The EU and Sustainable Low-Emission Transport? Current State and Challenges of Environmentally Sustainable and Low-Emission Transport in the EU

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

• The study is very interesting; please give numerical important results at the end of the abstract.
• No clear research gap is identified; the paper reads more as a policy commentary than an original empirical study. Please make it clear.
• Figures 1–3 are referenced in the text but not legible/absent from the submission; raw output (R console text) appears in Fig. 2.. Please check.
• The bivariate correlation (Table 2) and regression (Fig. 2) are presented without stating assumptions or diagnostics. With only 27 observations (EU member states), the model has very low degrees of freedom. No multicollinearity check is reported despite CO₂ and population being highly correlated (r = 0.94). The adjusted R² of 0.43 is described inconsistently — at one point as "not entirely low" and elsewhere as "median value." The authors should provide: (a) VIF scores, (b) residual plots, (c) justification for the regression specification, and (d) a honest interpretation of the model's limited explanatory power.
• Figure 2 reproduces raw R console output verbatim, which is not publishable. All figures must be reformatted as proper publication-quality graphics with labeled axes, legends, and figure captions that are self-explanatory. The scatter plot matrix (Fig. 1) is too small to be legible at publication resolution.
• The paper conflates two distinct meanings of "SMART": the management acronym (Specific-Measurable-Achievable-Relevant-Timed) and the concept of technology-enabled "smart cities." This creates persistent ambiguity throughout. One of these usages should be dropped or clearly differentiated at first use.
• Claims such as "more than 94% of all studies on SMART cities are devoted to economic or social aspects" (lines 54–56) require a clearly identified source and date range. Several references appear to be EU policy documents rather than peer-reviewed literature. The references section mixes citation styles inconsistently (some include DOIs, others do not). References [1] and [2] are EU reports but are cited as if they were systematic analyses — the distinction should be made explicit.
• Figure 2 reproduces raw R console output, which is not publishable. All three figures need to be redrawn to publication standard with labeled axes and self-contained captions. The access date on Reference [1] ("2025-15-30") is impossible and suggests the reference list was not proofread.

Author Response

Comment: The study is very interesting; please give numerical important results at the end of the abstract.

Response: Calculated another model and gived the results to the abstract.

Comment: No clear research gap is identified; the paper reads more as a policy commentary than an original empirical study. Please make it clear.

Response: 

Chapter 1.1. improved:

The article assesses the current progress of the transition to low-emission and zero-emission transport within individual EU member states, with a focus on the regional level (if the regional datasets are available). The article analyze the relationship between the level of transport transformation in the EU and the performance of individual member states.

Comment: Figures 1–3 are referenced in the text but not legible/absent from the submission; raw output (R console text) appears in Fig. 2.. Please check.

Response: Checked, repaired and the new results added.

Comment: The bivariate correlation (Table 2) and regression (Fig. 2) are presented without stating assumptions or diagnostics. With only 27 observations (EU member states), the model has very low degrees of freedom. No multicollinearity check is reported despite CO₂ and population being highly correlated (r = 0.94). The adjusted R² of 0.43 is described inconsistently — at one point as "not entirely low" and elsewhere as "median value." The authors should provide: (a) VIF scores, (b) residual plots, (c) justification for the regression specification, and (d) a honest interpretation of the model's limited explanatory power.

Response: I checked, calculated the proposed indicators, tested for correlation, heteroscedasticity and outliers.. Then I just calculed another model (ordered logit model) - more suitable for the data.

Comment: Figure 2 reproduces raw R console output verbatim, which is not publishable. All figures must be reformatted as proper publication-quality graphics with labeled axes, legends, and figure captions that are self-explanatory. The scatter plot matrix (Fig. 1) is too small to be legible at publication resolution.

Response: Figure 1 and 2 was deleted. Figures are reformatted, but some details are not clearly visited in the manuscript, but are visible in the individual figures folder.

