The tourism industry is the business card of a city and an important source of financial revenue. As tourism is becoming increasingly popular, tourism satisfaction has become a key indicator for Yangzhou tourism. As an important business model, e-commerce has developed into a branch of mobile e-commerce. Mobile e-commerce can be combined with the tourism industry to provide services such as information access and city tours for tourism at the city level. The tourism mobile e-commerce service quality evaluation is multiple-attribute group decision-making (MAGDM). In recent times, Exponential TODIM (ExpTODIM) and VIKOR methods were employed to tackle the challenges of MAGDM. To handle uncertain data during the evaluation of tourism mobile e-commerce service quality, Probabilistic Linguistic Term Sets (PLTSs) have been adopted as a valuable tool. This paper presents the Probabilistic Linguistic ExpTODIM-VIKOR (PL-ExpTODIM-VIKOR) method as solution for MAGDM under PLTSs. Additionally, numerical case study is included to validate the proposed method within the context of evaluating the quality of tourism mobile e-commerce services. The primary contributions of this study can be summarized: (1) extension of ExpTODIM technique, based on VIKOR to PLTSs; (2) utilization of information entropy to derive weights based on expected values and deviation degree under PLTSs; (3) introduction of the PL-ExpTODIM-VIKOR technique to effectively manage MAGDM under PLTSs; and (4) execution of numerical study and comparative analysis to verify the effectiveness of PL-ExpTODIM-VIKOR in evaluating the quality of tourism mobile e-commerce services.
KamelSEl SherifA, eds. The role of small and medium-sized enterprises in developing Egypt's tourism industry using e-commerce. In: Portland International Conference on Management of Engineering and Technology (PICMET 01), 29 Jul-02 Aug 2001, Portland, OR. New York: IEEE, 2001.
2.
LiYXYangLMYangP, eds. The development of e-commerce and tourism's global distribution system (GDS). In: 3rd International Conference on Electronic Commerce Engineering; 2003 Oct 24–27; Zhejiang Univ, Hangzhou, Peoples R China. Hong Kong: International Academic Publishers Ltd, 2003.
3.
PalkoskaJPuhretmairFWagnerRR,et al.Strategies for e-commerce applications in tourism. In: BauknechtKTjoaAMQuirchmayrG (eds) E-commerce and web technologies, proceedings. Lecture notes in computer science. 2738. Berlin: Springer-Verlag Berlin, 2003, pp.303–314.
4.
YanZXYuanJChengCXChaiHYLiJM, eds. Strategic research on developing tourism e-commerce in the Yangtze's cruise industry. In: 3rd Wuhan International Conference on E-Business - Global Business Interface, Jun 04–07 2004, Wuhan, Peoples R China. Alfred: Alfred Univ, 2004.
5.
LiuSQ, ed. The thought of tourism e-commerce. In: 4th Wuhan International Conference on E-Business - Global Business Interface, 04–05 Jun 2005, Wuhan, Peoples R China. Alfred: Alfred Univ, 2005.
6.
LiuSQ, ed. A theoretic discussion of tourism e-commerce. In: 7th International Conference on Electronic Commerce (ICEC 2005), 15–17 Aug 2005, Xian, Peoples R China. New York: Assoc Computing Machinery, 2005.
7.
ChenZGYangQ, eds. Study of china's tourism e-commerce. In: 5th Wuhan International Conference on E-Business, 27–28 May 2006, Wuhan, Peoples R China. Alfred: Alfred Univ, 2006.
8.
LiuKMaXYLiZPGaoXY, Acm, eds. Research on rural economic development based on e-commerce and tourism informatization. In: 4th International Conference on Management Engineering, Software Engineering and Service Sciences (ICMSS), 17–19 Jan 2020, Wuhan, Peoples R China. New York: Assoc Computing Machinery, 2020.
9.
XuJH. A study on the development of the tourism e-commerce platform in small and medium-sized cities based on swot analysis - a case study of ma'anshan city. Int J Electr Eng Educ2020; 18.
10.
DariesNCristobal-FransiEFerrer-RosellB. Implementation of website marketing strategies in sports tourism: Analysis of the online presence and e-commerce of golf courses. J Theor Appl Electron Commerce Res2021; 16: 542–561.
11.
PanHLZhangZJ. Research on context-awareness mobile tourism e-commerce personalized recommendation model. J Signal Process Syst Signal Image Video Technol2021; 93: 147–154.
12.
TangGHZengH. Evaluation of tourism e-commerce user satisfaction. J Organ End User Comput2021; 33: 25–41.
13.
WeiCWangQALiuCY. Application of an artificial neural network optimization model in e-commerce platform based on tourism management. EURASIP J Wireless Commun Networking2021; 2021: 21.
