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Cross-Platform Distributed Product Online Ratings Aggregation Approach for Decision Making with Basic Uncertain Linguistic Information

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Abstract

The research on decision making driven by product rankings faces challenges due to the rise of extensive positive reviews and the widespread distribution of electronic word of mouth (eWOM) across multiple platforms. There is a limited body of research that examines the impact of platform credibility on the quality of product rankings. Hence, based on the basic uncertain linguistic information (BULI), which enables simultaneous representation of information and its credibility, we investigate the development of a ratings aggregation approach for cross-platform distribution (CPD) with the aim of facilitating decision-making processes, focusing specifically on the aspect of credibility. To begin with, this paper introduces the concept of BULI as a means to effectively represent both product ratings and their corresponding levels of credibility. Subsequently, we proceeded to devise the BULI-based aggregation functions that are well suited for the aggregation of CPD ratings and that can be degraded to the existing operator. In addition, we develop a credibility evaluation index system and credibility calculation model for the platform in order to derive a product BULI matrix consisting of ratings and their corresponding levels of credibility. In this study, we propose two models, namely the feature information-based user weighting model and the BULI distance measure-based technique for order preference by similarity to an ideal solution (BULI-TOPSIS) model, to enhance the product ratings aggregation approach for decision-making purposes. The utilization of the proposed method is exemplified through the case study of passenger car ranking, showcasing its practicality and efficiency.

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References

  1. Bhattacharyya, S., Bose, I.: S-commerce: Influence of facebook likes on purchases and recommendations on a linked e-commerce site. Decis. Support Syst. 138, 113383 (2020)

    Google Scholar 

  2. Benitez, J., Ruiz, L., Castillo, A., Llorens, J.: How corporate social responsibility activities influence employer reputation: the role of social media capability, Post-Print (2020)

  3. Chen, Z.-S., Yang, L.-L., Rodríguez, R.M., Xiong, S.-H., Chin, K.-S., Martínez, L.: Power-average-operator-based hybrid multiattribute online product recommendation model for consumer decision-making. Int. J. Intell. Syst. 36, 2572–2617 (2021)

    MATH  Google Scholar 

  4. Jha, A.K., Shah, S.: Disconfirmation effect on online review credibility: an experimental analysis. Decis. Support Syst. 145, 113519 (2021)

    MATH  Google Scholar 

  5. Banerjee, S., Bhattacharyya, S., Bose, I.: Whose online reviews to trust? Understanding reviewer trustworthiness and its impact on business. Decis. Support Syst. 96, 17–26 (2017)

    MATH  Google Scholar 

  6. Hlsa, B., Kpl, A., Hao, L.C., Dbc, D.: Evaluating user reputation of online rating systems by rating statistical patterns-sciencedirect. Knowl. Based Syst. 219, 106895 (2021)

    Google Scholar 

  7. Esposito, C., Galli, A., Moscato, V., Sperlí, G.: Multi-criteria assessment of user trust in social reviewing systems with subjective logic fusion. Inf. Fus. 77, 1–18 (2022)

    Google Scholar 

  8. Xiang, Z., Du, Q., Ma, Y., Fan, W.: A comparative analysis of major online review platforms: implications for social media analytics in hospitality and tourism. Tour. Manag. 58, 51–65 (2017)

    MATH  Google Scholar 

  9. Meel, P., Vishwakarma, D.K.: Fake news, rumor, information pollution in social media and web: a contemporary survey of state-of-the-arts, challenges and opportunities. Expert Syst. Appl. 153, 112986 (2020)

    MATH  Google Scholar 

  10. Wu, Q., Liu, X., Qin, J., Wang, W., Zhou, L.: A linguistic distribution behavioral multi-criteria group decision making model integrating extended generalized todim and quantum decision theory. Appl. Soft Comput. 98, 106757 (2021)

    MATH  Google Scholar 

  11. Kou, G., Yang, P., Peng, Y., Xiao, H., Xiao, F., Chen, Y., Alsaadi, F.E.: A cross-platform market structure analysis method using online product reviews. Technol. Econ. Dev. Econ. 27, 992–1018 (2021)

