Table 4 Average technical, allocative... | Emerald Publishing

Table 4

Average technical, allocative and revenue efficiency with weight restrictions for the period 2000–2020

		Technical	Revenue	Allocative
		Efficiency	Efficiency	Efficiency
1	Melbourne	0.3016	0.25	0.82
2	Sidney	0.3415	0.28	0.83
3	Metro Vancouver	0.5157	0.42	0.82
4	Guangzhou Harbor	1	0.8	0.8
5	Qingdao	1	1	1
6	Shenzhen	0.7143	0.69	0.96
7	Tianjin	1	0.76	0.76
8	Dalian	0.6969	0.52	0.75
9	Xiamen	0.3528	0.31	0.87
10	Ningbo-Zhoushan	0.7776	0.68	0.88
11	Lianyungung	0.3192	0.21	0.67
12	Yingkou	0.7614	0.49	0.64
13	Shanghai	1	1	1
14	Busan, South Korea	0.3777	0.32	0.84
15	Kwangyang	0.834	0.5	0.6
16	Long Beach, USA	0.2314	0.19	0.82
17	Los Angeles, USA	0.274	0.2	0.74
18	Okland – Sn Francisco Bay Area	0.5382	0.37	0.7
19	Tacoma	0.7126	0.6	0.84
20	Seattle	0.6999	0.33	0.47
21	Manila	0.5807	0.25	0.43
22	Hong Kong, China	0.7561	0.68	0.9
23	Tanjung Priok, Jakarta	0.7245	0.67	0.93
24	Tanjung Perak, Surabaya	0.7033	0.55	0.78
25	Keihin ports*, Japan	0.5235	0.36	0.7
26	Hanshin* ports, Japan	0.433	0.28	0.65
27	Nagoya	0.522	0.27	0.52
28	Port Kelang	0.2865	0.26	0.9
29	Tanjung Pelepas	0.2055	0.13	0.66
30	Manzanillo	0.4401	0.42	0.95
31	Lázaro Cárdenas	0.2024	0.17	0.83
32	Callao	0.3176	0.22	0.68
33	Singapore	1	1	1
34	Laem Chabang	0.227	0.19	0.82
35	Bankgok	1	1	1
36	Kaohsiung	0.3063	0.28	0.92
37	Keelung	1	0.63	0.63
38	Ho Chi Minh	0.6338	0.59	0.93

		Technical	Revenue	Allocative
		Efficiency	Efficiency	Efficiency
1	Melbourne	0.3016	0.25	0.82
2	Sidney	0.3415	0.28	0.83
3	Metro Vancouver	0.5157	0.42	0.82
4	Guangzhou Harbor	1	0.8	0.8
5	Qingdao	1	1	1
6	Shenzhen	0.7143	0.69	0.96
7	Tianjin	1	0.76	0.76
8	Dalian	0.6969	0.52	0.75
9	Xiamen	0.3528	0.31	0.87
10	Ningbo-Zhoushan	0.7776	0.68	0.88
11	Lianyungung	0.3192	0.21	0.67
12	Yingkou	0.7614	0.49	0.64
13	Shanghai	1	1	1
14	Busan, South Korea	0.3777	0.32	0.84
15	Kwangyang	0.834	0.5	0.6
16	Long Beach, USA	0.2314	0.19	0.82
17	Los Angeles, USA	0.274	0.2	0.74
18	Okland – Sn Francisco Bay Area	0.5382	0.37	0.7
19	Tacoma	0.7126	0.6	0.84
20	Seattle	0.6999	0.33	0.47
21	Manila	0.5807	0.25	0.43
22	Hong Kong, China	0.7561	0.68	0.9
23	Tanjung Priok, Jakarta	0.7245	0.67	0.93
24	Tanjung Perak, Surabaya	0.7033	0.55	0.78
25	Keihin ports*, Japan	0.5235	0.36	0.7
26	Hanshin* ports, Japan	0.433	0.28	0.65
27	Nagoya	0.522	0.27	0.52
28	Port Kelang	0.2865	0.26	0.9
29	Tanjung Pelepas	0.2055	0.13	0.66
30	Manzanillo	0.4401	0.42	0.95
31	Lázaro Cárdenas	0.2024	0.17	0.83
32	Callao	0.3176	0.22	0.68
33	Singapore	1	1	1
34	Laem Chabang	0.227	0.19	0.82
35	Bankgok	1	1	1
36	Kaohsiung	0.3063	0.28	0.92
37	Keelung	1	0.63	0.63
38	Ho Chi Minh	0.6338	0.59	0.93

Source(s): Author’s own elaboration based on the DEA methodology