Selecting Indicators to Assess the Sustainability of Urban Freight Transport Using a Multi-Criteria Analysis

Round 1

Reviewer 1 Report (Previous Reviewer 1)

Comments and Suggestions for Authors

·  Some authors responses of the first review round should be added in the text, some others points should be added as perspectives in the conclusion

I I think that the title should contain the main used method. For example: Selection indicators for assessing urban freight transport sustainability using a non-compensatory conjunctive method.

TThe used method should be more explained and justified in the text. More information about the method selection should be added. There are mainly two categories of methods make a decision-making strategy: non-compensatory method, and compensatory method Explain in the text, Why and How choose…. See in the literature, if there are research works about the same goal (indicators selection) but in other areas.

TThe Research implication and discussion should be more detailed. The experts should be mentioned and defined in the text, and the validation step still missing (using for example a case study: How proof that the selected 18 indicators are goods and suitable)

 

Author Response

• I think that the title should contain the main used method. For example: Selection indicators for assessing urban freight transport sustainability using a non-compensatory conjunctive method.

We are very thankful for your relevant your suggestion. As suggested by the reviewer, the title of the paper is changed as follows: “Selection indicators for assessing urban freight transport sustainability using a multi-criteria analysis”

• The used method should be more explained and justified in the text. More information about the method selection should be added. There are mainly two categories of methods make a decision-making strategy: non-compensatory method, and compensatory method Explain in the text, Why and How choose…. See in the literature, if there are research works about the same goal (indicators selection) but in other areas.

We would like to thank the reviewer for his/her comment. We agree that we had not made fully justification for some choice. Justifications for the choice of method used in this research are clarified below.

Conceptually, we can distinguish between compensatory and no compensatory approaches when modeling choice behavior. In a compensatory decision-making process, the lower utility (evaluation, satisfaction, etc.) due to a particular attribute of the alternative can be compensated by the higher utility derived from one or more of her remaining attributes. In the case of a non-compensatory decision-making process, it is assumed that no such compromise is made. Instead, attributes are typically assumed to be evaluated on an attribute-by-attribute basis. If an alternative selection is not accepted on this basis, it will not be selected, regardless of the utility it derives from other attributes. For those reasons, non-compensatory conjunctive method was used.

• The Research implication and discussion should be more detailed. The experts should be mentioned and defined in the text, and the validation step still missing (using for example a case study: How proof that the selected 18 indicators are goods and suitable)

We would like to thank you for your remark. In fact, the choice is validated by the two experts during the application of the non-compensatory method. The non-compensatory conjunctive method is used for indicator selection by evaluating the long list based on the five properties. However, we are tested the selected indicators in another submitted article with a case study in the Sfax city.

Furthermore, we have examined the chosen indicators in a separate article (submitted), incorporating a case study conducted in Sfax city.

Changes in manuscript:

Firstly, the proposed approach involves compiling a comprehensive list of sustainability indicators derived from the literature. This necessitates filtering, analyzing, discussing, and validating the initial set of indicators through experts, considering five key properties. The obtained results carry significant theoretical and managerial implications for the stakeholders involved. The managerial contributions of this research can be summarized as follows:

• The proposed approach empowers stakeholders in freight transport to effectively monitor the sustainability of UFT, thereby bolstering economic, environmental, social, political, and spatial sustainability.
• It enables stakeholders to assess the current state of UFT sustainability according to selecting indicators.
• The developed indicators offer UFT companies a valuable tool for evaluating the sustainability of their operations.

In contrast, the theoretical contributions are outlined as follows:

• The study presents eighteen indicators aimed at enhancing the sustainability of UFT.
• The proposed approach assesses sustainability across five dimensions: economic, environmental, social/societal, political, and spatial, thereby making a noteworthy contribution to the current body of literature.
• The suggested indicators serve as a valuable reference for assessing the sustainability of UFT.

 

Author Response File: Author Response.pdf

Reviewer 2 Report (Previous Reviewer 2)

Comments and Suggestions for Authors

Starting from a well-conducted literature review, the Authors propose a set of indicators which should help the decision-makers in the assessment of the sustainability of urban freight transport operations. Table 4 itemizes 18 final indicators which should represent the right mix and successfully help achieving the right assessment.

