As a constituent element of tourism system, tourist attraction is the spatial carrier of tourism activity. Those tourist attractions that can provide the high-quality service for the tourists will obtain the satisfactory tourists, drum for more tourists and achieve the good performance. Therefore service quality is the crucial factor to build the market image, acquire the steady tourist flow and increase the profit. It is the life-line of tourist attractions. The crux of service quality management in tourist attractions is how to evaluate and proceed to improve the service quality of tourist attractions. In this paper, we utilize Einstein operations to develop some triangular fuzzy aggregation operators: triangular fuzzy Einstein weighted average (TFEWA) operator, triangular fuzzy Einstein ordered weighted average (TFEOWA) operator and triangular fuzzy Einstein hybrid average (TFEHA) operator. Then, we have utilized these operators to develop some approaches to solve the triangular fuzzy comprehensive evaluation problems for fuzzy quantitative evaluation on tourist scenic spot service quality in the perspective of Wechat marketing. Finally, a practical example for fuzzy quantitative evaluation on tourist scenic spot service quality in the perspective of Wechat marketing is given to verify the developed approach.
ChenT.Y., The inclusion-based TOPSIS method with interval-valued intuitionistic fuzzy sets for multiple criteria group decision making, Appl Soft Comput26 (2015), 57–73.
2.
LiD.F., Mathematical-programming approach to matrix games with payoffs represented by Atanassov’s interval-valued intuitionistic fuzzy sets, IEEE Transactions on Fuzzy Systems18 (2010), 1112–1128.
3.
LiD.F., Closeness coefficient based nonlinear programming method for interval-valued intuitionistic fuzzy multiattribute decision making with incomplete preference information, Applied Soft Computing11 (2011), 3402–3418.
4.
WeiG.W.WangJ.M. and ChenJ., Potential optimality and robust optimality in multiattribute decision analysis with incomplete information: A comparative study, Decision Support Systems55(3) (2013), 679–684.
5.
WeiG.W., Picture fuzzy cross-entropy for multiple attribute decision making problems, Journal of Business Economics and Management17(4) (2016), 491–502.
6.
WeiG.W.AlsaadiF.E.HayatT. and AlsaediA., Hesitant fuzzy linguistic arithmetic aggregation operators in multiple attribute decision making, Iranian Journal of Fuzzy Systems13(4) (2016), 1–16.
7.
ChenT.Y., An interval-valued intuitionistic fuzzy permutation method with likelihood-based preference functions and its application to multiple criteria decision analysis, Applied Soft Computing42 (2016), 390–409.
8.
ChenT.Y., The inclusion-based TOPSIS method with interval-valued intuitionistic fuzzy sets for multiple criteria group decision making, Applied Soft Computing26 (2015), 57–73.
9.
QinJ.LiuX. and PedryczW., Multi-attribute group decision making based on Choquet integral under interval-valued intuitionistic fuzzy environment, Int. J. Computational Intelligence Systems9(1) (2016), 133–152.
10.
LuM.WeiG.W.AlsaadiF.E.HayatT. and AlsaediA., Hesitant pythagorean fuzzy hamacher aggregation operators and their application to multiple attribute decision making, Journal of Intelligent and Fuzzy Systems33(2) (2017), 1105–1117.
11.
WeiG.W.LuM.AlsaadiF.E.HayatT. and AlsaediA., Pythagorean 2-tuple linguistic aggregation operators in multiple attribute decision making, Journal of Intelligent and Fuzzy Systems33(2) (2017), 1129–1142.
12.
WeiG.W., Interval valued hesitant fuzzy uncertain linguistic aggregation operators in multiple attribute decision making, International Journal of Machine Learning and Cybernetics7(6) (2016), 1093–1114.
13.
YeJ., Cosine similarity measures for intuitionistic fuzzy sets and their applications, Mathematical and Computer Modelling53(1–2) (2011), 91–97.
14.
LiD.F. and RenH.P., Multi-attribute decision making method considering the amount and reliability of intuitionistic fuzzy information, Journal of Intelligent and Fuzzy Systems28(4) (2015), 1877–1883.
15.
TangY.WenL.L. and WeiG.W., Approaches to multiple attribute group decision making based on the generalized Dice similarity measures with intuitionistic fuzzy information, International Journal of Knowledge-Based and Intelligent Engineering Systems21(2) (2017), 85–95.
16.
WanS.P. and LiD.F., Fuzzy mathematical programming approach to heterogeneous multiattribute decision-making with interval-valued intuitionistic fuzzy truth degrees, Information Science325 (2015), 484–503.
17.
WangH.J.ZhaoX.F. and WeiG.W., Dual hesitant fuzzy aggregation operators in multiple attribute decision making, Journal of Intelligent and Fuzzy Systems26(5) (2014), 2281–2290.
18.
WeiG.W.AlsaadiF.E.HayatT. and AlsaediA., Picture 2-tuple linguistic aggregation operators in multiple attribute decision making, Soft Computing (2016). doi: 10.1007/s00500-016-2403-8.
19.
MerigoJ.M. and CasanovasM., Induced aggregation operators in decision making with the Dempster-Shafer belief structure, International Journal of Intelligent Systems24 (2009), 934–954.
20.
XuZ.S., Fuzzy harmonic mean operators, International Journal of Intelligent Systems24 (2009), 152–172.
21.
WeiG.W., FIOWHM operator and its application to multiple attribute group decision making, Expert Systems with Applications38(4) (2011), 2984–2989.
22.
WeiG.W.ZhaoX.LinR. and WangH., Generalized triangular fuzzy correlated averaging operator and their application to multiple attribute decision making, Applied Mathematical Modelling36(7) (2012), 2975–2982.
