Location Screening

4.5.1Location Screening

As mentioned earlier, in the backloading analysis only trips with empty legs over 100 kms were included in the analysis. The software tools allow the user to vary this threshhold distance. 573 empty legs (as shown in Figure 4.10) met this criterion across the fleets of the thirteen companies in the sample.

The search areas were defined as cycles centred at the origin and destination of an empty leg with a radius of 50 kilometres. The distance between a potential load’s start and finish points, or the empty running distance of the potential load, also had to be over 1/3 of the distance of the empty leg.

Load Matching by Location

Figure 4.10. Empty Legs Selected for Backloading Analysis

The results of an interactive backloading analysis based on a selected sample of empty legs are shown in Table E.1 in Appendix E. Detailed information about the matched cases is stored in separate tables.

Of the 573 empty legs over 100 km, 229 have potential load matches based on the location and direction of the freight movement. However, there are some conflicts among these matches. Some of the potential loads are matched to more than one empty leg, while some empty legs are matched with more than one load. Roughly a third (181) of the empty legs could be allocated unique loads.

4.5.1.1 Backloading opportunities at sub-sector level

Table 4.3 shows that of the total 2957 trips selected for backloading analysis, over three quarters were at the secondary distribution level. There are clear distinctions in terms of average journey distance. Primary distribution has the longest average distance of 116 km per journey leg. Mixed distribution and secondary distribution have similar average distances in the sample (around 80km), while tertiary distribution has the shortest average distance of just about 50 kilometres.

Table 4. 3 . Sample statistics at sub-sector level

sector average distance _{per leg (km)} number _{of legs} number of _trips

M 80.9 181 63 2.1%

P 116.0 814 293 9.9%

S 82.7 6,953 2,298 77.7%

T 49.9 1,046 303 10.2%

Table 4. 4 . Backloading opportunities at sub-sector level Matched Loads Frequency M P S T Total M 1 1 0.6% P 1 23 24 48 26.5% S 22 99 3 124 68.5% T 2 6 8 4.4% 1 47 130 3 181 Empty Legs Total 0.6% 26.0% 71.8% 1.7% 100.0%

Table 4.4 shows the opportunities of backloading at sub-sector level based on location screening. Most of the backloading opportunities are arise from primary and secondary distribution. Over two-thirds of them are within the same sub-sector. Secondary distribution provides about 50% of the backloading opportunities for primary distribution and obtains about 18% of its backloading opportunities from primary distribution. Other matches (about one-third of the total) are between other pairs of sectors. In the sample, the backhaul opportunities for the mixed and tertiary distribution account for only 5% of the total.

4.5.1.2 Backloading opportunities at company level

Sample statistics at company level are shown in Table F.1 in Appendix F. The sample is largely skewed by one company, which accounts for a large proportion of the sample of empty legs for backloading analysis. (12 of the fifteen fleets which this company committed to the 2003 KPI survey were included in the backloading analysis.) This company has an extensive distribution network across the UK. Analysis of its KPI data reveals the extent to which backloads can be generated internally within a large companies’ distribution systems.

As shown in Table 4.5, there are wide variations of backloading opportunities among the thirteen sample companies in terms of both the number of backloads carried and provided. The dominant company could have obtained 71 matched loads internally, accounting for about 40% of the total backloading opportunities. This company attracted 35% potential backloads from other companies. It provided 32 backloads for other companies’ transport operations.

4.5.1.3 Backloading opportunities within a company’s operation

The internal opportunities for backloading were examined in detail for the company with twelve fleets in the sample. As shown is Table 4.6, a third of the backhaul opportunities were within these fleets, the remainder between fleets.

Backloading opportunities were not proportional to the size of fleets in the sample. They are much more closely related to the geographical distribution of the company’s warehouses. The biggest fleet in the sample, fleet9_3, could have found more loads than other fleets; it is also the biggest generator of loads for other fleets. However, fleet9_12 with only 3% of trips in the sample could have obtained 18% of the loads. It is also shown that there is strong connection between fleets based at particular pairs of depots. The existence of such bonds between these fleets is mainly due to the close proximity of their vehicle base.

Interactive Analysis

The GIS interface allows the user interactively to search for backloading opportunities within particular areas, for particular fleets or companies and or even for individual empty legs. The screening results are stored in separate tables that can be displayed in table or form format as shown in Table F.1 and F.2 in Appendix F.

Table 4. 5 . Backloading opportunities at company level Matched Loads Frequency 1 3 4 6 8 9 10 11 12 13 Total 1 4 1 1 2 8 3 1 14 1 13 1 1 1 1 33 4 3 3 5 1 1 6 1 1 8 1 4 1 6 9 2 13 3 4 71 1 2 1 12 109 10 1 1 1 1 4 11 1 2 3 12 1 1 2 4 13 1 1 1 3 1 2 9 Empty Legs Total 4 32 3 1 6 103 4 4 6 18 181

Table 4. 6 . Backloading opportunities within a company’s operation Matched Loads Frequency 9_1 9_10 9_11 9_12 9_2 9_3 9_4 9_5 9_8 9_9 Total 9_1 1 1 9_10 3 3 6 9_11 2 1 3 9_12 4 9 13 9_2 7 7 9_3 6 7 1 14 9_4 5 5 9_5 1 1 4 1 7 9_6 1 1 2 9_8 4 4 9_9 3 1 1 2 2 9 Empty Legs Total 1 7 6 9 6 15 11 6 3 7 71