Fuzz Knowl-Based Syst 16(2):19–32

    MathSciNet  MATH  Google Scholar 

  16. Kang D, Park Y (2014) Review-based measurement of customer satisfaction in mobile service: Sentiment analysis and VIKOR approach. Expert Syst Appl 41(4):1041–1050

    Article  Google Scholar 

  17. Liang D, Dai ZY, Wang MW (2021) Assessing customer satisfaction of O2O takeaway based on online reviews by integrating fuzzy comprehensive evaluation with AHP and probabilistic linguistic term sets. Appl Soft Comput:98

  18. Chen K, Kou G, Shang J, Chen Y (2015) Visualizing market structure through online product reviews: Integrate topic modeling, TOPSIS, and multi-dimensional scaling approaches. Electron Commer Res Appl 14(1):58–74

    Article  Google Scholar 

  19. Liang X, Liu PD, Wang ZH (2019) Hotel selection utilizing online reviews: a novel decision support model based on sentiment analysis and DL-VIKOR method. Technol Econ Dev Econ 25(6):1139–1161

    Article  Google Scholar 

  20. Kwok P, Laub H (2019) Hotel selection using a modified TOPSIS-based decision support algorithm. Decis Support Syst 120:95– 105

    Article  Google Scholar 

  21. Peng HG, Zhang HY, Wang JQ (2018) Cloud decision support model for selecting hotels on TripAdvisor.com with probabilistic linguistic information. Int J Hosp Manag 68:124–138

    Article  Google Scholar 

  22. Zhou M, Liu XB, Chen YW, Qian XF, Yang JB, Wu J (2020) Assignment of attribute weights with belief distributions for MADM under uncertainties. Knowl-Based Syst 189:1–18

    Article  Google Scholar 

  23. Zhang CB, Zhang HY, Wang JQ (2018) Personalized restaurant recommendation method combining group correlations and customer preferences. Inf Sci 454-455:128–143

    Article  Google Scholar 

  24. Wu J, Li X, Chiclana F, Yager R (2019) An attitudinal trust recommendation mechanism to balance consensus and harmony in group decision making. IEEE Trans Fuzzy Syst 27(11):2163–2175

    Article  Google Scholar 

  25. Li Y, Chen X, Dong YC, Herrera F (2020) Linguistic group decision making: Axiomatic distance and minimum cost consensus. Inf Sci 541:242–258

    Article  MathSciNet  Google Scholar 

  26. Wu J, Cao MS, Chiclana F, Dong YC, Herrera-Viedma E (2020) An optimal feedback model to prevent manipulation behaviours in consensus under social network group decision making. IEEE Trans Fuzzy Syst:1–14

  27. Zhang BW, Dong YC, Feng X, Pedrycz W (2020) Maximum fuzzy consensus feedback mechanism with minimum cost and private interest in group decision making. IEEE Trans Fuzzy Syst:1–12

  28. Wu J, Liu YJ, Liang CY (2014) A consensus-and harmony-based feedback mechanism for multiple attribute group decision making with correlated intuitionistic fuzzy sets. Int Trans Oper Res 22(6):1033–1054

    Article  MathSciNet  Google Scholar 

  29. Liu YJ, Liang CY, Chiclana F, Wu J (2017) A trust induced recommendation mechanism for reaching consensus in group decision making. Knowl-Based Syst 119:221–231

    Article  Google Scholar 

  30. Liu YJ, Liang CY, Chiclana F, Wu J (2021) A knowledge coverage-based trust propagation for recommendation mechanism in social network group decision making. Appl Soft Comput J:101

  31. Ureña R, Chiclana F, Melançon G, Herrera-Viedma E (2019) A social network based approach for consensus achievement in multiperson decision making. Inf Fusion 47:72–87

    Article  Google Scholar 

  32. Gong ZW, Xu XX, Zhang HH, Ozturk U, Herrera-Viedma E, Xu C (2015) The consensus models with interval preference opinions and their economic interpretation. Omega 55:81–90

    Article  Google Scholar 

  33. Wu J, Dai LF, Chiclana F, Fujita H, Herrera-Viedma E (2018) A minimum adjustment cost feedback mechanism based consensus model for group decision making under social network with distributed linguistic trust. Inf Fusion 41:232–242

    Article  Google Scholar 

  34. Tu HL, Tang XB (2016) Tourist sentiment analysis model building based on online reviews. J Modern Inf 36(4):70–77

    Google Scholar 

  35. Morente-Molinera J, Kou G, Pang C, Cabrerizo F, Herrera-Viedma E (2019) An automatic procedure to create fuzzy ontologies from Users’ opinions using sentiment analysis procedures and multi-granular fuzzy linguistic modelling methods. Inf Sci 476:222–238

