A SBM-DDF-GML Algorithm for GTFP of Smart City Agglomeration Based on Matlab

The urban agglomeration in the Changjiang River Delta is one of the most important regional economic centers in mainland China and even the world. In this paper, the annual balance panel data of 27 cities in urban agglomeration in the Changjiang River Delta from 2010 to 2019 were collected, and the energy input and unexpected output were incorporated into the analysis framework of total factor productivity to construct the SBM-DDF model, and the efficiency value based on the SBM-DDF was calculated. From the static point of view, the overall GTFP of the Changjiang River Delta urban agglomeration presents a relatively stable trend. From the perspective of provinces, GTFP from high to low is ANHUI province, JIANGSU Province, SHANGHAI, ZHEJIANG Province; In terms of cities, HEFEI, ANQING, XUANCHENG, CHIZHOU, WENZHOU, CHUZHOU, YANCHENG and JINHUA have higher GTFP, while JIAXING, CHANGZHOU, HUZHOU and MA’ANSHAN have lower GTFP. From the dynamic point of view, when calculated by provinces in the Changjiang River Area, the average value of GML index of GTFP from high to low are SHANGHAI, JIANGSU, ZHEJIANG and ANHUI. Specifically, the GTFP of SHANGHAI, NANJING, NANTONG, WENZHOU, YANCHENG and ZHENJIANG is improving, while that of TAIZHOU, XUANCHENG, SUZHOU and TONGLING is declining. From the decomposition of GML index. Technological advances have deeply influenced changes in the GML index. The conclusion of this study has important policy implications for the Chinese modernization being promoted in mainland China.