Población de estudio

Self-confidence is the third component influencing intent in the TPB. Its influence, as shown in Table 12-2 and Table 12-3, is similar in magnitude to the subjective norm. As shown in Table 12-1, there were significant increases in the average value of self-confidence after respondents were shown pro- transit messages and the seven alternative transportation options. Because self-confidence does have a significant effect on intent, and because our survey panel survey results indicate self-confidence can be improved, it is worthwhile to try to understand the factors that affect self-confidence.

Dependent Variable: Final Subjective Norm Independent Variable: Final Normative Beliefs

(with the new services available, Coefficient t-Statistic Probability

Constant 0.97* 5.1 .0001

my family would be more supportive of my walking more and taking public transportation

more. 0.54* 5.1 .0001

my friends would be more supportive of my walking more and taking public transportation

more. 0.04 0.3 .7334

my neighbors would be more supportive of my walking more and taking public transportation

more. -0.02 -0.2 .8393

my co-workers would be more supportive of my walking more and taking public transportation

more. 0.09 1.0 .3252

* indicates significant coefficients at p < .05 R2_{= 34%, 501 observations.}

Table 12-8. Regression for final subjective norm with seven alternative services available.

Motivation to

Comply with: Mean (SD)

My family 5.1 (2.0)

My friends 4.2 (1.9)

My coworkers 2.8 (1.6)

My neighbors 2.5 (1.6)

Table 12-7. Mean ratings for final motivation to comply.

In the TPB, SN is influenced by the control beliefs and the power of each of those beliefs. Table 10-7 in Chapter 10 showed the mean control beliefs; these are shown again in Table 12-9. As can be seen, the highest rated item had to do with the need to make local trips. This was followed by three items rated second in magnitude: (a) the need for access to a car to make spur-of-the-moment trips, (b) the need for ac- cess to a car to carry heavy things, and (c) the bother of wait- ing for transit and not knowing when it was coming. Concern about being stranded was rated above neutral, at 4.7. The lowest rated beliefs were concern about getting downtown, encountering crime while walking, and dealing with the fare payment system.

Regression analysis was used as an alternative method for judging the influence of the control beliefs. Table 12-10 shows a regression using the power of control variables and SCF from the final TPB exercise. The order of the coefficients shown in Table 12-10 is very different from the order of the control beliefs shown in Table 12-9. As can be seen in the regression results, there are only two significant coefficients, with “I worry about being stranded” having the largest mag- nitude. Those that said they would have less concern about being stranded also had a higher rating for SCF.

The second significant variable had to do with making trips downtown. The negative coefficient says that respondents who agreed that it would be more difficult to get downtown tended to have lower self-confidence. Although, on the whole, respondents rated their need to get downtown the

lowest of all of the control beliefs, their belief in their ability to travel downtown with the seven transportation options was significantly associated with their confidence in their ability to walk and take public transportation more. On the other hand, although they rated the control belief “I need to make local trips” highest, their belief in their ability to make local trips with the seven transportation options did not appear associated with their confidence that they could increase walking and public transportation use.

The R2_{for the regression shown in Table 12-10 is the low-}

est for the regressions shown in this chapter and indicates that there are many other factors underlying SCF than identified in this research.

Summary

This chapter examined the relationships between the direct measures of the TPB and also between the direct measures and the indirect measures, using the data from the Phase 2 Inter- net panel survey. The statistical technique of regression analy- sis was used to analyze the relationships between variables.