    MATH  Google Scholar 

  12. Zhao, M., Li, L., Xu, Z.: Study on hotel selection method based on integrating online ratings and reviews from multi-websites. Inf. Sci. 572, 460–481 (2021)

    MATH  Google Scholar 

  13. Mesiar, R., Borkotokey, S., Jin, L., Kalina, M.: Aggregation under uncertainty. IEEE Trans. Fuzzy Syst. 26, 2475–2478 (2017)

    MATH  Google Scholar 

  14. Jin, L.S., Mesiar, R., Borkotokey, S., Kalina, M.: Certainty aggregation and the certainty fuzzy measures. Int. J. Intell. Syst. 33, 759–770 (2018)

    MATH  Google Scholar 

  15. Jin, L., Chen, Z., Yager, R.R., Senapati, T., Mesiar, R., García-Zamora, D., Dutta, B., Martinez, L.: Ordered weighted averaging operators for basic uncertain information granules. Inf. Sci. 645, 119357 (2023)

    MATH  Google Scholar 

  16. Jin, L., Mesiar, R., Yager, R., Kaya, S.K.: Interval basic uncertain information and related aggregations in decision making. J. Intell. Fuzzy Syst. 42, 3551–3558 (2022)

    MATH  Google Scholar 

  17. Jin, L., Yager, R. R., Chen, Z.-S., Špirková, J., Mesiar, R.: Interval and BUI type basic uncertain information in multi-sources evaluation and rules based decision making. Int. J. Gen. Syst. 52(4), 443–454 (2023)

    MathSciNet  MATH  Google Scholar 

  18. Jin, L., Yager, R. R., Chen, Z.-S., Mesiar, M., Bustince, H.: Unsymmetrical basic uncertain information with some decisionmaking methods. J. Intell. Fuzzy Syst. 43(4), 4457–4463 (2022b)

    MATH  Google Scholar 

  19. Chen, Z.S., Martinez, L., Chang, J.P., Wang, X.J., Xionge, S.H., Chin, K.S.: Sustainable building material selection: A QFD- and ELECTRE III-embedded hybrid MCGDM approach with consensus building. Eng. Appl. Artif. Intell. 85, 783–807 (2019)

    Google Scholar 

  20. Chen, Z.S., Yang, L.L., Chin, K.S., Yang, Y., Pedrycz, W., Chang, J.P., Martinez, L., Skibniewski, M.J.: Sustainable building material selection: an integrated multi-criteria large group decision making framework. Appl. Soft Comput. 113, 107903 (2021)

    MATH  Google Scholar 

  21. Xu, J., Jin, L., Chen, Z., Mesiar, R., Yager, R.R.: Induced aggregation operators for interval basic uncertain information. J. Intell. Fuzzy Syst. 44, 3595–3602 (2023)

    MATH  Google Scholar 

  22. Chen, Z.-S., Lu, J.-Y., Wen, J.-T., Wang, X.-J., Deveci, M., Skibniewski, M.J.: BIM-enabled decision optimization analysis for architectural glass material selection considering sustainability. Inf. Sci. 647, 119450 (2023)

    MATH  Google Scholar 

  23. Yang, Y., Chen, Z.-S., Pedrycz, W., Gmez, M., Bustince, H.: Using i-subgroup-based weighted generalized interval t-norms for aggregating basic uncertain information. Fuzzy Sets Syst. 476, 108771 (2024)

    MathSciNet  Google Scholar 

  24. Rodrłguez, R.M., Martinez, L., HerreraLiu, F.: Hesitant fuzzy linguistic term sets for decision making. IEEE Trans. Fuzzy Syst. 20, 109–119 (2011)

    MATH  Google Scholar 

  25. Yager, R.R.: Multicriteria decision making with ordinal/linguistic intuitionistic fuzzy sets for mobile apps. IEEE Trans. Fuzzy Syst. 24, 590–599 (2015)

