Integrated Approach to Construction of Benchmarking Network in DEA-Based Stepwise Benchmark Target Selection
Abstract
:1. Introduction
2. Problem Definition
3. Proposed Method
3.1. Stratification of DMUs
3.2. Classification of DMUs Based on Similarity of Benchmarking Direction
3.3. Benchmarking Network Construction
4. Application
5. Concluding Remarks
Author Contributions
Conflicts of Interest
Abbreviations
DEA | data envelopment analysis |
DMUs | decision-making units |
IBTs | intermediate benchmark targets |
UBT | ultimate benchmark target |
Appendix A
Store | x1 | x2 | y | Efficiency | |||
---|---|---|---|---|---|---|---|
CRS | VRS | SE | Returns to Scale | ||||
A | 2 | 4 | 1 | 1.00 | 1.00 | 1.00 | CRS |
B | 4 | 2 | 1 | 1.00 | 1.00 | 1.00 | CRS |
C | 8 | 1 | 1 | 1.00 | 1.00 | 1.00 | CRS |
D | 3 | 6 | 1 | 0.66 | 0.66 | 1.00 | CRS |
E | 4 | 3 | 1 | 0.85 | 0.85 | 1.00 | CRS |
F | 5 | 2 | 1 | 0.92 | 0.92 | 1.00 | CRS |
G | 5 | 6 | 1 | 0.54 | 0.54 | 1.00 | CRS |
H | 6 | 3 | 1 | 0.66 | 0.66 | 1.00 | CRS |
I | 6 | 5 | 1 | 0.54 | 0.54 | 1.00 | CRS |
J | 6 | 9 | 1 | 0.40 | 0.40 | 1.00 | CRS |
K | 6 | 4 | 1 | 0.60 | 0.60 | 1.00 | CRS |
L | 7 | 7 | 1 | 0.42 | 0.42 | 1.00 | CRS |
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Store | A | B | C | D | E | F | G | H | I | J | K | L |
---|---|---|---|---|---|---|---|---|---|---|---|---|
x1 | 2 | 4 | 8 | 3 | 4 | 5 | 5 | 6 | 6 | 6 | 6 | 7 |
x2 | 4 | 2 | 1 | 6 | 3 | 2 | 6 | 3 | 5 | 9 | 4 | 7 |
y | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
Target DMUs | |||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
A | B | C | D | E | F | G | H | I | J | K | L | ||
Competitor DMUs | A | 1.000 | 0.500 | 0.250 | 0.667 | 0.500 | 0.400 | 0.400 | 0.333 | 0.286 | 0.333 | 0.333 | 0.286 |
B | 0.500 | 1.000 | 0.500 | 0.333 | 0.667 | 0.800 | 0.333 | 0.667 | 0.571 | 0.222 | 0.500 | 0.286 | |
C | 0.250 | 0.500 | 1.000 | 0.167 | 0.333 | 0.500 | 0.167 | 0.333 | 0.333 | 0.111 | 0.250 | 0.143 | |
D | 1.000 | 0.500 | 0.250 | 0.667 | 0.500 | 0.400 | 0.400 | 0.334 | 0.286 | 0.334 | 0.334 | 0.286 | |
E | 0.643 | 0.857 | 0.429 | 0.429 | 0.857 | 0.686 | 0.429 | 0.571 | 0.490 | 0.286 | 0.571 | 0.367 | |
F | 0.462 | 0.923 | 0.577 | 0.308 | 0.615 | 0.923 | 0.308 | 0.615 | 0.615 | 0.205 | 0.462 | 0.264 | |
G | 0.818 | 0.681 | 0.341 | 0.545 | 0.681 | 0.545 | 0.545 | 0.454 | 0.389 | 0.363 | 0.454 | 0.389 | |
H | 0.500 | 1.000 | 0.500 | 0.334 | 0.667 | 0.800 | 0.334 | 0.667 | 0.572 | 0.222 | 0.500 | 0.286 | |
I | 0.474 | 0.948 | 0.553 | 0.316 | 0.632 | 0.885 | 0.316 | 0.632 | 0.632 | 0.211 | 0.474 | 0.271 | |
J | 0.900 | 0.600 | 0.300 | 0.600 | 0.600 | 0.480 | 0.480 | 0.400 | 0.343 | 0.400 | 0.400 | 0.343 | |
K | 0.600 | 0.900 | 0.450 | 0.400 | 0.800 | 0.720 | 0.400 | 0.600 | 0.514 | 0.267 | 0.600 | 0.343 | |
L | 0.751 | 0.751 | 0.375 | 0.501 | 0.751 | 0.601 | 0.501 | 0.501 | 0.429 | 0.334 | 0.501 | 0.429 |
A | B | C | D | E | F | G | H | I | J | K | |
---|---|---|---|---|---|---|---|---|---|---|---|
B | 0.058 | ||||||||||
C | −0.245 | 0.473 | |||||||||
D | 1.000 | 0.057 | −0.246 | ||||||||
