Conceptual clarifi cation, micro-level individual attributes and residential
3.6 Micro-level individual attributes and residential context
Based on the above information, the schematic outline of a multimodal trip introduced in Figure - is further developed and shown in Figure -. Figure - shows the profi le for trips originating from home. e width of the bars provide an indication of the share of the mode in the diff erent stages while the length provides an indication of the mean length of the stage with the particular mode. Also shown is the mean and th percentile access and egress distance ranges (dotted arches).
e above section provided a conceptual framework of multimodal transportation (trips) and extended this framework with empirical fi ndings based on the Dutch National Travel Survey. Conclusions were drawn regarding the use of multimodal transportation and it was investigated how the characteristics of the access, egress and main mode, i.e. mode choice and distance, infl uence the use and possibly the potential for multimodal transport. e following section focuses more on personal and household characteristics of multimodal transportation users using the same NTS data set.
an increased use of multimodal transportation relative to the reference category while negative values show a decline in the use of multimodal transportation. e last column, EXP (B), gives the odds of a person actually undertaking a multimodal trip compared to the reference category.
Odds ratios greater than indicates an increased chance of an event. For example, in the case of people in the age class -, the odds of a multimodal trip occurring are . as high as for people aged -.
.. Interpretation of the parameters
Considering all the variables, car availability and car availability and car availability urban intensity/development density have the urban intensity/development density have the urban intensity/development density strongest relationship with the multimodal transportation. Car availability, and specifi cally the ownership of a personal car, strongly reduces the inclination to use multimodal transportation.
e NTS data reveal that approximately of multimodal transportation users do not own a personal car, and are generally referred to as captive users. In addition, of multimodal transportation users do not own a personal or personal or personal household car.household car.household
Concerning age, the relationship is less strong, the exception being pensioners who use substantially less multimodal transportation than other age categories. As for the remaining individual level attributes, the relationship is not always clear and straightforward. Table -
show that males are slightly less inclined to make use of multimodal transportation. e NTS males are slightly less inclined to make use of multimodal transportation. e NTS males survey reports that . of the survey respondents are male and . are female. Likewise, an analysis of the multimodal users reveal that . are male and . are female.
As the amount of weekly hours worked decreases so does the use of multimodal transportation. weekly hours worked decreases so does the use of multimodal transportation. weekly hours worked Full-time employed people are much more likely to use multimodal transportation than other employment categories. Again, pensioners use much less multimodal transportation. Income has a moderate and variable eff ect. Lower income people are less likely to use multimodal transportation while there is increasing use amongst higher income earners. Arguably, higher income earners will also work longer hours (be classifi ed as full time employed). is supports the results obtained above. is result is also signifi cant in that, generally, income is also linked to car ownership. Based on these results it is theorized that there is a signifi cant proportion of higher income people with car ownership that use multimodal transportation.
Household size, somewhat unexpectedly, show a negative correlation with multimodal transportation with larger household making less use of multimodal transportation. is might be explained with reference to the number of children in larger households. Children seem to discourage multimodal transportation use. Especially the presence of younger children seems to be negatively associated with multimodal transportation. Household heads also use multimodal transportation more than their partners do. Considering that partners are more likely to be primarily responsible for child rearing activities, this is in line with the above fi ndings.
Urban intensity refers to the density of home and work place addresses. Generally an increase Urban intensity refers to the density of home and work place addresses. Generally an increase Urban intensity
in intensity stimulates an increased use of multimodal transportation, with the odds of people living in higher density areas using multimodal transportation double compared those living in lower intensity areas. Arguably, high intensity urban areas have more multimodal infrastructure and higher service levels. Some modes, for example tram and metro services, are exclusively available in densely developed areas.
Table -: (Binary) Logistic regression model of mode choice
95% CI for Exp(B)
Variable B SE sig R Exp(B) Lower Upper
Age Categories 0.000 0.091
0-17 (Reference)
18-24 -0.714 0.074 0.000 -0.030 0.490 0.423 0.566
24-40 -0.657 0.077 0.000 -0.027 0.518 0.446 0.602
40-65 -0.194 0.082 0.018 -0.006 0.824 0.701 0.967
65+ -1.944 0.097 0.000 -0.063 0.143 0.118 0.173
Gender
Woman (Reference)
Man -0.306 0.039 0.000 -0.024 0.737 0.682 0.796
Car Availability 0.000 0.147
No drivers license and no car (Reference)
Drivers license and no car -0.094 0.061 0.121 -0.002 0.910 0.809 1.025 No drivers license but family car -0.534 0.062 0.000 -0.027 0.586 0.519 0.663 Drivers license and family car -0.811 0.058 0.000 -0.044 0.445 0.397 0.498 Drivers license and car -2.243 0.058 0.000 -0.122 0.106 0.095 0.119
Employment Status 0.000 0.070
Work Full time (incl. Students) (Reference)
Employed part time (less than 30 hours/week) -0.212 0.049 0.000 -0.013 0.809 0.735 0.891
Unemployed -0.791 0.106 0.000 -0.023 0.453 0.368 0.558
Pensioned -1.442 0.069 0.000 -0.066 0.237 0.207 0.271
Personal Income 0.000 0.046
No Income (Reference)
Less than 18,000 (+/- $7,500) -0.170 0.055 0.002 -0.009 0.844 0.758 0.940
18-27 (+/- $11,250) -0.559 0.067 0.000 -0.026 0.572 0.501 0.653
27-34 (+/- $14,000) -0.396 0.072 0.000 -0.017 0.673 0.584 0.775
35-42 (+/- $17,500) -0.202 0.074 0.006 -0.007 0.817 0.708 0.944
42-58 (+/- $25,000) 0.016 0.075 0.827 0.000 1.017 0.878 1.177
58+ 0.340 0.078 0.000 0.013 1.405 1.205 1.639
Household Size 0.000 0.016
1 Person hold (Reference)
2 Person household -0.247 0.058 0.000 -0.013 0.781 0.698 0.875
3 Person household -0.361 0.077 0.000 -0.014 0.697 0.599 0.811
4 Person household -0.388 0.082 0.000 -0.014 0.678 0.578 0.796
5 Person household -0.330 0.095 0.001 -0.010 0.719 0.596 0.866
6 Person household -0.174 0.115 0.130 -0.002 0.840 0.671 1.053
Presence & Age of Child 0.000 0.020
No Child (Reference)
Child (0-5 years) -0.353 0.077 0.000 -0.014 0.702 0.604 0.816
Child (6-12 years) -0.368 0.072 0.000 -0.015 0.692 0.601 0.798
Child (12-17 years) -0.035 0.057 0.543 0.000 0.966 0.865 1.080
Household Role 0.000 0.032
Single (Reference)
Head of household 0.650 0.079 0.000 0.026 1.915 1.641 2.235
Partner of Head -0.174 0.061 0.004 -0.008 0.840 0.745 0.947
Urban Intensity 0.000 0.049
Not Urban Area (Reference)
Low intensity -0.081 0.051 0.108 -0.002 0.922 0.835 1.018
Medium 0.027 0.051 0.599 0.000 1.027 0.930 1.134
High 0.191 0.048 0.000 0.012 1.210 1.102 1.330
Very high 0.627 0.052 0.000 0.038 1.873 1.691 2.074