14.
ZhangHQGuoTTSuXB. Application of big data technology in the impact of tourism e-commerce on tourism planning. Complexity2021; 2021: 10.
15.
ZhaoMLZhouJMuJ. Swot research on the development of rural tourism e-commerce system under the background of big data era. Mobile Inf Syst2021; 2021: 13.
16.
LiK. Swot analysis of e-commerce development of rural tourism farmers’ professional cooperatives in the era of big data. IET Commun2022; 16: 592–603.
17.
LinHCLiuXHuangY,et al.Determinants of continued use of tourism and hospitality e-commerce platforms and the role of information transparency. Curr Issues Tourism2022; 20.
18.
LiuXLZhangLChenQ. The effects of tourism e-commerce live streaming features on consumer purchase intention: The mediating roles of flow experience and trust. Front Psychol2022; 13: 14.
19.
PengX. Single-valued neutrosophic linguistic reducible weighted msm for tourism mobile e-commerce service quality evaluation. Sci Iran2022; 29: 247–264.
20.
XieCWYuJHuangSS,et al.Tourism e-commerce live streaming: Identifying and testing a value-based marketing framework from the live streamer perspective. Tourism Manage2022; 91: 13.
21.
YangWHLinYG. Research on the interactive operations research model of e-commerce tourism resources business based on big data and circular economy concept. J Enterp Inf Manage2022; 35: 1348–1373.
22.
YinXYHeJN. Construction of tourism e-commerce platform based on artificial intelligence algorithm. Comput Intell Neurosci2022; 2022: 12.
23.
YuJXieCWHuangS,et al.Configuring the value-versus-attachment combinations in determining consumer purchase intention in tourism e-commerce live streaming: A fsqca approach. Curr Issues Tourism2022; 17.
24.
ZhaoJCZhangPL. Investigating the role of e-commerce marketing capabilities to achieve the strategic performance of tourism firms. Front Psychol2023; 14.
25.
FaiziSSalabunWUllahS, et al.A new method to support decision-making in an uncertain environment based on normalized interval-valued triangular fuzzy numbers and comet technique. Symmetry Basel2020; 12: 16.
26.
ShekhovtsovAWieckowskiJWatrobskiJ, eds. Toward reliability in the mcda rankings: Comparison of distance-based methods. In: 13th International KES Conference on Intelligent Decision Technologies (KES-IDT), 14–16 Jun 2021, Electr Network. Cham: Springer International Publishing Ag, 2021.
27.
DeviPKizielewiczBGuleriaA, et al.Decision support in selecting a reliable strategy for sustainable urban transport based on laplacian energy of t-spherical fuzzy graphs. Energies2022; 15: 20.
28.
KizielewiczBWieckowskiJParadowskiBSalabunW, eds. Dealing with nonmonotonic criteria in decision-making problems using fuzzy normalization. In: 4th International Conference on Intelligent and Fuzzy Systems (INFUS), 19–21 Jul 2022, Bornova, TURKEY. Cham: Springer International Publishing Ag, 2022.
29.
WieckowskiJKizielewiczBSalabunW. Pyfdm: A python library for uncertainty decision analysis methods. Softwarex2022; 20: 6.
WieckowskiJKizielewiczBShekhovtsovA,et al.Rancom: A novel approach to identifying criteria relevance based on inaccuracy expert judgments. Eng Appl Artif Intell2023; 122: 21.
32.
WieckowskiJWatrobskiJKizielewiczB,et al.Complex sensitivity analysis in multi-criteria decision analysis: An application to the selection of an electric car. J Cleaner Prod2023; 390: 15.
33.
LiuYChangWJJiaXF. A group consensus model for multiple attributes group decision making with interval belief distribution and interval distributed preference relation. Group Decis Negotiation2023; 32: 701–727.
34.
NguyenTMHNguyenVPNguyenDT. Selecting cloud database services provider through multi-attribute group decision making: A probabilistic uncertainty linguistics todim model. Appl Math Sci Eng2023; 31: 26.
35.
RaniDGargH. Multiple attributes group decision-making based on trigonometric operators, particle swarm optimization and complex intuitionistic fuzzy values. Artif Intell Rev2023; 56: 1787–1831.
36.
WangHLMahmoodTUllahK. Improved cocoso method based on frank softmax aggregation operators for t-spherical fuzzy multiple attribute group decision-making. Int J Fuzzy Syst2023; 25: 1275–1310.
37.
WangJCaiQWangHJ, et al.An integrated decision-making methodology for green supplier selection based on the improved ivif-cpt-mabac method. J Intell Fuzzy Syst2023; 44: 8535–8560.
38.
GuptaSKumarSBangareSL, et al.Homogeneous decision community extraction based on end-user mental behavior on social media. Comput Intell Neurosci2022; 2022: 9.
