{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,2]],"date-time":"2026-03-02T23:41:31Z","timestamp":1772494891290,"version":"3.50.1"},"reference-count":81,"publisher":"Emerald","issue":"5","license":[{"start":{"date-parts":[[2020,3,17]],"date-time":"2020-03-17T00:00:00Z","timestamp":1584403200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IMDS"],"published-print":{"date-parts":[[2020,3,17]]},"abstract":"<jats:sec><jats:title content-type=\"abstract-subheading\">Purpose<\/jats:title><jats:p>The purpose of this paper is to examine the potential impacts of various variables on product return activities after online shopping. Previous studies on customer behaviour have been predominantly concerned with return on used products and other product-quality-related constructs in the model. This study aims to specially examine the logistics service-related and customer intention\u2013related variables for general products under the e-commerce circumstance.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Design\/methodology\/approach<\/jats:title><jats:p>Structured questionnaire data for this study were collected in the two southeast cities of China (162 useable responses). Structural equation modelling was used to examine the latent variables.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Findings<\/jats:title><jats:p>The results confirmed that product return intention has the greatest impact on online shopping returns with a direct effect of 0.63, followed by the flexibility in return (logistics service) with a direct effect of 0.49.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Originality\/value<\/jats:title><jats:p>Such a model not only enriches the theoretical understanding of customer behaviour studies but also offers online shopping stores and platforms a quantitative benchmark and new perspective on the design of online shopping supply chains by considering product returns so as to improve the customer satisfaction.<\/jats:p><\/jats:sec>","DOI":"10.1108\/imds-05-2019-0296","type":"journal-article","created":{"date-parts":[[2020,3,18]],"date-time":"2020-03-18T21:30:00Z","timestamp":1584567000000},"page":"883-902","source":"Crossref","is-referenced-by-count":16,"title":["Analysis of customers' return behaviour after online shopping in China using SEM"],"prefix":"10.1108","volume":"120","author":[{"given":"Danping","family":"Lin","sequence":"first","affiliation":[]},{"given":"Carman Ka Man","family":"Lee","sequence":"additional","affiliation":[]},{"given":"M.K.","family":"Siu","sequence":"additional","affiliation":[]},{"given":"Henry","family":"Lau","sequence":"additional","affiliation":[]},{"given":"King Lun","family":"Choy","sequence":"additional","affiliation":[]}],"member":"140","reference":[{"issue":"6","key":"key2020050410064445600_ref001","doi-asserted-by":"crossref","first-page":"1353","DOI":"10.1108\/BPMJ-02-2015-0022","article-title":"An integrated model of factors affecting 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