Comment: The paper conflates two distinct meanings of "SMART": the management acronym (Specific-Measurable-Achievable-Relevant-Timed) and the concept of technology-enabled "smart cities." This creates persistent ambiguity throughout. One of these usages should be dropped or clearly differentiated at first use.

Response: I rewrite it to the right meaning: Cities that utilize modern information systems, their integration, innovation, and collaboration, and learning for future development, with the aim of improving residents’ quality of life, increasing competitiveness, and supporting technological development within a comprehensive urban system.

Comment: Claims such as "more than 94% of all studies on SMART cities are devoted to economic or social aspects" (lines 54–56) require a clearly identified source and date range. Several references appear to be EU policy documents rather than peer-reviewed literature. The references section mixes citation styles inconsistently (some include DOIs, others do not). References [1] and [2] are EU reports but are cited as if they were systematic analyses — the distinction should be made explicit.

Response: Repared.

Comment: Figure 2 reproduces raw R console output, which is not publishable. All three figures need to be redrawn to publication standard with labeled axes and self-contained captions. The access date on Reference [1] ("2025-15-30") is impossible and suggests the reference list was not proofread.

Response: Repared. Fig. 2 deleted. All figures redrawn to publication standard. The access date repared.

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

1-A very major issue here: The manuscript lacks a clearly defined methodology section. Key elements such as data sources, variable construction, model specification, statistical tools, and underlying assumptions are either missing or insufficiently described. This significantly limits the transparency, reproducibility, and credibility of the analysis. A dedicated methodology section should be added, clearly outlining the dataset, analytical approach, regression model, and diagnostic testing procedures.

2- Then let's start with the title. I looked carefully throughout the paper, and I did not see a technology gap that has been bridged. Would you kindly revise the title to reflect the actual content and contribution of the paper?

3-From the first line in the abstract and in some locations in the manuscript, I noticed that the author uses "climate protection" or "climate change protection." This terminology is not common. Do you mean climate change mitigation? This has to be fixed.

4-I am also conceptually confused. The use of SMART here is mixed up between (SMART cities, which refer to technology-driven cities, and SMART as a framework concept referring to S: Specific, M: measurable, etc. Hence, the author should define the terms earlier and clarify their use properly.

5- Another issue is that the model results are slightly overstated. Around lines 420–423, the paper says the adjusted R² of 0.43 is “not low.” However, statistically, we know that an R² of 0.43 is moderate, not strong. This means the model explains some of the variation, but not all.

6-The study lacks a strong theoretical framework (e.g., innovation diffusion, environmental governance, or socio-technical transitions) to anchor findings. 

7-Regarding policy, the issue is that several policies can be suggested, but it is recommended to keep those that are PRACTICAL and RELEVANT.

8-Why do the conclusions have references?

9- Kindly add the limitation section

10- Language should be revised; there are lots of repetitions, also the terminology, as I mentioned earlier " protection vs mitigation), some sentences are so long, etc. 

Comments on the Quality of English Language

Needs improvement

Author Response

Comment: 1-A very major issue here: The manuscript lacks a clearly defined methodology section. Key elements such as data sources, variable construction, model specification, statistical tools, and underlying assumptions are either missing or insufficiently described. This significantly limits the transparency, reproducibility, and credibility of the analysis. A dedicated methodology section should be added, clearly outlining the dataset, analytical approach, regression model, and diagnostic testing procedures.

Response: I rewrite the whole manuscript. Data, methodology, results, discussion, limitation and other sections are included.

Comment: 2- Then let's start with the title. I looked carefully throughout the paper, and I did not see a technology gap that has been bridged. Would you kindly revise the title to reflect the actual content and contribution of the paper?

Response: Rewrited:

EU and Sustainable Low-Emission Transport? Current State and Challenges of Environmentally Sustainable and Low-Emission Transport in EU

Comment: 3-From the first line in the abstract and in some locations in the manuscript, I noticed that the author uses "climate protection" or "climate change protection." This terminology is not common. Do you mean climate change mitigation? This has to be fixed.

