Construction And Performance Analysis Of Inbound Tourism Destination Evaluation Model Based On Probabilistic Linguistic Term Set

Inbound tourism plays a positive role in expanding foreign exchange,increasing employment and enhancing international visibility.Therefore,expanding inbound tourism market has become an important means for cities to enhance their competitiveness and expand foreign economic and trade advantages.With the development of economy and the improvement of tourism resources,the preference of inbound tourists is gradually diversified,which leads to the expansion of inbound tourism scale difference.Therefore,in order to strengthen the construction of world tourism,it is very necessary to construct a reasonable and scientific evaluation model to analyze the competitiveness of each tourist destination.However,in the decision-making process,there are some situations in which it is difficult to express the preferences of decision-makers with specific numbers.To break through this dilemma,the language vocabulary system based on probability emerges as the times require.As the key content of decision theory,probabilistic linguistic terminology transforms qualitative information into quantitative information through linguistic scale and corresponding probability,which can make the evaluation results more acceptable.Based on the above content,this paper discusses the multi-attribute decision making problem of inbound tourism destination selection in the probabilistic linguistic environment,and makes a comprehensive and reasonable evaluation of tourism destinations by integrating various influencing factors and evaluation methods.The research results of this paper are as follows:(1)Based on the research status of inbound tourism destination selection,identify the influencing factors of inbound tourism destination selection and build a reasonable inbound tourism destination evaluation index system.(2)For the competitiveness assessment of inbound tourism destination whose evaluation information is a probabilistic linguistic term set and the attribute weight is unknown,probabilistic linguistic MAUT evaluation model,probabilistic linguistic PROMETHEE II evaluation model,probabilistic linguistic PL-PAMSSEM II evaluation model and probabilistic linguistic PL-MAUT-PAMSSEM II evaluation model are proposed to solve this problem.(3)The constructed three evaluation models are applied to the calculation example of inbound tourism destination selection,and the big data analysis is carried out on a large number of tourism samples in this paper.At the same time,the validity of the four evaluation models is verified by validity test and comparative analysis,and the advantages of the combined method are pointed out.The innovations of this paper include:(1)Combined design of multi-attribute decision-making method is carried out to improve the overall performance of the method;(2)Construct a tourist destination evaluation index system based on qualitative indicators,so as to break through the traditional evaluation methods of inbound tourist destinations.