{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,19]],"date-time":"2025-10-19T15:49:35Z","timestamp":1760888975786,"version":"3.41.2"},"reference-count":29,"publisher":"Emerald","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2015,2,2]]},"abstract":"<jats:sec>\n                  <jats:title>Purpose<\/jats:title>\n                  <jats:p>\u2013 The purpose of this paper is to elevate the accuracy when predicting the gross domestic product (GDP) on research and development (R&amp;D) and to develop the grey delay Lotka-Volterra model.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Design\/methodology\/approach<\/jats:title>\n                  <jats:p>\u2013 Considering the lag effects between input in R&amp;D and output in GDP, this paper estimated the delay value via grey delay relation analysis. Taking the delay into original Lotka-Volterra model and combining with the thought of grey theory and grey transform, the authors proposed grey delay Lotka-Volterra model, estimated the parameter of model and gave the discrete time analytic expression.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Findings<\/jats:title>\n                  <jats:p>\u2013 Collecting the actual data of R&amp;D and GDP in Wuhan China from 1995 until 2008, this paper figure out that the delay between R&amp;D and GDP was 2.625 year and found the dealy time would would gradually be reduced with the economy increasing.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Practical implications<\/jats:title>\n                  <jats:p>\u2013 Constructing the grey delay Lotka-Volterra model via above data, this paper shown that the precision was satisfactory when fitting the data of R&amp;D and GDP. Comparing the forecasts with the actual data of GDP in Wuhan from 2009 until 2012, the error was small.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Social implications<\/jats:title>\n                  <jats:p>\u2013 The result shows that R&amp;D and GDP would be both growing fast in future. Wuhan will become a city full of activity.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Originality\/value<\/jats:title>\n                  <jats:p>\u2013 Considering the lag between R&amp;D and GDP, this work estimated the delay value via a grey delay relation analysis and constructed a novel grey delay Lotka-Volterra model.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1108\/gs-11-2014-0042","type":"journal-article","created":{"date-parts":[[2015,2,13]],"date-time":"2015-02-13T09:35:58Z","timestamp":1423820158000},"page":"74-88","source":"Crossref","is-referenced-by-count":6,"title":["The impact of R&amp;D on GDP study based on grey delay Lotka-Volterra model"],"prefix":"10.1108","volume":"5","author":[{"given":"Shuhua","family":"Mao","sequence":"first","affiliation":[{"name":"Reliability Engineering Center, Wuhan University of technology, Wuhan, China"}]},{"given":"Mingyun","family":"Gao","sequence":"additional","affiliation":[{"name":"School of Science, Wuhan University of Technology, Wuhan, China"}]},{"given":"Min","family":"Zhu","sequence":"additional","affiliation":[{"name":"School of Science, Wuhan University of Technology, Wuhan, China"}]}],"member":"140","reference":[{"issue":"10","key":"2025072817353900600_b1","doi-asserted-by":"crossref","first-page":"3000","DOI":"10.1016\/j.cnsns.2009.10.021","article-title":"Three-dimensional discrete -time Lotka-Volterra models with an application to industrial clusters","volume":"15","author":"","year":"2010","journal-title":"Communications in Nonlinear Science and Numerical Simulation"},{"issue":"3","key":"2025072817353900600_b2","doi-asserted-by":"crossref","first-page":"335","DOI":"10.1007\/s00180-007-0044-1","article-title":"Parameter cascades and profiling in functional data analysis","volume":"22","author":"","year":"2007","journal-title":"Computational Statistics"},{"issue":"2","key":"2025072817353900600_b3","doi-asserted-by":"crossref","first-page":"383","DOI":"10.1016\/j.techfore.2011.05.007","article-title":"An application of Lotka-Volterra model to Taiwan\u2019s transition from 200\u2009mm to 300\u2009mm silicon wafers","volume":"79","author":"","year":"2012","journal-title":"Technological Forecasting and Social Change"},{"key":"2025072817353900600_b4","unstructured":"Cobb, C.W.\n           and Douglas, P.H. 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