Response: 

Yes, I fixed it.

Comment: 4-I am also conceptually confused. The use of SMART here is mixed up between (SMART cities, which refer to technology-driven cities, and SMART as a framework concept referring to S: Specific, M: measurable, etc. Hence, the author should define the terms earlier and clarify their use properly.

Response: I rewrite it to the right meaning: Cities that utilize modern information systems, their integration, innovation, and collaboration, and learning for future development, with the aim of improving residents’ quality of life, increasing competitiveness, and supporting technological development within a comprehensive urban system.

Comment: 5- Another issue is that the model results are slightly overstated. Around lines 420–423, the paper says the adjusted R² of 0.43 is “not low.” However, statistically, we know that an R² of 0.43 is moderate, not strong. This means the model explains some of the variation, but not all.

Response: I rewrited the sentence.

Comment: 6-The study lacks a strong theoretical framework (e.g., innovation diffusion, environmental governance, or socio-technical transitions) to anchor findings. 

Response: I rewrite the theoretical background and include more information.

Comment: 7-Regarding policy, the issue is that several policies can be suggested, but it is recommended to keep those that are PRACTICAL and RELEVANT.

Response: I include more practical information. 

Comment: 8-Why do the conclusions have references?

Response: It was discussion and conclusion together. Now it is whole rewrited.

Comment: 9- Kindly add the limitation section.

Response: Added.

Comment: 10- Language should be revised; there are lots of repetitions, also the terminology, as I mentioned earlier " protection vs mitigation), some sentences are so long, etc. 

Response: I give the manuscript to the english revision.

Reviewer 3 Report

Comments and Suggestions for Authors

The scope and purpose of the paper is interesting, however a major revision is needed to improve its readability and content. Some general remarks are presented below:

A. The distinction between “smart” cities, in terms of an ICT-based urban development model through technological innovation (supporting sustainability principles), and S.M.A.R.T., in terms of Specific, Measurable, Achievable, Realistic, and Timely, should be made clear. It is not the same term and creates confusion from the introductory section as regards the scope of the paper.

B. The whole document includes many references to the European Green Deal, which is indeed the current overarching EU policy framework. However, there are sectoral policy documents, e.g. Sustainable and Smart Mobility Strategy, New EU urban mobility framework etc., which implement the EGD and include specific elements which should be considered in the paper.

C. The narrative of the paper is not focused. The structure is weak and should be reorganized. More specifically, section 3 should be restructured to be better supported by the theoretical background of section 2, to adequately describe the methodology, to present results in a concrete way and provide a synthetic analysis of the findings. The research questions and objectives as well as the ways that the methodology addresses them are not clear. The link between digital and green transitions is not sufficiently argued. The “technology gap” refers both to states and community groups in different parts of the paper, without providing a sufficient relation between the two. Smart transport is not defined in the context of the paper, while references are made to interurban and urban modes, transport and data management technologies, shared mobility etc.

In the above framework, some specific comments are given below:

1. Line 33. What is the “EU’s plan”? Please elaborate and provide references.

2. Lines 42-47. Smart transport, in terms of New Mobility Services, Intelligent Transport Systems and, in general, the use of technology-driven and innovative transport solutions, is not by definition linked to environmental sustainability. So, it cannot be defined as a fundamental environmental issue, unless the link between smart and environmental friendly mobility is explained (in this case possibly through the EU policy framework).

3. Line 48. The phrase “The EU and research” is vague. What is it meant by “EU”? EU policy perhaps? Does “research” refer to international research literature? Please clarify.

