Study and Characterization of New KPIs for Measuring Efficiency in Urban Loading and Unloading Zones Using the OEE (Overall Equipment Effectiveness) Model

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

Point 1: In lines 83–85, the authors state that the aim of the study is to define a new indicator based on the OEE model to evaluate the use of a LUZ or a set of LUZs "over a specific time horizon." It is recommended that the authors clearly specify the exact time period this refers to (e.g., day, week, month), in order to provide better methodological transparency and help readers more precisely understand the scope of the evaluation.

Point 2:In the introduction, the authors present a comprehensive overview of KPIs identified in the literature related to the evaluation of loading and unloading zones (LUZ) in Table 1. While this classification is valuable and demonstrates a thorough understanding of existing research, it is recommended that the authors highlight and further elaborate on the most frequently cited indicators—such as average parking duration, vehicle arrival rate, and occupancy rate—in the narrative text. Specifically, it would be useful to explain what conclusions previous researchers have drawn from these KPIs and how they relate to the identified inefficiencies in LUZs.

Point 2: In subsection 2.1.1.2, the authors state that non-commercial and unauthorized vehicles were identified and excluded from the calculation of the efficiency indicator, but it is not clear how these vehicles were identified during field observation. It is recommended to further clarify the data collection methodology—whether visual assessment, license plate recognition, interviews with drivers, or another form of verification was used.

Point 4: The analyzed LUZs are described in detail; however, it is not clear how the authors selected these specific zones for the sample, nor is the data collection methodology sufficiently explained.

Point 5: Please make a language correction in Tables 10, 11, 13, and 14.

Point 6: All results are presented exclusively through tables, which in this case makes interpretation rather difficult. It is recommended to include graphical representations of the results to enhance clarity and facilitate a better understanding of the key findings.

Point 7: The discussion clearly explains the results obtained in this study. However, it would benefit from a comparative analysis with the findings of previous similar studies.

Point 8: Although the issue of manual data collection is acknowledged as a limitation, it would be helpful expanding the limitations section to include other potential constraints of the study, such as geographical scope, observational bias…

Author Response

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Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

The use of urban space is a very important aspect nowadays, particularly the management of loading and unloading. The work carried out and presented in this article has the merit of contributing to the management of these spaces, introducing an algorithm for measuring the efficiency of spaces.

An improvement to this study (as already mentioned by the authors) would be the implementation of a series of data collection sensors, allowing automatic and real-time collection of data that could be used automatically by OLE.

This would greatly facilitate city management, allowing possible inflation to be known in real time, allowing the authorities to be aware of it immediately and take action.

Another advantage would be the possibility of developing an application that could make available spaces available in real time, which could contribute to better use of spaces and reduce the waste of time on the part of users (since they could move immediately to an available space).

Furthermore, automatic storage would also allow this data to be processed, possibly with an improved algorithm and even based on historical data, it would be possible to predict the use of the spaces made available for loading and unloading.

The ideal would be to implement these ideas in practical terms, as this is not easily possible (as is the case), so they would be well mentioned in the article.

Author Response

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Reviewer 3 Report

Comments and Suggestions for Authors

The application of the OEE model to urban loading/unloading zones lacks sufficient novelty. Clearly highlight how your methodology advances beyond existing approaches.

 Has the potential bias inherent in manual data collection been considered? Discuss explicitly the validity and limitations associated with your observational method.

The analysis is predominantly descriptive. Incorporating more robust statistical or inferential analyses could significantly strengthen your findings.

Findings from a single city (Zaragoza) limit the broader applicability of results. Consider additional cases or comparative studies for enhanced generalizability.

Recommendations provided are vague (e.g., public awareness, increased police presence). Propose specific, actionable, and evidence-based policy implications from your results.

The interpretation of findings lacks depth. Please clearly relate the results to broader urban planning and mobility contexts.

Author Response

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Reviewer 4 Report

Comments and Suggestions for Authors

I congratulate the authors for the research. In that spirit, I add comments to enhance the manuscript. The authors should evaluate these observations and, if they consider that any of these aspects can be clarified, feel free to explain it in their responses.

1. Insufficient methodological description of field data collection.
   The article does not detail precisely the protocol followed for recording the observations. It is not specified who carried out the measurements, under what conditions they were performed, whether prior training of the observers existed, or how possible inter-observer biases were controlled.
2. Lack of statistical validation of the results obtained.
   The work lacks a statistical analysis that allows evaluating the robustness and significance of the reported results. There are no confidence intervals, and no hypothesis tests or sensitivity analyses are applied regarding possible measurement errors. As an empirical study that aims to offer a new evaluation model, it is important that statistical analyses be included to support the consistency and reliability of the reported results.
3. Lack of explicit quantification of the main numerical results in the Abstract and in the conclusions.
   Both in the abstract and in the conclusions, the article conceptually presents the methodological contributions and the scope of the proposal but omits to include the most relevant quantitative results obtained during the study.
4. Weakness in the drafting of the Featured Application section due to lack of scientific precision.
   The Featured Application presents general content without quantitative data. It is stated that "an in-depth research" has been carried out, although in reality the study is limited to manual observations in five specific zones of a city, which could be questioned later; the authors are suggested to evaluate the use of this expression. Likewise, subjective expressions such as "provides a very clear vision" are used, which are subjective and lack technical rigor. Finally, the section does not explicitly quantify the expected practical impact, such as the potential improvement in the efficiency of LUZ use, the reduction in occupation times, or the effect on vehicular congestion.

Author Response

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Author Response File: Author Response.pdf

Round 2

Reviewer 3 Report

Comments and Suggestions for Authors

The revised manuscript looks fine.

Reviewer 4 Report

Comments and Suggestions for Authors

Dear Authors

The revised manuscript has significantly enhanced and now addresses the main concerns raised during the first review. The methodology is clearly described, the results are well supported, and the conclusions are aligned with the evidence presented. Therefore, I recommend the article for publication.