Socio-Cognitive Determinants of Pedestrians’ Intention to Cross on a Red Light Signal: An Application of the Theory of Planned Behaviour

Round 1

Reviewer 1 Report

Overall, this manuscript aims to develop valid and reliable scales representing the extension of the Theory of planned behavior (TPB) by using the EFA, and the contribution of traditional components of TPB, such as attitudes, subjective norms, and perceived behavioral control, in the prediction of pedestrians' intentions to cross on a red light, as well as some additional predictors for which it is presupposed that can significantly contribute to the predictive capability of the model.  Overall, this manuscript was organized well with sufficient details. Still, I think some concerns need further clarification before its potential acceptance.

(1) Unique motivations, current challenges, and main contributions should be carefully explained in the introduction.

(2) The scale of the questionnaire size (383) seems relatively small.

(3) Why not conduct a further CFA?

(4) The corresponding implications and countermeasures were not discussed in detail.

Author Response

Dear Reviewer,

We want to extend our appreciation for taking the time and effort necessary to provide such insightful guidance. We would like to thank you for your comments and suggestions.

The revision, based on the review team’s collective input, includes a number of positive changes. We have revised the manuscript according to your suggestions. The changes were highlighted in the revised manuscript.

We hope that these revisions improve the paper so that you now deem it worthy of publication in Safety.

The revised version contains the following changes and amendments:

 Overall, this manuscript aims to develop valid and reliable scales representing the extension of the Theory of planned behavior (TPB) by using the EFA, and the contribution of traditional components of TPB, such as attitudes, subjective norms, and perceived behavioral control, in the prediction of pedestrians' intentions to cross on a red light, as well as some additional predictors for which it is presupposed that can significantly contribute to the predictive capability of the model. Overall, this manuscript was organized well with sufficient details. Still, I think some concerns need further clarification before its potential acceptance.

(1) Unique motivations, current challenges, and main contributions should be carefully explained in the introduction.

Response:

Thanks for the suggestion. The text is revised to clarify this issue.

(2) The scale of the questionnaire size (383) seems relatively small.

Response:

Thanks for the comment. The reliability of factor analysis is dependent on sample size. In statistical literature there are no uniform rules of thumb for the necessary sample size for factor analysis. However, „Kass and Tinsley (1979) recommended having between 5 and 10 participants per variable up to a total of 300 (beyond which test parameters tend to be stable regardless of the participant to variable ratio). Indeed, Tabachnick and Fidell (2007) agree that ‘it is comforting to have at least 300 cases for factor analysis’ (p. 613) and Comrey and Lee (1992) class 300 as a good sample size, 100 as poor and 1000 as excellent“. According to Field (2009), it is reccomended to use the Kaiser–Meyer–Olkin measure of sampling adequacy (KMO). KMO values between 0.5 and 0.7 are mediocre, values between 0.7 and 0.8 are good, values between 0.8 and 0.9 are great and values above 0.9 are superb. In our research KMO = 0.87 and all KMO values for individual variable were higher than 0.68, which is good, because the lower acceptable limit is 0.50 (see page 6, lines 203 and 204). Therefore, we believe that the sample size is adequate for factor analysis.

(3) Why not conduct a further CFA?

Response:

Thanks for the comment. In fact, in scientific circles there is continuing debate concerns the appropriate role for factor analysis. Many researchers consider it only exploratory, useful in searching for structure among a set of variables or as a data reduction method. In this perspective, factor analytic techniques “take what the data give you” and do not set any a priori constraints on the estimation of components or the number of components to be extracted. For many, if not most applications, this use of factor analysis is appropriate. We agree that it is common practice to conduct CFA after EFA. However, methodologically, EFA and CFA models cannot be employed in the same data. Taking into account that our sample is 383 participants, it is nost possible to divide it into two subgroups in order to provide both quality analyses. We recommend conducting further factor analysis (i.e., CFA) to assess the degree to which the data meet the expected structure.

(4) The corresponding implications and countermeasures were not discussed in detail.

 Response:

 Thank you for your helpful suggestion. We have made the changes as suggested by the Reviewer. In the revised manuscript, the section about road safety implications has been re-written. The text is revised to clarify this issue. We hope that you find these revisions an improvement.