However, according to my experience in the field of urban logistics and working with municipalities on that, the Table 4 set of indicators is an exercise in style rather than an actual support, as the Authors suggest.

The Authors, to assess the feasibility of the proposed indicators, should provide evidence on how to measure them in real operational scenarios. How to measure the Table 4 set in urban areas where  self-replenishment is common? Or where gig economy is taking momentum? How to convince the plethora of urban logistic operators of a given city to provide data to feed the political or the economic sets of indicators? Moreover, some indicators might be really difficult to measure according to the units of measurement proposed; one case for all, how can be SO4's unit of measurement dB (is it db(A), actually?) if the proposed indicator is the ratio between "freight vehicles within noise limits versus the total number of freight vehicles"?  Ditto for EN1 or EN2, if the mileage is not included in the unit of measurement?

Past EC projects like BESTUFFS or those within the CIVITAS initiative in Europe proved the difficulty in getting this type of data. The lack of practical examples with actual facts and figures demonstrate that hardly this set of indicators can be adopted anywhere, which raises the question of its soundness for the journal readership. 

The Authors are encouraged to submit a new paper where the provide quantitative data for the proposed indicators starting from real operational scenarios. The manuscript, in the present form, is just a well-known list of indicators, of no specific attractivenes for the readership.

Author Response

Response to Reviewer 2

• Starting from a well-conducted literature review, the Authors propose a set of indicators which should help the decision-makers in the assessment of the sustainability of urban freight transport operations. Table 4 itemizes 18 final indicators which should represent the right mix and successfully help achieving the right assessment. However, according to my experience in the field of urban logistics and working with municipalities on that, the Table 4 set of indicators is an exercise in style rather than an actual support, as the Authors suggest. The Authors, to assess the feasibility of the proposed indicators, should provide evidence on how to measure them in real operational scenarios.

1. How to measure the Table 4 set in urban areas where self-replenishment is common? Or where gig economy is taking momentum?
2. How to convince the plethora of urban logistic operators of a given city to provide data to feed the political or the economic sets of indicators?
3. Moreover, some indicators might be really difficult to measure according to the units of measurement proposed; one case for all, how can be SO4's unit of measurement dB (is it db(A), actually?) if the proposed indicator is the ratio between "freight vehicles within noise limits versus the total number of freight vehicles"?  Ditto for EN1 or EN2, if the mileage is not included in the unit of measurement?

Thank you very much to the anonymous reviewer for your constructive feedback

1. Measuring the indicators in Table 4, particularly in urban areas with common self-replenishment, involves collecting data and assessing each indicator within its specific context. Below is a general guide on how you might measure each indicator:

		Indicator
Economic	EC1	Modal split	Collect data on the distribution of freight across different modes of transportation (e.g., road, rail). Calculate the share of each mode in the total freight movement.
	EC2	Loading rate	Measure the efficiency of loading and unloading operations. Calculate the loading rates.
	EC3	Congestion	Assess traffic congestion in key freight routes. Use the total lane miles to determine the average daily peak congestion per lane mile in kilometers per hour.
Environmental	EN1	GHG emissions	Quantify greenhouse gas emissions from freight activities. Use emission factors and activity data to estimate carbon dioxide equivalents.
	EN2	Air pollutants emissions (PM2.5, PM10, NOx, …)	Measure emissions of PM2.5, PM10, NOx, and other pollutants. Use air quality monitoring stations or modeling techniques to estimate emissions.
	EN3	Energy consumption	Calculate the energy consumption associated with freight transport activities. Determine the amount of energy consumed and the distance traveled
	EN4	Sustainable freight vehicles	Track the percentage of the fleet that consists of sustainable vehicles (e.g., electric, hybrid). Monitor the adoption of environmentally friendly technologies.
Social/societal	SO1	Accidents	Collect data on accidents, fatalities, and injuries related to freight transport. Analyze trends and identify areas or situations with high accident rates.
	SO2	Fatalities
	SO3	Injuries
	SO4	Noise	Measure noise levels in areas affected by freight transport activities. Assess the impact of noise pollution on the surrounding community.
	SO5	Freight transport personnel certification	Track the certification status of personnel involved in freight transport. Ensure that personnel meet the required standards and certifications.
Political	PO1	Financial resources	Assess the financial resources allocated to freight transport infrastructure and services. Analyze budgets, funding sources, and expenditures.
	PO2	Sustainable businesses	Monitor the number and performance of sustainable businesses in the freight sector. Consider certifications, environmental initiatives, and sustainable practices.
	PO3	Spatial restriction	Evaluate any spatial or temporal restrictions on freight transport. Assess regulations, policies, and planning restrictions.
	PO4	Temporal restriction
Spatial	TE1	Peripheral infrastructure capacity	Assess the capacity of peripheral infrastructure supporting freight transport. Evaluate road networks, storage facilities, and distribution centers.
	TE2	Nodal infrastructure capacity	Evaluate the capacity of nodal infrastructure (e.g., ports, terminals). Consider throughput, handling capacity, and efficiency.

