Method Of Assessing The Location Attractiveness Of The Warehouse Market
Table 3: Ranking of location attractiveness based on the indicator
| No. | Location | Value of the indicator | Level of location attractiveness | Limit values (SI) |
| 1 | Silesian conurbation | 0,658 | Highest (A) | 4 |
| 2 | Lodz agglomeration | 0,554 | ||
| 3 | Warsaw region | 0,536 | ||
| 4 | Krakow agglomeration | 0,498 | High (B) | |
| 5 | Częstochowa | 0,486 | ||
| 6 | Warsaw (city) | 0,481 | ||
| 7 | Wrocław agglomeration | 0,478 | ||
| 8 | Radom | 0,477 | ||
| 9 | Poznań agglomeration | 0,463 | ||
| 10 | Legnica | 0,456 | Mediocre (C) | |
| 11 | Kutno | 0,454 | ||
| 12 | Kielce | 0,405 | ||
| 13 | Tarnów | 0,401 | ||
| 14 | Włocławek | 0,398 | ||
| 15 | Kalisz | 0,392 | ||
| 16 | Zielona Góra | 0,392 | ||
| 17 | Opole | 0,388 | ||
| 18 | Rzeszów | 0,381 | ||
| 19 | Gorzów Wlkp. | 0,380 | ||
| 20 | Bydgoszcz-Toruń | 0,377 | ||
| 21 | Elbląg | 0,375 | Low (D) | |
| 22 | Konin | 0,372 | ||
| 23 | Lublin | 0,357 | ||
| 24 | Tri-City | 0,347 | ||
| 25 | Świebodzin-Słubice | 0,340 | ||
| 26 | Olsztyn | 0,313 | Lowest (E) | |
| 27 | Szczecin agglomeration | 0,312 | ||
| 28 | Białystok | 0,291 | ||
| 29 | Piła | 0,280 |
