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 |