Ranking Luxury Hotels in Lisbon Using the 2T-AEC-TOPSIS Model

  1. Shu, Ziwei 1
  2. Carrasco, Ramón Alberto 1
  1. 1 Universidad Complutense de Madrid
    info

    Universidad Complutense de Madrid

    Madrid, España

    ROR 02p0gd045

Libro:
Marketing and Smart Technologies

ISSN: 2190-3018,  2190-3026

ISBN: 9789819715510,  9789819715527

Año de publicación: 2024

Páginas: 669-686

Tipo: Capítulo de Libro

DOI: 10.1007/978-981-97-1552-7_45 GOOGLE SCHOLAR lock_openAcceso abierto editor

Resumen

Hotel rankings help customers choose accommodations quickly and assist hotel managers in improving their performance by comparing them to competitors. However, most ranking models use equal weighting for various hotel aspect performances. From a business perspective, improving weight determination to reflect better the varying importance of multiple aspects in hotel rankings and enhancing ranking results interpretation is necessary. Therefore, this paper introduces the 2T-AEC-TOPSIS model for hotel ranking, incorporating five fundamental concepts: the 2-tuple linguistic model, Analytic Hierarchy Process (AHP) method, Entropy method, CRiteria Importance Through Intercriteria Correlation (CRITIC) method, and Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) method. The 2-tuple linguistic model aggregates linguistic ratings for each hotel aspect, avoiding information loss in linguistic fusion. The AHP, Entropy, and CRITIC methods generate weights for each hotel aspect that are combined to form integrated weights that blend the benefits of objective and subjective weighting approaches. These integrated weights are employed to execute the necessary steps in the TOPSIS method to rank hotels. The functionality of the proposed model has been evaluated with a dataset of over 26,000 customer reviews gathered from TripAdvisor for luxury hotels in Lisbon. The results show that the proposed model achieves a relatively balanced and realistic weight distribution in the weight assignment within the TOPSIS method, and produces a top 10 list of luxury hotels in Lisbon for different scenarios. It provides hotel managers and customers with more interpretable ranking results for making more informed and faster decisions.

