A spatial origin‐destination approach for the analysis of local tourism demand in Italy

IF 2.3 3区 经济学 Q2 ECONOMICS Papers in Regional Science Pub Date : 2023-04-01 DOI:10.1111/pirs.12726
Salvatore Costantino , Maria Francesca Cracolici , J. Paul Elhorst
{"title":"A spatial origin‐destination approach for the analysis of local tourism demand in Italy","authors":"Salvatore Costantino ,&nbsp;Maria Francesca Cracolici ,&nbsp;J. Paul Elhorst","doi":"10.1111/pirs.12726","DOIUrl":null,"url":null,"abstract":"<div><div>The article assesses the competitiveness of tourist destinations, while accounting for spatial features of tourism and information on both the origin and the destination of tourists. Using a dynamic spatial panel data model with common factors within the origin‐destination framework, it explores unilateral inbound tourism flows in 110 Italian regions from 23 European origin countries over the period 2004–2017. The estimation and test results confirm the need to consider this advanced spatial econometric model. In an empirical application measuring tourism resilience of regions based on this model, the results demonstrate the importance of promoting coordinated actions between neighbouring destinations to support the attractiveness of local clusters.</div></div>","PeriodicalId":51458,"journal":{"name":"Papers in Regional Science","volume":"102 2","pages":"Pages 393-420"},"PeriodicalIF":2.3000,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Papers in Regional Science","FirstCategoryId":"96","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1056819023000933","RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ECONOMICS","Score":null,"Total":0}
引用次数: 0

Abstract

The article assesses the competitiveness of tourist destinations, while accounting for spatial features of tourism and information on both the origin and the destination of tourists. Using a dynamic spatial panel data model with common factors within the origin‐destination framework, it explores unilateral inbound tourism flows in 110 Italian regions from 23 European origin countries over the period 2004–2017. The estimation and test results confirm the need to consider this advanced spatial econometric model. In an empirical application measuring tourism resilience of regions based on this model, the results demonstrate the importance of promoting coordinated actions between neighbouring destinations to support the attractiveness of local clusters.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
意大利地方旅游需求分析的空间重力模型方法
本文在考虑旅游空间特征和游客来源地和目的地信息的基础上,对旅游目的地的竞争力进行了评价。该研究使用具有始发目的地框架内共同因素的动态空间面板数据模型,探讨了2004-2017年期间来自23个欧洲原籍国的110个意大利地区的单边入境旅游流量。估算和检验结果证实了考虑这种先进的空间计量模型的必要性。在基于该模型的区域旅游弹性测量实证应用中,结果表明促进邻近目的地之间的协调行动对支持当地集群吸引力的重要性。
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 去求助
来源期刊
CiteScore
4.40
自引率
4.80%
发文量
58
期刊介绍: Regional Science is the official journal of the Regional Science Association International. It encourages high quality scholarship on a broad range of topics in the field of regional science. These topics include, but are not limited to, behavioral modeling of location, transportation, and migration decisions, land use and urban development, interindustry analysis, environmental and ecological analysis, resource management, urban and regional policy analysis, geographical information systems, and spatial statistics. The journal publishes papers that make a new contribution to the theory, methods and models related to urban and regional (or spatial) matters.
期刊最新文献
Do more transport opportunities lead to higher income? The effects of public transit access on transit-adjacent neighborhoods
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1