E | 0.341 | 0.870 | 0.239 | 0.340 | |||||||
F | −0.027 | 0.968 | 0.584 | −0.027 | 0.781 | ||||||
G | 0.854 | 0.429 | −0.140 | 0.854 | 0.725 | 0.312 | |||||
H | 0.058 | 1.000 | 0.473 | 0.057 | 0.870 | 0.968 | 0.429 | ||||
I | −0.010 | 0.982 | 0.551 | −0.010 | 0.806 | 0.997 | 0.338 | 0.982 | |||
J | 0.972 | 0.205 | −0.234 | 0.972 | 0.508 | 0.100 | 0.946 | 0.205 | 0.122 | ||
K | 0.237 | 0.937 | 0.320 | 0.236 | 0.984 | 0.863 | 0.629 | 0.937 | 0.885 | 0.401 | |
L | 0.671 | 0.655 | 0.003 | 0.671 | 0.903 | 0.539 | 0.944 | 0.655 | 0.567 | 0.805 | 0.834 |
Resource | Min. | Max. | Avg. | Std. Dev. | |
---|---|---|---|---|---|
Inputs | Berth length | 181 | 15,585 | 4054 | 3210 |
Total area | 105,000 | 7,156,000 | 1,697,593 | 1,524,231 | |
CFS area | 5000 | 1,535,000 | 161,850 | 288,312 | |
Loading machine | 8 | 1955 | 363 | 369 | |
Outputs | Unloading TEU | 46,393 | 7,180,397 | 1,280,869 | 1,639,527 |
Loading TEU | 44,537 | 7,386,658 | 1,290,066 | 1,650,742 |
Port No. | Port Name | θ | Reference set | Port No. | Port Name | θ | Reference set |
---|---|---|---|---|---|---|---|
1 | Hong Kong | 1.000 | - | 18 | Colombo | 0.924 | 1, 2, 26 |
2 | Singapore | 1.000 | - | 19 | Bangkok | 0.303 | 1, 26 |
3 | Kaohsiung | 1.000 | - | 20 | Osaka | 0.281 | 1, 2, 3, 26 |
4 | Rotterdam | 0.297 | 1, 2, 26 | 21 | Hampton Roads | 0.339 | 1, 2, 3 |
5 | Busan | 0.818 | 1, 31 | 22 | Charleston | 0.281 | 1, 3 |
6 | Hamburg | 0.260 | 1, 3 | 23 | Melbourne | 0.217 | 1, 2, 3 |
7 | Yokohama | 0.369 | 1, 2, 3, 26 | 24 | La Spezia | 0.389 | 1, 2, 26 |
8 | Los Angeles | 0.492 | 2, 26 | 25 | Genoa | 0.310 | 1, 2, 3 |
9 | Antwerp | 0.152 | 1, 2, 3 | 26 | Laem Chabang | 1.000 | - |
10 | New York | 0.147 | 1, 2 | 27 | Qingdao | 0.670 | 2, 3, 26 |
11 | Dubai | 0.421 | 1, 2 | 28 | Southampton | 0.441 | 1, 2, 3 |
12 | Keelung | 0.319 | 1, 2, 26 | 29 | Santos | 0.752 | 1, 31 |
13 | Manila | 0.183 | 1, 2, 26 | 30 | Barcelona | 0.207 | 1, 2, 3, 26 |
14 | Oakland | 0.213 | 1, 2, 3 | 31 | Jeddah | 1.000 | - |
15 | Seattle | 0.184 | 1, 2, 26 | 32 | Sydney | 0.055 | 1, 2, 3, 26 |
16 | Tanjung Priok | 0.559 | 1, 2 | 33 | Khor Fakkan | 0.510 | 2, 26 |
17 | Port Klang | 0.233 | 1, 2, 26 | 34 | Valencia | 0.149 | 1, 2 |
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Park, J.; Sung, S.-I. Integrated Approach to Construction of Benchmarking Network in DEA-Based Stepwise Benchmark Target Selection. Sustainability 2016, 8, 600. https://doi.org/10.3390/su8070600
Park J, Sung S-I. Integrated Approach to Construction of Benchmarking Network in DEA-Based Stepwise Benchmark Target Selection. Sustainability. 2016; 8(7):600. https://doi.org/10.3390/su8070600
Chicago/Turabian StylePark, Jaehun, and Si-Il Sung. 2016. "Integrated Approach to Construction of Benchmarking Network in DEA-Based Stepwise Benchmark Target Selection" Sustainability 8, no. 7: 600. https://doi.org/10.3390/su8070600
APA StylePark, J., & Sung, S.-I. (2016). Integrated Approach to Construction of Benchmarking Network in DEA-Based Stepwise Benchmark Target Selection. Sustainability, 8(7), 600. https://doi.org/10.3390/su8070600