{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,20]],"date-time":"2026-02-20T01:56:02Z","timestamp":1771552562513,"version":"3.50.1"},"reference-count":21,"publisher":"Emerald","issue":"3","license":[{"start":{"date-parts":[[2015,11,2]],"date-time":"2015-11-02T00:00:00Z","timestamp":1446422400000},"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":[[2015,11,2]]},"abstract":"\n Purpose<\/jats:title>\n \u2013 The purpose of this paper is to find the reason which the results of grey variable weight clustering method do not correspond with the reality. It proposes reconstructing the whitenization weight function, outlining why and how inconsistency is avoided. The study aims to improve the model of grey clustering method based on the whitenization weight function and list the steps of the new clustering model so that analysis and application of innovation capacity in a broader range is normally found. <\/jats:p>\n <\/jats:sec>\n \n Design\/methodology\/approach<\/jats:title>\n \u2013 First the reason for the problem that the clustering results of grey variable weight clustering do not correspond with the reality is analyzed in two existing literature. And then a new whitenization weight function is reconstructed, two properties of the whitenization weight function are proved. The solution of the new grey variable weight clustering based on the whitenization weight function is built by following six steps. <\/jats:p>\n <\/jats:sec>\n \n Findings<\/jats:title>\n \u2013 The paper provides a new whitenization weight function which satisfies the normative and non-triplecrossing. It suggests that successful clustering results of innovation capacity act on two levels: integrating the elements of innovation capacity indexes, and following steps of grey variable weight clustering. <\/jats:p>\n <\/jats:sec>\n \n Originality\/value<\/jats:title>\n \u2013 This paper improves the existing method of grey variable weight clustering and fulfills an identified need to study how cities\u2019 innovation capacity can be clustered.<\/jats:p>\n <\/jats:sec>","DOI":"10.1108\/gs-03-2015-0010","type":"journal-article","created":{"date-parts":[[2015,10,27]],"date-time":"2015-10-27T15:42:06Z","timestamp":1445960526000},"page":"344-353","source":"Crossref","is-referenced-by-count":5,"title":["Quantitative analysis of the cities\u2019 innovation capacity based on grey variable weight clustering"],"prefix":"10.1108","volume":"5","author":[{"given":"Yeqing","family":"Guan","sequence":"first","affiliation":[]},{"given":"Hua","family":"Liu","sequence":"additional","affiliation":[]},{"given":"Ying","family":"Zhu","sequence":"additional","affiliation":[]}],"member":"140","reference":[{"key":"key2020121920143632300_b4","unstructured":"Chi, G.T.\n and \n Cheng, Y.Q.\n (2010), \u201cThe society evaluation model based on grey clustering and its empirical study of cities under province\u201d, \n Chinese Journal of Management Science\n , Vol. 18 No. 6, pp. 185-192."},{"key":"key2020121920143632300_b8","unstructured":"Dang, Y.G.\n , \n Liu, S.F.\n and \n Liu, B.\n (2005), \u201cStudy on the integrated grey clustering method under the clustering coefficient with non-distinguished difference\u201d, \n Chinese Journal of Management Science\n , Vol. 13 No. 4, pp. 69-73."},{"key":"key2020121920143632300_b1","doi-asserted-by":"crossref","unstructured":"Deng, J.L.\n (1982), \u201cThe control problem of grey systems\u201d, \n Systems & Control Letter\n , Vol. 1 No. 5, pp. 288-294.","DOI":"10.1016\/S0167-6911(82)80025-X"},{"key":"key2020121920143632300_b9","unstructured":"Dong, Y.Z.\n and \n Dang, Y.G.\n (2009), \u201cGrey clustering method based on maximizing deviations\u201d, \n Systems Engineering-Theory & Practice\n , Vol. 29 No. 9, pp. 141-146."},{"key":"key2020121920143632300_b17","unstructured":"Duan, L.Z.\n and \n Liu, S.F.\n (2004), \u201cAppraisement of city innovation ability by gray cluster analysis\u201d, \n Journal of Beijing University of Technology\n , Vol. 29 No. 4, pp. 508-512."},{"key":"key2020121920143632300_b16","unstructured":"He, R.\n (2012), \u201cResearch on the evaluation to innovation ability of innovative cities\u201d, Hefei University of Technology, Hefei."},{"key":"key2020121920143632300_b6","unstructured":"Li, M.\n (2011), \u201cWater quality of pipe network based on the grey clustering method\u201d, \n Systems Engineering\n , Vol. 29 No. 7, pp. 123-126."},{"key":"key2020121920143632300_b12","unstructured":"Liu, L.\n , \n Chen, J.H.\n and \n Zheng, H.L.\n (2012), \u201cEvaluation system of mineral resource utilization for mining based on grey variable weight cluster and dominance-based rough set\u201d, \n Journal of Central South University (Science and Technology)\n , Vol. 43 No. 1, pp. 278-286."},{"key":"key2020121920143632300_b2","unstructured":"Liu, S.F.\n (1997), \u201cForrest. 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