Data presentation Case Study 4: Theory-testing research: testing a probabilistic relation

7.2.10 Data analysis

Our hypotheses state that it is likely that a retailer’s sensitivity to time window pressure in cases with comparatively high values on distribution strategy dimensions is higher than in cases with comparatively low val- ues on these dimensions. We tested them by classifying the cases into four groups for each dimension of distribution strategy separately: number of stops, vehicle capacity, stopping time, and distance to shops. We used the following procedure. First, we sorted the cases by increas- ing value on that dimension, and then for each dimension we formed Group 1 by taking the three cases with the lowest value, Group 2 con- sisting of the next four cases, Group 3 consisting of the subsequent four cases, and finally Group 4 with the three cases with the highest value on the dimension. For the dimension self-imposed time windows, we grouped all cases into three groups corresponding to the three values available on our measurement scale for this variable see Table 7.2. After having formed these groups, we compared the steepness of the rise in distribution costs resulting from the increase in the number of time access windows from level 1 to 6 between these groups. Table 7.2 Distribution strategy dimensions per case Case Stops per Vehicle Stopping time Distance between Self-imposed roundtrip capacity per vehicle stores and DC time windows 1 5.4 3.9 64 110 normal 2 1.2 5.6 122 127 normal 3 2.4 3.5 155 103 normal 4 3.4 4.9 83 76 normal 5 1.0 4.9 63 89 strict 6 4.2 5.5 185 116 normal 7 9.1 5.0 181 198 long 8 8.3 1.8 165 103 long 9 7.2 1.0 72 86 normal 10 10.2 2.6 256 102 long 11 1.2 4.9 47 71 normal 12 1.3 4.7 78 42 normal 13 1.1 3.0 17 32 normal 14 6.3 4.9 134 42 normal Our hypotheses predicted the following pattern for each dimension of distribution strategy: Group 1 will have the lowest and the least steep line; Group 2 will have a higher and steeper line than Group 1; Group 3 will have a higher and steeper line than Group 2; and Group 4 will have the VEHICLE CAPACITY Costs – scenario C 1 small 2 3 4 large 1 small distance 2 3 4 large distance A B 1C 1 strict 2 normal 3 long STOPS PER ROUNDTRIP Costs – scenario C 1 f ew stops 2 3 4 many stops 10 20 30 40 50 60 20 40 60 80 100 10 20 30 40 50 60 70 80 Stores affected 20 40 60 80 100 120 10 20 30 40 50 60 70 80 Stores affected Stores affected 10 20 30 40 50 60 70 80 Stores affected Stores affected 1 br ief 2 3 4 long Percentage increase C 10 20 30 40 50 60 Percentage increase E 10 20 30 40 50 60 Percentage increase 10 20 30 40 50 60 70 80 Percentage increase D 5 10 15 20 25 30 35 40 Percentage increase STOPPING TIME PER VEHICLE Costs – scenario C DISTANCE BETWEEN DC AND STORES Costs – scenario C SELF-IMPOSED TIME WINDOWS Costs – scenario C Figure 7.1 Increase of distribution costs due to increase of time window pressure for different values of the dimension of strategy. Each graph A–E represents a dimension of strategy and each line within a graph represents a value of the dimension of strategy. All graphs are for stable time window length scenario C, see Table 6.2.