    Article  Google Scholar 

  36. Liang X, Jiang YP, Gao M (2017) Product selection methods based on online reviews. J Northeast Univ (Nat Sci) 38(1):143–147

    Google Scholar 

  37. Liu Y, Bi JW, Fan ZP (2017) Ranking products through online reviews: a method based on sentiment analysis technique and intuitionistic fuzzy set theory. Inf Fusion 36:149–161

    Article  Google Scholar 

  38. Qin JD, Liu XW, Pedrycz W (2017) An extended TODIM multi-criteria group decision making method for green supplier selection in interval type-2 fuzzy environment. Eur J Oper Res 258(2):626–638

    Article  MathSciNet  Google Scholar 

  39. Lin MW, Xu ZS, Zhai YL, Yao ZQ (2018) Multi-attribute group decision-making under probabilistic uncertain linguistic environment. J Oper Res Soc 69(2):157–170

    Article  Google Scholar 

  40. Wang JQ, Zhang HY, Zhang Z (2010) Fuzzy multi-criteria decision-making approach with incomplete information based on evidential reasoning. J Syst Eng Electron 21(4):604–608

    Article  Google Scholar 

  41. Liu D, Li TR, Zhang JB (2014) A rough set-based incremental approach for learning knowledge in dynamic incomplete information systems. Int J Approx Reason 55(8):1764–1786

    Article  MathSciNet  Google Scholar 

  42. Liu JP, Liao XW, Yang JB (2015) A group decision-making approach based on evidential reasoning for multiple criteria sorting problem with uncertainty. Eur J Oper Res 246(3):858–873

    Article  MathSciNet  Google Scholar 

  43. Bao TT, Xie XL, Long PY, Wei ZK (2017) MADM Method based on prospect theory and evidential reasoning approach with unknown attribute weights under intuitionistic fuzzy environment. Expert Syst Appl 88:305–317

    Article  Google Scholar 

  44. Liang Q, Liao XW, Liu JP (2017) A social ties-based approach for group decision-making problems with incomplete additive preference values. Knowl-Based Syst 119:68–86

    Article  Google Scholar 

  45. Wu J, Chiclana F, Herrera-Viedma E (2015) Trust based consensus model for social network in an incomplete linguistic information context. Appl Soft Comput 35:827–839

    Article  Google Scholar 

  46. Liu HB, Ma Y, Jiang L (2019) Managing incomplete preferences and consistency improvement in hesitant fuzzy linguistic preference values with applications in group decision making. Inf Fusion 51:19–29

    Article  Google Scholar 

  47. Herrera-Viedma E, Chiclana F, Herrera F, Alonso S (2017) Group decision-making model with incomplete fuzzy preference values based on additive consistency. IEEE Trans Syst Man Cybern Part B (Cybern) 37(1):176–189

    Article  Google Scholar 

  48. Xu Y, Da L, Liu L (2009) Normalizing rank aggregation method for priority of a fuzzy preference relation and its effectiveness. Int J Approx Reas:50(8)

  49. Zhang GQ, Dong YC, Xu YF (2014) Consistency and consensus measures for linguistic preference relations based on distribution assessments. Inf Fusion 17:46–55

    Article  Google Scholar 

Download references

Acknowledgements

The authors are very grateful to the anonymous referees for their valuable comments and suggestions. This work was supported by National Natural Science Foundation of China (NSFC) under the Grant No. 71971135, 72001134, 71571166. And industrial and Informationalization Ministry of China for Cruise Program (No. 2018-473), and Key Project of National Social and Scientific Fund Program (18ZDA052).

Author information

Authors and Affiliations

  1. School of Economics and Management, Shanghai Maritime University, Shanghai, 201306, China

    Jian Wu, Qing Hong, Mingshuo Cao & Yujia Liu

  2. Iwate Prefectural University, Iwate, Japan

    Hamido Fujita

Authors
  1. Jian Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Qing Hong
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Mingshuo Cao
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Yujia Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Hamido Fujita
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yujia Liu.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wu, J., Hong, Q., Cao, M. et al. A group consensus-based travel destination evaluation method with online reviews. Appl Intell 52, 1306–1324 (2022). https://doi.org/10.1007/s10489-021-02410-6

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10489-021-02410-6

Keywords

Search

Navigation