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A Decision-Making Model Under Probabilistic Linguistic Circumstances with Unknown Criteria Weights for Online Customer Reviews

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Abstract

Online customer reviews (OCRs) provide much information about products or service, but the mass of information increases the difficulty for customers to make decisions. Thus, we establish a multi-criteria decision making (MCDM) model to evaluate products or service. To analyze OCRs, the sentiment analysis (SA) is introduced to identify the sentiment orientation of reviews. Considering that the textual information in OCRs is linguistic information, probabilistic linguistic term sets (PLTSs) are applied to present the results of the SA. A process of extracting probabilistic linguistic information based on SA from OCRs is also presented. Then, for the MCDM problems with unknown criteria weights, we combine the PP (projection pursuit) method and the MULTIMOORA (multiplicative multi-objective optimization by ratio analysis) method, and develop an extended method (named as the PP-MULTIMOORA method). The projection pursuit (PP) method is developed to derive objective criteria weights and the MULTIMOORA method is to derive final rankings of products or service. Finally, we apply the proposed model to a case of evaluating doctors’ service quality and further conduct a comparative analysis to illustrate the effectiveness of our work.

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References

  1. Li, Z., Shimizu, A.: Impact of online customer reviews on sales outcomes: an empirical study based on prospect theory. Rev. Socionetw. Strat. 12(2), 135–151 (2018)

    Article  Google Scholar 

  2. Maslowska, E., Malthouse, E. C., Bernritter, S.F.: The effect of online customer reviews’ characteristics on sales. In: 14th international conference on research in advertising (ICORIA), pp. 87–100 (2017)

  3. Öğüt, H., Taş, B.K.O.: The influence of Internet customer reviews on the online sales and prices in hotel industry. Serv. Ind. J. 32(2), 197–214 (2012)

    Article  Google Scholar 

  4. Kostyra, S.D., Reiner, J., Natter, M., Klapper, D.: Decomposing the effects of online customer reviews on brand, price, and product attributes. Int. J. Res. Mark. 33(1), 11–26 (2016)

    Article  Google Scholar 

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

    Article  Google Scholar 

  6. Picazo-Vela, S.: The effect of online reviews on customer satisfaction: an expectation disconfirmation approach. AMCIS 2009 Doctoral Consortium. (2009)

  7. Suzuki, T., Gemba, K., Aoyama, A.: Identifying customer satisfaction estimators using review mining. Int. J. Technol. Mark. 9(2), 187–210 (2014)

    Article  Google Scholar 

  8. Wang, Y.R., Lu, X., Tan, Y.J.: Impact of product attributes on customer satisfaction: an analysis of online reviews for washing machines. Electron. Commer. R. A. 29, 1–11 (2018)

    Article  Google Scholar 

  9. Zhou, L.Q., Ye, S., Pearce, P.L., Wu, M.Y.: Refreshing hotel satisfaction studies by reconfiguring customer review data. Int. J. Hospit. Manag. 38, 1–10 (2014)

    Article  Google Scholar 

  10. Dewi, D.S., Sudiarno, A., Saputra H., Dewi, R.S.: The effect of emotional design and online customer review on customer repeat purchase intention in online stores. In: IOP Conference series: materials science and engineering. 337, (2018)

  11. Hsu, C.L., Yu, L.C., Chang, K.C.: Exploring the effects of online customer reviews, regulatory focus, and product type on purchase intention: perceived justice as a moderator. Comput. Hum. Behav. 69, 335–346 (2017)

    Article  Google Scholar 

  12. Lü, K., Elwalda, A.: The impact of online customer reviews (OCRs) on customers’ purchase decisions: an exploration of the main dimensions of OCRs. J. Customer Behav. 15(2), 123–152 (2016)

    Article  Google Scholar 

  13. Maslowska, E., Malthouse, E.C., Viswanathan, V.: Do customer reviews drive purchase decisions? The moderating roles of review exposure and price. Decis. Support Syst. 98, 1–9 (2016)

    Article  Google Scholar 

  14. Yan, X.B., Wang, J., Chau, M.: Customer revisit intention to restaurants: evidence from online reviews. Inf. Syst. Front. 17(3), 645–657 (2015)

    Article  Google Scholar 

  15. Gensler, S., Völckner, F., Egger, M., Fischbach, K., Schoder, D.: Listen to your customers: insights into brand image using online consumer-generated product reviews. Int. J. Electron. Comm. 20(1), 112–141 (2015)

    Article  Google Scholar 

  16. See-To, E.W.K., Ngai, E.W.T.: Customer reviews for demand distribution and sales nowcasting: a big data approach. Ann. Oper. Res. 270(1–2), 415–431 (2018)

    Article  MATH  Google Scholar 

  17. Qiao, Z.L., Wang, G.A., Zhou, M., Fan, W.G.: The impact of customer reviews on product innovation: Empirical evidence in mobile apps. Analytics and data science. Annals of information systems, pp. 95–110. Springer, Cham (2018)

