# American Institute of Mathematical Sciences

## Tourism destination competitiveness evaluation in Sichuan province using TOPSIS model based on information entropy weights

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

* Corresponding author: Maozhu Jin, E-mail: jinmaozhu@scu.edu.cn

Received  June 2017 Revised  December 2017 Published  November 2018

This study applied the combined methods of Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and Information Entropy Weights to evaluate the tourism destination competitiveness (TDC) of 13 cities in Sichuan Province. In the empirical study, IEW was used to determine the subjective weights of four aspects and 26 evaluation indexes, which have the influence on TDC. In addition, applying the essential ideas of TOPSIS, chosen alternative should have the shortest geometric from the positive ideal solution (PIS) and the longest geometric distance from the negative ideal solution (NIS), to conduct a comprehensive evaluation and sort-based analysis. In the end, the essay arranged the TDC of 13 cities in Sichuan Province from high to low, then produced policy recommendations. The results represent that IEW & TOPSIS were an efficient and effective way to evaluate TDC.

Citation: Tao Gu, Peiyu Ren, Maozhu Jin, Hua Wang. Tourism destination competitiveness evaluation in Sichuan province using TOPSIS model based on information entropy weights. Discrete & Continuous Dynamical Systems - S, doi: 10.3934/dcdss.2019051
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##### References:
 [1] J. M. Amigó and Á. Giménez, Applications of the min-max symbols of multimodal maps, Applied Mathematics and Nonlinear Sciences, 1 (2016), 87-98. [2] F. Balibrea, On problems of Topological Dynamics in non-autonomous discrete systems, Applied Mathematics and Nonlinear Sciences, 1 (2016), 391-404. [3] D. Buhalis, Marketing the competitive destination of the future, Tourism Management, 21 (2000), 97-116. [4] R. Couch, Destination competitiveness: ExploringFoundations for a long term research program, Proceedings of the Administrative Sciences Association of Canada 1994. Annual Conference 1994. [5] A. M. d'Hauteserre, Lessons in managed destination competitiveness: The case of foxwoods casino resort, Tourism Management, 21 (2000), 23-32. [6] L. Dwyer, T. H. P. Forsyth and P. Rao, The price competitiveness of travel and tourism: A comparison of 19 destinations, Tourism Management, 21 (2000), 9-22. [7] M. J. Enright and J. Newton, Determinants ofTourism destination competitiveness in asia pacific: Comprehensiveness and universality, Journal of TravelResearch, 2005. [8] N. Gooroochurn and G. Sugiyarto, Competitiveness indicators in the travel and tourism industry, Tourism Economics, 11 (2005), 25-46. [9] N. Gooroochurn and G. Sugiyarto, Competitiveness indicators in the travel and tourism industry, Tourism Economics, 11 (2005), 25-46. [10] S. S. Hassan, Determinants of market competitiveness in an environmentally sustainable tourism industry, Journal of Travel Research, 38 (2000), 239-245. [11] C. L. Hwang and K. Yoon, Multiple Attribute Decision Making: Method and Application, Springer-Verlag, Berlin-New York, 1981. [12] S. S. Kim, Y. Z. Guo and J. Agrusa, Preference and positioning analyses of overseas destinations by mainland chinese outbound pleasure tourists, Journal of Travel Research, 44 (2005), 212-220. [13] M. Kozak and M. Rimmington, Measuring tourist destination competitiveness: Conceptual considerations and empirical findings, Hospitality Management, 18 (1999), 273-283. [14] M. Kozak and M. Rimmington, Measuring tourist destination competitiveness: Conceptual considerations and empirical findings, Hospitality Management, 18 (1999), 273-283. [15] C. E. Shannon, A mathematical theory of communication, Bell System Technical Journal, 27 (1948), 379-423,623-656. doi: 10.1002/j.1538-7305.1948.tb01338.x. [16] D. Larry and K. Chulwon, Destination Competitiveness: Determinants and Indicators, Current Issues in Tourism, 2003. [17] K.-L. Wang and C.-S. Wu, A Study of Competitiveness of International Tourism in the South East Asian Region, Eleventh Annual East Asian Seminar on Economics: Trade in Services, June 22-24, 2000, Seoul, Korea. [18] Y. Yoon, Development of a Structural Model for Tourism Destination Competitiveness from Stakeholders Perspectives, 2002.