39.
GurmaniSHChenHYBaiYH. An extended mabac method for multiple-attribute group decision making under probabilistic t-spherical hesitant fuzzy environment. Kybernetes2022; 20.
40.
KhanQBantanRARElgarhyM. Applications of hesitant interval neutrosophic linguistic schweizer-sklar power aggregation operators to madm. J Funct Spaces2022; 2022: 30.
41.
KhanQGargHKhattakH, et al.A novel magdm approach based on cubic q-rung orthopair fuzzy power generalized maclaurin symmetric mean operator. J Funct Spaces2022; 2022: 33.
42.
KumarKChenSM. Multiple attribute group decision making based on advanced linguistic intuitionistic fuzzy weighted averaging aggregation operator of linguistic intuitionistic fuzzy numbers. Inf Sci2022; 587: 813–824.
43.
HerreraFMartinezL. A 2-tuple fuzzy linguistic representation model for computing with words. IEEE Trans Fuzzy Syst2000; 8: 746–752.
44.
HerreraFMartinezL. An approach for combining linguistic and numerical information based on the 2-tuple fuzzy linguistic representation model in decision-making. Int J Uncertainty Fuzziness Knowledge-Based Syst2000; 8: 539–562.
45.
HerreraFMartinezL. The 2-tuple linguistic computational model. Advantages of its linguistic description, accuracy and consistency. Int J Uncertainty Fuzziness Knowledge-Based Syst2001; 9: 33–48.
46.
BegIJamilRNRashidT. Diminishing choquet hesitant 2-tuple linguistic aggregation operator for multiple attributes group decision making. Int J Anal Appl2019; 17: 76–104.
47.
RashidTFaiziSZafarS. Outranking method for intuitionistic 2-tuple fuzzy linguistic information model in group decision making. Soft Comput2019; 23: 6145–6155.
48.
SohaibONaderpourMHussainW,et al.Cloud computing model selection for e-commerce enterprises using a new 2-tuple fuzzy linguistic decision-making method. Comput Ind Eng2019; 132: 47–58.
49.
YangMSAliZMahmoodT. Three-way decisions based on q-rung orthopair fuzzy 2-tuple linguistic sets with generalized maclaurin symmetric mean operators. Mathematics2021; 9: 20.
50.
ZhaoMWWeiGWWuJ, et al.Todim method for multiple attribute group decision making based on cumulative prospect theory with 2-tuple linguistic neutrosophic sets. Int J Intell Syst2021; 36: 1199–1222.
51.
AkramMNoreenUAl-ShamiriMMA,et al.Integrated decision-making methods based on 2-tuple linguistic m-polar fuzzy information. AIMS Math2022; 7: 14557–14594.
52.
NazSAkramMAl-ShamiriMMA, et al.A new magdm method with 2-tuple linguistic bipolar fuzzy heronian mean operators. Math Biosci Eng2022; 19: 3843–3878.
53.
SajjadMSalabunWFaiziS, et al.Statistical and analytical approach of multi-criteria group decision-making based on the correlation coefficient under intuitionistic 2-tuple fuzzy linguistic environment. Expert Syst Appl2022; 193: 11.
54.
EdalatpanahSASmarandacheFGargH. Guest editorial: Preface to the special issue on the neutrosophical approach: Applications in management decision and organizational research methods. Manage Decis2023; 61: 357–362.
55.
GaraiTGargHBiswasG. Possibilistic index-based multi-criteria decision-making with an unknown weight of air pollution model under bipolar fuzzy environment. Soft Comput2023; 19.
56.
GargHUllahKAliK, et al.Multi-attribute decision-making based on sine trigonometric aggregation operators for t-spherical fuzzy information. Soft Comput2023; 15.
57.
HussainAWangHLUllahK, et al.Maclaurin symmetric mean aggregation operators based on novel frank t-norm and t-conorm for intuitionistic fuzzy multiple attribute group decision-making. Alexandria Eng J2023; 71: 535–550.
58.
SirbiladzeGGargHKhutsishviliI, et al.Associated probabilities aggregations in multistage investment decision-making. Kybernetes2023; 52: 1370–1399.
59.
LeonetiABGomesAMFL. A novel version of the todim method based on the exponential model of prospect theory: The exptodim method. Eur J Oper Res2021; 295: 1042–1055.
60.
SunHYangZCaiQ, et al.An extended exp-todim method for multiple attribute decision making based on the z-wasserstein distance. Expert Syst Appl2023; 214: 14.
61.
OpricovicSTzengGH. Compromise solution by mcdm methods: A comparative analysis of vikor and topsis. Eur J Oper Res2004; 156: 445–455.
62.