4. Lines 49-51. I do not think that the argument: “Research and policy have generally focused primarily on economic sustainability, but not on technological, environmental and social sustainability” can stand as it is. It is true that the analysis of EU transport policy in the last decade of the 20^th century focused on economic sustainability via market liberalization etc., but the policies from 2001 and beyond progressively cover the environmental and social aspects as well. Moreover, research is covering social and environmental sustainability in cities for many decades (see for example Banister’s sustainable mobility paradigm from 2008). Thus, the argument could be rephrased. The same applies for Lines 53-54.

5. I believe that the statistics in Lines 55-57 refer only to reference [10] and not to [9] and [10].

6. In Line 90, both references refer to electromobility, while the concept described is more general.

7. In Lines 97-100, the references to PPP and PESTEL are not sufficiently connected to the discussion. Please elaborate.

8. In Lines 190-193 the gap of access to mobility services, beyond access to ICT, should be elaborated and supported by literature.

9. How are Lines 219-225 linked to the exclusion and inequalities discussed in the above section?

10. Section 2.1. refers to individual behavioral aspects, but these individual aspects are not analyzed. Are you referring to distrust faced with innovation or indifference towards environmental sustainability? How is the “technological gap” connected with this section?

11. Section 2.2 begins with the technological divide, mostly focused on different age groups, and then discusses renewable energy sources. The link is again unclear, as the use of renewable sources does not necessarily mean that the end user should be more digitally literate.

12. In 3.1 it is mentioned: “The areas that European cities can influence are as follows: high-speed rail and road transport. While high-speed rail is usually planned at the level of states and larger territorial units (e.g., EU NUTS regions), individual regions and cities can take action in the area of road transport to meet the EGD's low-emission targets.” So high-speed rail cannot be an area that cities can influence.

13. The methodology for the data analysis in 3.1 should be described in a more systematic way. The way that input derived from CCPI and EEA should be presented.

14. In 3.1, why transport beyond the urban level (e.g. air transport) is brought into the conversation, as it is the case with high-speed rail in a previous section? This is not related to policy about smart transport in cities (see New EU Urban Mobility Framework).

15. The purpose of section 3.2 is not clear. It presents some examples and some lessons from advanced cities. However, it would be beneficial to provide some concrete recommendations based on the examples but also on the findings from 3.1.

 

Author Response

The scope and purpose of the paper is interesting, however a major revision is needed to improve its readability and content. Some general remarks are presented below:

Comment: A. The distinction between “smart” cities, in terms of an ICT-based urban development model through technological innovation (supporting sustainability principles), and S.M.A.R.T., in terms of Specific, Measurable, Achievable, Realistic, and Timely, should be made clear. It is not the same term and creates confusion from the introductory section as regards the scope of the paper.

Response: 

I rewrite it to the right meaning: Cities that utilize modern information systems, their integration, innovation, and collaboration, and learning for future development, with the aim of improving residents’ quality of life, increasing competitiveness, and supporting technological development within a comprehensive urban system.

Comment: B. The whole document includes many references to the European Green Deal, which is indeed the current overarching EU policy framework. However, there are sectoral policy documents, e.g. Sustainable and Smart Mobility Strategy, New EU urban mobility framework etc., which implement the EGD and include specific elements which should be considered in the paper.

Response: Added to the manuscript:

The key transport documents in EU (Sustainable and Smart Mobility Strategy and New EU Urban Mobility Framework) outline specific measures and proposals for achieving the EGD’s objectives. These include e.g. promoting low-emission transport to work (in the case the “home office” is not possible), integrating AI into urban smart systems, and establishing a functional charging infrastructure for alternative-fuel vehicles.

Comment: C. The narrative of the paper is not focused. The structure is weak and should be reorganized. More specifically, section 3 should be restructured to be better supported by the theoretical background of section 2, to adequately describe the methodology, to present results in a concrete way and provide a synthetic analysis of the findings. The research questions and objectives as well as the ways that the methodology addresses them are not clear. The link between digital and green transitions is not sufficiently argued. The “technology gap” refers both to states and community groups in different parts of the paper, without providing a sufficient relation between the two. Smart transport is not defined in the context of the paper, while references are made to interurban and urban modes, transport and data management technologies, shared mobility etc.