Author Response File: Author Response.docx

Reviewer 2 Report

The article validates an instrument to assess the determinants of pedestrians' intention to violate traffic rules. Therefore, the results present relevant practical applications in the traffic and urban mobility sector, especially at the local level. In the following, I will make some suggestions to the authors.

The introduction adequately contextualizes the problem, although I recommend dividing it into various subsections "background", "situation in the region of application", "objectives and hypotheses of the study", etc. 

Regarding the methodology, in addition to the sociodemographic characteristics of the participants and the variables evaluated with the instrument applied, aspects related to the administration of the questionnaire, statistical analyses applied, and ethical aspects of the study, among others, should be included.

The results are clear, and the discussion presents the data obtained contrasting them with other research, which is adequate. Only, I recommend briefly mentioning potential preventive measures to reduce pedestrian offending behaviors such as communication campaigns or road safety training programs for adults (e.g. https://doi.org/10.17583/ijep.8805).

Finally, I recommend including a specific section for conclusions indicating the main practical applications of the study and future lines of research.

Author Response

Dear Reviewer,

We want to extend our appreciation for taking the time and effort necessary to provide such insightful guidance. We would like to thank you for your comments and suggestions.

The revision, based on the review team’s collective input, includes a number of positive changes. We have revised the manuscript according to your suggestions. The changes were highlighted in the revised manuscript.

We hope that these revisions improve the paper so that you now deem it worthy of publication in Safety.

The revised version contains the following changes and amendments:

 The article validates an instrument to assess the determinants of pedestrians' intention to violate traffic rules. Therefore, the results present relevant practical applications in the traffic and urban mobility sector, especially at the local level. In the following, I will make some suggestions to the authors.

1. The introduction adequately contextualizes the problem, although I recommend dividing it into various subsections "background", "situation in the region of application", "objectives and hypotheses of the study", etc.

Response:

Thank you for your helpful suggestion. The ‘Introduction’ section has been revised and the comments were mostly adopted in our revision

Regarding the methodology, in addition to the sociodemographic characteristics of the participants and the variables evaluated with the instrument applied, aspects related to the administration of the questionnaire, statistical analyses applied, and ethical aspects of the study, among others, should be included.

Response:

Thanks for the suggestion. Text is revised as directed.

The results are clear, and the discussion presents the data obtained contrasting them with other research, which is adequate. Only, I recommend briefly mentioning potential preventive measures to reduce pedestrian offending behaviors such as communication campaigns or road safety training programs for adults (e.g. https://doi.org/10.17583/ijep.8805).

Response:

Thanks for the suggestion. Text is revised as directed.

Finally, I recommend including a specific section for conclusions indicating the main practical applications of the study and future lines of research.

Response:

Thank you for your helpful suggestion. We have made the changes as suggested by the Reviewer. In the revised manuscript, the section about road safety implications and further recommendations has been re-written. The text is revised to clarify this issue. We hope that you find these revisions an improvement.

Author Response File: Author Response.pdf

Reviewer 3 Report

This study develops an extended TPB model for the pedestrians’ intentions to cross on a red-light signal. This study employed quota sampling to gather 383 valid responses. Principal component analysis and hierarchical regression was used to analyze the data. Personal norm was found the as the most important predictor of pedestrians’ intentions to cross on red light signal. Though the study conveys some important findings, however, it contains several major issues which needs to be addressed. Please find point by point comments below;

1. In the title, “red light sign” was written which should be revised as “red light signal” 

2. Several behavioral theories exist in transportation literature such as social cognitive theory, push pull theory but TPB was used for this aspect. The authors should explain the reasons in the introduction to frame their research better. Please refer to:

3. This study lacks in defining its contribution. Merely a scale development can not be contribution as many studies in the past have developed the questionnaires for the same issues. The study should explain how it is different from existing studies and what new has been contributed to the science. Similar studies are as follows; 

• Suo Q, Zhang D (2016) Psychological Differences toward Pedestrian Red Light Crossing between University Students and Their Peers. PLOS ONE 11(1): e0148000. https://doi.org/10.1371/journal.pone.0148000

• Zhou, H., Romero, S. B., & Qin, X. (2016). An extension of the theory of planned behavior to predict pedestrians’ violating crossing behavior using structural equation modeling. Accident Analysis & Prevention, 95, 417-424.

