Andrea Pellegrini , Antonio Borriello , John M. Rose
{"title":"在 Logit 混合 Logit 模型框架内,澳大利亚社区对酒店检疫选择的偏好","authors":"Andrea Pellegrini , Antonio Borriello , John M. Rose","doi":"10.1016/j.jocm.2024.100473","DOIUrl":null,"url":null,"abstract":"<div><p>In response to the Covid-19 pandemic, many countries have adopted measures to contain the spread of the virus, including mandatory quarantine for inbound travellers. This research investigates the preferences of residents of New South Wales, Australia, towards the mandatory quarantine protocol adopted in the state. Heterogeneity in individual preferences is explored by advancing the Logit Mixed Logit (LML) model defined by Train (2016). Two approaches are suggested to decompose individual heterogeneity in this framework and are applied to data collected via a stated preference experiment. The empirical findings demonstrate that on average, the community prefers returned travellers be quarantined in dedicated quarantine facilities rather than be quarantined at home or using hotels, but are mostly indifferent to how long travellers are quarantined for, and how many travellers are allowed to return to Australia. The sample do however have a preference, on average for travellers having to pay less to quarantine, meaning they wish to see greater government subsidies. However, the modelling approach demonstrates that the common use of averages potentially masks diverse preferences, and is not representative of community wants and desires, thus possibly leading to incorrect inferences about policy impacts.</p></div>","PeriodicalId":46863,"journal":{"name":"Journal of Choice Modelling","volume":"50 ","pages":"Article 100473"},"PeriodicalIF":2.8000,"publicationDate":"2024-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S175553452400006X/pdfft?md5=5d3108f3679923ab3cb80ea059643fee&pid=1-s2.0-S175553452400006X-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Australian community preferences for hotel quarantine options within the Logit Mixed Logit Model framework\",\"authors\":\"Andrea Pellegrini , Antonio Borriello , John M. Rose\",\"doi\":\"10.1016/j.jocm.2024.100473\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>In response to the Covid-19 pandemic, many countries have adopted measures to contain the spread of the virus, including mandatory quarantine for inbound travellers. This research investigates the preferences of residents of New South Wales, Australia, towards the mandatory quarantine protocol adopted in the state. Heterogeneity in individual preferences is explored by advancing the Logit Mixed Logit (LML) model defined by Train (2016). Two approaches are suggested to decompose individual heterogeneity in this framework and are applied to data collected via a stated preference experiment. The empirical findings demonstrate that on average, the community prefers returned travellers be quarantined in dedicated quarantine facilities rather than be quarantined at home or using hotels, but are mostly indifferent to how long travellers are quarantined for, and how many travellers are allowed to return to Australia. The sample do however have a preference, on average for travellers having to pay less to quarantine, meaning they wish to see greater government subsidies. However, the modelling approach demonstrates that the common use of averages potentially masks diverse preferences, and is not representative of community wants and desires, thus possibly leading to incorrect inferences about policy impacts.</p></div>\",\"PeriodicalId\":46863,\"journal\":{\"name\":\"Journal of Choice Modelling\",\"volume\":\"50 \",\"pages\":\"Article 100473\"},\"PeriodicalIF\":2.8000,\"publicationDate\":\"2024-02-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S175553452400006X/pdfft?md5=5d3108f3679923ab3cb80ea059643fee&pid=1-s2.0-S175553452400006X-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Choice Modelling\",\"FirstCategoryId\":\"96\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S175553452400006X\",\"RegionNum\":3,\"RegionCategory\":\"经济学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ECONOMICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Choice Modelling","FirstCategoryId":"96","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S175553452400006X","RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECONOMICS","Score":null,"Total":0}
Australian community preferences for hotel quarantine options within the Logit Mixed Logit Model framework
In response to the Covid-19 pandemic, many countries have adopted measures to contain the spread of the virus, including mandatory quarantine for inbound travellers. This research investigates the preferences of residents of New South Wales, Australia, towards the mandatory quarantine protocol adopted in the state. Heterogeneity in individual preferences is explored by advancing the Logit Mixed Logit (LML) model defined by Train (2016). Two approaches are suggested to decompose individual heterogeneity in this framework and are applied to data collected via a stated preference experiment. The empirical findings demonstrate that on average, the community prefers returned travellers be quarantined in dedicated quarantine facilities rather than be quarantined at home or using hotels, but are mostly indifferent to how long travellers are quarantined for, and how many travellers are allowed to return to Australia. The sample do however have a preference, on average for travellers having to pay less to quarantine, meaning they wish to see greater government subsidies. However, the modelling approach demonstrates that the common use of averages potentially masks diverse preferences, and is not representative of community wants and desires, thus possibly leading to incorrect inferences about policy impacts.