Referencias bibliográficas

  • Hwang, C.-L., Yoon, K.: Multiple Attribute Decision Making: Methods and Applications: A State-of-the-Art Survey. Springer, Heidelberg (1981)
  • Kalbar, P.P., Karmakar, S., Asolekar, S.R.: Selection of an appropriate wastewater treatment technology: a scenario-based multiple-attribute decision-making approach. J. Environ. Manage. 113, 158–169 (2012)
  • Balioti, V., Tzimopoulos, C., Evangelides, C.: Multi-criteria decision making using TOPSIS method under fuzzy environment. Application in spillway selection. Proceedings 2, 637 (2018)
  • Li, X.: TOPSIS model with entropy weight for eco geological environmental carrying capacity assessment. Microprocess. Microsyst. 82, 103805 (2021)
  • Zhao, D.-Y., Ma, Y.-Y., Lin, H.-L.: Using the entropy and TOPSIS models to evaluate sustainable development of islands: a case in China. Sustainability 14(6), 3707 (2022)
  • Rostamzadeh, R., Ghorabaee, M.K., Govindan, K., Esmaeili, A., Nobar, H.B.K.: Evaluation of sustainable supply chain risk management using an integrated fuzzy TOPSIS-CRITIC approach. J. Clean. Prod. 175, 651–669 (2018)
  • Abdel-Basset, M., Mohamed, R.: A novel plithogenic TOPSIS-CRITIC model for sustainable supply chain risk management. J. Clean. Prod. 247, 119586 (2020)
  • Sharma, M., Joshi, S.: Brand sustainability among young consumers: an AHP-TOPSIS approach. Young Consum. 20(4), 314–337 (2019)
  • Ma, P., Yao, N., Yang, X.: Service quality evaluation of terminal express delivery based on an integrated SERVQUAL-AHP-TOPSIS approach. Math. Probl. Eng. 2021, e8883370 (2021)
  • Tao, Z., Si Jun, B., Xi Bai, R.: Research on marketing management system based on independent ERP and business BI using fuzzy TOPSIS. J. Intell. Fuzzy Syst. 40(4), 8247–8255 (2021)
  • Kwok, P.K., Lau, H.Y.K.: Hotel selection using a modified TOPSIS-based decision support algorithm. Decis. Support Syst. 120, 95–105 (2019)
  • Nilashi, M., Mardani, A., Liao, H., Ahmadi, H., Manaf, A.A., Almukadi, W.: A hybrid method with TOPSIS and machine learning techniques for sustainable development of green hotels considering online reviews. Sustainability 11(21), 6013 (2019)
  • Forouzandeh, S., Berahmand, K., Nasiri, E., Rostami, M.: A hotel recommender system for tourists using the artificial bee colony algorithm and fuzzy TOPSIS model: a case study of TripAdvisor. Int. J. Inf. Technol. Decis. Mak. 20(01), 399–429 (2021)
  • Abdullah, M.A., Aldisa, R.T.: Perbandingan Metode Preference Selection Index dan Kombinasi Preference Selection Index dan TOPSIS dalam Penilaian Kinerja Karyawan Hotel. KLIK Kajian Ilmiah Inf. Komput. 3(6), 1080–1087 (2023)
  • Shannon, C.E.: A mathematical theory of communication. Bell Syst. Tech. J. 27(3), 379–423 (1948)
  • Chen, P.: Effects of the entropy weight on TOPSIS. Expert Syst. Appl. 168, 114186 (2021)
  • Saaty, T.L.: The Analytic Hierarchy Process: Planning, Priority Setting, Resource Allocation. McGraw-Hill International Book Company (1980)
  • Opricovic, S.: Multicriteria optimization of civil engineering systems. Fac. Civ. Eng. Belg. 2(1), 5–21 (1998)
  • Baccour, L.: Amended fused TOPSIS-VIKOR for classification (ATOVIC) applied to some UCI data sets. Expert Syst. Appl. 99, 115–125 (2018)
  • Diakoulaki, D., Mavrotas, G., Papayannakis, L.: Determining objective weights in multiple criteria problems: the critic method. Comput. Oper. Res. 22(7), 763–770 (1995)
  • Herrera, F., Martínez, L.: A 2-tuple fuzzy linguistic representation model for computing with words. IEEE Trans. Fuzzy Syst. 8(6), 746–752 (2000)
  • Martínez, L., Herrera, F.: An overview on the 2-tuple linguistic model for computing with words in decision making: extensions, applications and challenges. Inf. Sci. 207, 1–18 (2012)
  • Li, M.-Y., Fan, Z.-P., Liu, Y.-Z., Cao, P.-P.: Representing and aggregating linguistic information based on semantic three-tuple. Comput. Ind. Eng. 132, 114–123 (2019)
  • Uztürk, D., Büyüközkan, G.: 2-tuple linguistic model-based circular maturity assessment methodology: a case for agriculture. IFAC-PapersOnLine 55(10), 2036–2041 (2022)
  • Shu, Z., Carrasco González, R.A., García-Miguel, J.P., Sánchez-Montañés, M.: Hotel customer segmentation using the integrated entropy-CRITIC method and the 2T-RFMB model. In: Reis, J.L., Peter, M.K., Varela González, J.A., Bogdanović, Z. (eds.) Proceedings of ICMarkTech 2022, Marketing and Smart Technologies, vol. 2, pp. 55–72. Springer Nature, Singapore (2023)
  • Carrasco, R.A., Blasco, M.F., Herrera-Viedma, E.: A 2-tuple fuzzy linguistic RFM model and its implementation. Procedia Comput. Sci. 55, 1340–1347 (2015)
  • Geng, X., Qiu, H., Gong, X.: An extended 2-tuple linguistic DEA for solving MAGDM problems considering the influence relationships among attributes. Comput. Ind. Eng. 112, 135–146 (2017)
  • Carrasco, R.A., Sánchez-Fernández, J., Muñoz-Leiva, F., Francisca Blasco, M., Herrera-Viedma, E.: Evaluation of the hotels e-services quality under the user’s experience. Soft. Comput. 21(4), 995–1011 (2017)
  • Wu, Q., Wu, P., Zhou, L., Chen, H., Guan, X.: Some new Hamacher aggregation operators under single-valued neutrosophic 2-tuple linguistic environment and their applications to multi-attribute group decision making. Comput. Ind. Eng. 116, 144–162 (2018)
  • Herrera-Viedma, E., Carrasco, R.A., Blasco, M.F., García-Madariaga, J.: A fuzzy linguistic RFM model applied to campaign management. Int. J. Interact. Multimed. Artif. Intell. 5(4), 21–27 (2019)
  • Labella, Á., Dutta, B., Martínez, L.: An optimal best-worst prioritization method under a 2-tuple linguistic environment in decision making. Comput. Ind. Eng. 155, 107141 (2021)
  • Llorens, M., Carrasco, R., Bueno, I., Herrera-Viedma, E., Morente-Molinera, J.A.: Multiple criteria approach applied to digital transformation in fashion stores: the case of physical retailers in Spain. Technol. Econ. Dev. Econ. 28(2), 500–530 (2022)
  • Li, C., Yu, X.: Consensus reaching model for counter-intuitive in D-S evidence theory and application under 2-tuple linguistic representation. Eng. Appl. Artif. Intell. 112, 104832 (2022)
  • Shu, Z., Carrasco, R.A., García-Miguel, J.P., Sánchez-Montañés, M.: Multiple scenarios of quality of life index using fuzzy linguistic quantifiers: the case of 85 countries in numbeo. Mathematics 10(12), 2091 (2022)
  • Marín Díaz, G., Carrasco González, R.A.: Fuzzy logic and decision making applied to customer service optimization. Axioms 12(5), 448 (2023)
  • Herrera-Viedma, E., Herrera, F., Martı́nez, L., Herrera, J.C., López, A.G.: Incorporating filtering techniques in a fuzzy linguistic multi-agent model for information gathering on the web. Fuzzy Sets Syst. 148(1), 61–83 (2004)
  • Zafar, S., Alamgir, Z., Rehman, M.H.: An effective blockchain evaluation system based on entropy-CRITIC weight method and MCDM techniques. Peer-to-Peer Netw. Appl. 14(5), 3110–3123 (2021)
  • Saaty, T.L.: What Is the Analytic Hierarchy Process? Springer, Berlin Heidelberg (1988)
  • Saaty, T.L., Vargas, L.G.: Models, Methods, Concepts & Applications of the Analytic Hierarchy Process. Springer, US (2012)
  • Mustapha, M.T., Uzun, B., Ozsahin, D.U., Ozsahin, I.: A comparative study of X-ray based medical imaging devices. In: Ozsahin, I., Ozsahin, D.U., Uzun, B. (eds.) Applications of Multi-Criteria Decision-Making Theories in Healthcare and Biomedical Engineering, pp. 163–180. Academic Press (2021)