• Xiao, Y., Liu, Y., & Liang, Z. (2021). Study on road-crossing violations among young pedestrians based on the theory of planned behavior. Journal of advanced transportation, 2021, 1-11.

• Zhu, D. (2022). Red light running behavior and safety of pedestrians at signalized crossings.

4. Line 80-84 about variability needs reference to support this claim. 

5. All tables should be revised to make them self-explanatory. Please add note for the abbreviations used in the tables, i.e., AA, CA, HBT…. And so on. 

6. The term “Sign” was used in the items to measure the constructs. Please explain how come a don’t walk sign and red light signal is a same thing? For the clarity, please add pictures if possible. 

7. Please check normality of the data using skewness and kurtosis. 

8. Please justify the usage of hierarchical regression as many studies have been using structural equation modeling for the similar studies. Please explain why hierarchical regression is important to use here. 

9. References section is missing, so, I cannot verify the references. 

10. Data Availability statement is not appropriate. The authors should consider to provide the relevant data on reasonable request. 

Moderate improvement is required

Author Response

Dear Reviewer,

We want to extend our appreciation for taking the time and effort necessary to provide such insightful guidance. We would like to thank you for your comments and suggestions.

The revision, based on the review team’s collective input, includes a number of positive changes. We have revised the manuscript according to your suggestions. The changes were highlighted in the revised manuscript.

We hope that these revisions improve the paper so that you now deem it worthy of publication in Safety.

The revised version contains the following changes and amendments:

This study develops an extended TPB model for the pedestrians’ intentions to cross on a red-light signal. This study employed quota sampling to gather 383 valid responses. Principal component analysis and hierarchical regression was used to analyze the data. Personal norm was found the as the most important predictor of pedestrians’ intentions to cross on red light signal. Though the study conveys some important findings, however, it contains several major issues which needs to be addressed. Please find point by point comments below;

1. In the title, “red light sign” was written which should be revised as “red light signal” 

Response:

We are in agreement with the comments. It was corrected.

2. Several behavioral theories exist in transportation literature such as social cognitive theory, push pull theory but TPB was used for this aspect. The authors should explain the reasons in the introduction to frame their research better. Please refer to:

• Jiang, Q., Huang, H., Zhao, W., Baig, F., Lee, J., & Li, P. (2021). Intention of risk-taking behavior at unsignalized intersections under the connected vehicle environment. IEEE Access, 9, 50624-50638.
• Baig, F., Zhang, D., Lee, J., & Xu, H. (2022). Shaping inclusiveness of a transportation system: Factors affecting seat-yielding behavior of university students in public transportation. Transportation Research Part A: Policy and Practice, 155, 79-94.
• Baig, F., Talpur, A., Das, G. et al. Willingness to Shift towards Biogas-fueled Bus Rapid Transit in Karachi, Pakistan. KSCE J Civ Eng (2024). https://doi.org/10.1007/s12205-024-1636-9

Lee, J., Baig, F., Talpur, M. A. H., & Shaikh, S. (2021). Public intentions to purchase electric vehicles in Pakistan. Sustainability, 13(10), 5523.

Response:

Thank you for your helpful suggestion. The ‘Introduction’ section has been revised and the comments were mostly adopted in our revision

3. This study lacks in defining its contribution. Merely a scale development can not be contribution as many studies in the past have developed the questionnaires for the same issues. The study should explain how it is different from existing studies and what new has been contributed to the science. Similar studies are as follows;

• Suo Q, Zhang D (2016) Psychological Differences toward Pedestrian Red Light Crossing between University Students and Their Peers. PLOS ONE 11(1): e0148000. https://doi.org/10.1371/journal.pone.0148000
• Zhou, H., Romero, S. B., & Qin, X. (2016). An extension of the theory of planned behavior to predict pedestrians’ violating crossing behavior using structural equation modeling. Accident Analysis & Prevention, 95, 417-424.
• Xiao, Y., Liu, Y., & Liang, Z. (2021). Study on road-crossing violations among young pedestrians based on the theory of planned behavior. Journal of advanced transportation, 2021, 1-11.
• Zhu, D. (2022). Red light running behavior and safety of pedestrians at signalized crossings.