    Google Scholar 

  18. Zhou, F., Jiao, R.J.: Latent customer needs elicitation for big-data analysis of online product reviews. In: 2015 IEEE international conference on industrial engineering and engineering management (IEEM), pp. 1850–1854. IEEE (2015)

  19. Qi, J.Y., Zhang, Z.P., Jeon, S., Zhou, Y.Q.: Mining customer requirements from online reviews: a product improvement perspective. Inf. Manag. 53(8), 951–963 (2016)

    Article  Google Scholar 

  20. Li, S., Nahar, K., Fung, B.C.M.: Product customization of tablet computers based on the information of online reviews by customers. J. Intell. Manuf. 26(1), 97–110 (2015)

    Article  Google Scholar 

  21. Xu, K.Q., Liao, S.S.Y., Li, J.X., Song, Y.X.: Mining comparative opinions from customer reviews for competitive intelligence. Decis. Support Syst. 50(4), 743–754 (2011)

    Article  Google Scholar 

  22. Hsieh, H.Y., Wu, S.H.: Ranking online customer reviews with the SVR model. In: 2015 IEEE international conference on information reuse and integration, pp. 550–555, IEEE (2015)

  23. Najmi, E., Hashmi, K., Malik, Z., Rezgui, A., Khan, H.U.: CAPRA: a comprehensive approach to product ranking using customer reviews. Computing 97(8), 843–867 (2015)

    Article  MathSciNet  Google Scholar 

  24. Zhang, K.P., Narayanan, R., Choudhary, A.: Voice of the customers: Mining online customer reviews for product feature-based ranking. In: WOSN’10 Proceedings of the 3rd conference on online social networks, pp. 1-9, (2010)

  25. Kong, R., Wang, Y.G., Xin, W., Yang, T., Hu, J.B., Zhong, C.: Customer reviews for individual product feature-based ranking. In: 2011 first international conference on instrumentation, measurement, computer, communication and control, pp. 449–453, IEEE (2011)

  26. Chutmongkolporn, K., Manaskasemsak, B., Rungsawang, A.: Graph-based opinion entity ranking in customer reviews. In: 15th international symposium on communications and information technologies (ISCIT), pp. 161–164, IEEE (2015)

  27. Peng, Y., Kou, G., Li, J.: A fuzzy PROMETHEE approach for mining customer reviews in Chinese. Arab. J. Sci. Eng. 39(6), 5245–5252 (2014)

    Article  Google Scholar 

  28. Aquino, J.T., Melo, F.J.C., Barros Jerônimo, T., Medeiros, D.D.: Evaluation of quality in public transport services: the use of quality dimensions as an input for fuzzy TOPSIS. Int. J. Fuzzy Syst. 21(1), 176–193 (2019)

    Article  Google Scholar 

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

    Article  Google Scholar 

  30. Hu, J.H., Zhang, X.H., Yang, Y., Liu, Y.M., Chen, X.H.: New doctors ranking system based on VIKOR method. Intl. Trans. Op. Res. 27, 1–26 (2018)

    MathSciNet  Google Scholar 

  31. Tooranloo, H.S., Ayatollah, A.S.: Pathology the Internet banking service quality using failure mode and effect analysis in interval-valued intuitionistic fuzzy environment. Int. J. Fuzzy Syst. 19(1), 109–123 (2017)

    Article  Google Scholar 

  32. Ji, P., Zhang, H.Y., Wang, J.Q.: A fuzzy decision support model with sentiment analysis for items comparison in e-commerce: the case study of PConline.com. In: IEEE transactions on systems, man, and cybernetics: systems (Early Access), pp. 1–12 IEEE (2018)

  33. Liang, R.X., Wang, J.Q.: A linguistic intuitionistic cloud decision support model with sentiment analysis for product selection in e-commerce. Int. J. Fuzzy Syst. 21(3), 963–977 (2019)

    Article  Google Scholar 

  34. Xu, Z.S., Zhao, N.: Information fusion for intuitionistic fuzzy decision making: an overview. Inf. Fusion. 28, 10–23 (2016)

    Article  Google Scholar 

  35. Pang, Q., Wang, H., Xu, Z.S.: Probabilistic linguistic term sets in multi-attribute group decision making. Inf. Sci. 369, 128–143 (2016)

    Article  Google Scholar 

  36. Wu, X.L., Liao, H.C.: An approach to quality function deployment based on probabilistic linguistic term sets and ORESTE method for multi-expert multi-criteria decision making. Inf. Fusion. 43, 13–26 (2018)

    Article  Google Scholar 

  37. Xie, W.Y., Xu, Z.S., Ren, Z.L., Wang, H.: Probabilistic linguistic analytic hierarchy process and its application on the performance assessment of Xiongan new area. Int. J. Inf. Technol. Decis. Mak. 17(06), 1693–1724 (2018)

    Article  Google Scholar 

  38. Xiao, F., Wang, J.Q.: Multistage decision support framework for sites selection of solar power plants with probabilistic linguistic information. J. Clean. Prod. 230, 1396–1409 (2019)

