{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,12]],"date-time":"2026-05-12T01:34:22Z","timestamp":1778549662050,"version":"3.51.4"},"reference-count":26,"publisher":"Emerald","issue":"1","license":[{"start":{"date-parts":[[2019,2,4]],"date-time":"2019-02-04T00:00:00Z","timestamp":1549238400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["GS"],"published-print":{"date-parts":[[2019,2,4]]},"abstract":"<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Purpose<\/jats:title>\n<jats:p>The purpose of this paper is to predict the main economic indices of online shopping in China.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Design\/methodology\/approach<\/jats:title>\n<jats:p>A fractional order weakening buffer operator (WBO) for the GM(1,1) model is put forward in order to solve the problem of limited nonlinear data. The order number of WBO can adjust in line with the scenario.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Findings<\/jats:title>\n<jats:p>The experimental results indicate that the proposed method can consider the scenario and obtain more accurate forecasting results.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Originality\/value<\/jats:title>\n<jats:p>This study found that the slowdown of growth trend after the previous high speed expansion period will continue, and the online shopping sellers should make more efforts to develop potential consumers to increase its turnover.<\/jats:p>\n<\/jats:sec>","DOI":"10.1108\/gs-08-2018-0036","type":"journal-article","created":{"date-parts":[[2018,12,5]],"date-time":"2018-12-05T09:30:31Z","timestamp":1544002231000},"page":"128-140","source":"Crossref","is-referenced-by-count":9,"title":["Using fractional order weakening buffer operator to forecast the main indices 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