OPTIMIZING TOUR ROUTE PLANNING FOR OLD STREETS- THE CASE OF TAICHUNG NANTUN OLD STREET IN TAIWAN

IF 1.4 Q3 HOSPITALITY, LEISURE, SPORT & TOURISM
Yao-Tsung Ko
{"title":"OPTIMIZING TOUR ROUTE PLANNING FOR OLD STREETS- THE CASE OF TAICHUNG NANTUN OLD STREET IN TAIWAN","authors":"Yao-Tsung Ko","doi":"10.3727/108354223x16787457804410","DOIUrl":null,"url":null,"abstract":"It is very important for tourists to optimize the tour route planning in advance. This paper presents a quantifying and planning method for the optimal tour route of an old street based on an algebraic matrix technique. A quantified structure matrix (QISM) that combines the quantifying evaluation method and the interpretive structural model (ISM) is established. The proposed QISM is a Boolean matrix that can quantify the dependency and interaction strength between two tour spots and optimize tour route planning. Clustering and tearing algorithms are utilized to restructure a QISM, allowing the interdependent relationships within tour spots in the route planning process to be obtained. A systematic clustering method that is efficient and yet flexible is developed for tour route planning based on the transitive rule. The proposed QISM can enhance the performance of tour route planning management by reducing visit time, offering tour route variety, and raising tour satisfaction. A case study of Taichung Nantun Old Street is employed to illustrate the proposed method. We hope the results of this study can satisfy the needs of tourists and promote the development of old street sightseeing.","PeriodicalId":23157,"journal":{"name":"Tourism Analysis","volume":"1 1","pages":""},"PeriodicalIF":1.4000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Tourism Analysis","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3727/108354223x16787457804410","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"HOSPITALITY, LEISURE, SPORT & TOURISM","Score":null,"Total":0}
引用次数: 0

Abstract

It is very important for tourists to optimize the tour route planning in advance. This paper presents a quantifying and planning method for the optimal tour route of an old street based on an algebraic matrix technique. A quantified structure matrix (QISM) that combines the quantifying evaluation method and the interpretive structural model (ISM) is established. The proposed QISM is a Boolean matrix that can quantify the dependency and interaction strength between two tour spots and optimize tour route planning. Clustering and tearing algorithms are utilized to restructure a QISM, allowing the interdependent relationships within tour spots in the route planning process to be obtained. A systematic clustering method that is efficient and yet flexible is developed for tour route planning based on the transitive rule. The proposed QISM can enhance the performance of tour route planning management by reducing visit time, offering tour route variety, and raising tour satisfaction. A case study of Taichung Nantun Old Street is employed to illustrate the proposed method. We hope the results of this study can satisfy the needs of tourists and promote the development of old street sightseeing.
优化老街旅游线路规划——以台湾台中南屯老街为例
游客提前优化旅游线路规划是非常重要的。本文提出了一种基于代数矩阵技术的老街最优游览路线量化规划方法。将量化评价方法与解释结构模型相结合,建立了量化结构矩阵。提出的QISM是一个布尔矩阵,可以量化两个旅游点之间的依赖关系和相互作用强度,从而优化旅游路线规划。利用聚类和撕裂算法重构QISM,得到路线规划过程中各旅游点之间的相互依存关系。提出了一种高效灵活的基于传递规则的旅游线路规划系统聚类方法。所提出的质量管理理论可以通过缩短游客参观时间、提供丰富的旅游线路种类和提高游客满意度来提高旅游线路规划管理的绩效。最后,以台中市南屯老街为例进行了实证分析。希望本研究的结果能够满足游客的需求,促进老街旅游的发展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Tourism Analysis
Tourism Analysis HOSPITALITY, LEISURE, SPORT & TOURISM-
CiteScore
2.50
自引率
11.10%
发文量
42
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信