Response: The whole manuscript is rewrited. Now it contain theoretical part, methodology and dat, results, discussion, limitation and conlcusion. 

In the above framework, some specific comments are given below:

Comment: 1. Line 33. What is the “EU’s plan”? Please elaborate and provide references.

Response: 

Rewrited to European Green Deal (EGD).

Comment: 2. Lines 42-47. Smart transport, in terms of New Mobility Services, Intelligent Transport Systems and, in general, the use of technology-driven and innovative transport solutions, is not by definition linked to environmental sustainability. So, it cannot be defined as a fundamental environmental issue, unless the link between smart and environmental friendly mobility is explained (in this case possibly through the EU policy framework).

Response: Rewrited.

Comment: 3. Line 48. The phrase “The EU and research” is vague. What is it meant by “EU”? EU policy perhaps? Does “research” refer to international research literature? Please clarify.

Response: 

Rewrited to EU policy.

Comment: 4. Lines 49-51. I do not think that the argument: “Research and policy have generally focused primarily on economic sustainability, but not on technological, environmental and social sustainability” can stand as it is. It is true that the analysis of EU transport policy in the last decade of the 20^th century focused on economic sustainability via market liberalization etc., but the policies from 2001 and beyond progressively cover the environmental and social aspects as well. Moreover, research is covering social and environmental sustainability in cities for many decades (see for example Banister’s sustainable mobility paradigm from 2008). Thus, the argument could be rephrased. The same applies for Lines 53-54.

Response: Rewrited and actualised.

Comment: 5. I believe that the statistics in Lines 55-57 refer only to reference [10] and not to [9] and [10].

Response: Rewrited.

Comment: 6. In Line 90, both references refer to electromobility, while the concept described is more general.

Response: 

After rewriting the introduction, this paragraph was deleted.

Comment: 7. In Lines 97-100, the references to PPP and PESTEL are not sufficiently connected to the discussion. Please elaborate.

Response: 

Rewrited: The successful implementation of Public Private Partnership (PPP) is studied in different aspects in these days by scholars.

Comment: 8. In Lines 190-193 the gap of access to mobility services, beyond access to ICT, should be elaborated and supported by literature.

Response: Rewrited.

Comment: 9. How are Lines 219-225 linked to the exclusion and inequalities discussed in the above section?

Response: The whole section was deleted and only important parts are concluded in the manuscript.

Comment: 10. Section 2.1. refers to individual behavioral aspects, but these individual aspects are not analyzed. Are you referring to distrust faced with innovation or indifference towards environmental sustainability? How is the “technological gap” connected with this section?

Response: 

I agree and delete this section.

Comment: 11. Section 2.2 begins with the technological divide, mostly focused on different age groups, and then discusses renewable energy sources. The link is again unclear, as the use of renewable sources does not necessarily mean that the end user should be more digitally literate.

Response: Rewrited to more suitable text for the manuscript.

Comment: 12. In 3.1 it is mentioned: “The areas that European cities can influence are as follows: high-speed rail and road transport. While high-speed rail is usually planned at the level of states and larger territorial units (e.g., EU NUTS regions), individual regions and cities can take action in the area of road transport to meet the EGD's low-emission targets.” So high-speed rail cannot be an area that cities can influence.

Response: Rewrited: 

The area that European cities can influence is road transport. The high-speed railway is being planned at the national and EU levels (e.g. EU NUTS regions), but it will have an impact on transportation in the affected SMART cities.

Comment: 13. The methodology for the data analysis in 3.1 should be described in a more systematic way. The way that input derived from CCPI and EEA should be presented.

Response: The whole methodology and data part was rewrited and more data sets included.

