A Safe Location for a Trip? How the Characteristics of an Area Affect Road Accidents—A Case Study from Poznań

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

Dear Author, 

I appreciate you hard work and research in such important safety area but there are some comments and suggestions I believe it is better to be considered to sound research paper. 

 

Kind regards, 

Reviewer.

Comments for author File: Comments.odt

Author Response

Thank you very much for you suggestions. I attached a file with revisions, yours comments are marked in red.

Author Response File: Author Response.docx

Reviewer 2 Report

Comments and Suggestions for Authors

This article investigates a highly relevant and timely topic: "A safe location for a trip? How the characteristics of an area affect road accidents – a case study from Poznań." The subject matter is important, and the analytical methods are generally appropriate. However, I have identified several concerns that, if addressed, could significantly enhance the clarity, depth, and academic rigor of the manuscript:

1. The study aims to examine the factors influencing the number of accidents in Poznań. However, Figure 3 presents crash severity categorized into three levels, while the analysis applies only a single OLS model focused on crash frequency. This raises a concern about analytical alignment. Why did the authors not consider a disaggregated analysis by crash severity level (e.g., minor, serious, fatal)? Since different factors may influence different levels of crash severity, using a single model could obscure important variations and policy-relevant insights.
2. The manuscript does not account for differences in crash types (e.g., involving pedestrians, motorcycles, or large vehicles). Prior research has shown that crash characteristics and outcomes vary significantly by vehicle type and between single-vehicle and multi-vehicle incidents. The lack of classification may limit the interpretability of the findings and reduce their policy relevance. The authors should justify why they chose not to disaggregate by crash type, or discuss how this limitation may affect the robustness of the conclusions.
3. The use of only one year of crash data raises concerns about temporal stability and representativeness. Crash frequencies and patterns may fluctuate year to year due to various factors (e.g., weather, infrastructure changes, enforcement measures). Relying on a single year may lead to biased estimates or limit the generalizability of findings for long-term safety planning. The authors should acknowledge this limitation and discuss its potential impact on the study's conclusions.
4. The Discussion section currently lacks depth and structure. A more organized synthesis of the key findings—particularly those related to spatial characteristics or accident hotspots—should be presented. Additionally, the study would benefit from a more thorough discussion of policy implications, including recommendations for traffic safety improvements, spatial planning, and prioritization of road safety investments. Consider using subheadings or distinct paragraphs to clearly present findings, implications, and directions for future research.

Author Response

Thank you very much for your suggestions. I attached a revised file, your comments are marked in red.

Author Response File: Author Response.docx

Reviewer 3 Report

Comments and Suggestions for Authors

In this paper, Ordinary Least Squares (OLS) and Geographically Weighted Regression (GWR) methods are employed to analyze the factors influencing road traffic accidents, focusing on the scale data of urban road infrastructure. Several additional details are recommended for inclusion.

1. In the introduction, a comprehensive analysis of accident factors, including weather and gender, is presented. Additionally, relevant literature related to the factors analyzed in this paper is suggested for further supplementation, thereby establishing the research focus of this study.

2. In Figure 2, please add a legend.

3. The parameters primarily utilized in the regression process are static data from the relevant category. However, the occurrence of road accidents exhibits a degree of randomness and is influenced by the current state of road traffic. How does the author address this issue?

4. To enhance the visualization of the spatial clustering of road accidents, it is recommended to include a map illustrating the results of the Moran's Global Statistics.

Author Response

Thank you very much for your suggestions. I attached a revised file, your comments are marked in red.

Author Response File: Author Response.docx

Reviewer 4 Report

Comments and Suggestions for Authors

The paper employs robust statistical techniques, including OLS and GWR, to analyze spatial determinants of road accidents, providing valuable insights into localized factors. Some concerns and suggestions are as follows.

1. The study focuses solely on 2023 data, which may not account for seasonal or annual variations. If possible, expanding the time frame could strengthen the generalizability of the results.
2. While the paper identifies significant variables, it does not deeply explore causal mechanisms. For example, why do more traffic lights (LN) correlate with higher accidents? Further discussion is needed.
3. The findings are specific to Poznań. A brief comparison with similar cities or regions could highlight the uniqueness or universality of the results.
4. The paper could elaborate more on specific, actionable policy measures derived from the GWR results, such as targeted infrastructure improvements in high-risk zones.

The paper is well-structured and methodologically sound, but addressing the above points—particularly expanding the discussion would enhance its depth and applicability. The revisions are minor and do not undermine the overall quality of the work.

Author Response

Thank you very much for your suggestions. I attached a revised file, your comments are marked in red.

Author Response File: Author Response.docx