    MATH  Google Scholar 

  26. Chen, Z., Chin, K.-S., Li, Y., Yang, Y.: Proportional hesitant fuzzy linguistic term set for multiple criteria group decision making. Inf. Sci. 357, 61–87 (2016)

    MathSciNet  MATH  Google Scholar 

  27. Chen, Z.-S., Zhou, J., Zhu, C.-Y., Wang, Z.-J., Xiong, S.-H., Rodríguez, R.M., Martínez, L., Skibniewski, M.J.: Prioritizing real estate enterprises based on credit risk assessment: an integrated multi-criteria group decision support framework. Financ. Innov. 9, 120 (2023)

    MATH  Google Scholar 

  28. Chang, J., Chen, Z., Wang, Z., Jin, L., Pedrycz, W., Martinez, L., Skibniewski, M.J.: Assessing spatial synergy between integrated urban rail transit system and urban form: a buli-based mclsga model with the wisdom of crowds. IEEE Trans. Fuzzy Syst. 31, 434–448 (2022)

    Google Scholar 

  29. Liu, L., Chen, X., Yang, Y., Yang, J., Chen, J.: Prioritization of off-grid hybrid renewable energy systems for residential communities in china considering public participation with basic uncertain linguistic information. Sustainability 15, 8454 (2023)

    MATH  Google Scholar 

  30. Beliakov, G., Sola, H. B., Sánchez, T. C.: A practical guide to averaging functions, Springer, (2016)

  31. Kelman, H.C., Hovland, C.I.: “Reinstatement" of the communicator in delayed measurement of opinion change. J. Abnorm. Soc. Psychol. 48, 327–335 (1953)

    MATH  Google Scholar 

  32. Balmer, J.: Identity based views of the corporation: insights from corporate identity, organisational identity, social identity, visual identity, corporate brand identity and corporate image. Eur. J. Mark. 42, 879–906 (2008)

    MATH  Google Scholar 

  33. Brown, J.O., Broderick, A.J., Lee, N.: Word of mouth communication within online communities: conceptualizing the online social network. J. Interact. Mark. 21, 2–20 (2007)

    MATH  Google Scholar 

  34. Li, Y.-M., Lai, C.-Y., Lin, L.-F.: A diffusion planning mechanism for social marketing. Inf. Manag. 54, 638–650 (2017)

    MATH  Google Scholar 

  35. Hsu, M.H., Chang, C.M., Chu, K.K., Lee, Y.J.: Determinants of repurchase intention in online group-buying: the perspectives of delone & mclean is success model and trust. Comput. Hum. Behav 36, 234–245 (2014)

    MATH  Google Scholar 

  36. Sigurdsson, V., Larsen, N.M., Alemu, M.H., Gallogly, J.K., Menon, R., Woodside, A.G.: Assisting sustainable food consumption: the effects of quality signals stemming from consumers and stores in online and physical grocery retailing. J. Bus. Res. 112, 458–471 (2020)

    Google Scholar 

  37. Kang, J.-W., Namkung, Y.: The information quality and source credibility matter in customers’ evaluation toward food o2o commerce. Int. J. Hosp. Manag. 78, 189–198 (2019)

    MATH  Google Scholar 

  38. Chou, H.Y.: Units of time do matter: How countdown time units affect consumers’ intentions to participate in group-buying offers. Electron. Commer. Res. Appl. 35, 100839 (2019)

    MATH  Google Scholar 

  39. Zhang, C., Tian, Y.-X.: Forecast daily tourist volumes during the epidemic period using covid-19 data, search engine data and weather data. Expert Syst. Appl. 210, 118505 (2022)

    Google Scholar 

  40. Bi, J.-W., Liu, Y., Li, H.: Daily tourism volume forecasting for tourist attractions. Ann. Tour. Res. 83, 102923 (2020)

    MATH  Google Scholar 

  41. Li, W., Yang, G., Li, X.: Correlation between pm2.5 pollution and its public concern in china: evidence from baidu index. J. Clean. Prod. 293, 126091 (2021)