Comment: 14. In 3.1, why transport beyond the urban level (e.g. air transport) is brought into the conversation, as it is the case with high-speed rail in a previous section? This is not related to policy about smart transport in cities (see New EU Urban Mobility Framework).

Response: 

Rewrited for actual state of the documents.

Comment: 15. The purpose of section 3.2 is not clear. It presents some examples and some lessons from advanced cities. However, it would be beneficial to provide some concrete recommendations based on the examples but also on the findings from 3.1.

Response: 3.2. was modified to be more suitable for the manuscript.

Reviewer 4 Report

Comments and Suggestions for Authors

This study discusses the relationships between low-emission and zero-emission transport transition levels, technological divides, and climate performance across EU member states and smart cities. The topic is timely and interesting. However, several major concerns should be addressed as follows:

1. The introduction needs to present the urgency of the problem more directly by using quantitative statistics, such as transport-sector emissions in the EU, the contribution of urban transport to air pollution, and disparities in EV adoption and charging infrastructure deployment across member states. This would strengthen the motivation of the study and clarify its policy relevance.
2. The literature review should be updated by incorporating recent studies from the last 3 to 5 years on low-carbon transport transition, equity in smart mobility, and carbon-neutral urban transport policies. (1) How far does your food travel on the highway? Food miles and carbon footprint, (2) Does smart city policy promote urban green and low-carbon development?
3. From a methodological perspective, the study simultaneously discusses national-level analysis and smart-city-level cases, which creates ambiguity in the unit of analysis. A clearer research design is required, whether through country-level panel analysis, comparative city case studies, or a multilevel framework linking national and urban scales.
4. The regression model should include additional key explanatory variables such as GDP per capita, urbanization rate, vehicle ownership rate, public transport mode share, renewable energy generation share, fuel prices, and government subsidy levels. Explaining national rankings only with a limited set of environmental indicators raises a high risk of omitted variable bias. In particular, policy capacity and economic resources are critical determinants of sustainable transport transition and should be explicitly considered.
5. Since the dependent variable, CCPI ranking, is ordinal ranking data, methods more appropriate than simple OLS regression should be considered, such as ordered logit models, rank regression, or models using the original CCPI score. Rankings do not imply equal intervals between countries, which limits the interpretation of linear regression coefficients. Robustness checks using alternative sustainability indicators would further strengthen the empirical validity.
6. The smart city case analysis requires clearer case selection criteria and a standardized comparative framework. If Stockholm, Helsinki, and Ostrava are presented as examples, they should be compared using common indicators such as population size, fiscal capacity, modal share, charging station density, and carbon reduction performance. This would improve the analytical rigor and practical implications of the case discussion.

Author Response

This study discusses the relationships between low-emission and zero-emission transport transition levels, technological divides, and climate performance across EU member states and smart cities. The topic is timely and interesting. However, several major concerns should be addressed as follows:

Comment:

The introduction needs to present the urgency of the problem more directly by using quantitative statistics, such as transport-sector emissions in the EU, the contribution of urban transport to air pollution, and disparities in EV adoption and charging infrastructure deployment across member states. This would strengthen the motivation of the study and clarify its policy relevance.

Response: 

Rewrited in introduction about the current state:

The issue of sustainable transport is so urgent, given the hard data, that it is also addressed in the EGD. GHG emissions from transport in the EU reached 794 MtCO2 in 2023. For 2024, the estimate is 800 MtCO2. When looking at individual transport sectors, the most polluting type of transport is international aviation, which has increased by 230% compared to 1990 (base year). GHG emissions from road transport in 2023 were at 122% of 1990 levels (the EGD plan is to reach 100% by 2030—that is, the same level of GHG emissions as in 1990—and to continue reducing these emissions). Rail transport is currently the least polluting mode of transport, with GHG emissions in 2023 at 26% of 1990 levels. Norway and Sweden are currently leading the way in the adoption of electric vehicles, thanks to high adoption rates, strong government policies, and incentives. In the context of sustainable transportation, it is also necessary to build the appropriate infrastructure. In 2024, there were 1 million public charging points available (a 35% increase compared to 2023). 61% of EU charging points are located in three countries: the Netherlands, Germany, and France. The target by 2030 is 2.6 million additional charging points. Leaders in electromobility (Sweden and Norway) do not have as many public charging points because most charging points are private (at homes and businesses).

