{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,2]],"date-time":"2025-08-02T18:10:58Z","timestamp":1754158258328,"version":"3.41.2"},"reference-count":12,"publisher":"Emerald","issue":"1","license":[{"start":{"date-parts":[[2014,1,28]],"date-time":"2014-01-28T00:00:00Z","timestamp":1390867200000},"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":[[2014,1,28]]},"abstract":"\n Purpose<\/jats:title>\n \u2013 At present, financial agglomeration tendency in domestic and foreign countries is increasingly evident. Therefore, from a comparative perspective, this paper aims to assess and predict the financial agglomeration degree in central five cities. <\/jats:p>\n <\/jats:sec>\n \n Design\/methodology\/approach<\/jats:title>\n \u2013 According to the diversity of evaluating indexes and the uncertainty of financial agglomeration, this paper constructs a set of indexes of evaluating the financial agglomeration degree, comprehensively evaluates the financial agglomeration degree of the five cities \u2013 Wuhan, Changsha, Zhengzhou, Nanchang and Hefei \u2013 in China's middle region from 2001 to 2010 by using the multiple dimension grey fuzzy decision-making model, and predicts their development tendency by using the GM (1, 1, \u03b2<\/jats:italic>) model. <\/jats:p>\n <\/jats:sec>\n \n Findings<\/jats:title>\n \u2013 The results show that the multiple dimension grey fuzzy decision-making pattern cannot only be used to determine the weights of evaluating indexes, but also get the fuzzy partition and ranking order of the financial agglomeration in central five cities. The grey prediction results can objectively reflect the development tendency of the financial agglomeration in central five cities. <\/jats:p>\n <\/jats:sec>\n \n Practical implications<\/jats:title>\n \u2013 From the results, it is necessary for any competitive city to clarify their relative strengths and weaknesses in order for the accurate location and scientific development, and it also provides a reference for the government decision-making. <\/jats:p>\n <\/jats:sec>\n \n Originality\/value<\/jats:title>\n \u2013 The paper succeeds in using the multiple dimension grey fuzzy decision-making model to measure the financial agglomeration degree of the five central cities and the grey prediction model to predict future trends.<\/jats:p>\n <\/jats:sec>","DOI":"10.1108\/gs-11-2013-0031","type":"journal-article","created":{"date-parts":[[2014,1,23]],"date-time":"2014-01-23T23:52:12Z","timestamp":1390521132000},"page":"95-103","source":"Crossref","is-referenced-by-count":1,"title":["Grey assessment and prediction of the financial agglomeration degree in central five cities"],"prefix":"10.1108","volume":"4","author":[{"given":"Li","family":"Li","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guo-hui","family":"Hu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"140","reference":[{"key":"key2021010322351359200_b4","unstructured":"Ding, Y.\n , \n Li, S.C.\n and \n Li, L.\n (2009), \u201cEvaluation of financial agglomeration degree in China\u201d, Soft Science, Vol. 22 No. 6, pp. 13-17 (in Chinese)."},{"key":"key2021010322351359200_b7","unstructured":"Huang, J.Y.\n and \n Yang, Z.B.\n (2006), Financial Agglomeration Theory, China Social Sciences Press, Beijing (in Chinese)."},{"key":"key2021010322351359200_b11","unstructured":"Ji, P.R.\n , \n Zhang, J.\n and \n Zhou, H.B.\n (2011), \u201cA modified unbiased GM(1, 1)\u201d, Proceeding of 2011 IEEE International Conference on Grey Systems and Intelligent Service, pp. 186-189."},{"key":"key2021010322351359200_b2","unstructured":"Kindleberger, C.\n (1974), The Formation of Financial Centers: A Study in Comparative Economy History, Princeton University, Princeton, NJ."},{"key":"key2021010322351359200_b3","unstructured":"Li, J.\n (2010), \u201cFinancial industry agglomeration: a review\u201d, Financial and Economic, Vol. 28 No. 8, pp. 96-99 (in Chinese)."},{"key":"key2021010322351359200_b10","unstructured":"Li, X.C.\n and \n Wang, J.\n (2009), \u201cThe pattern of multi-objective and multi-dimensional grey-fuzzy decision with itself feedback\u201d, Proceedings of 2009 IEEE International Conference on Grey Systems and Intelligent Services, pp. 1087-1091."},{"key":"key2021010322351359200_b12","doi-asserted-by":"crossref","unstructured":"Li, X.C.\n , \n Yu, T.\n and \n Yuan, Z.\n (2013), \u201cGrey GM (1, 1, \u03b2) model and its applicable region\u201d, Grey Systems: Theory and Application, Vol. 3 No. 3, pp. 266-275.","DOI":"10.1108\/GS-04-2013-0005"},{"key":"key2021010322351359200_b9","unstructured":"Liu, H.\n (2008), \u201cThe growth and radiation effects of the financial agglomeration on the regional economic\u201d, Financial and Economic, Vol. 28 No. 6, pp. 15-20 (in Chinese)."},{"key":"key2021010322351359200_b1","unstructured":"Porteous, D.J.\n (1995), Geography of Finance, Aldershot Press, Aldershot."},{"key":"key2021010322351359200_b5","unstructured":"Yin, X.S.\n , \n He, Y.F.\n and \n Xu, H.S.\n (2003), \u201cAnalysis on the financial agglomeration situation in the Yangtze River Delta and ways to enhance competitiveness\u201d, Shanghai Financial, Vol. 23 No. 8, pp. 42-44 (in Chinese)."},{"key":"key2021010322351359200_b6","unstructured":"Zhang, Z.H.\n (2005), \u201cThe indicators evaluation methods and system of the international financial center\u201d, Social Science Research, Vol. 26 No. 1, pp. 49-52 (in Chinese)."},{"key":"key2021010322351359200_b8","unstructured":"Zong, X.W.\n (2008), The Financial Agglomeration Factors Research in China's Regional Economic Growth, Nanjing Normal University, Nanjing (in Chinese)."}],"container-title":["Grey Systems: Theory and 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