    MATH  Google Scholar 

  42. El Barachi, M., AlKhatib, M., Mathew, S., Oroumchian, F.: A novel sentiment analysis framework for monitoring the evolving public opinion in real-time: case study on climate change. J. Clean. Prod. 312, 127820 (2021)

    Google Scholar 

  43. Zhang, S., Li, Y., Hao, Y., Zhang, Y.: Does public opinion affect air quality? Evidence based on the monthly data of 109 prefecture-level cities in China. Energy Policy 116, 299–311 (2018)

    MATH  Google Scholar 

  44. Dyck, A., Volchkova, N., Zingales, L.: The corporate governance role of the media: evidence from Russia, The. J. Financ. 63, 1093–1135 (2008)

    MATH  Google Scholar 

  45. Park, Y.A., Gretzel, U., Sirakaya-Turk, E.: Measuring web site quality for online travel agencies. J. Travel Tour. Mark. 23, 15–30 (2007)

    Google Scholar 

  46. Hadiyati, E.: Study of marketing mix and aida model to purchasing on line product in Indonesia. Br. J. Mark. Stud. 4, 49–62 (2016)

    Google Scholar 

  47. Xu, X., Schrier, T.: Hierarchical effects of website aesthetics on customers’ intention to book on hospitality sharing economy platforms. Electron. Commer. Res. Appl. 35, 100856 (2019)

    Google Scholar 

  48. Fu, J.-R., Lu, I.-W., Chen, J.H., Farn, C.-K.: Investigating consumers’ online social shopping intention: an information processing perspective. Int. J. Inf. Manag. 54, 102189 (2020)

    Google Scholar 

  49. Yuan, C., Moon, H., Wang, S., Yu, X., Kim, K.H.: Study on the influencing of b2b parasocial relationship on repeat purchase intention in the online purchasing environment: an empirical study of B2B E-commerce platform. Ind. Mark. Manag. 92, 101–110 (2021)

    Google Scholar 

  50. Chiu, C.-M., Wang, E.T., Fang, Y.-H., Huang, H.-Y.: Understanding customers’ repeat purchase intentions in B2C e-commerce: the roles of utilitarian value, hedonic value and perceived risk. Inf. Syst. J. 24, 85–114 (2014)

    Google Scholar 

  51. Lindgaard, G., Fernandes, G., Dudek, C., Brown, J.: Attention web designers: you have 50 milliseconds to make a good first impression! Behav. Inf. Technol. 25, 115–126 (2006)

    Google Scholar 

  52. Tajvidi, M., Wang, Y., Hajli, N., Love, P.: Brand value co-creation in social commerce: The role of interactivity, social support, and relationship quality, Newcastle University (2021)

  53. Leung, E.K.H., Lau, H., Nakandala, D., Kong, X.T., Ho, G.: Standardising fresh produce selection and grading process for improving quality assurance in perishable food supply chains: an integrated fuzzy ahp-topsis framework. Enterp. Inf. Syst. 15, 651–675 (2021)

    Google Scholar 

  54. Liu, Y., Wang, X. J., Chen, Z. S., Zhang, Y., Zhao, S., Devici, M., ... & Skibniewski, M. J.: Evaluating Digital Health Services Quality via Social Media. IEEE Trans. Eng. Manag. 2023. https://doi.org/10.1109/TEM.2023.3298906

    Article  Google Scholar 

  55. Saaty, T.L.: How to make a decision: the analytic hierarchy process. Eur. J. Oper. Res. 48, 9–26 (1990)

    MATH  Google Scholar 

  56. Okwu, M.O., Tartibu, L.K.: Sustainable supplier selection in the retail industry: a topsis-and anfis-based evaluating methodology. Int. J. Eng. Bus. Manag. 12, 1847979019899542 (2020)

    MATH  Google Scholar 

  57. Lin, M., Xu, Z., Zhai, Y., Yao, Z.: Multi-attribute group decision-making under probabilistic uncertain linguistic environment. J. Oper. Res. Soc. 69, 157–170 (2018)

    MATH  Google Scholar 

  58. Wang, L., Zhang, Z., Ishizaka, A., Wang, Y., Martinez, L.: Todimsort: A todim based method for sorting problems. Omega-Int. J. Manag. Sci. 115, 102771 (2023)

    MATH  Google Scholar 

  59. Zhang, Z., Wang, L., Wang, Y., Martinez, L.: A novel alpha-level sets based fuzzy dematel method considering experts hesitant information. Expert Syst. Appl. 213, 118925 (2023)

    Google Scholar 

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Acknowledgements

This work was supported by the National Natural Science Foundation of China under Grants 72201097, 72171182, and 72031009.