weight of indexes in TDC
Data of tourism resources in Sichuan Province
Data of tourism capacity in Sichuan Province
 City Number of travel agency (units) Number of star-reated hotels (units) Civilian-owned value added of tertiary industry (%) Chengdu 462 128 109.4 Guangyuan 14 20 108.6 Luzhou 27 23 109.2 Leshan 75 33 109.9 Mianyang 61 30 110.0 Nanchong 49 26 110.6 Aba 34 19 110.5 Yibin 27 15 110.1 Dazhou 27 10 110.4 Ya'an 12 21 112.3 Ganzi 20 9 107.2 Suining 13 22 119.2 Zigong 21 8 109.4
 City Number of travel agency (units) Number of star-reated hotels (units) Civilian-owned value added of tertiary industry (%) Chengdu 462 128 109.4 Guangyuan 14 20 108.6 Luzhou 27 23 109.2 Leshan 75 33 109.9 Mianyang 61 30 110.0 Nanchong 49 26 110.6 Aba 34 19 110.5 Yibin 27 15 110.1 Dazhou 27 10 110.4 Ya'an 12 21 112.3 Ganzi 20 9 107.2 Suining 13 22 119.2 Zigong 21 8 109.4
Data of tourism industrial strength in Sichuan Province
 City Number of domestic tourist arrivals (10000 person times) Domestic tourist income (100 million yuan) Number of international tourist arrivals (10000 preson times) International tourist income (UAD 10000) Chengdu 18423.02 1616.95 197.8 85768.11 Guangyuan 2769.43 158.69 0.18 40.96 Luzhou 2539.51 2539.51 0.22 57.31 Leshan 3342.14 383.9 12.79 4656.25 Mianyang 2821.12 277.13 0.74 212.25 Nanchong 3076.5 253.28 0.25 71.07 Aba 2861.34 240.78 15.44 2852.81 Yibin 2822.24 256.02 0.17 63.21 Dazhou 1351.01 90.36 0.29 99.29 Ya'an 1658.91 108.6 0.37 102.92 Ganzi 792.66 79.03 6.25 1799.29 Suining 2432.79 201.09 0.72 148.95 Zigong 2106 200.38 0.16 52.5
 City Number of domestic tourist arrivals (10000 person times) Domestic tourist income (100 million yuan) Number of international tourist arrivals (10000 preson times) International tourist income (UAD 10000) Chengdu 18423.02 1616.95 197.8 85768.11 Guangyuan 2769.43 158.69 0.18 40.96 Luzhou 2539.51 2539.51 0.22 57.31 Leshan 3342.14 383.9 12.79 4656.25 Mianyang 2821.12 277.13 0.74 212.25 Nanchong 3076.5 253.28 0.25 71.07 Aba 2861.34 240.78 15.44 2852.81 Yibin 2822.24 256.02 0.17 63.21 Dazhou 1351.01 90.36 0.29 99.29 Ya'an 1658.91 108.6 0.37 102.92 Ganzi 792.66 79.03 6.25 1799.29 Suining 2432.79 201.09 0.72 148.95 Zigong 2106 200.38 0.16 52.5
Data of economic support ability
 City GDP per capita (yuan) Total investment in fix asset (100 million yuan) Passenger-kilometers of highways (10000 passenger-km) Possession of civil motor vehicles (10000 units) Total lengh of highways (km) Chengdu 70019 6620.37 1231084 312.8 22789 Guangyuan 22117 561.74 183548 14.0 19520 Luzhou 29655 1181.03 641482 21.0 13516 Leshan 37125 863.91 247432 22.3 11658 Mianyang 33558 1080.37 336848 37.8 19887 Nanchong 22639 1244.54 466942 27.7 22446 Aba 27043 383.34 254599 10.4 13218 Yibin 32318 1130.26 330827 19.2 18301 Dazhou 24411 1176.20 241365 18.1 19510 Ya'an 30052 471.40 106689 11.8 6286 Ganzi 18096 465.72 142998 7.4 29584 Suining 24691 913.68 201427 13.3 8805 Zigong 39145 597.61 183364 13.8 6456
