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From page 195... ... D-1 A p p e n d i x d Transit Service Attribute Models Contents D-1 Overview D-2 Model Results of Unscaled Attributes D-15 Model Results of Scaled Attributes D-24 Details of the Transit Attribute Models D-33 Summary of Key Findings on Transit Attributes Overview The objective of the current research effort is to evaluate the relative importance of a selected set of transit service attributes (see TABLE D-3) and to quantify their effect in the context of mode choice decision. Read the entire page →
From page 196... ... D-2 Characteristics of premium Transit Services that Affect Choice of Mode and cost trade-offs relative to these additional service attributes (more on this in the next section) Read the entire page →
From page 197... ... Transit Service Attribute Models D-3 FIGURE D-1. Values of unscaled marginal rates of substitution (min. Read the entire page →
From page 198... ... D-4 Characteristics of premium Transit Services that Affect Choice of Mode are comfortable and a good size, and easy to board; doors are level with platform or curb) are also among the least important attributes for both work and non-work travelers. Read the entire page →
From page 199... ... FIGURE D-2. Unscaled marginal rates of substitution (in minutes) Read the entire page →
From page 200... ... FIGURE D-3. Relative importance of transit attributes (in %) Read the entire page →
From page 201... ... Transit Service Attribute Models D-7 Several interesting observations may be made from ( FIGURE D-2 and FIGURE D-3) Read the entire page →
From page 202... ... Relative importance of attributes at mean distance FIGURE D-4. Relative importance of transit attributes by distance for Chicago (commute trip) Read the entire page →
From page 203... ... Relative importance of attributes at mean distance FIGURE D-5. Relative importance of transit attributes by distance for Chicago (non-commute trip) Read the entire page →
From page 204... ... D-10 Characteristics of premium Transit Services that Affect Choice of Mode An intuitive and interesting observation is that the level of importance of transit attributes is not the same across all strata of commuters in Chicago. For example, parking distance is regarded as the most important transit attribute by full-time employed commuters relative to self-employed/part-time employed commuters with the same characteristics. Read the entire page →
From page 205... ... FIGURE D-6. Unscaled marginal rates of substitution (in minutes) Read the entire page →
From page 206... ... FIGURE D-7. Relative importance of transit attributes (in %) Read the entire page →
From page 207... ... Relative importance of attributes at mean distance FIGURE D-8. Relative importance of transit attributes by distance for Charlotte (commute trip) Read the entire page →
From page 208... ... TABLE D-1. Relative importance of attributes by trip purpose -- comparison of Chicago, Charlotte, and Salt Lake City. Read the entire page →
From page 209... ... Transit Service Attribute Models D-15 D-15 Finally, there are more similarities between the residents the in Chicago and Charlotte areas (in terms of their preferences regarding the transit attributes) than between the residents in Chicago and Salt Lake City or between the residents in Charlotte and Salt Lake City (see TABLE D-1) Read the entire page →
From page 210... ... D-16 Characteristics of premium Transit Services that Affect Choice of Mode – Category B: All other unbundled attributes belong to this category. The overall coefficients for the station/stop design and on-board features bundles available from the mode choice and MaxDiff models are used to scale the coefficients under this category. Read the entire page →
From page 211... ... Transit Service Attribute Models D-17 TABLE D-2. Coefficients from the mode choice model used in the MaxDiff models. Read the entire page →
From page 212... ... D-18 Characteristics of premium Transit Services that Affect Choice of Mode TABLE D-3. Scaled coefficients of bundled attributes for work travel: Salt Lake City. Read the entire page →
From page 213... ... Transit Service Attribute Models D-19 Once the transit attributes are incorporated, the mode choice models may be used to analyze future scenarios such as testing the effects of improving one or a set of attributes on transit mode share. TABLE D-5 and TABLE D-6 also provide information on how much additional time the commuters and non-commuters in the study areas may be willing to add to their in-vehicle travel time to include the corresponding attributes on the route (see the "Scaled Marginal Rates of Substitution" column) Read the entire page →
From page 214... ... TABLE D-5. Scaled MaxDiff model results and marginal rates of substitution for Chicago. Read the entire page →
From page 215... ... TABLE D-6. Scaled MaxDiff model results and marginal rates of substitution for Charlotte. Read the entire page →
From page 216... ... D-22 Characteristics of Premium Transit Services that Affect Choice of Mode FIGURE D-9. Cumulative scaled equivalent minutes of in-vehicle travel time for Chicago. Read the entire page →
From page 217... ... Transit Service Attribute Models D-23 FIGURE D-10. Cumulative scaled equivalent minutes of in-vehicle travel time for Charlotte. Read the entire page →
From page 218... ... D-24 Characteristics of premium Transit Services that Affect Choice of Mode Details of the Transit Attribute Models The following tables provide more detailed model results for the Maximum Difference Scaling models presented in Chapter 3 of TCRP Report 166: TABLE D-7. MaxDiff model estimation results for commute trips (t-stat) Read the entire page →
From page 219... ... TABLE D-7. MaxDiff model estimation results for commute trips (t-stat) Read the entire page →
From page 220... ... TABLE D-8. MaxDiff model estimation results for non-commute trips (t-stat) Read the entire page →
From page 221... ... TABLE D-9. Relative rank of attributes by individual demographics, household demographics, trip characteristics, and attitudinal variables (relative importance in %) Read the entire page →
From page 222... ... TABLE D-10. Relative rank of attributes by individual demographics, household demographics, trip characteristics, and attitudinal variables (relative importance in %) Read the entire page →
From page 223... ... TABLE D-11. MaxDiff model estimation results for commute trips (t-stat) Read the entire page →
From page 224... ... TABLE D-12. MaxDiff model estimation results for non-commute trips (t-stat) Read the entire page →
From page 225... ... TABLE D-13. Relative rank of attributes by individual demographics, household demographics, trip characteristics, and attitudinal variables (relative importance in %) Read the entire page →
From page 226... ... TABLE D-14. Relative rank of attributes by individual demographics, household demographics, trip characteristics, and attitudinal variables (relative importance in %) Read the entire page →
From page 227... ... Transit Service Attribute Models D-33 Summary of Key Findings on Transit Attributes TABLE D-15 shows a comparison of scaled values of premium transit attributes across all three cities where surveys were conducted. The values are in equivalent minutes of in-vehicle travel time and coefficients from which these values have been derived were estimated for bus and train modes combined. Read the entire page →
From page 228... ... D-34 Characteristics of premium Transit Services that Affect Choice of Mode There are key findings derived from this comparison that are useful for planning purposes: Reliability and on-board seating availability have relatively high values irrespective of trip purpose or geographic location. In terms of size, Chicago and Charlotte can be considered as ends of the spectrum. Read the entire page →

From page 195...

... D-1 A p p e n d i x d Transit Service Attribute Models Contents D-1 Overview D-2 Model Results of Unscaled Attributes D-15 Model Results of Scaled Attributes D-24 Details of the Transit Attribute Models D-33 Summary of Key Findings on Transit Attributes Overview The objective of the current research effort is to evaluate the relative importance of a selected set of transit service attributes (see TABLE D-3) and to quantify their effect in the context of mode choice decision.