As shown in prior chapters, SN, SCF, and intent increased significantly between the initial TPB exercise and the final exercise, but ATT did not increase significantly. Regression analysis was used to examine the relationship between the re- spondents’ intentions to increase their use of public trans- portation and walking and their ATT, SN, and SCF. In both the initial and final TPB exercise, intent to increase the use of Belief (Rated on a Seven-Point Scale) Mean (SD)

I need to make local trips (to reach destinations such as the library, post

office, restaurant, or coffee shop). (not very often to very often) 5.5 (1.6) I need access to a car to make spur of the moment trips. (not very often to

very often) 5.1 (1.9)

I need access to a car to carry heavy things (not very often to very often) 5.1 (1.8) I find waiting for the bus or train and not knowing when it is com ing is a

bother. (strongly disagree to strongly agree) 5.1 (1.9) I worry about being stranded if I rely on public transportation and miss

the bus or train. (strongly disagree to strongly agree) 4.7 (2.0) I worry about crime or other disturbing behavior on public transportation.

(strongly disagree to strongly agree) 4.1 (2.0)

I need to travel to other parts of the region. (not very often to very often) 4.1 (2.1) I find dealing with the fare for public transportation is a bother. (strongly

disagree to strongly agree) 3.9 (2.0)

I worry encountering crime or other disturbing behavior when walking.

(strongly disagree to strongly agree) 3.8 (2.0)

I need to travel downtown (not very often to very often) 3.4 (2.3)

public transportation and walking was most closely related to a respondent’s attitude. Intent was also related to SN and SCF; these were of similar influence to each other, but smaller influence than attitude.

Regression analysis was used to examine whether the behavioral beliefs measured in the final TPB exercise were sig- nificantly related to the respondent’s attitude. The most important belief was found to be that with the new services available, “I would rely on public transportation and walking to get me to my destination in a timely way.” The next most important belief was a composite of beliefs about improving health and reducing pollution. While respondents increased their rating of their ability to rely on public transportation and walking, they decreased their rating of improving health and reducing pollution. This result may explain why attitude did not change significantly.

Regression analysis was also used to examine the relation- ship between the normative beliefs and the final SN. The most important belief was found to be that “with the new services

available, my family would be more supportive of my walk- ing more and taking public transportation more.” The sig- nificant increase in this normative belief corresponds with the positive change in the SN.

Finally, regression analysis was used to examine the rela- tionship between the power of control ratings and SCF. The most important power of control statement was “With the new services available, I would have less concern about being lost or stranded by missing the bus or train.”

The overall message of this exercise seems to be that to increase transit use and walking requires the following: • The perceived reliability of the system must be improved. • The positive health and environmental impact of walking

more and taking public transportation more must be more convincing.

• Customers must be convinced that they will not be left stranded.

• Families must approve of increased transit use and walking. Dependent Variable: Perceived Behavioral Control (SCF)

Independent Variable:

Final Power of Control Coefficient t-Statistic Probability

Constant 3.13* 8.33 .0001

Have less concern about being stranded 0.30* 4.52 .0001 Feel safer from crime and other disturbing behavior 0.09 1.47 .1425

Paying the fare would be simple 0.09 1.16 .2459

Easy to know the schedule 0.06 0.78 .4384

More difficult to get to the region 0.03 0.53 .5942

Harder to make spur of the moment trips -0.07 -1.28 .2025

Harder to carry heavy things -0.09 -1.57 .1163

More difficult to make local trips -0.05 -0.69 .4882

More difficult to get downtown -0.18* -2.71 .0069

* indicates significant coefficient at p < .05 R2_{= 23%, 501 observations}

Table 12-10. Regression for final self-confidence with seven alternative services available.

The primary objectives of this research were twofold— namely, to understand how people make travel and location decisions and to derive practical implications and policy guidance for encouraging more use of public transportation and walking. An underlying assumption is that growing urban congestion and impaired mobility can be mitigated by encouraging people to substitute public transportation and walking for individual automobile use. A practical challenge, is, of course, how to promote this kind of behavior in enough instances to have a measurable, beneficial effect on travel con- ditions. The premise of this research is that by gaining a bet- ter understanding of the links between individuals’ attitudes, intentions, and behaviors with regard to travel alternatives to the automobile, strategies can be better configured and targeted to help achieve the desired outcomes.