Comment: The literature review should be updated by incorporating recent studies from the last 3 to 5 years on low-carbon transport transition, equity in smart mobility, and carbon-neutral urban transport policies. (1) How far does your food travel on the highway? Food miles and carbon footprint, (2) Does smart city policy promote urban green and low-carbon development?

Response: 

I agreed and I expend the introduction:

In the context of sustainable transportation, attention is now also being paid to food transportation. For example, Study by Lee and Stoeltje aims to more accurately estimate food miles and related CO2 emissions. The results indicate total annual food miles of 2,719,898 kt-km and CO2 emissions of 274 kt.

The SMART cities initiative is important because it has been demonstrated that smart city policies promote sustainable and low-carbon urban development by increasing the level of technological innovation in cities, modernizing the construction of smart infrastructure, and optimizing the quality of smart management and services.

Comment:

From a methodological perspective, the study simultaneously discusses national-level analysis and smart-city-level cases, which creates ambiguity in the unit of analysis. A clearer research design is required, whether through country-level panel analysis, comparative city case studies, or a multilevel framework linking national and urban scales.

Response: 

I rewrite the text to multilevel framework focused on a national level and if it´s possible, regional level.

Comment: 

The regression model should include additional key explanatory variables such as GDP per capita, urbanization rate, vehicle ownership rate, public transport mode share, renewable energy generation share, fuel prices, and government subsidy levels. Explaining national rankings only with a limited set of environmental indicators raises a high risk of omitted variable bias. In particular, policy capacity and economic resources are critical determinants of sustainable transport transition and should be explicitly considered.

Response:

The article incorporates an ordered logit model using data proposed by the article’s reviewer (explanatory variables such as GDP per capita, urbanization rate, vehicle ownership rate, public transport mode share, renewable energy generation share, fuel prices, and government subsidy levels). However, given the limited amount of data and the correlation between the individual indicators, only GDP per capita, government subsidy levels, vehicle ownership rate, and public transport mode share could be used in the calculation.

Comment:

Since the dependent variable, CCPI ranking, is ordinal ranking data, methods more appropriate than simple OLS regression should be considered, such as ordered logit models, rank regression, or models using the original CCPI score. Rankings do not imply equal intervals between countries, which limits the interpretation of linear regression coefficients. Robustness checks using alternative sustainability indicators would further strengthen the empirical validity.

Response:

Ordered logit model was calculated. The urbanization rate and the ratio of vehicle ownership rate to public transport mode share have a significant effect on the model at the p < 0.05 level.

Comment:

The smart city case analysis requires clearer case selection criteria and a standardized comparative framework. If Stockholm, Helsinki, and Ostrava are presented as examples, they should be compared using common indicators such as population size, fiscal capacity, modal share, charging station density, and carbon reduction performance. This would improve the analytical rigor and practical implications of the case discussion.

Response: 

The common indicator was written to the manuscript.

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

Thank you for your revision

Author Response

Comment 1: Thank you for your revision.

Response: Thank you for your suggestions, which have helped improve the content of this article.

Reviewer 2 Report

Comments and Suggestions for Authors

Now ok

Comments on the Quality of English Language

Needs improvement

Author Response

Comment 1: Needs improvement of English.

Response: The English has been reviewed by an expert and the text has been revised to the appropriate level.

Reviewer 3 Report

Comments and Suggestions for Authors

Thank you for considering my comments and making changes throughout the paper. The following are some additional minor comments in the revised version:

In the introduction, the phrase: “…SMART city (explained like cities that…” should be “…smart city (defined as cities that…”. In the whole document, SMART, when referring to the above concept, should not be in capital letters.

