{"title":"Airbnb的成功:取决于谁在衡量?","authors":"V. Agarwal, J. V. Koch, R. McNab","doi":"10.1177/19389655211029914","DOIUrl":null,"url":null,"abstract":"Because individual listing data for Airbnb typically are not publicly available, private companies have emerged to estimate the performance of Airbnb listings. The implicit assumption of a growing number of academics, policymakers, and consultants is that Airdna’s performance measures are directly comparable with those of STR. We argue that Airdna’s measures of Occupancy, Average Daily Rate (ADR), and Revenue per Available Room (RevPAR) do not conform to industry standards and exhibit significant bias. We expand available evidence by explicitly quantifying the sources and magnitude of the biases for Airdna’s performance measures for Airbnb listings. Using Airdna’s individual listing data for Virginia between the first quarter of 2015 and the 4th quarter of 2019, we find, on average, Airdna’s performance measures for Occupancy, ADR, and RevPAR were biased upward by 60 percent, 78 percent, and 179 percent, respectively.","PeriodicalId":47888,"journal":{"name":"Cornell Hospitality Quarterly","volume":null,"pages":null},"PeriodicalIF":3.4000,"publicationDate":"2021-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/19389655211029914","citationCount":"1","resultStr":"{\"title\":\"Airbnb’s Success: Does It Depend on Who Is Measuring?\",\"authors\":\"V. Agarwal, J. V. Koch, R. McNab\",\"doi\":\"10.1177/19389655211029914\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Because individual listing data for Airbnb typically are not publicly available, private companies have emerged to estimate the performance of Airbnb listings. The implicit assumption of a growing number of academics, policymakers, and consultants is that Airdna’s performance measures are directly comparable with those of STR. We argue that Airdna’s measures of Occupancy, Average Daily Rate (ADR), and Revenue per Available Room (RevPAR) do not conform to industry standards and exhibit significant bias. We expand available evidence by explicitly quantifying the sources and magnitude of the biases for Airdna’s performance measures for Airbnb listings. Using Airdna’s individual listing data for Virginia between the first quarter of 2015 and the 4th quarter of 2019, we find, on average, Airdna’s performance measures for Occupancy, ADR, and RevPAR were biased upward by 60 percent, 78 percent, and 179 percent, respectively.\",\"PeriodicalId\":47888,\"journal\":{\"name\":\"Cornell Hospitality Quarterly\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.4000,\"publicationDate\":\"2021-07-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1177/19389655211029914\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Cornell Hospitality Quarterly\",\"FirstCategoryId\":\"91\",\"ListUrlMain\":\"https://doi.org/10.1177/19389655211029914\",\"RegionNum\":4,\"RegionCategory\":\"管理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"HOSPITALITY, LEISURE, SPORT & TOURISM\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cornell Hospitality Quarterly","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.1177/19389655211029914","RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"HOSPITALITY, LEISURE, SPORT & TOURISM","Score":null,"Total":0}
Airbnb’s Success: Does It Depend on Who Is Measuring?
Because individual listing data for Airbnb typically are not publicly available, private companies have emerged to estimate the performance of Airbnb listings. The implicit assumption of a growing number of academics, policymakers, and consultants is that Airdna’s performance measures are directly comparable with those of STR. We argue that Airdna’s measures of Occupancy, Average Daily Rate (ADR), and Revenue per Available Room (RevPAR) do not conform to industry standards and exhibit significant bias. We expand available evidence by explicitly quantifying the sources and magnitude of the biases for Airdna’s performance measures for Airbnb listings. Using Airdna’s individual listing data for Virginia between the first quarter of 2015 and the 4th quarter of 2019, we find, on average, Airdna’s performance measures for Occupancy, ADR, and RevPAR were biased upward by 60 percent, 78 percent, and 179 percent, respectively.
期刊介绍:
Cornell Hospitality Quarterly (CQ) publishes research in all business disciplines that contribute to management practice in the hospitality and tourism industries. Like the hospitality industry itself, the editorial content of CQ is broad, including topics in strategic management, consumer behavior, marketing, financial management, real-estate, accounting, operations management, planning and design, human resources management, applied economics, information technology, international development, communications, travel and tourism, and more general management. The audience is academics, hospitality managers, developers, consultants, investors, and students.