 City GDP per capita (yuan) Total investment in fix asset (100 million yuan) Passenger-kilometers of highways (10000 passenger-km) Possession of civil motor vehicles (10000 units) Total lengh of highways (km) Chengdu 70019 6620.37 1231084 312.8 22789 Guangyuan 22117 561.74 183548 14.0 19520 Luzhou 29655 1181.03 641482 21.0 13516 Leshan 37125 863.91 247432 22.3 11658 Mianyang 33558 1080.37 336848 37.8 19887 Nanchong 22639 1244.54 466942 27.7 22446 Aba 27043 383.34 254599 10.4 13218 Yibin 32318 1130.26 330827 19.2 18301 Dazhou 24411 1176.20 241365 18.1 19510 Ya'an 30052 471.40 106689 11.8 6286 Ganzi 18096 465.72 142998 7.4 29584 Suining 24691 913.68 201427 13.3 8805 Zigong 39145 597.61 183364 13.8 6456
Data of eco-environment support ability in Sichuan Province
 City Air quality index Rate of forest coverage (%) Public green area per capita (sq.m) Chengdu 8.95 38.4 13.5 Guangyuan 5.99 55.3 11.2 Luzhou 6.05 50 9.01 Leshan 7 55.47 9.03 Mianyang 6.79 52.4 9.63 Nanchong 6 39.8 11.6 Aba 2.98 24.95 5.5 Yibin 6.58 44.2 13.08 Dazhou 7.66 41.5 11.7 Ya'an 6.26 63.1 13.08 Ganzi 3.83 33.04 9 Suining 4.9 39.01 6.8 Zigong 7.69 33.7 11.3
 City Air quality index Rate of forest coverage (%) Public green area per capita (sq.m) Chengdu 8.95 38.4 13.5 Guangyuan 5.99 55.3 11.2 Luzhou 6.05 50 9.01 Leshan 7 55.47 9.03 Mianyang 6.79 52.4 9.63 Nanchong 6 39.8 11.6 Aba 2.98 24.95 5.5 Yibin 6.58 44.2 13.08 Dazhou 7.66 41.5 11.7 Ya'an 6.26 63.1 13.08 Ganzi 3.83 33.04 9 Suining 4.9 39.01 6.8 Zigong 7.69 33.7 11.3
Ranking of tourism resources in Sichuan province and the value of $d^+$, $d^-$, $c_i$
 $d^+$ $d^-$ $C_i$ Rank 1 Chengdu 0.550814 0.669486 0.548624 2 2 Guangyuan 0.621754 0.422017 0.404320 5 3 Luzhou 0.850805 0.331103 0.280143 9 4 Leshan 0.663612 0.437401 0.397272 7 5 Mianyang 0.591847 0.578172 0.494156 3 6 Nanchong 0.769232 0.520604 0.403620 6 7 Aba 0.477572 0.697994 0.593752 1 8 Yibin 0.834214 0.293777 0.260443 10 9 Dazhou 0.861676 0.297350 0.256552 11 10 Ya'an 0.834464 0.350878 0.296014 8 11 Ganzhi 0.720549 0.517163 0.417838 4 12 Suining 0.911916 0.154774 0.145097 13 13 Zigong 0.898165 0.251098 0.218486 12
 $d^+$ $d^-$ $C_i$ Rank 1 Chengdu 0.550814 0.669486 0.548624 2 2 Guangyuan 0.621754 0.422017 0.404320 5 3 Luzhou 0.850805 0.331103 0.280143 9 4 Leshan 0.663612 0.437401 0.397272 7 5 Mianyang 0.591847 0.578172 0.494156 3 6 Nanchong 0.769232 0.520604 0.403620 6 7 Aba 0.477572 0.697994 0.593752 1 8 Yibin 0.834214 0.293777 0.260443 10 9 Dazhou 0.861676 0.297350 0.256552 11 10 Ya'an 0.834464 0.350878 0.296014 8 11 Ganzhi 0.720549 0.517163 0.417838 4 12 Suining 0.911916 0.154774 0.145097 13 13 Zigong 0.898165 0.251098 0.218486 12