    Article  Google Scholar 

  39. Jin, C., Wang, H., Xu, Z.S.: Uncertain probabilistic linguistic term sets in group decision making. Int. J. Fuzzy Syst. 21(4), 1241–1258 (2019)

    Article  MathSciNet  Google Scholar 

  40. Zhang, Y.X., Xu, Z.S., Liao, H.C.: Water security evaluation based on the TODIM method with probabilistic linguistic term sets. Soft. Comput. 23(15), 6215–6230 (2019)

    Article  Google Scholar 

  41. Wu, X.L., Liao, H.C., Xu, Z.S., Hafezalkotob, A., Herrera, F.: Probabilistic linguistic MULTIMOORA: a multi-criteria decision making method based on the probabilistic linguistic expectation function and the improved borda rule. IEEE Trans. Fuzzy Syst. 26(6), 3688–3702 (2018)

    Article  Google Scholar 

  42. Brauers, W.K., Zavadskas, E.K.: Project management by MULTIMOORA as an instrument for transition economies. Technol. Econ. Dev. Econ. 16(1), 5–24 (2010)

    Article  Google Scholar 

  43. Huber, P.J.: Projection pursuit. Ann. Stat. 13(2), 435–475 (1985)

    Article  MathSciNet  MATH  Google Scholar 

  44. Nicola, L.: Finite mixtures, projection pursuit and tensor rank: a triangulation. Adv. Data Anal. Classif. 13(1), 1–29 (2019)

    Article  MathSciNet  MATH  Google Scholar 

  45. Espezua, S., Villanueva, E., Maciel, D.C.: Towards an efficient genetic algorithm optimizer for sequential projection pursuit. Neurocomputing. 123, 40–48 (2014)

    Article  Google Scholar 

  46. Hou, S., Wentzell, P.D.: Fast and simple methods for the optimization of kurtosis used as a projection pursuit index. Anal. Chim. Acta 704(1–2), 1–15 (2011)

    Article  Google Scholar 

  47. Bickel, P.J., Kur, G., Nadler, B.: Projection pursuit in high dimensions. Proc. Natl. Acad. Sci. U.S.A. 115(37), 9151–9156 (2018)

    Article  MathSciNet  MATH  Google Scholar 

  48. Brauers, W.K., Zavadskas, E.K.: Robustness of MULTIMOORA: a method for multi-objective optimization. Informatica. 23(1), 1–25 (2012)

    MathSciNet  MATH  Google Scholar 

  49. Hafezalkotob, A., Hafezalkotob, A.: Interval MULTIMOORA method with target values of attributes based on interval distance and preference degree: biomaterials selection. J. Ind. Eng. Int. 13(2), 181–198 (2017)

    Article  MATH  Google Scholar 

  50. Brauers, W.K., Zavadskas, E.K.: MULTIMOORA optimization used to decide on a bank loan to buy property. Technol. Econ. Dev. Econ. 17(1), 174–188 (2011)

    Article  Google Scholar 

  51. Hafezalkotob, A., Hafezalkotob, A.: Comprehensive MULTIMOORA method with target-based attributes and integrated significant coefficients for materials selection in biomedical applications. Mater. Des. 87, 949–959 (2015)

    Article  Google Scholar 

  52. Parasuraman, A., Zeithaml, V., Berry, L.: SERVQUAL: a multiple-item scale for measuring consumer perceptions of service quality. J. Retail. 64(1), 12–40 (1988)

    Google Scholar 

  53. Zhang, H., Gu, C.L., Gu, L.W., Zhang, Y.: The evaluation of tourism destination competitiveness by TOPSIS & information entropy—a case in the Yangtze River Delta of China. Tour. Manage. 32(2), 443–451 (2011)

    Article  Google Scholar 

  54. Wang, Y.M.: Using the method of maximizing deviation to make decision for multiindices. J. Syst. Eng. Electron. 8(3), 21–26 (1997)

    Google Scholar 

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Acknowledgements

This study was funded by the National Natural Science Foundation of China (Nos. 71771155, 71571123), the scholarship under the UK-China Joint Research and Innovation Partnership Fund PhD Placement Programme (No. 201806240416) and the Teacher-Student Joint Innovation Research Fund of Business School of Sichuan University (No. H2018016).

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Authors and Affiliations

  1. Business School, Sichuan University, Chengdu, 610064, Sichuan, China

    Yang Li, Yixin Zhang & Zeshui Xu

  2. Department of Computer Science, University of Manchester, Manchester, M13 9PL, UK

    Yixin Zhang

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  1. Yang Li
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Corresponding author

Correspondence to Zeshui Xu.

Appendix

Appendix

Tables 7, 8 and 9.

Table 7 The Chinese sentiment dictionary of the review over doctor
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Table 8 The Chinese dictionary of degree adverbs
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Table 9 The Chinese dictionary of negatives
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Li, Y., Zhang, Y. & Xu, Z. A Decision-Making Model Under Probabilistic Linguistic Circumstances with Unknown Criteria Weights for Online Customer Reviews. Int. J. Fuzzy Syst. 22, 777–789 (2020). https://doi.org/10.1007/s40815-020-00812-1

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