{"title":"OTA 最佳目的地公寓列表分析:泰国与日本","authors":"Mathupayas Thongmak","doi":"10.1108/cbth-07-2023-0085","DOIUrl":null,"url":null,"abstract":"\nPurpose\nThe sharing economy enables apartment owners to generate income from their assets. “Agoda Homes” is an online travel agent (OTA) that directly competes with Airbnb. A destination has to discover its competitiveness, but few studies have provided an overview of accommodation attributes in each destination, which are crucial to shaping its brand image. This paper aims to illustrate firm-generated content or attributes that apartment owners list about their properties on an OTA platform to comprehend factual information about apartments in each destination with various star ratings and user ratings and to formulate a research model for future studies.\n\n\nDesign/methodology/approach\nInformational content and accommodation attributes for apartments are automatically collected using a Web scraping tool (the Data Miner). Descriptive statistics and text analysis (word cloud and word frequency) are used to analyze data.\n\n\nFindings\nFindings reveal the primary location, facilities, cleanliness and safety attributes for all apartments in each destination, along with star ratings and user ratings. A research framework for scholars is also suggested. Guidelines for stakeholders in the tourism industry are additionally furnished.\n\n\nOriginality/value\nThis work concentrates on apartments, which have received less attention in the tourism literature. The study gathers factual data from a website to mitigate respondent bias issues inherent in the traditional survey methods.\n","PeriodicalId":271272,"journal":{"name":"Consumer Behavior in Tourism and Hospitality","volume":"82 19","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An analysis of apartment listings in best destinations on an OTA: Thailand versus Japan\",\"authors\":\"Mathupayas Thongmak\",\"doi\":\"10.1108/cbth-07-2023-0085\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\nPurpose\\nThe sharing economy enables apartment owners to generate income from their assets. “Agoda Homes” is an online travel agent (OTA) that directly competes with Airbnb. A destination has to discover its competitiveness, but few studies have provided an overview of accommodation attributes in each destination, which are crucial to shaping its brand image. This paper aims to illustrate firm-generated content or attributes that apartment owners list about their properties on an OTA platform to comprehend factual information about apartments in each destination with various star ratings and user ratings and to formulate a research model for future studies.\\n\\n\\nDesign/methodology/approach\\nInformational content and accommodation attributes for apartments are automatically collected using a Web scraping tool (the Data Miner). Descriptive statistics and text analysis (word cloud and word frequency) are used to analyze data.\\n\\n\\nFindings\\nFindings reveal the primary location, facilities, cleanliness and safety attributes for all apartments in each destination, along with star ratings and user ratings. A research framework for scholars is also suggested. Guidelines for stakeholders in the tourism industry are additionally furnished.\\n\\n\\nOriginality/value\\nThis work concentrates on apartments, which have received less attention in the tourism literature. The study gathers factual data from a website to mitigate respondent bias issues inherent in the traditional survey methods.\\n\",\"PeriodicalId\":271272,\"journal\":{\"name\":\"Consumer Behavior in Tourism and Hospitality\",\"volume\":\"82 19\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-04-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Consumer Behavior in Tourism and Hospitality\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1108/cbth-07-2023-0085\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Consumer Behavior in Tourism and Hospitality","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1108/cbth-07-2023-0085","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
目的共享经济使公寓业主能够从其资产中获得收入。"Agoda Homes "是与 Airbnb 直接竞争的在线旅行社(OTA)。一个目的地必须发现自己的竞争力,但很少有研究对每个目的地的住宿属性进行概述,而这些属性对塑造其品牌形象至关重要。本文旨在说明公司生成的内容或公寓所有者在 OTA 平台上列出的有关其物业的属性,以了解各目的地公寓的事实信息,包括各种星级评分和用户评分,并为今后的研究制定一个研究模型。设计/方法/途径使用网络搜刮工具(数据挖掘器)自动收集公寓的信息内容和住宿属性。调查结果调查结果揭示了每个目的地所有公寓的主要位置、设施、清洁度和安全属性,以及星级和用户评分。此外,还为学者们提出了一个研究框架。原创性/价值 本研究集中于公寓,而公寓在旅游文献中受到的关注较少。研究通过网站收集事实数据,以减少传统调查方法中固有的受访者偏差问题。
An analysis of apartment listings in best destinations on an OTA: Thailand versus Japan
Purpose
The sharing economy enables apartment owners to generate income from their assets. “Agoda Homes” is an online travel agent (OTA) that directly competes with Airbnb. A destination has to discover its competitiveness, but few studies have provided an overview of accommodation attributes in each destination, which are crucial to shaping its brand image. This paper aims to illustrate firm-generated content or attributes that apartment owners list about their properties on an OTA platform to comprehend factual information about apartments in each destination with various star ratings and user ratings and to formulate a research model for future studies.
Design/methodology/approach
Informational content and accommodation attributes for apartments are automatically collected using a Web scraping tool (the Data Miner). Descriptive statistics and text analysis (word cloud and word frequency) are used to analyze data.
Findings
Findings reveal the primary location, facilities, cleanliness and safety attributes for all apartments in each destination, along with star ratings and user ratings. A research framework for scholars is also suggested. Guidelines for stakeholders in the tourism industry are additionally furnished.
Originality/value
This work concentrates on apartments, which have received less attention in the tourism literature. The study gathers factual data from a website to mitigate respondent bias issues inherent in the traditional survey methods.