The ranking of $d^+$, $d^-$, $c_i\sum$ and $c_i$ of Sichuan province
 d+ d- Ci Rank Chengdu 0.54862 2 0.67592 1 0.82103 1 0.87753 1 0.68903 2 0.06354 0.96347 0.93813 1 Guangyuan 0.40432 5 0.08201 12 0.05213 8 0.23084 8 0.66767 3 0.74736 0.43434 0.36755 6 Luzhou 0.28014 9 0.11224 10 0.39159 2 0.26133 5 0.53443 10 0.66540 0.40101 0.37604 3 Leshan 0.39727 7 0.18843 4 0.10089 3 0.18735 9 0.62099 6 0.71011 0.42463 0.37421 4 Mianyang 0.49416 3 0.17271 5 0.06571 6 0.29001 4 0.61834 7 0.67970 0.49456 0.42117 2 Nanchong 0.40362 6 0.17270 6 0.06767 5 0.31423 3 0.55298 9 0.69664 0.41520 0.37344 5 Aba 0.59375 1 0.14770 7 0.07580 4 0.15504 11 0.00000 13 0.80958 0.46607 0.36536 7 Yibin 0.26044 10 0.12460 9 0.06293 7 0.26075 6 0.66484 4 0.77253 0.37281 0.32550 9 Dazhou 0.25655 11 0.13029 8 0.01438 13 0.24862 7 0.64432 5 0.79596 0.360216616 0.31156 10 Ya'an 0.29601 8 0.20576 3 0.02281 11 0.08964 12 0.77753 1 0.79706 0.435391142 0.35327 8 Ganzhi 0.41784 4 0.01219 13 0.01869 12 0.33984 2 0.28915 11 0.79262 0.341512783 0.301121399 11 Suining 0.14510 13 0.38640 2 0.04866 9 0.08901 13 0.28881 12 0.85787 0.283852311 0.248617312 13 Zigong 0.21849 12 0.09030 11 0.04191 10 0.15590 10 0.55993 8 0.84206131 0.296212909 0.260229832 12
 d+ d- Ci Rank Chengdu 0.54862 2 0.67592 1 0.82103 1 0.87753 1 0.68903 2 0.06354 0.96347 0.93813 1 Guangyuan 0.40432 5 0.08201 12 0.05213 8 0.23084 8 0.66767 3 0.74736 0.43434 0.36755 6 Luzhou 0.28014 9 0.11224 10 0.39159 2 0.26133 5 0.53443 10 0.66540 0.40101 0.37604 3 Leshan 0.39727 7 0.18843 4 0.10089 3 0.18735 9 0.62099 6 0.71011 0.42463 0.37421 4 Mianyang 0.49416 3 0.17271 5 0.06571 6 0.29001 4 0.61834 7 0.67970 0.49456 0.42117 2 Nanchong 0.40362 6 0.17270 6 0.06767 5 0.31423 3 0.55298 9 0.69664 0.41520 0.37344 5 Aba 0.59375 1 0.14770 7 0.07580 4 0.15504 11 0.00000 13 0.80958 0.46607 0.36536 7 Yibin 0.26044 10 0.12460 9 0.06293 7 0.26075 6 0.66484 4 0.77253 0.37281 0.32550 9 Dazhou 0.25655 11 0.13029 8 0.01438 13 0.24862 7 0.64432 5 0.79596 0.360216616 0.31156 10 Ya'an 0.29601 8 0.20576 3 0.02281 11 0.08964 12 0.77753 1 0.79706 0.435391142 0.35327 8 Ganzhi 0.41784 4 0.01219 13 0.01869 12 0.33984 2 0.28915 11 0.79262 0.341512783 0.301121399 11 Suining 0.14510 13 0.38640 2 0.04866 9 0.08901 13 0.28881 12 0.85787 0.283852311 0.248617312 13 Zigong 0.21849 12 0.09030 11 0.04191 10 0.15590 10 0.55993 8 0.84206131 0.296212909 0.260229832 12
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