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Correspondence to Muhammet Deveci or Zhen-Song Chen.

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Appendices

Appendix A

The following presents the BULI matrix for Step 4.5 within subsection 6.1.

$$\begin{aligned} \begin{array}{l} BULI - UT = \\ \left[ {\begin{array}{*{20}{c}} {\left\langle {{\Delta _S}\left( 2 \right) ,0.8} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 2 \right) ,1} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 3 \right) ,0.8} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 4 \right) ,0.8} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 3 \right) ,0.8} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 3 \right) ,0.8} \right\rangle }\\ {\left\langle {{\Delta _S}\left( 2 \right) ,0.6} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 3 \right) ,0.4} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 3 \right) ,0.4} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 4 \right) ,0.4} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 3 \right) ,0.4} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 2 \right) ,0.4} \right\rangle }\\ {\left\langle {{\Delta _S}\left( 3 \right) ,0.4} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 2 \right) ,0.6} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 4 \right) ,0.6} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 4 \right) ,0.6} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 5 \right) ,0.6} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 2 \right) ,0.4} \right\rangle }\\ {\left\langle {{\Delta _S}\left( 4 \right) ,0.2} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 3 \right) ,0.8} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 3 \right) ,0.2} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 4 \right) ,1} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 3 \right) ,0.6} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 3 \right) ,0.2} \right\rangle }\\ {\left\langle {{\Delta _S}\left( 2 \right) ,0.4} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 3 \right) ,0.2} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 2 \right) ,0.6} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 3 \right) ,0.8} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 3 \right) ,0.4} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 2 \right) ,0.6} \right\rangle }\\ {\left\langle {{\Delta _S}\left( 1 \right) ,0.2} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 4 \right) ,0.4} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 2 \right) ,0.4} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 4 \right) ,0.6} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 4 \right) ,0.2} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 3 \right) ,0.2} \right\rangle }\\ {\left\langle {{\Delta _S}\left( 1 \right) ,0.2} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 3 \right) ,1} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 3 \right) ,0.6} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 4 \right) ,0.6} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 3 \right) ,0.2} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 3 \right) ,0.6} \right\rangle }\\ {\left\langle {{\Delta _S}\left( 2 \right) ,0.2} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 2 \right) ,0.4} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 1 \right) ,0.4} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 3 \right) ,1} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 3 \right) ,0.4} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 3 \right) ,0.4} \right\rangle } \end{array}} \right. \\ \left. {\begin{array}{*{20}{c}} {\left\langle {{\Delta _S}\left( 4 \right) ,0.8} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 4 \right) ,1} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 4 \right) ,0.6} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 2 \right) ,0.8} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 2 \right) ,0.8} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 2 \right) ,0.8} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 2 \right) ,0.8} \right\rangle }\\ {\left\langle {{\Delta _S}\left( 3 \right) ,0.4} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 4 \right) ,0.6} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 3 \right) ,0.2} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 2 \right) ,0.8} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 2 \right) ,0.8} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 2 \right) ,0.4} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 2 \right) ,0.6} \right\rangle }\\ {\left\langle {{\Delta _S}\left( 4 \right) ,0.2} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 3 \right) ,0.6} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 3 \right) ,0.2} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 3 \right) ,0.6} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 3 \right) ,0.6} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 2 \right) ,0.4} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 3 \right) ,0.4} \right\rangle }\\ {\left\langle {{\Delta _S}\left( 4 \right) ,0.2} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 4 \right) ,1} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 4 \right) ,0.4} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 2 \right) ,0.4} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 2 \right) ,0.4} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 2 \right) ,0.4} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 2 \right) ,0.2} \right\rangle }\\ {\left\langle {{\Delta _S}\left( 3 \right) ,0.6} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 3 \right) ,0.8} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 3 \right) ,0.4} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 2 \right) ,0.8} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 2 \right) ,0.8} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 3 \right) ,0.8} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 1 \right) ,0.4} \right\rangle }\\ {\left\langle {{\Delta _S}\left( 3 \right) ,0.4} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 4 \right) ,0.4} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 4 \right) ,0.2} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 3 \right) ,0.2} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 2 \right) ,0.8} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 2 \right) ,1} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 2 \right) ,0.6} \right\rangle }\\ {\left\langle {{\Delta _S}\left( 4 \right) ,1} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 4 \right) ,1} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 3 \right) ,0.6} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 2 \right) ,1} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 1 \right) ,1} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 3 \right) ,0.6} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 1 \right) ,1} \right\rangle }\\ {\left\langle {{\Delta _S}\left( 3 \right) ,0.6} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 3 \right) ,0.6} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 4 \right) ,0.2} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 2 \right) ,0.4} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 1 \right) ,0.2} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 2 \right) ,0.4} \right\rangle }&{}{\left\langle {{\Delta _S}\left( 1 \right) ,0.8} \right\rangle } \end{array}} \right] \end{array} \end{aligned}$$

