{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,13]],"date-time":"2026-02-13T20:28:10Z","timestamp":1771014490765,"version":"3.50.1"},"reference-count":112,"publisher":"Emerald","issue":"2","license":[{"start":{"date-parts":[[2016,6,6]],"date-time":"2016-06-06T00:00:00Z","timestamp":1465171200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2016,6,6]]},"abstract":"<jats:sec>\n               <jats:title content-type=\"abstract-heading\">Purpose<\/jats:title>\n               <jats:p> \u2013 China is the world\u2019s largest user market for digital technologies and experiencing unprecedented rates of rural-urban migration set to create the world\u2019s first \u201curban billion\u201d. This is an important context for studying nuanced adoption behaviours that define a digital divide. Large-scale studies are required to determine what behaviours exist in such populations, but can offer limited ability to draw inferences about why. The purpose of this paper is to report a large-scale study inside China that probes a nuanced \u201cdigital divide\u201d behaviour: consumer demographics indicating ability to pay by electronic means but behaviour suggesting lack of willingness to do so, and extends current demographics to help explain this. <\/jats:p>\n            <\/jats:sec>\n            <jats:sec>\n               <jats:title content-type=\"abstract-heading\">Design\/methodology\/approach<\/jats:title>\n               <jats:p> \u2013 The authors report trans-national access to commercial \u201cBig Data\u201d inside China capturing the demographics and consumption of millions of consumers across a wide range of physical and digital market channels. Focusing on one urban location we combine traditional demographics with a new measure that reflecting migration: \u201cDistance from Home\u201d, and use data-mining techniques to develop a model that predicts use behaviour. <\/jats:p>\n            <\/jats:sec>\n            <jats:sec>\n               <jats:title content-type=\"abstract-heading\">Findings<\/jats:title>\n               <jats:p> \u2013 Use behaviour is predictable. Most use is explained by value of the transaction. \u201cDistance from Home\u201d is more predictive of technology use than traditional demographics. <\/jats:p>\n            <\/jats:sec>\n            <jats:sec>\n               <jats:title content-type=\"abstract-heading\">Research limitations\/implications<\/jats:title>\n               <jats:p> \u2013 Results suggest traditional demographics are insufficient to explain \u201cwhy\u201d use\/non-use occurs and hence an insufficient basis to formulate and target government policy. <\/jats:p>\n            <\/jats:sec>\n            <jats:sec>\n               <jats:title content-type=\"abstract-heading\">Originality\/value<\/jats:title>\n               <jats:p> \u2013 The authors understand this to be the first large-scale trans-national study of use\/non-use of digital channels within China, and the first study of the impact of distance on ICT adoption.<\/jats:p>\n            <\/jats:sec>","DOI":"10.1108\/itp-10-2014-0243","type":"journal-article","created":{"date-parts":[[2016,5,16]],"date-time":"2016-05-16T04:37:57Z","timestamp":1463373477000},"page":"250-279","source":"Crossref","is-referenced-by-count":10,"title":["Able but not willing? Exploring divides in digital versus physical payment use in China"],"prefix":"10.1108","volume":"29","author":[{"given":"Ashley D.","family":"Lloyd","sequence":"first","affiliation":[]},{"given":"Mario","family":"Antonioletti","sequence":"additional","affiliation":[]},{"given":"Terence M.","family":"Sloan","sequence":"additional","affiliation":[]}],"member":"140","reference":[{"key":"key2020121504214356600_b1","doi-asserted-by":"crossref","unstructured":"Akka\u015f, E.\n               , \n                  Akina, L.\n               , \n                  \u00c7ubuk\u00e7ua, H.E.\n                and \n                  Artuner, H.\n                (2015), \u201cApplication of decision tree algorithm for classification and identification of natural minerals using SEM-EDS\u201d, \n                  Computers & Geosciences\n               , Vol. 80, pp. 38-48.","DOI":"10.1016\/j.cageo.2015.03.015"},{"key":"key2020121504214356600_b2","unstructured":"Alipay\n                (2013), 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