Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/192860
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dc.titleResponsive Split Questionnaire Survey Design for the Estimation of Tourist Expenditure
dc.contributor.authorHargreaves, Carol Anne
dc.contributor.authorAng, Khay Wee
dc.date.accessioned2021-07-01T07:18:56Z
dc.date.available2021-07-01T07:18:56Z
dc.date.issued2021-07-30
dc.identifier.citationHargreaves, Carol Anne, Ang, Khay Wee (2021-07-30). Responsive Split Questionnaire Survey Design for the Estimation of Tourist Expenditure. American Journal of Business and Society 6 (3) : 57-63. ScholarBank@NUS Repository.
dc.identifier.urihttps://scholarbank.nus.edu.sg/handle/10635/192860
dc.description.abstractThis survey design is motivated by the need to address the consequences such as non-response, high respondent burden and poor data quality, that lengthy surveys are often associated with. Responsive split design is a survey design technique that directly addresses these consequences. The objective of this study was to reduce the respondent burden and to increase the response rate by using the Split Questionnaire Design (SQD). We leveraged on the idea of issuing only relevant surveys to each respondent as this directly reduces the connotation of being probed with irrelevant questions which is regarded as a primary reason for non-response. To achieve this, we developed a responsive design by utilising the prior information that we collected as part of the questionnaire, and then created decision rules for the administration of the relevant micro-surveys. The results that we have attained are promising in terms of the trade-off between precision and responsiveness. The responsive design offered the advantage of being more responsive to the tourist and was able to detect rare expenditures. This suggests that the responsive design provides improvements in issues regarding missing and rare events. Besides meeting the objectives, we also demonstrated that a secondary advantage of responsive split questionnaires also brings about significant cost savings to the survey organisation.
dc.publisherAmerican Institute of Science
dc.sourceElements
dc.subjectResponsive Split Questionnaire Design
dc.subjectSplit Questionnaire Design
dc.subjectMachine Learning
dc.subjectTourism
dc.typeArticle
dc.date.updated2021-06-30T13:39:10Z
dc.contributor.departmentSTATISTICS & APPLIED PROBABILITY
dc.description.sourcetitleAmerican Journal of Business and Society
dc.description.volume6
dc.description.issue3
dc.description.page57-63
dc.published.statePublished
dc.description.redepositCompleted
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