AI-Driven Energy Optimization in Urban Logistics: Implications for Smart SCM in Dubai
Round 1
Reviewer 1 Report
Comments and Suggestions for AuthorsIn this paper, the authors analyse the impact of AI on energy optimization of logistics operations in Dubai. One of the main strengths is the definition of a mixed approach, which combines quantitative analysis of performance indicators (such as energy savings, CO2 reduction, and delivery efficiency) with qualitative analysis of the results of semi-structured interviews.
This work focuses on a city like Dubai, with a proven digital transformation and sustainability strategy.
Finally, the article identifies key barriers, such as the complexity of integrating legacy systems, and proposes strategic recommendations for overcoming them.
However, in my opinion, the article also presents some key weaknesses that need to be addressed:
First, it doesn't specify in sufficient detail what type of AI is used in each of the organizations, in more technical terms, such as algorithms and architectures. This limits the replicability of the study and doesn't allow us to discern whether the adoption of strategies aimed at implementing a particular type of AI (CNN, machine learning, transfer learning, LLM, to name just a few examples) yields better results than other strategies. My question is:
What types of AI algorithms (e.g., supervised learning, neural networks, evolutionary algorithms) were specifically used in the organizations studied, and how was their comparative performance evaluated?
The simulation conducted, while useful and contributing to the robustness of the study, could benefit from validation with real data or comparison with alternative scenarios.
The authors should also consider, within their strategic recommendations, the potential ethical or social risks associated with the application of AI in logistics, in terms of (i) intensive automation and impact on employment, (ii) possible gender bias in AI-based reasoning, and (iii) privacy of the data used for training and reasoning.
Minor corrections:
- leaning their operations -> aligning their operations
- Unify the use of technical terms: for example, “AI optimization” and “AI-driven optimization” are often used interchangeably; standardization is recommended.
- Provide meaning of DEWA, first time this acronym appears.
Author Response
Detailed response to reviewer 1 is attached.
Author Response File: 
Author Response.pdf
Reviewer 2 Report
Comments and Suggestions for AuthorsHello,
It is recommended to create AI-Driven Energy Optimization in Urban Logistics: Implica-2
tions for Smart SCM in Dubai model.
It is recommended to add 70 references, which are included in Scopus and Web of Sciences data basis.
Its is recommended to create novelty and novelty and relevance of the article, the problem in the introduction. This is how to emphasize what the research objectives are. The purpose and objectives of the work must be reflected in the introduction.
Please describe the interview results in more detail.
Comments for author File: Comments.pdf
Author Response
Detailed response to reviewer 2 is attached.
Author Response File: Author Response.pdf
Reviewer 3 Report
Comments and Suggestions for Authors-
1. The mixed-methods description on Page 5 needs more detail on specific techniques, data integration, and rationale. Clarify the framework, tools for thematic coding, and synthesis process. Enhance Figure 1’s caption for clarity.
2. On Page 8, deepen the analysis of response bias and generalizability limitations. Explain bias mitigation and propose a framework for adapting findings to other urban contexts, addressing regulatory or technological factors.
3. Fix inconsistent citations and ensure completeness. Link references clearly to claims and add recent AI logistics studies to strengthen the theoretical foundation, adhering to the journal’s style guide.
4. Fig 2 and 3 should be adjusted to a better quality.
5. Section 3 methodology must be enhanced, the model applied should be addressed systematically.
6. Although, the paper presents a highlight at the beginning of the context, the contribution is not clear, especially the value for implementation and theoretical development. It can be added in section 1 Introduction. While doing so, please connect the contribution with the highlight and the critical problems of the paper to make a reasonable discussion.
7. The related works should be summarized systematically by using figures and table to address the internal logic of the existence references. In this the contribution of the paper will be easy to be understood.
Author Response
Detailed response to reviewer 3 is attached
Author Response File: Author Response.pdf
Round 2
Reviewer 1 Report
Comments and Suggestions for AuthorsI thank the authors for this second version of their paper. In my first review I detected some weaknesses related to the lack of detail of the type of AI used in each of the studied organizations, limiting in my opinion the applicability of the study.
In this new version this part has been improved. Now the types of AI algorithms specifically used in the organizations are provided.
Also, authors clarified the real data used for their experiments. They added a new comparison scenario, as requested by the reviewer.
A new section has been added, dedicated to the potential ethical/social risks associated with the application of AI in logistics.
Authors need to improve the styles of Figures.
Figure 1: It is distorted by having a larger width than the correct aspect ratio.
Figure 2: Being an extension of previous figure, the style (colours, fonts, etc), should be the same as in Figure 1.
Figure 3 Style can be improved (using non-capital letters, some colours, modern font-type)
Figure 6 has too big font size, and text exceeds the width of the squares
Author Response
response to reviewer 1- round 2 is attached.
Author Response File: Author Response.pdf
Reviewer 3 Report
Comments and Suggestions for AuthorsCheck grammarical eroors.
Author Response
response to reviewer 3 - round 2 is attached
Author Response File: Author Response.pdf