1. These indicators depend on the availability and accuracy of data. Regular monitoring and periodic assessments will help track changes and identify areas for improvement in the urban freight transport system.

Convincing a multitude of urban logistic operators to provide data for political or economic indicators involves addressing their concerns, highlighting the benefits, and building a collaborative and transparent relationship. Here are some strategies to consider: Demonstrate Impact.  However, both parties need to make efforts for this to happen.

1. I apologize for any confusion in my previous responses. by transportation activities. The most common unit of measurement for noise is decibels (dB). To clarify, if the suggested indicator is not the ratio of "freight vehicles within noise limits versus the total number of freight vehicles," then the unit of measurement for the indicator is expressed in decibels (dB). The process of measuring a noise transport indicator entails evaluating the noise levels produced by transportation activities, with decibels being the predominant unit of measurement for noise.

• Past EC projects like BESTUFFS or those within the CIVITAS initiative in Europe proved the difficulty in getting this type of data. The lack of practical examples with actual facts and figures demonstrate that hardly this set of indicators can be adopted anywhere, which raises the question of its soundness for the journal readership. 

We express our gratitude to the reviewer for the insightful comment. It is acknowledged that the challenge in obtaining this specific data type can be regarded as a constraint. In light of this, the present study acknowledges certain inherent limitations that warrant attention in future research on the evaluation of freight transport sustainability. Primarily, the outcomes obtained from the indicators hinge on data extracted from publicly accessible sources. Therefore, the accuracy of these findings is directly influenced by the quality and ease of access to the data.

• The Authors are encouraged to submit a new paper where the provide quantitative data for the proposed indicators starting from real operational scenarios. The manuscript, in the present form, is just a well-known list of indicators, of no specific attractivenes for the readership.

We appreciate your feedback. In response, we present the methodology for selecting indicators. Furthermore, we have examined the chosen indicators in a separate article (submitted), incorporating a case study conducted in Sfax city.

Author Response File: Author Response.pdf

Reviewer 3 Report (Previous Reviewer 3)

Comments and Suggestions for Authors

The paper has a significant improvement in comparison to ints initial form,

please improve the presentation of the results, the tables are not in the standard format,

use several figures to show the achieved results in a better way,

The conclusion is week and can be improved by adding some insights about this research

Author Response

Response to Reviewer 3

• The paper has a significant improvement in comparison to ints initial form, please improve the presentation of the results, the tables are not in the standard format, use several figures to show the achieved results in a better way,

We are very thankful for your relevant remarks and suggestions. We improved these in the revised version.

• The conclusion is week and can be improved by adding some insights about this research

We thank the reviewer in pointing out this. The conclusions were improved in the revised version

Changes in manuscript: New conclusions

Currently, most cities are trying to combat the intensification of freight transportation with large numbers of trucks in city centers. Its aim is to solve various problems in freight transport while ensuring sustainability. In this context, this research work presented sustainability indicators of UFT. The list of sustainability indicators was developed in three steps. First, a long list of indicators for assessing the sustainability of UFT, identified from an extensive literature review. The most commonly used properties are then selected. Following this, a non-compensatory conjunctive method was adopted to reduce the long list of sustainability indicators from 83 indicators to 18 indicators. These indicators are classified according to five dimensions: economic, environmental, social, political, and spatial.