Response:

We are in agreement with the comments. The ‘Introduction’ section was revised and the comments were adopted in our revision.

4. Line 80-84 about variability needs reference to support this claim. 

Response:

Text is revised as directed.

5. All tables should be revised to make them self-explanatory. Please add note for the abbreviations used in the tables, i.e., AA, CA, HBT…. And so on.

Response:

We are in agreement with the comments. It was corrected.

6. The term “Sign” was used in the items to measure the constructs. Please explain how come a don’t walk sign and red light signal is a same thing? For the clarity, please add pictures if possible.

Response:

Thanks for the suggestion. The text is revised to clarify this issue.

7. Please check normality of the data using skewness and kurtosis.

Response:

Thanks for the suggestion. The text is revised to clarify this issue.

8. Please justify the usage of hierarchical regression as many studies have been using structural equation modeling for the similar studies. Please explain why hierarchical regression is important to use here. 

Response:

Thanks for the comment. In fact, in liretature there is no ’rule of thumb’ whether to use SEM or regression analysis. We agree that that SEM is more comprehensive approach. However, it depends on what we want to explore. If we want to analyze indirect effects of factors and their impact on two the dependent variable simultaneously, SEM will be better option. Regression can however measure only one dependent variable at at time. Thaking into account that we initially used exploratory approach to reduce number of items and examine factor structure of the extended TPB model, and that we have just one dependent variable (intention), we decided to use EFA → hierarchical regression approach.

9. References section is missing, so, I cannot verify the references.

Response:

In the original Manuscript that we uploaded on the Journal’s platform, there were references. Probably due to technical problems, the references section was deleted. Nevertheless, we added this section and conducted correction in accordance with Reviewer's suggestion.

10. Data Availability statement is not appropriate. The authors should consider to provide the relevant data on reasonable request.

Response:

It was corrected.

Author Response File: Author Response.pdf

Reviewer 4 Report

The paper is about a self-reported instrument that measures the determinants of pedestrians’ intentions to violate traffic rules. 

The title of this paper is somewhat misleading: The paper seems to result in factors that predict pedestrians’ intentions, however the instrument has not been tested in practice. So it is not certain that the factors are really relevant for crossing behaviour. Please let the title express this uncertainty. 

The introduction is mainly focussed on the theoretical aspects of the method used. It is not quite clear why you have chosen the behaviour of crossing pedestrians as the subject for this paper. 

The paper gives a straightforward report about the findings. The section with discussion and conclusions is quite extensive and could be more concise.

Author Response

Dear Reviewer,

We want to extend our appreciation for taking the time and effort necessary to provide such insightful guidance. We would like to thank you for your comments and suggestions.

The revision, based on the review team’s collective input, includes a number of positive changes. We have revised the manuscript according to your suggestions. The changes were highlighted in the revised manuscript.

We hope that these revisions improve the paper so that you now deem it worthy of publication in Safety.

The revised version contains the following changes and amendments:

 The paper is about a self-reported instrument that measures the determinants of pedestrians’ intentions to violate traffic rules.

1. The title of this paper is somewhat misleading: The paper seems to result in factors that predict pedestrians’ intentions, however the instrument has not been tested in practice. So it is not certain that the factors are really relevant for crossing behaviour. Please let the title express this uncertainty.

Response:

The text has been revised to clarify this issue.

2. The introduction is mainly focussed on the theoretical aspects of the method used. It is not quite clear why you have chosen the behaviour of crossing pedestrians as the subject for this paper.

Response:

We are in agreement with the comments. The ‘Introduction’ section was revised and the comments were adopted in our revision.

3. The paper gives a straightforward report about the findings. The section with discussion and conclusions is quite extensive and could be more concise.

Response:

Thanks for the suggestion. The text is revised to clarify this issue.