OpricovicSTzengGH. Extended vikor method in comparison with outranking methods. Eur J Oper Res2007; 178: 514–529.
63.
LinMWXuZSZhaiYL,et al.Multi-attribute group decision-making under probabilistic uncertain linguistic environment. J Oper Res Soc2018; 69: 157–170.
64.
PangQWangHXuZS. Probabilistic linguistic linguistic term sets in multi-attribute group decision making. Inf Sci2016; 369: 128–143.
65.
ZhaiYLXuZSLiaoHC. Probabilistic linguistic vector-term set and its application in group decision making with multi-granular linguistic information. Appl Soft Comput2016; 49: 801–816.
66.
ZhangYXXuZSWangH,et al.Consistency-based risk assessment with probabilistic linguistic preference relation. Appl Soft Comput2016; 49: 817–833.
67.
ShannonCE. A mathematical theory of communication. Bell Syst Tech J1948; 27: 379–423.
68.
LinMXuZ. Probabilistic linguistic distance measures and their applications in multi-criteria group decision making, pp.411–440, 2018.
69.
TverskyAKahnemanD. Prospect theory: An analysis of decision under risk. Econometrica1979; 47: 263–291.
70.
LeonetiABGomesL. A novel version of the todim method based on the exponential model of prospect theory: The exptodim method. Eur J Oper Res2021; 295: 1042–1055.
71.
ShenFYangZYCaiDL. Integrating an extended outranking-topsis method with probabilistic linguistic term sets for multiattribute group decision-making. Complexity2021; 2021: 19.
72.
ChenLXGouXL. The application of probabilistic linguistic codas method based on new score function in multi-criteria decision-making. Comput Appl Math2022; 41: 25.
73.
LiuSYZhouYWangX. Wdba method for probabilistic linguistic magdm with entropy weight and application to consumer competitiveness evaluation in creative and cultural industries. J Intell Fuzzy Syst2023; 44: 3399–3409.
74.
WuXLLiaoHCXuZS, et al.Probabilistic linguistic multimoora: A multicriteria decision making method based on the probabilistic linguistic expectation function and the improved borda rule. IEEE Trans Fuzzy Syst2018; 26: 3688–3702.
75.
WeiGWWeiCGuoYF. Edas method for probabilistic linguistic multiple attribute group decision making and their application to green supplier selection. Soft Comput2021; 25: 9045–9053.
76.
SalabunWUrbaniakK, eds. A new coefficient of rankings similarity in decision-making problems. In: 20th Annual International Conference on Computational Science (ICCS); 03–05 Jun 2020, Amsterdam, Netherlands. Cham: Springer International Publishing Ag, 2020.
77.
SałabunWWątróbskiJShekhovtsovA. Are mcda methods benchmarkable? A comparative study of topsis, vikor, copras, and promethee ii methods. Symmetry2020; 12: 1549.
78.
WięckowskiJKizielewiczBShekhovtsovA,et al.Rancom: A novel approach to identifying criteria relevance based on inaccuracy expert judgments. Eng Appl Artif Intell2023; 122: 106114.
SalabunWKarczmarczykA, eds. Using the comet method in the sustainable city transport problem: An empirical study of the electric powered cars. In: 22nd International Conference on Knowledge-Based and Intelligent Information and Engineering Systems (KES), 03–05 Sep 2018, Belgrade, Serbia. Amsterdam: Elsevier Science Bv, 2018.
81.
SalabunWKarczmarczykAWatrobskiJ, eds. Decision-making using the hesitant fuzzy sets comet method: An empirical study of the electric city buses selection. In: 8th IEEE Symposium Series on Computational Intelligence (IEEE SSCI); 2018 Nov 18–21, Bengaluru, India. New York: IEEE, 2018.
82.
WatrobskiJBaczkiewiczAKrolR,et al.Green electricity generation assessment using the codas-comet method. Ecol Indic2022; 143: 32.
83.
HadianSTabarestaniESPhamQB. Multi attributive ideal-real comparative analysis (mairca) method for evaluating flood susceptibility in a temperate mediterranean climate. Hydrol Sci J2022; 67: 401–418.
84.
NguyenHQNguyenVTPhanDP, et al.Multi-criteria decision making in the pmedm process by using marcos, topsis, and mairca methods. Appl Sci Basel2022; 12: 11.
85.
ChenTYChangCHLuJFR. The extended qualiflex method for multiple criteria decision analysis based on interval type-2 fuzzy sets and applications to medical decision making. Eur J Oper Res2013; 226: 615–625.
86.
ChenTY. Interval-valued intuitionistic fuzzy qualiflex method with a likelihood-based comparison approach for multiple criteria decision analysis. Inf Sci2014; 261: 149–169.
