The Psychological Decision-Making Process Model of Giving up Driving under Parking Constraints from the Perspective of Sustainable Traffic

Round 1

Reviewer 1 Report

Overall—I found the math interesting and as someone who has not done this type of work, I am intrigued.  It clearly offers a way to address the importance of some unobservable perceptions.  (For instance, this technique could possibly be used to help us determine differences between direct out of pocket costs per trip, such as paying for fuel, and more hidden costs, such as paying for auto insurance periodically). 

There are two flaws, however—and unfortunately, I do not see how these can be addressed without doing the study anew.  However, the authors may have a solution.

First—some of the labels appear either duplicative or closely associated.  For example, bi5 (“Give up driving because parking charges are too high”) and ba1 (“Giving up driving helps to reduce travel costs”) both measure some degree of economy, and it may be the case that differences in these two sets of responses have more to do with how the question is asked than with how respondents make decisions.  In the authors’ defense, one could still argue that is valuable to know this information because it would be used to adjust marketing campaigns (e.g., one would not say “save money by not driving” but rather one would say “save money by not having to pay for parking!”).  Such a nuance is not fully developed in section 4 but perhaps steps 3 and 4 in section 4 can be expanded—but overall, some more explanation of the overlap of the variables in Table 1 is needed—or perhaps the same data can be used but with a more rational way of categorizing the variables.  (As another example, there seems to be overlap between ptp4 and bi1—both relate to reliability of transit over parking.  Again, from a marketing perspective, I can see this distinction as being valuable for messaging, but in terms of how people make decisions, the data acquired appear to indicate how the question is asked as much as differences in respondents’ values).

Second—we don’t have a robust way of determining what portion of behavioral change is explained by observable factors.  For instance, a much simpler survey could have given respondents modes, costs, travel time, and reliability and then determined what proportion of variance was explained by those observable factors; the difference between that and 1.0 gives us a clue as to how important these unobservable attributes are.   The reported R2 values in the paper are certainly high:  an 84% for BI or a 76% for PTP would be a great model if BI and PTP as reported could be used for predictive power.  However, what the paper needs to show is the portion of variance that is explained by unobserved attributes.  Consider, for instance, when the authors write “Control the number of parking berths reasonably.”  Such controls will logically increase the price of parking which will make other modes such as transit more attractive—but the results are silent as to how an increase of the price by x will affect mode shift by y.  A better approach would be a more traditional survey that quantifies how cost affects mode shift—and then the best approach would be to combine this more traditional survey with what the authors have done, so that one could see how psychological factors can be used to explain additional variance not explained by observations of cost, time, and reliability.

Can the authors resolve those two flaws?

On a more minor note, there are several statements that are simply made but not supported.  I’d either eliminate these or give supporting evidence.  Here are some examples:

• “The large number of car trips is one of the direct causes of the problems.”

Suggestion:  quantify the role of mobile source emissions in a region’s emissions budget.  For example, you might state the following:  “In the United States, on-road vehicles accounted for an estimated 40% of nitrogen oxide (NOx) emissions in 2014, with the remaining sources being power plants, other types of fuel combustion, industrial processes such as manufacturing plants, and off-road engines such as farm equipment (U.S. Environmental Protection Agency, undated).

The new source to support the above that you could then add is:  “U.S. Environmental Protection Agency.  Report on the Environment:  Nitrogen Oxide Emissions, Washington, D.C., undated.  https://cfpub.epa.gov/roe/indicator_pdf.cfm?i=15.  Accessed August 10, 2020.”

The above is an example--you can use other citations besides what I provided, but this is just an example of how to support an assertion.

Other statements that need supporting evidence are as follows:

• “more and more people realize the influence of static traffic on dynamic traffic” (I am not sure what this means.)
• “However, with the in-depth study of travel behavior, it was found that people’s decisions were not necessarily completely rational, and some factors that cannot be directly observed, such as travelers’ attitudes, perceptions and values, will also have impact on the behavior decision to some extent.”

Suggestion:   I understand what the authors are seeking to convey, but I’d recommend saying something like “Time, out of pocket cost, and convenience have been found to explain X% of the variance in mode choice, with the remainder attributed to factors that cannot be directly observed.” Then cite a couple of sources that say what these factors are and their importance compared to factors that can be observed such as time and cost.  Also, unless you mean something different for “attitudes” from “perceptions” from “values”, you might just pick one of these words and then give examples.  One example is a perception that public transportation is not safe, another perception might be that carpooling is infeasible because the motorist might need to go home in an emergency.

• “Commuting is the most important travel purpose of urban residents.”

Suggestion:  Please clarify and cite evidence.  For example, you might say that “although commute trips account for only 15% of all household trips (Bureau of Transportation Statistics, 2020); the accounted for between 30% and 34%, depending on how the data are tabulated, of household vehicle miles traveled (U.S. Department of Transportation, 2018).”  Then, the sources you would add are as follows:

Bureau of Transportation Statistics.  National Household Travel Survey Daily Travel Quick Facts, Washington, D.C., 2017.  https://www.bts.gov/statistical-products/surveys/national-household-travel-survey-daily-travel-quick-facts.  Accessed August 10, 2020.

U.S. Department of Transportation.   Table 1-42:  Average Annual PMT, VMT Person Trips and Trip Length by Trip Purpose, National Household Travel Survey, Washington, D.C., 2018.  https://www.bts.gov/content/average-annual-pmt-vmt-person-trips-and-trip-length-trip-purpose.  Accessed August 10, 2020.

Again, the above is an example--you can use other citations besides what I provided, but this is just an example of how to support an assertion.

Very minor comment:  there is an extra space in Table 2 following ptp2, ptp3, and ptp5.

Author Response

Please find the modification instructions in the attachment, thank you.

Author Response File: Author Response.pdf

Reviewer 2 Report

First of all the authors should explain the gap of the international literature, and how they intend to overcome this lack of studies.

Subsequently, they shoud explain in detail how their paper might provide a significant contribution to scientific research.

The results should be confirmed, and the transferability of results should be also proved.

The addresses of future research should be also written.

Author Response

Dear reviewer, please find the modification instructions in the attachment. Thank you.

Author Response File: Author Response.pdf

Round 2

Reviewer 2 Report

No comments

This manuscript is a resubmission of an earlier submission. The following is a list of the peer review reports and author responses from that submission.