{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T04:51:26Z","timestamp":1777611086343,"version":"3.51.4"},"reference-count":27,"publisher":"Emerald","issue":"3","license":[{"start":{"date-parts":[[2020,9,3]],"date-time":"2020-09-03T00:00:00Z","timestamp":1599091200000},"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":[[2021,6,18]]},"abstract":"<jats:sec><jats:title content-type=\"abstract-subheading\">Purpose<\/jats:title><jats:p>The purpose of this paper is to examine the effectiveness of an improved dummy variables control grey model (<jats:italic>DVCGM<\/jats:italic>) considering the hysteresis effect of government policies in China's energy intensity (EI) forecasting.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Design\/methodology\/approach<\/jats:title><jats:p>Energy consumption is considered as an important driver of economic development. China has introduced policies those aim at the optimization of energy structure and EI. In this study, EI is forecasted by an improved <jats:italic>DVCGM<\/jats:italic>, considering the hysteresis effect of energy-saving policies of the government. A nonlinear optimization method based on particle swarm optimization (PSO) algorithm is constructed to calculate the hysteresis parameter. A one-step rolling mechanism is applied to provide input data of the prediction model. Grey model (<jats:italic>GM<\/jats:italic>) (1, N), <jats:italic>DVCGM<\/jats:italic> (1, N) and <jats:italic>ARIMA<\/jats:italic> model are applied to test the accuracy of the improved <jats:italic>DVCGM<\/jats:italic> (1, N) model prediction.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Findings<\/jats:title><jats:p>The results show that the improved <jats:italic>DVCGM<\/jats:italic> provides reliable results and works well in simulation and predictions using multivariable data in small sample size and time-lag virtual variable. Accordingly, the improved <jats:italic>DVCGM<\/jats:italic> notes the hysteresis effect of government policies and significantly improves the prediction accuracy of China's EI than the other three models.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Originality\/value<\/jats:title><jats:p>This study estimates the EI considering the hysteresis effect of energy-saving policies in China by using an improved <jats:italic>DVCGM<\/jats:italic>. The main contribution of this paper is to propose a model to estimate EI, considering the hysteresis effect of energy-saving policies and improve forecasting accuracy.<\/jats:p><\/jats:sec>","DOI":"10.1108\/gs-02-2020-0022","type":"journal-article","created":{"date-parts":[[2020,9,3]],"date-time":"2020-09-03T05:57:58Z","timestamp":1599112678000},"page":"372-393","source":"Crossref","is-referenced-by-count":9,"title":["Forecasting China's energy intensity by using an improved <i>DVCGM<\/i> (1, N) model considering the hysteresis 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