Transport actors and other decision-makers could draft plans to solve problems, mediate conflicts and transform systems by providing a set of alternatives. Indicators can be also used to help decision-makers choose the best solution to meet specific objectives. These indicators can be considered as tools that guarantee communication between private and public actors to reach a compromise for priority improvements. This approach assesses the sustainability of urban freight transport while recognizing the local economic, environmental, social, political and spatial development situation of the studied city.

This study has some inherent limitations which needed to be considered for future research on the assessment of freight transport sustainability. First, the indicator results are based on data from publicly available sources. Therefore, the accuracy of the results depends on the quality and availability of the data.

Given the multi-dimensionality of the set of indicators, the aggregation of these indicators into a composite indicator facilitates, therefore, the decision-making process. In this context, we propose in our future research an assessment approach for urban freight transport sustainability based on a composite indicator with sustainability perspectives. We suggest also that future research focus on integrating resilience considerations and sustainability into urban freight transport. This involves a comprehensive decision analysis process by including resilience assessment 

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report (Previous Reviewer 1)

Comments and Suggestions for Authors

The paper is now good for publication. 

Author Response

I appreciate your positive feedback. Thank you very much. It's certainly gratifying to know that the paper has met the criteria for publication.

Author Response File: Author Response.pdf

Reviewer 2 Report (Previous Reviewer 2)

Comments and Suggestions for Authors

 Although the  Authors tried to improve its content, the weakness of the manuscript is that this is a pure exercise in itemizing indicators. It was asked to assess the feasibility of the proposed indicators and provide evidence on how to measure them in real operational scenarios, but no case studies are proposed. Unfit for publication as the literature on indicators already abounds.

Author Response

Thank you for your insightful comments. We sincerely appreciate your thorough evaluation of our manuscript. We acknowledge your feedback regarding the perceived weakness in our work, specifically the concern that the manuscript primarily itemizes indicators without adequately addressing the feasibility and measurement in real operational scenarios. We understand the importance of providing evidence through case studies, and we regret that this aspect was not sufficiently addressed in the current version. Your constructive criticism is invaluable. However, our aim is to present a selection method and a standardized set of sustainability indicators. Our methodology entails a comprehensive analysis of existing indicators and their associated dimensions, leveraging insights from the literature. We extend beyond the traditional dimensions of freight transport, incorporating essential elements for a comprehensive sustainability evaluation. In making sustainable decisions, we advocate for the consideration of not only the traditional dimensions—economic, environmental, and social/societal—but also the political and spatial dimensions. This approach ensures a more nuanced and encompassing evaluation framework for sustainable practices. Formalizing and computing individual indicators is certainly feasible; however, our primary strategic focus is directed towards embracing a qualitative approach when conducting evaluations at the strategic level.

Allow me to clarify our research objective. Our paper is a component of my thesis topic, and our primary aim from the outset has been to conduct qualitative analyses. This is why we did not provide detailed information on the calculation of the indicators. Additionally, we have thoroughly explored the selected indicators in a separate article (already submitted), which incorporates a case study conducted in Sfax city.

Changes in manuscript:

The measurement of these indicators can be determined as follows:

• Modal split: To measure this indicator, follow these steps:
  • Determine Total Tonnes-Kilometers: Calculate the total distance in Tonnes-Kilometers for all modes of freight transport. This involves multiplying the weight of goods transported by the distance traveled for each mode.
  • Calculate Modal Split Percentage for Each Mode: For each mode of transport (road, rail, sea, air, etc.), calculate its percentage share of the total Tonnes-Kilometers.
  • Interpretation: The resulting Modal Split Percentage for each mode will provide insights into the distribution of freight transport, indicating the proportion of total freight carried by each mode.
• Loading rate: To measure this indicator, follow these steps:
  • Maximum Weight-Carrying Capacity: This is the maximum weight of goods that the vehicle is capable of transporting in a single load. This measurement is typically expressed in tons.
  • Volume-Carrying Capacity: This represents the maximum volume of goods that the vehicle can accommodate in a single load. The measurement is often expressed in cubic meters or any other relevant volume unit.
  • Loaded Vehicle Travel Rate: This expresses the percentage of the maximum load capacity utilized during transportation.
• Congestion: To measure the congestion, follow these steps
• Total Daily Congestion Kilometers: Measure the total distance of congestion during daily peak hours. This can be obtained by analyzing specific road segments where congestion is observed.
• Total Kilometers of Motorized Transport Lanes: Calculate the total length of all motorized transport lanes during the analysis period.
• Calculation of Average Kilometric Congestion: Divide the total daily congestion kilometers by the total kilometers of motorized transport lanes.
• The indicator for greenhouse gas (GHG) emissions from freight transport vehicles is typically calculated by measuring the total quantity of GHGs emitted by these vehicles, expressed in kilograms of carbon dioxide equivalent (Kg CO2 eq). This indicator provides insight into the environmental impact of emissions from freight transport, helping to assess and monitor the carbon footprint associated with these activities.
• Air pollutants emissions (PM2.5, PM10, NOx, …): The calculation of the indicator for emissions of other atmospheric pollutants such as PM2.5, PM10, NOx, etc., involves measuring the total quantity of these pollutants emitted into the atmosphere. This quantity is often expressed in specific units associated with each pollutant.
• Energy consumption: The average energy consumption of freight vehicles is calculated by measuring the total amount of energy consumed by these vehicles to cover a specific distance. This indicator provides insight into the energy efficiency of freight vehicles, expressing the amount of energy required to transport goods over a given distance.
• Sustainable freight vehicles: This indicator is calculated by establishing the ratio between the number of sustainable vehicles and the total number of vehicles, and then expressing this ratio as a percentage.
• Accidents: This indicator expresses the percentage of road accidents compared to the overall number of accidents, providing a measure of the prevalence of road-related incidents in the total accident count.
• Fatalities: This indicator expresses the ratio of traffic-related fatal accidents to the total population, providing a measure of the number of deaths per capita resulting from such accidents.
• Injuries: This indicator expresses the ratio of traffic-related injuries to the total population, providing a measure of the number of injuries per capita resulting from traffic incidents.
• Noise: The process of measuring a noise transport indicator entails evaluating the noise levels produced by transportation activities, with decibels being the predominant unit of measurement for noise.
• Freight transport personnel certification: The indicator for Certification of Freight Transport Personnel is calculated by establishing the ratio between the number of certified freight transport personnel and the total number of freight transport personnel, and then expressing this ratio as a percentage. This indicator provides insights into the percentage of certified personnel within the overall workforce in freight transport, reflecting the level of certification within the industry.
• Financial resources: The indicator for financial resources for the UFT projects is calculated by establishing the ratio between the budget allocated to the UFT projects and the total transport budget, and then expressing this ratio as a percentage.
• Sustainable businesses: The indicator for Sustainable Businesses is calculated by establishing the ratio between the number of businesses certified with ISO 14001 and the total number of businesses, and then expressing this ratio as a percentage.
• Spatial restriction: The Spatial Restriction indicator is calculated by establishing the compliance rate with spatial restrictions on traffic and parking. This indicator provides insights into the extent to which spatial restrictions on traffic and parking are adhered to, expressed as a percentage of compliant observations relative to the total number of observations.
• Temporal restriction: The Temporal Restriction indicator is calculated by establishing the compliance rate with temporal restrictions on traffic and parking. This indicator provides insights into the extent to which temporal restrictions on traffic and parking are adhered to, expressed as a percentage of compliant observations relative to the total number of observations.
• Peripheral infrastructure capacity: this indicator measures the degree of compliance with spatial restrictions regarding traffic and parking. It assesses the extent to which vehicles adhere to the defined rules and limits for their movement and parking in specific areas
• Nodal infrastructure capacity: This indicator measures the level of compliance with time-based restrictions on traffic and parking. It assesses how well vehicles adhere to specific time-related rules, such as the hours during which traffic or parking is allowed or prohibited.