In lines 295-296 it is mentioned that: “for example, the Czech Republic had a 6% share of alternative vehicles in 2024, while Sweden had 35%”. However, in Table 1, it seems that these shares refer not to the vehicle fleet but to the share of energy from renewable sources used in transport. The paper should be scanned by the authors to correct such inconsistencies.

In line 343 I believe that there is a syntax error in the sentence: “For more robust results is the ordered logit model calculated also”. The same for lines 379-381: “From multicollinearity check is visible highly correlation between CO₂ and population (r = 0.94) and middle correlation between CCPI and GHG (r = 0.66) and CCPI and Renewable energy (r = 0.54). From the Variance Inflation Factor (VIF) scores is visible multicollinearity of CO₂ (VIF = 10) and population (VIF =10.08).”

The conclusions in the revised version is a brief summary of the paper, presenting what has been done but not what can be concluded. I believe the conclusions should be enriched with a qualitative and synthetic description of the main findings, along with a suggestion of how the paper’s method and approach contribute to the specific research and policy field and maybe some directions for follow-up or further research.

Author Response

Comment 1: Thank you for considering my comments and making changes throughout the paper. The following are some additional minor comments in the revised version:

In the introduction, the phrase: “…SMART city (explained like cities that…” should be “…smart city (defined as cities that…”. In the whole document, SMART, when referring to the above concept, should not be in capital letters.

Response: Rewritten:  … smart city (defined as the cities that … and in the whole document rewritten the term SMART to smart.

Comment 2: In lines 295-296 it is mentioned that: “for example, the Czech Republic had a 6% share of alternative vehicles in 2024, while Sweden had 35%”. However, in Table 1, it seems that these shares refer not to the vehicle fleet but to the share of energy from renewable sources used in transport. The paper should be scanned by the authors to correct such inconsistencies.

Response: Rewritten: …for example, the Czech Republic had a 6% share of energy from renewable sources used in transport in 2024…

Comment 3: In line 343 I believe that there is a syntax error in the sentence: “For more robust results is the ordered logit model calculated also”. The same for lines 379-381: “From multicollinearity check is visible highly correlation between CO₂ and population (r = 0.94) and middle correlation between CCPI and GHG (r = 0.66) and CCPI and Renewable energy (r = 0.54). From the Variance Inflation Factor (VIF) scores is visible multicollinearity of CO₂ (VIF = 10) and population (VIF =10.08).”

Response: Rewritten:

An ordered logit model is also estimated to obtain more robust results.

The multicollinearity check reveals a high correlation between CO₂ and population (r = 0.94) and moderate correlations between the CCPI and GHG (r = 0.66) and between the CCPI and Renewable energy (r = 0.54). The values of the Variance Inflation Factor (VIF) indicate multicollinearity between CO₂ (VIF = 10) and population (VIF = 10.08).

Comment 4: The conclusions in the revised version is a brief summary of the paper, presenting what has been done but not what can be concluded. I believe the conclusions should be enriched with a qualitative and synthetic description of the main findings, along with a suggestion of how the paper’s method and approach contribute to the specific research and policy field and maybe some directions for follow-up or further research.

Response: Expanded conclusion: The ordered logit model is not commonly used in research focused on the transformation of transportation in the EU; however, the value of this model—particularly when combined with other methods such as regression analysis—lies in the depth and coherence of the findings. Thanks to these findings, it is possible to better understand the factors influencing the transition to low-emission transport, including the success of their implementation. At the same time, it is possible to develop concrete proposals that will lead to successful implementation at both the national and regional levels.

Reviewer 4 Report

Comments and Suggestions for Authors

I am happy with the responses.

Author Response

Comment 1: I am happy with the responses.

Response: Thank you for your suggestions, which have helped improve the content of this article.