{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T02:00:51Z","timestamp":1760061651303,"version":"3.41.2"},"reference-count":37,"publisher":"Emerald","issue":"4","license":[{"start":{"date-parts":[[2017,11,20]],"date-time":"2017-11-20T00:00:00Z","timestamp":1511136000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["LHT"],"published-print":{"date-parts":[[2017,11,20]]},"abstract":"<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Purpose<\/jats:title>\n<jats:p>This research intends to look at the regional characteristics through an analysis of crowd preference and confidence, and investigates how regional characteristics are going to affect human beings at all aspects in a scenario of sharing economy. The purpose of this paper is to introduce an approach to provide an understandable rating score. Furthermore, the paper aims to find the relationships between different features classified in this study by using machine learning methods. Furthermore, due to the importance of performance of methods, the performance of the features is also improved.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Design\/methodology\/approach<\/jats:title>\n<jats:p>The Rating Matching Rate (RMRate) approach is proposed to provide score in terms of simplicity and understandability for all features. The relationships between features can be extracted from accommodation data set using decision tree (DT) algorithms (J48, HoeffdingTree, and REPTree). Usability of these methods was evaluated using different metrics. Two techniques, \u201cClassBalancer\u201d and \u201cSpreadSubsample,\u201d are applied to improve the performance of algorithms.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Findings<\/jats:title>\n<jats:p>Experimental outcomes using the RMRate approach show that the scores are very easy to understand. Three property types are very popular almost in all of selected countries in this study (\u201capartment\u201d, \u201chouse\u201d, and \u201cbed and breakfast\u201d). The findings also indicate that \u201cEntire home\/apt\u201d is the most common room-type and 4.5 and 5 star-rating are the most given star-rating by users. The proposed DT algorithms can find the relationships between features significantly. In addition, applied CB and SS techniques could improve the performance of algorithms efficiently.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Originality\/value<\/jats:title>\n<jats:p>This study gives precise details about the guests\u2019 preferences and hosts\u2019 preferences. The proposed techniques can effectively improve the performance in predicting the behavior of users in sharing economy. The findings can also help group decision making in P2P platforms efficiently.<\/jats:p>\n<\/jats:sec>","DOI":"10.1108\/lht-01-2017-0030","type":"journal-article","created":{"date-parts":[[2017,10,30]],"date-time":"2017-10-30T19:13:03Z","timestamp":1509390783000},"page":"521-541","source":"Crossref","is-referenced-by-count":18,"title":["Understanding regional characteristics through crowd preference and confidence mining in P2P accommodation rental service"],"prefix":"10.1108","volume":"35","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3059-6357","authenticated-orcid":false,"given":"Moloud","family":"Abdar","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Neil Y.","family":"Yen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"140","reference":[{"issue":"3-4","key":"key2020120501484303600_ref001","first-page":"203","article-title":"Sharing economy and its effect on human behavior changes in accommodation: a survey on Airbnb","volume":"2","year":"2017","journal-title":"International Journal of Social and Humanistic Computing"},{"key":"key2020120501484303600_ref002","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/ACCESS.2017.2735242","article-title":"Design of a universal user model for dynamic crowd preference sensing and decision-making behavior analysis","volume":"5","year":"2017","journal-title":"IEEE Access"},{"year":"2015","key":"key2020120501484303600_ref003","article-title":"Understanding the sharing economy: the role of response to negative reviews in the peer-to-peer accommodation sharing network"},{"year":"2017","key":"key2020120501484303600_ref004","article-title":"The silent treatment: LGBT discrimination in the sharing economy"},{"year":"2017","key":"key2020120501484303600_ref005","article-title":"An empirical study of the web presence model to evaluate the web features of small-and-medium-sized hotels (SMHs) in the Malaysian hotel industry"},{"key":"key2020120501484303600_ref006","doi-asserted-by":"crossref","unstructured":"Ert, E., Fleischer, A. and Magen, N. 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