		Indicator
Economic	EC1	Modal split	Collect data on the distribution of freight across different modes of transportation (e.g., road, rail). Calculate the share of each mode in the total freight movement.
	EC2	Loading rate	Measure the efficiency of loading and unloading operations. Calculate the loading rates.
	EC3	Congestion	Assess traffic congestion in key freight routes. Use the total lane miles to determine the average daily peak congestion per lane mile in kilometers per hour.
Environmental	EN1	GHG emissions	Quantify greenhouse gas emissions from freight activities. Use emission factors and activity data to estimate carbon dioxide equivalents.
	EN2	Air pollutants emissions (PM2.5, PM10, NOx, …)	Measure emissions of PM2.5, PM10, NOx, and other pollutants. Use air quality monitoring stations or modeling techniques to estimate emissions.
	EN3	Energy consumption	Calculate the energy consumption associated with freight transport activities. Determine the amount of energy consumed and the distance traveled
	EN4	Sustainable freight vehicles	Track the percentage of the fleet that consists of sustainable vehicles (e.g., electric, hybrid). Monitor the adoption of environmentally friendly technologies.
Social/societal	SO1	Accidents	Collect data on accidents, fatalities, and injuries related to freight transport. Analyze trends and identify areas or situations with high accident rates.
	SO2	Fatalities
	SO3	Injuries
	SO4	Noise	Measure noise levels in areas affected by freight transport activities. Assess the impact of noise pollution on the surrounding community.
	SO5	Freight transport personnel certification	Track the certification status of personnel involved in freight transport. Ensure that personnel meet the required standards and certifications.
Political	PO1	Financial resources	Assess the financial resources allocated to freight transport infrastructure and services. Analyze budgets, funding sources, and expenditures.
	PO2	Sustainable businesses	Monitor the number and performance of sustainable businesses in the freight sector. Consider certifications, environmental initiatives, and sustainable practices.
	PO3	Spatial restriction	Evaluate any spatial or temporal restrictions on freight transport. Assess regulations, policies, and planning restrictions.
	PO4	Temporal restriction
Spatial	TE1	Peripheral infrastructure capacity	Assess the capacity of peripheral infrastructure supporting freight transport. Evaluate road networks, storage facilities, and distribution centers.
	TE2	Nodal infrastructure capacity	Evaluate the capacity of nodal infrastructure (e.g., ports, terminals). Consider throughput, handling capacity, and efficiency.

 

Author Response File: Author Response.pdf

Round 3

Reviewer 2 Report (Previous Reviewer 2)

Comments and Suggestions for Authors

The Authors still provide a list of theorethical KPIs which are already available in the general literature on sustainable mobility. All the elements of weakness already stressed are still in place. To reject in the present form

Author Response

Dear Reviewer,

Thank you for your thorough evaluation and feedback. We appreciate your attention to detail. We understand your concerns regarding the inclusion of theoretical Key Performance Indicators.

In response to your comments, I have worked on improving the current version and included specific measurement details for each indicator. Below is an extended version with some qualitative examples:

 

Dimension		Indicator	Qualitative Examples
Economic	EC1	Modal split	Percentage distribution of freight transport modes (e.g., road, rail, water) in a given urban area.
	EC2	Loading rate	Assessment of the efficiency in loading freight vehicles, considering weight and volume capacity.
	EC3	Congestion	Monitoring travel time during peak hours and congestion intensity caused by freight transport.
Environmental	EN1	GHG emissions	Quantifying greenhouse gas emissions (CO2 equivalent) resulting from freight transport activities.
	EN2	Air pollutants emissions	Measuring emissions of particulate matter (PM2.5/PM10) and nitrogen oxides (NOx) from freight transport.
	EN3	Energy consumption	Calculating the energy efficiency of freight vehicles by assessing energy consumed per distance.
	EN4	Sustainable freight vehicles	Promoting the use of eco-friendly vehicles, such as electric or tricycle freight vehicles.
Social/societal	SO1	Accidents	Monitoring the occurrence of road accidents involving freight vehicles in urban areas.
	SO2	Fatalities	Assessing the number of fatalities resulting from traffic accidents involving freight transport.
	SO3	Injuries	Evaluating the number of injuries caused by accidents related to urban freight transport.
	SO4	Noise	Measuring noise levels generated by freight transport activities, considering recommended limits.
	SO5	Freight transport personnel certification	Percentage of certified personnel contributing to improved road safety and service quality.
Political	PO1	Financial resources	Allocation of budget to sustainable urban freight transport projects compared to the overall transport budget.
	PO2	Sustainable businesses	Percentage of businesses certified with ISO 14001, showcasing commitment to environmental sustainability.
	PO3	Spatial restriction	Compliance rate with spatial restrictions on traffic and parking, ensuring adherence to regulations.
	PO4	Temporal restriction	Compliance rate with temporal restrictions on traffic and parking, contributing to effective traffic management.
Spatial	TE1	Peripheral infrastructure capacity	Evaluation of the capacity of linear infrastructures (roads, railways) covering industrial areas.
	TE2	Nodal infrastructure capacity	Assessing the capacity and efficiency of nodal infrastructures for freight storage and movements.

