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

2019 ◽  
Vol 12 (4-5) ◽  
pp. 771-782 ◽  
Author(s):  
Tao Gu ◽  
◽  
Peiyu Ren ◽  
Maozhu Jin ◽  
Hua Wang
Keyword(s):  
Information Entropy ◽  
Sichuan Province ◽  
Tourism Destination ◽  
Model Based ◽  
Destination Competitiveness ◽  
Topsis Model

Attribute Recognition Model Based on Entropy Weight and Its Application to Evaluation of Groundwater Quality

2010 ◽  
Vol 29-32 ◽  
pp. 2698-2702
Author(s):  
Xian Qi Zhang ◽  
Wen Hong Feng ◽  
Nan Nan Li
Keyword(s):  
Water Quality ◽  
Groundwater Quality ◽  
Information Entropy ◽  
Simple Calculation ◽  
Weight Coefficient ◽  
Entropy Theory ◽  
Entropy Weight ◽  
Recognition Model ◽  
Model Based ◽  
Attribute Recognition

It is necessary to take into account synthetically attribute of every index because of independence and incompatibility resulted from single index evaluating outcomes. Through the information entropy theory and attribute recognition model being combined together, attribute recognition model based on entropy weight is constructed and applied to evaluating groundwater quality by a new method, weight coefficient by the law of entropy value is exercised so that it is more objective. The outcome from concrete application indicates that it is suitable to evaluate water quality with reasonable conclusion and simple calculation.

Stakeholder views on sustainability in an urban destination context: an inclusive path to destination competitiveness

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Gaurav Panse ◽  
Alan Fyall ◽  
Sergio Alvarez
Keyword(s):  
Urban Tourism ◽  
Research Approach ◽  
Exploratory Research ◽  
Tourism Destination ◽  
Urban Settings ◽  
Content Type ◽  
Cultural Sustainability ◽  
Mass Tourism ◽  
Destination Competitiveness ◽  
Development Goals

Purpose Mass tourism in urban settings has proven to be economically significant in many parts of the world. To date, however, the academic debate on sustainable tourism has focused primarily on the ecological and socio-cultural sustainability of tourism in rural and coastal, rather than urban, settings. This paper aims to review the emerging debate on sustainable urban tourism, its complexities and challenges, and questions how urban destinations that are striving to become sustainable cities, can leverage benefit from the implementation of sustainable policies and practices to achieve tourism ‘destination’ competitiveness. Design/methodology/approach The paper uses a qualitative, exploratory research approach using in-depth interviews to seek responses from key stakeholders on their views and experiences of sustainability in the context of an urban destination. Thematic analysis is used to analyze and present the findings. Findings This study concludes that destinations need to be viewed in their broader regional context. Rather than be viewed solely as destinations that are ‘kind to the environment,’ sustainable urban destinations need to demonstrate a deeper commitment to all stakeholder groups, and especially local residents, to provide a fair and desirable ecosystem for achievement of the UN Sustainable Development Goals. Originality/value This paper reflects on the potential relationship between ‘urban sustainability’ and the ‘destination competitiveness’ of an urban tourism destination. This then will provide the platform for sustainability to truly contribute to future destination competitiveness.

scholarly journals A Forecasting Model Based on High-Order Fluctuation Trends and Information Entropy

Entropy ◽  
2018 ◽  
Vol 20 (9) ◽  
pp. 669 ◽  
Author(s):  
Hongjun Guan ◽  
Zongli Dai ◽  
Shuang Guan ◽  
Aiwu Zhao
Keyword(s):  
Information Entropy ◽  
Prediction Models ◽  
Stock Exchange ◽  
Two Dimensions ◽  
High Order ◽  
Stock Index ◽  
Neutrosophic Sets ◽  
Prediction Ability ◽  
Model Based ◽  
Logical Rules

Most existing high-order prediction models abstract logical rules that are based on historical discrete states without considering historical inconsistency and fluctuation trends. In fact, these two characteristics are important for describing historical fluctuations. This paper proposes a model based on logical rules abstracted from historical dynamic fluctuation trends and the corresponding inconsistencies. In the logical rule training stage, the dynamic trend states of up and down are mapped to the two dimensions of truth-membership and false-membership of neutrosophic sets, respectively. Meanwhile, information entropy is employed to quantify the inconsistency of a period of history, which is mapped to the indeterminercy-membership of the neutrosophic sets. In the forecasting stage, the similarities among the neutrosophic sets are employed to locate the most similar left side of the logical relationship. Therefore, the two characteristics of the fluctuation trends and inconsistency assist with the future forecasting. The proposed model extends existing high-order fuzzy logical relationships (FLRs) to neutrosophic logical relationships (NLRs). When compared with traditional discrete high-order FLRs, the proposed NLRs have higher generality and handle the problem caused by the lack of rules. The proposed method is then implemented to forecast Taiwan Stock Exchange Capitalization Weighted Stock Index and Heng Seng Index. The experimental conclusions indicate that the model has stable prediction ability for different data sets. Simultaneously, comparing the prediction error with other approaches also proves that the model has outstanding prediction accuracy and universality.

Tourism destination competitiveness and tourism performance

2019 ◽  
Vol 29 (5) ◽  
pp. 592-621 ◽  
Author(s):  
Mohd Hafiz Hanafiah ◽  
Muhammad Izzat Zulkifly
Keyword(s):  
Structural Equation ◽  
Secondary Data ◽  
Partial Least Square ◽  
Least Square ◽  
Tourism Destination ◽  
Actual Performance ◽  
Content Type ◽  
Factors Affecting ◽  
Travel And Tourism ◽  
Destination Competitiveness

Purpose This study aims to examine the relationships between tourism destination competitiveness (TDC) determinants and tourism performance. This study specifically assessed the soundness of the TDC attributes and evaluated their ability in explaining tourism performance. Design/methodology/approach The Dwyer and Kim’s (2003) destination competitiveness integrated model (IM) was used. Secondary data of 115 nations available from the Travel and Tourism Competitiveness Index (TTCI) and other international reports were also used. The hypothesised relationships were tested via partial least square-structural equation modelling (PLS-SEM). Findings This study confirms that the core resources, complementary condition, globalisation and tourism price significantly explain tourism performance. Results have shown differences in the competitiveness level and actual performance among nations, highlighting specific limitations of the current TDC model and TTCI report reliability. Research limitations/implications Future study could segment the sample base on destinations characteristic and then analyse it based on smaller sub-samples of similar destinations. Moreover, drivers of destination performance in developed and less develop destinations are quite diverse. Practical implications The incorrect competitiveness ranking evaluation will affect inward investment decisions. This study framework enables policymakers to arrive at more informed decisions than merely relying on the original competitiveness rankings. Originality/value The widespread acknowledgment of the importance of competitiveness for a tourism destination's success suggests that there is a crucial need for sound benchmarking of countries’ competitive capabilities. The proposed competitiveness determinants aid the policymakers in identifying the best competitiveness and tourism performance predictors, as well as how to identify crucial factors affecting the rankings.

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