23.
WeiG.W.ZhaoX.F.WangH.J. and LinR., Fuzzy power aggregating operators and their application to multiple attribute group decision making, Technological and Economic Development of Economy19(3) (2013), 377–396.
24.
ZhaoX.F.LinR. and WeiG.W., Fuzzy prioritized operators and their application to multiple attribute group decision making, Applied Mathematical Modelling37 (2013), 4759–4770.
25.
Van LaarhovenP.J.M. and PedryczW., A fuzzy extension of Saaty’s priority theory, Fuzzy Sets and Systems11 (1983), 229–241.
26.
ZétényiT., Fuzzy Sets in Psychology, North-Holland, Amsterdam, 1988.
27.
WangW.P., A fuzzy linguistic computing approach to supplier evaluation, Applied Mathematical Modelling34 (2010), 3130–3141.
28.
WeiG.W., Picture 2-tuple linguistic Bonferroni mean operators and their application to multiple attribute decision making, International Journal of Fuzzy Systems19(4) (2017), 997–1010.
29.
ParkD.G.KwunY.C.ParkJ.H. and ParkI.Y., Correlation coefficient of interval-valued intuitionistic fuzzy sets and its application to multiple attribute group decision-making problems, Mathematical and Computer Modelling50 (2009), 1279–293.
30.
ParkJ.H.ParkY.YoungC.K. and XueT., Extension of the TOPSIS method for decision making problems under interval-valued intuitionistic fuzzy environment, Applied Mathematical Modeling35 (2011), 2544–2556.
31.
JiangX.P. and WeiG.W., Some Bonferroni mean operators with 2-tuple linguistic information and their application to multiple attribute decision making, Journal of Intelligent and Fuzzy Systems27 (2014), 2153–2162.
32.
WeiG.W.AlsaadiF.E.HayatT. and AlsaediA., Hesitant bipolar fuzzy aggregation operators in multiple attribute decision making, Journal of Intelligent and Fuzzy Systems33(2) (2017), 1119–1128.
33.
WeiG.W.Tasawar HayatF.E.A. and AlsaediA., Projection models for multiple attribute decision making with picture fuzzy information, International Journal of Machine Learning and Cybernetics, 2016. doi: 10.1007/s13042-016-0604-1.
34.
YeJ., Multiple attribute group decision-making methods with unknown weights in intuitionistic fuzzy setting and interval-valued intuitionistic fuzzy setting, International Journal of General Systems42(5) (2013), 489–502.
35.
Herrera-ViedmaE.MartinezL.MataF. and ChiclanaF., A consensus support system model for group decision-making problems with multigranular linguistic preference relations, IEEE Transactions on Fuzzy Systems13 (2005), 644–658.
36.
XuZ.S., A note on linguistic hybrid arithmetic averaging operator in multiple attribute group decision making with linguistic information, Group Decision and Negotiation15(6) (2006), 593–604.
37.
XuZ.S., A method based on linguistic aggregation operators for group decision making with linguistic preference relations, Information Sciences166(1) (2004), 19–30.
38.
WeiG.W.ZhaoX.F.LinR. and WangH.J., Uncertain linguistic Bonferroni mean operators and their application to multiple attribute decision making, Applied Mathematical Modelling37(7) (2013), 5277–5285.
39.
ZhouL.Y.LinR.ZhaoX.F. and WeiG.W., Uncertain linguistic prioritized aggregation operators and their application to multiple attribute group decision making, International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems21(4) (2013), 603–627.
40.
ZhangZ.WangC.TianD. and LiK., Induced generalized hesitant fuzzy operators and their application to multiple attribute group decision making, Computers & Industrial Engineering67 (2014), 116–138.
41.
ZhaoX.F. and WeiG.W., Some intuitionistic fuzzy Einstein hybrid aggregation operators and their application to multiple attribute decision making, Knowledge-Based Systems37 (2013), 472–479.
42.
HungW.L. and YangM.S., Similarity measures of intuitionistic fuzzy sets based on Hausdorff distance, Pattern Recognition Letters25 (2004), 1603–1611.
43.
LiuH.W., New similarity measures between intuitionistic fuzzy sets and between elements, Mathematical and Computer Modelling42 (2005), 61–70.
44.
YeJ., Vector similarity measures of simplified neutrosophic sets and their application in multicriteria decision making, International Journal of Fuzzy Systems16(2) (2014), 204–211.
45.
HungK.C., Applications of medical information: Using an enhanced likelihood measured approach based on intuitionistic fuzzy sets, IIE Transactions on Healthcare Systems Engineering2(3) (2012), 224–231.
46.
WeiG.W., Interval-valued dual hesitant fuzzy uncertain linguistic aggregation operators in multiple attribute decision making, Journal of Intelligent and Fuzzy Systems33(3) (2017), 1881–1893.
47.
LuM.WeiG.W.AlsaadiF.E.HayatT. and AlsaediA., Bipolar 2-tuple linguistic aggregation operators in multiple attribute decision making, Journal of Intelligent and Fuzzy Systems33(2) (2017), 1197-1207.
48.
WeiG.W., Picture fuzzy aggregation operators and their application to multiple attribute decision making, Journal of Intelligent and Fuzzy Systems33(2) (2017), 713–724.
49.
WeiG.W.AlsaadiF.E.HayatT. and AlsaediA., A linear assignment method for multiple criteria decision analysis with hesitant fuzzy sets based on fuzzy measure, International Journal of Fuzzy Systems19(3) (2017), 607–614.
50.
WeiG.W. and WangJ.M., A comparative study of robust efficiency analysis and data envelopment analysis with imprecise data, Expert Systems with Applications81 (2017), 28–38.