 

Author Response File: Author Response.pdf

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.

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The idea discussed in the paper is very interesting. However, to further highlight this article for effective publication, some questions and recommendations should be addressed:

1.    This presented research is oriented to a review paper no a research article.

2.    Many discussed ideas in this research are based on unpublished work (Ayadi el a. 2022a) which may affect the relevance of this current work.

3.    The selection method is not clear, and the results depend on situation and the country. It is better to select in the beginning the research a specific area or a specific case study.

4.    Table 2 is very long and poorly presented. The use of 0 or 1 has many significations, sometimes contradictory, and the answer could be ambiguous. In some cases, the answer itself requires an expert view, and a multi-criteria method may be required.

5.    Step 2 is mentioned in Figure 1 as a test process. If the response is No, how propose a new indicator? Give some examples, when new indicators are generated, and replace the symbol for this step with a 2-output diamond.

6.    How can you validate that the 18 selected indicators can improve the sustainability of UFT? There is a serious problem in this study which is related to research verification and validation steps.

7.    Why add political and spatial dimensions to sustainability is considered as original? Previously, they are implicitly integrated in the three well-known dimensions: economic, environmental, and social/societal.

Reviewer 2 Report

Comments and Suggestions for Authors

The manuscript introduces the most common Urban Freight Transport indicators usually available in the literature. These are presented in tables described in narrative and refer to selected references sources. But this is not enough to attract readership, nor to advance knowledge, being these indicators well-known. Where is the research question? What are the scientific advances? These are not clear in the narrative, nor corroborated by actual case studies. Why would readers need to read an article summarizing a selection of indicators, when there is a plethora of case studies in literature reporting more or less the same? If the goal is to provide a synthesis of available indicators, then probably the literature search need to be extended.  and more critcal insights provided (e.g. about heir actual feasibility). Being unable to provide new information and data the manuscript is unfit for publication

Reviewer 3 Report

Comments and Suggestions for Authors

The authors have addressed urban freight transport and presented some indicators for improving the sustainability of such systems. The idea of the paper is interesting, however, the following comments should be considered:

1. The introduction provides good background but could be strengthened by citing specific statistics on growth of urban freight transport and resulting issues. This helps frame the purpose and importance of the research. 

2. In the literature review section, consider organizing past studies on indicators by common methodology types used rather than chronologically. This helps highlight key approaches in the field.

3. In Table 2, include the number of indicators used in each study cited to illustrate the variation in indicator set sizes. 

4. For Table 3, alphabetize the properties for easier reference. Consider consolidating properties that are similar (e.g. data availability and achievability). 

5. In describing the methodology, provide more details on how the initial long list of indicators was compiled - was it solely from Table 2 or additional sources?

6. Explain the reasoning behind choosing the specific 5 properties used to evaluate the long list of indicators.

7. In presenting the results, consider organizing the selected indicators in a summary table by dimension for conciseness before describing each one. 

8. For each indicator presented, relate it back to supporting literature on why it is relevant and important to consider.

9. In the discussion of implications, also consider limitations of the set of indicators proposed and opportunities to expand or refine it through future research.

10. Address how the set of indicators could be implemented in practice - data collection methods, calculation, analysis etc. 

11. Suggest how the indicator set could be validated through expert review or a pilot test case. 

12. For Managerial implications, also consider how the indicators can help evaluate policies, programs, and initiatives.

13. Proofread the paper to identify any typos, grammar issues, or awkward phrasing to improve readability.

14. In the conclusion, summarize the key contributions of the research and practical value of the indicator set proposed.

15. Consider developing a table or framework to visually summarize the indicators and dimensions for the reader.