Research Article
A Comparative Evaluation of Public Road Transportation Systems in India Using Multicriteria Decision-Making Techniques
Table 3
Efficiency and Q score for the DMUs (year 2015-2016).
| Sr. no. of the DMU | Accident | Traffic revenue | Expenses | Vehicle operations | Manpower | Maintenance | Utility score | Regret score | Q value | Rank | Weights | 0.084 | 0.258 | 0.258 | 0.136 | 0.154 | 0.109 |
| 1 | 1.000 | 1.000 | 1.000 | 0.979 | 0.887 | 1.000 | 0.033 | 0.023 | 0.050 | 3 | 2 | 0.660 | 1.000 | 0.512 | 1.000 | 0.921 | 0.483 | 0.403 | 0.245 | 0.855 | 5 | 3 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 | 0.707 | 0.049 | 0.049 | 0.117 | 37 | 4 | 1.000 | 1.000 | 0.914 | 0.867 | 0.251 | 0.768 | 0.301 | 0.154 | 0.573 | 23 | 5 | 0.487 | 1.000 | 0.963 | 1.000 | 0.785 | 0.345 | 0.256 | 0.109 | 0.440 | 30 | 6 | 0.488 | 1.000 | 0.659 | 1.000 | 0.852 | 0.450 | 0.377 | 0.171 | 0.681 | 14 | 7 | 1.000 | 0.774 | 0.767 | 1.000 | 0.863 | 0.450 | 0.347 | 0.117 | 0.543 | 20 | 8 | 1.000 | 0.986 | 1.000 | 0.750 | 0.395 | 1.000 | 0.253 | 0.124 | 0.467 | 16 | 9 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 | 0.584 | 0.070 | 0.070 | 0.178 | 6 | 10 | 0.494 | 1.000 | 1.000 | 1.000 | 0.718 | 0.447 | 0.233 | 0.092 | 0.383 | 10 | 11 | 0.714 | 0.957 | 0.585 | 0.846 | 0.492 | 0.585 | 0.524 | 0.208 | 0.899 | 40 | 12 | 0.822 | 1.000 | 0.764 | 0.935 | 0.480 | 0.764 | 0.325 | 0.118 | 0.525 | 19 | 13 | 0.889 | 1.000 | 0.822 | 1.000 | 0.370 | 0.483 | 0.323 | 0.130 | 0.546 | 21 | 14 | 0.867 | 0.839 | 0.977 | 0.720 | 0.839 | 0.743 | 0.324 | 0.136 | 0.559 | 22 | 15 | 0.724 | 1.000 | 0.628 | 0.925 | 0.557 | 0.619 | 0.423 | 0.186 | 0.757 | 34 | 16 | 0.634 | 1.000 | 0.648 | 1.000 | 0.598 | 0.487 | 0.405 | 0.176 | 0.719 | 33 | 17 | 0.691 | 1.000 | 0.615 | 1.000 | 0.720 | 0.608 | 0.367 | 0.193 | 0.716 | 32 | 18 | 1.000 | 0.794 | 1.000 | 1.000 | 1.000 | 0.883 | 0.120 | 0.100 | 0.289 | 8 | 19 | 0.608 | 1.000 | 0.634 | 1.000 | 1.000 | 0.472 | 0.336 | 0.183 | 0.666 | 29 | 20 | 1.000 | 0.469 | 1.000 | 1.000 | 0.402 | 1.000 | 0.381 | 0.258 | 0.861 | 38 | 21 | 1.000 | 0.645 | 0.912 | 1.000 | 0.599 | 0.667 | 0.355 | 0.173 | 0.663 | 28 | 22 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 | 0.941 | 0.010 | 0.010 | 0.000 | 1 | 23 | 0.905 | 1.000 | 0.732 | 1.000 | 1.000 | 0.609 | 0.215 | 0.134 | 0.450 | 15 | 24 | 0.695 | 0.988 | 0.537 | 0.943 | 0.565 | 0.509 | 0.487 | 0.232 | 0.911 | 42 | 25 | 0.614 | 1.000 | 0.510 | 0.989 | 0.804 | 0.476 | 0.442 | 0.246 | 0.895 | 39 | 26 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 | 0.749 | 0.042 | 0.042 | 0.096 | 4 | 27 | 0.568 | 1.000 | 0.792 | 1.000 | 0.683 | 0.408 | 0.339 | 0.104 | 0.510 | 25 | 28 | 0.705 | 1.000 | 0.654 | 1.000 | 1.000 | 0.523 | 0.302 | 0.173 | 0.613 | 18 | 29 | 0.770 | 1.000 | 0.714 | 1.000 | 0.274 | 0.637 | 0.391 | 0.149 | 0.651 | 36 | 30 | 0.840 | 0.920 | 0.625 | 0.944 | 0.472 | 0.619 | 0.453 | 0.188 | 0.789 | 11 | 31 | 1.000 | 0.947 | 1.000 | 1.000 | 0.432 | 0.719 | 0.190 | 0.117 | 0.390 | 31 | 32 | 0.888 | 0.702 | 0.847 | 0.860 | 0.564 | 0.738 | 0.441 | 0.145 | 0.691 | 13 | 33 | 0.868 | 1.000 | 0.796 | 1.000 | 0.495 | 0.796 | 0.262 | 0.104 | 0.434 | 27 | 34 | 0.587 | 1.000 | 0.485 | 1.000 | 1.000 | 0.427 | 0.422 | 0.258 | 0.900 | 41 | 35 | 1.000 | 1.000 | 1.000 | 0.968 | 1.000 | 1.000 | 0.016 | 0.016 | 0.017 | 2 | 36 | 0.896 | 1.000 | 0.637 | 1.000 | 1.000 | 0.514 | 0.280 | 0.182 | 0.609 | 24 | 37 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 | 0.494 | 0.085 | 0.085 | 0.223 | 7 | 38 | 1.000 | 1.000 | 0.758 | 1.000 | 1.000 | 0.546 | 0.197 | 0.121 | 0.406 | 12 | 39 | 1.000 | 1.000 | 0.713 | 1.000 | 1.000 | 0.464 | 0.233 | 0.144 | 0.487 | 17 | 40 | 1.000 | 1.000 | 0.518 | 1.000 | 1.000 | 0.500 | 0.325 | 0.242 | 0.773 | 35 | 41 | 1.000 | 1.000 | 1.000 | 1.000 | 0.346 | 1.000 | 0.135 | 0.135 | 0.372 | 9 | 42 | 1.000 | 1.000 | 0.601 | 1.000 | 1.000 | 0.600 | 0.267 | 0.200 | 0.633 | 26 |
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