Appendix B

The following presents the BULI matrices for Step 6.3 within subsection 6.1.

$$\begin{aligned}\begin{aligned}&BULI-{{{\bar{S}}}_{1}}= \\&\left[ \begin{matrix} \left\langle {{\Delta }_{S}}\left( 3.72 \right) ;0.51 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.35 \right) ;0.43 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.79 \right) ;0.55 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.50 \right) ;0.44 \right\rangle \\ \left\langle {{\Delta }_{S}}\left( 3.91 \right) ;0.63 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.64 \right) ;0.49 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.70 \right) ;0.51 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.73 \right) ;0.52 \right\rangle \\ \left\langle {{\Delta }_{S}}\left( 3.72 \right) ;0.51 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.54 \right) ;0.45 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.77 \right) ;0.54 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.56 \right) ;0.46 \right\rangle \\ \left\langle {{\Delta }_{S}}\left( 3.86 \right) ;0.59 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.54 \right) ;0.42 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.72 \right) ;0.51 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.653 \right) ;0.48 \right\rangle \\ \left\langle {{\Delta }_{S}}\left( 3.77 \right) ;0.53 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.42 \right) ;0.41 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.84 \right) ;0.58 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.44 \right) ;0.43 \right\rangle \\ \end{matrix} \right. \\&\left. \begin{matrix} \left\langle {{\Delta }_{S}}\left( 3.54 \right) ;0.46 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.59 \right) ;0.46 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.58 \right) ;0.46 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.65 \right) ;0.49 \right\rangle &{} \left\langle 0;0 \right\rangle \\ \left\langle {{\Delta }_{S}}\left( 3.72 \right) ;0.51 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.70 \right) ;0.51 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.67 \right) ;0.50 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.78 \right) ;0.54 \right\rangle &{} \left\langle 0;0 \right\rangle \\ \left\langle {{\Delta }_{S}}\left( 3.68 \right) ;0.49 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.62 \right) ;0.47 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.58 \right) ;0.46 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.76 \right) ;0.53 \right\rangle &{} \left\langle 0;0 \right\rangle \\ \left\langle {{\Delta }_{S}}\left( 3.66 \right) ;0.48 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.80 \right) ;0.55 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.28 \right) ;0.39 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.73 \right) ;0.51 \right\rangle &{} \left\langle 0;0 \right\rangle \\ \left\langle {{\Delta }_{S}}\left( 3.53 \right) ;0.44 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.59 \right) ;0.45 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.56 \right) ;0.43 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.61 \right) ;0.45 \right\rangle &{} \left\langle 0;0 \right\rangle \\ \end{matrix} \right] \\ \end{aligned}\\\begin{aligned}&BULI-{{{\bar{S}}}_{2}}= \\&\left[ \begin{matrix} \left\langle {{\Delta }_{S}}\left( 3.80 \right) ;0.68 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.06 \right) ;0.63 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.93 \right) ;0.85 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.23 \right) ;0.60 \right\rangle \\ \left\langle {{\Delta }_{S}}\left( 3.92 \right) ;0.84 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.61 \right) ;0.67 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.74 \right) ;0.71 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.78 \right) ;0.74 \right\rangle \\ \left\langle {{\Delta }_{S}}\left( 3.72 \right) ;0.70 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.26 \right) ;0.61 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.84 \right) ;0.77 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.13 \right) ;0.60 \right\rangle \\ \left\langle {{\Delta }_{S}}\left( 3.82 \right) ;0.75 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.16 \right) ;0.60 