Author Response File: Author Response.docx

Round 2

Reviewer 1 Report

Thanks for addressing my previous comments, I have no further questions at this round, and I will recommend it to be accepted by this journal.

Good luck with your future research.

Author Response

Dear Reviewer,

We want to extend our appreciation for taking the time and effort necessary to provide such insightful guidance. We would like to thank you for your comments and suggestions.

Author Response File: Author Response.docx

Reviewer 2 Report

The authors have taken into account the suggestions I provided in my previous review, so I consider that the manuscript is suitable for publication.

Author Response

Dear Reviewer,

We want to extend our appreciation for taking the time and effort necessary to provide such insightful guidance. We would like to thank you for your comments and suggestions.

Author Response File: Author Response.docx

Reviewer 3 Report

Thank you for the revisions. The authors has successfully resolved major issues. Few minor issues are as follows:

The authors claim that there are no similar studies which is not true. The authors should rephrase this sentence and avoid such strong claim. (144-156)

Response to my previous comment is not satisfactory. Please add the references to set the stage about social theories and then discuss the utilization of TPB. TPB is one of the famous theory used in transportation studies to study behavior. There are many existing theories and should be acknowledged in this study to let reader know the reasons why you found TPB suitable for your study:

Several behavioral theories exist in transportation literature such as social cognitive theory, push pull theory but TPB was used for this aspect. The authors should explain the reasons in the introduction to frame their research better. Please use these references to let the reader know the usability of different theories for different purposes:

In the section 2.2.1

Please use Likert scale consistently. Currently “uni polar” term and “Likert scale” was used interchangeably. Likert scale itself is uni polar in this study. Therefore, please use “Likert scale throughout for better clarity.

No major issue. Please proofread the manuscript carefully.

Author Response

Dear Reviewer,

We want to extend our appreciation for taking the time and effort necessary to provide such insightful guidance. We would like to thank you for your comments and suggestions.

The revision, based on the review team’s collective input, includes a number of positive changes. We have revised the manuscript according to your suggestions. The changes were highlighted in the revised manuscript.

We hope that these revisions improve the paper so that you now deem it worthy of publication in Safety.

The revised version contains the following changes and amendments:

Thank you for the revisions. The authors has successfully resolved major issues. Few minor issues are as follows:

The authors claim that there are no similar studies which is not true. The authors should rephrase this sentence and avoid such strong claim. (144-156)

Response:

Thanks for the suggestion. The text is revised to clarify this issue.

Response to my previous comment is not satisfactory. Please add the references to set the stage about social theories and then discuss the utilization of TPB. TPB is one of the famous theory used in transportation studies to study behavior. There are many existing theories and should be acknowledged in this study to let reader know the reasons why you found TPB suitable for your study:

Several behavioral theories exist in transportation literature such as social cognitive theory, push pull theory but TPB was used for this aspect. The authors should explain the reasons in the introduction to frame their research better. Please use these references to let the reader know the usability of different theories for different purposes:

- Baig, F., Talpur, A., Das, G. et al. Willingness to Shift towards Biogas-fueled Bus Rapid Transit in Karachi, Pakistan. KSCE J Civ Eng (2024)

- Lee, J., Baig, F., Talpur, M. A. H., & Shaikh, S. (2021). Public intentions to purchase electric vehicles in Pakistan. Sustainability, 13(10), 5523.

Response:

Thank you for your helpful suggestion. We have made the changes as suggested by the Reviewer. The ‘Introduction’ section was revised and the comments were adopted in our revision. We hope that you find these revisions an improvement.

In the section 2.2.1

Please use Likert scale consistently. Currently “uni polar” term and “Likert scale” was used interchangeably. Likert scale itself is uni polar in this study. Therefore, please use “Likert scale throughout for better clarity.

Response:

We are in agreement with the comments. It was corrected.

Author Response File: Author Response.docx

Reviewer 4 Report

Thank you for improving this paper.

Author Response

Dear Reviewer,

We want to extend our appreciation for taking the time and effort necessary to provide such insightful guidance. We would like to thank you for your comments and suggestions.

Author Response File: Author Response.pdf

Round 3

Reviewer 3 Report

No further comment

No further comment