Table 4 Potential improvement for the 38 cities.

From: Decomposing the comprehensive efficiency of major cities into divisions on governance, ICT and sustainability: network slack-based measure model

DMU	INPUT		Link		INPUT			Link	INPUT			OUTPUT
DMU	\({x}_{1j}^{g}\)(%)	\({x}_{2j}^{g}\)(%)	\({z}_{j}^{{gi}}\)(%)	\({z}_{j}^{{gs}}\)(%)	\({x}_{1j}^{i}\)(%)	\({x}_{2j}^{i}\)(%)	\({x}_{3j}^{i}\)(%)	\({z}_{j}^{{is}}\)(%)	\({x}_{1j}^{s}\)(%)	\({x}_{2j}^{s}\)(%)	\({x}_{3j}^{s}\)(%)	\({y}_{1j}^{s}\)(%)	\({u}_{1j}^{s}\)(%)	\({y}_{2j}^{s}\)(%)	\({y}_{3j}^{s}\)(%)	\({y}_{4j}^{s}\)(%)	\({u}_{2j}^{s}\)(%)	\({y}_{5j}^{s}\)(%)
Beijing	0	−0.03	0	0	−0.01	−0.01	0	0	0	0	0	0	0	0	0	0	0	0
Shanghai	0	0	−0.03	−67.26	−0.01	−0.01	−0.01	−0.06	0	0	0	0	0	0	0	0	0	0
Guangzhou	−19.91	−15.28	0	−0.01	−64.83	−71.32	−44.66	0	−0.06	−0.03	0	0	−0.04	0	0	0.02	−0.02	0
Shenzhen	−7.96	−1.93	0	−68.56	−50.78	−43.21	−22.22	0	0	0	0	0	0	0	0	0	0	0
Chengdu	−46.23	−25.16	0	−70.68	−90.25	−74.1	−72.06	0	0	0	0	0	0	0	0	0	0	0
Hangzhou	−44.44	−9.19	0	−66.93	−79.55	−53.59	−53.71	0	0	0	0	0	0	0	0	0	0	0
Chongqing	−37.53	−32.59	−35.1	−36.46	−33.84	−79.04	−81.47	13.61	0	−27.3	−34.88	102.72	0	0	44.61	59.99	−8.38	11.1
Wuhan	−60.12	−0.15	−41.11	−83.46	−74.15	−57.39	−59.4	43.72	−28.11	0	−59.3	0	0	0	0	39.04	−26.11	8.27
Xi’an	−35.74	−18.82	−7.57	−9.99	−74.71	−61.04	−49.75	66.25	−16.57	0	−60.13	28.42	−26.64	0	21.96	32.08	−45.41	10.67
Suzhou	−33.71	−3.34	0	−60.1	−58.43	−45.02	−58.4	0	0	0	0	0	0	0	0	0	0	0
Tianjin	−69.72	−28.26	−54.82	−71.28	−71.12	−61.39	−51.83	25.11	0	−29.82	−48.94	7.95	−20.16	0	0.78	23	−16.37	14.19
Nanjing	−50.29	0	0	−65.1	−87.14	−44.92	−59.38	0	0	0	0	0	0	0	0	0	0	0
Changsha	−42.11	−30.84	−25.65	−28.39	−3.18	−49.78	−39.7	158.39	−18.24	−5.1	−45.17	0	−1.95	0	23.99	62.62	−16.64	7.01
Zhengzhou	−31.62	0	0	−45.83	−78.51	−52.44	−53.58	0	0	0	0	0	0	0	0	0	0	0
Dongguan	−23.62	−27.53	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
Qingdao	−43.74	0	0	−55.35	−48.47	−45.75	−31.3	0	0	0	0	0	0	0	0	0	0	0
Shenyang	−44.33	−21.2	0	−3.27	−42.51	−45.29	−22.2	0	0	0	0	0	0	0	0	0	0	0
Hefei	−24.73	−40.1	−28.44	−77.54	−50.48	−35.73	−37.88	145.69	−44.71	−11.52	−76.77	0	−15.42	2.5	6.19	3.25	−28.57	0.68
Foshan	−31.21	−8.97	3.59	−71.38	0	−31.52	−5.57	0.47	−3.51	−0.78	−3.53	0	−1.91	1.42	0	1.42	−0.6	0
Wuxi	−24.55	0	0	−17.69	−62.79	−17.85	−30.88	0	0	0	0	0	0	0	0	0	0	0
Ningbo	−21.37	0	0	−53.54	−32.63	−31.51	−34	0	0	0	0	0	0	0	0	0	0	0
Kunming	−33.68	−39.18	0	2.25	−47.03	−39.97	−29.24	0	0	0	0	0	0	0	0	0	0	0
Dalian	−17.88	0	0	16.2	−73.22	−14.1	−0.34	0	0	0	0	0	0	0	0	0	0	0
Fuzhou	−33.12	−16.95	0	−31.06	−68.08	−30.09	−47.08	0	0	0	0	0	0	0	0	0	0	0
Xiamen	−18.5	−5.92	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
Harbin	0	0	0	0	−73.53	−37.97	−10.22	0	0	0	0	0	0	0	0	0	0	0
Jinan	−51.81	−2.84	0	−57.51	−80.05	−38.61	−51.38	0	0	0	0	0	0	0	0	0	0	0
Wenzhou	−29.19	−10.22	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
Nanning	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
Changchun	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
Quanzhou	0	−10.51	0	62.17	0	−8.25	−20.41	0	0	0	0	0	0	0	0	0	0	0
Shijiazhuang	−31.96	−32.88	−12.05	56.69	−68.1	−50.38	−50.46	23.73	−11.46	−24.46	−66.84	100.98	−41.8	0	18.18	55.92	−53.39	0
Guiyang	0	−13.75	0	−28.48	−49.85	−10.52	0	0	0	0	0	0	0	0	0	0	0	0
Nanchang	−17.06	−8.82	0	−37.51	−45.41	−30.61	−44.26	0	0	0	0	0	0	0	0	0	0	0
Jinhua	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
Changzhou	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
Nantong	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
Jiaxing	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
Average	−24.3718	−10.6437	−5.2942	−25.528	−39.7016	−30.5634	−27.9313	12.5503	−3.2279	−2.6055	−10.41	6.3176	−2.84	0.1032	3.045	7.2984	−5.1445	1.3663

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Table 4 Potential improvement for the 38 cities.

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