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.55 \right) ;0.64 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.53 \right) ;0.63 \right\rangle \\ \left\langle {{\Delta }_{S}}\left( 3.71 \right) ;0.69 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.17 \right) ;0.58 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.82 \right) ;0.76 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.16 \right) ;0.60 \right\rangle \\ \end{matrix} \right. \\&\left. \begin{matrix} \left\langle {{\Delta }_{S}}\left( 3.46 \right) ;0.61 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.54 \right) ;0.63 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.46 \right) ;0.60 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.73 \right) ;0.70 \right\rangle &{} \left\langle 0;0 \right\rangle \\ \left\langle {{\Delta }_{S}}\left( 3.57 \right) ;0.66 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.73 \right) ;0.71 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.62 \right) ;0.67 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.85 \right) ;0.78 \right\rangle &{} \left\langle 0;0 \right\rangle \\ \left\langle {{\Delta }_{S}}\left( 3.21 \right) ;0.61 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.24 \right) ;0.60 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.15 \right) ;0.58 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.52 \right) ;0.61 \right\rangle &{} \left\langle 0;0 \right\rangle \\ \left\langle {{\Delta }_{S}}\left( 3.60 \right) ;0.65 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.73 \right) ;0.70 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.84 \right) ;0.54 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.56 \right) ;0.63 \right\rangle &{} \left\langle 0;0 \right\rangle \\ \left\langle {{\Delta }_{S}}\left( 3.38 \right) ;0.60 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.46 \right) ;0.61 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.55 \right) ;0.61 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.40 \right) ;0.58 \right\rangle &{} \left\langle 0;0 \right\rangle \\ \end{matrix} \right] \\ \end{aligned}\\\begin{aligned}&BULI-{{{\bar{S}}}_{3}}= \\&\left[ \begin{matrix} \left\langle {{\Delta }_{S}}\left( 3.83 \right) ;0.57 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.13 \right) ;0.41 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.86 \right) ;0.59 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.28 \right) ;0.43 \right\rangle \\ \left\langle {{\Delta }_{S}}\left( 3.91 \right) ;0.64 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.66 \right) ;0.49 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.75 \right) ;0.53 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.77 \right) ;0.57 \right\rangle \\ \left\langle {{\Delta }_{S}}\left( 3.69 \right) ;0.48 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.28 \right) ;0.36 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.76 \right) ;0.52 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.27 \right) ;0.37 \right\rangle \\ \left\langle {{\Delta }_{S}}\left( 3.86 \right) ;0.60 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.28 \right) ;0.43 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.75 \right) ;0.52 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.63 \right) ;0.47 \right\rangle \\ \left\langle {{\Delta }_{S}}\left( 3.60 \right) ;0.46 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.30 \right) ;0.40 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.80 \right) ;0.55 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.20 \right) ;0.42 \right\rangle \\ \end{matrix} \right. \\&\text { }\left. \begin{matrix} \left\langle {{\Delta }_{S}}\left( 3.38 \right) ;0.41 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.57 \right) ;0.45 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.43 \right) ;0.42 \right\rangle &{} \left\langle 0;0 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.64 \right) ;0.46 \right\rangle \\ \left\langle {{\Delta }_{S}}\left( 3.58 \right) ;0.47 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.67 \right) ;0.50 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.62 \right) ;0.47 \right\rangle &{} \left\langle 0;0 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.85 \right) ;0.59 \right\rangle \\ \left\langle {{\Delta }_{S}}\left( 3.47 \right) ;0.40 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.33 \right) ;0.39 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.25 \right) ;0.37 \right\rangle &{} \left\langle 0;0 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.49 \right) ;0.41 \right\rangle \\ \left\langle {{\Delta }_{S}}\left( 3.65 \right) ;0.48 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.72 \right) ;0.51 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.37 \right) ;0.41 \right\rangle &{} \left\langle 0;0 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.71 \right) ;0.49 \right\rangle \\ \left\langle {{\Delta }_{S}}\left( 3.30 \right) ;0.41 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.49 \right) ;0.43 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.50 \right) ;0.42 \right\rangle &{} \left\langle 0;0 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.43 \right) ;0.41 \right\rangle \\ \end{matrix} \right] \\ \end{aligned}\\\begin{aligned}&BULI-{{{\bar{S}}}_{4}}= \\&\left[ \begin{matrix} \left\langle {{\Delta }_{S}}\left( 3.00 \right) ;0.69 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.58 \right) ;0.71 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.30 \right) ;0.67 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.77 \right) ;0.71 \right\rangle \\ \left\langle {{\Delta }_{S}}\left( 3.73 \right) ;0.73 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.33 \right) ;0.69 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.30 \right) ;0.68 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.30 \right) ;0.64 \right\rangle \\ \left\langle {{\Delta }_{S}}\left( 3.10 \right) ;0.66 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.98 \right) ;0.71 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.19 \right) ;0.67 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.97 \right) ;0.78 \right\rangle \\ \left\langle {{\Delta }_{S}}\left( 3.48 \right) ;0.68 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.98 \right) ;0.63 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.24 \right) ;0.62 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.95 \right) ;0.70 \right\rangle \\ \left\langle {{\Delta }_{S}}\left( 3.57 \right) ;0.67 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.63 \right) ;0.61 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.57 \right) ;0.68 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.96 \right) ;0.66 \right\rangle \\ \end{matrix} \right. \\&\text { }\left. \begin{matrix} \left\langle {{\Delta }_{S}}\left( 3.90 \right) ;0.72 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.87 \right) ;0.70 \right\rangle &{} \left\langle 0;0 \right\rangle &{} \left\langle 0;0 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.82 \right) ;0.68 \right\rangle \\ \left\langle {{\Delta }_{S}}\left( 3.10 \right) ;0.69 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.20 \right) ;0.65 \right\rangle &{} \left\langle 0;0 \right\rangle &{} \left\langle 0;0 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.33 \right) ;0.68 \right\rangle \\ \left\langle {{\Delta }_{S}}\left( 3.98 \right) ;0.68 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.78 \right) ;0.69 \right\rangle &{} \left\langle 0;0 \right\rangle &{} \left\langle 0;0 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.11 \right) ;0.68 \right\rangle \\ \left\langle {{\Delta }_{S}}\left( 3.94 \right) ;0.69 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.01 \right) ;0.68 \right\rangle &{} \left\langle 0;0 \right\rangle &{} \left\langle 0;0 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.03 \right) ;0.66 \right\rangle \\ \left\langle {{\Delta }_{S}}\left( 3.08 \right) ;0.66 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.07 \right) ;0.66 \right\rangle &{} \left\langle 0;0 \right\rangle &{} \left\langle 0;0 \right\rangle &{} \left\langle {{\Delta }_{S}}\left( 3.53 \right) ;0.61 \right\rangle \\ \end{matrix} \right] \\ \end{aligned}\end{aligned}$$

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Yang, Y., Xia, DX., Pedrycz, W. et al. Cross-Platform Distributed Product Online Ratings Aggregation Approach for Decision Making with Basic Uncertain Linguistic Information. Int. J. Fuzzy Syst. 26, 1936–1957 (2024). https://doi.org/10.1007/s40815-023-01646-3

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