Global Supply Chain Distribution and Natural Resources in the Era of Digitalization

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The paper "Global Supply Chain Distribution and Natural Resources in the Era of Digitalization" examines the impact of supply chain distribution and ICT product exports on natural resource rents in European countries from 2004 to 2022. Additionally, the paper analyzes the effects of other factors, such as economic growth, urban population, financial institutions, and patents, on natural resource rents. The topic is timely and holds notable research value. However, from an overall logical standpoint, the paper is an empirical study that lacks the essential research framework typically found in such studies. The explanation of estimation methods and variable indicators is somewhat insufficient, and the paper's structure requires improvement. Specific suggestions for revision are as follows:

（1）Formatting Issues: The article's format is somewhat disorganized, with several issues related to formatting and punctuation. The table formatting is inconsistent, and some expressions lack clarity. It is recommended that the author carefully proofread the entire manuscript and check for errors. Additionally, enhancing the visual quality of the charts and tables would improve the presentation of the paper.

（2）Methodology Section: The discussion of the methodology is inadequate. The estimation methods, such as KRLS estimation, are only briefly mentioned in the background section. It is suggested that the author expand this section, particularly by providing the relevant formulas and model derivation for the method used.

（3）Econometric Model Specification: Although this paper is an empirical study on influencing mechanisms, the econometric methods employed are standard techniques. However, the paper lacks a clear specification of the econometric models, presenting only the results. It is advisable for the author to include a detailed specification and explanation of the econometric models used in the analysis.

（4）Chapter Structure: The section titled "3.3. Findings and Discussion" is not appropriately placed in the "3. Data and Methodology" chapter. It is recommended that the author begin a new chapter to present a more thorough analysis of the empirical results.

（5）Variable Definitions and Measurement Methods: The article lacks comprehensive definitions and measurement methods for the primary research variables, making it difficult to clearly understand the specific definitions and measurement approaches. It is suggested that the author expand this section to increase the depth and clarity of the paper.

Author Response

Dear Reviewer,

 

Thank you for your valuable comments! We have addressed them asc per attached response letter. 

 

Best regards,

 

authors

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

The paper, allegedly investigates SCD and ICT exports on NRR of European countries during 2004-2022. The guiding research problem, however, is not well articulated and problematized. The article lacks a focused simple question, it can only give a list of relationships that shall be discussed. It is not so conceptually.  well-grounded introduction: it combines supply chain efficiency, ICT diffusion and environmental considerations without weaving them logical into a research gap. This vague framing seriously compromises the importance and scholarly quality of the research from the beginning.

Further, the paper falsely presents the paper as novel calling for research to “develop an understanding of linkages between digitalization, supply chain management and natural resources” when ample existing research – in (e.g.) ICT and resource efficiency, ICT and green logistics exists and the authors do not locate their work in relationship to this literature. This creates a false rationale for the study’s significance.

The links between ICT exports, supply chains, and environmental/resource consequences have been extensively documented in a range of economics, management and environment journals. The authors regurgitate old familiar findings and have nothing new to add theoretically, thematically or methodologically. They just reapply standard econometric tools to a bit more on an already well-scrutinised data set (European countries over 2004-2022) while presenting no novelty in approach, or distinct new explanations.

The result also appears to be recycled and less break-through: the study confirms that ICT enhances the reduction in resource rent and that stronger supply chain increases rent (both results have already been well acknowledged in existing literature). So, the knowledge contribution is minimal at best and originality claim is questionable.

Although the article purports to be employing relatively advanced methods (KRLS and quantile regressions) they are implemented in a methodologically questionable fashion on several accounts:

Model-research question mismatch The use of KRLS is a neat machine learning method, but there is no compelling reason why a non-parametric method should do better than the (say) fixed effects model for the economics question they are trying to address.

The paper explains KRLS and Bootstrap Quantile Regression, but not how the model is specified according to the variables, nor do they clarify the method adopted to control for the endogeneity, multicollinearity, or omitted variable bias.

Shoddy data treatment: The author mentions CSD of variables in another part of the paper, but does not persuasively model around that — just recognizes it and moves on, no adjustments (robust errors, second-generation panel models etc.)

SCDP is a variable that we calculate based on New York Fed's Global Supply Chain Pressure Index. But this climate- related index of supply chain dynamics reflects nothing specific either to our European natural resource rents, nor to geographies covered.

No further robustness checks are presented (e.g., alternative model specifications, outliers, causality tests) than for a second method (BSQREG), raising serious question on the results' credibility.

So instead of building complexity, it’s apparent that the article is a mess in terms of methodological discipline, and the lack of ‘real’ methodological rigor indeed results in losing the confidence in results.

The findings are tentative, cursory, and redundant.

The article basically repeats the results of the regression (such as ICT exports reduce NRR and financial investments in resource-intensive sectors raise NRR) without interpretation or critical engagement with their broader implications.

There is no serious discussion of the study's limitations (concerns concerning causality, limits to the data, potential omitted variables), which is crucial for a serious paper, because after all, no study is without limitations.

The policy prescriptions are of a general character and show no direct relation to the econometrical findings. For example, “promote sustainable investment by financial institutions” is one thing we all know should be done, but not something per se that is operationalized, not tightly tied to econometric evidence in a particularly rigorous manner.

In addition, the conclusions failed to consider possible inconsistencies in the findings, such as the paradox that urbanization is said to reduce natural resource rents (which is puzzling and not deeply analyzed).

The references used in this article appear to have a number of shortcomings.

Heavy use of secondary, non-refereed material: Although a substantial proportion of Euler et al. references are either to working papers, conference proceedings, or pre-publication preprints (so as to fail the high standard normally rigourously maintained for empirical papers in environmental and economic science). Thus, relying on preprints (Mahdavi & Sojoodi, 2021; Li et al., 2021) with no peer review for questionable reliability.

Out-of-date or decontextualized references Exemplar-based: The paper consistently uses previous literature (e.g., McKinnon, 2018; Hilty & Aebischer, 2014) on subjects (ICT, environmental management) for which vastly more contemporary literature on digitalization and resource management is available post-COVID-19. This gives the feeling that the article is not well-placed in the current state of the art.

There are numerous citations deposited in text without critical examination or being woven into a meaningful conceptual model. For example, literature reviews (section 2) tend to present (section 2) work one by one without contrasting or synthesising results, indicating weak integration with previous literature.

Many citations are repeated (eg, Shaaban-Nejad & Shirazi, 2022 are appearing twice), suggesting an irresponsible editorial work and a lack of attention to detail.

Several references are incomplete or incorrectly formatted (eg. volume or issue numbers missing, DOI's used inconsistently and mixed styles between journal articles and conference papers). This indicates an irrelevance to the editorial standards usually imposed by the journals, like Sustainability (MDPI).

The referencing is overall sloppy, outdated, and superficial, all of which utterly erode the academic credibility of the article.

The overall presentation of tables, figures and data in this paper is not good and raises serious issues:

Tables have inadequate explanatory notes as follows:

Legend or explanation of variables, units of measurement or explanation for the indices with which the readership might not be familiar, and other reference tables, if any, are not provided (for example, descriptive statistics, correlation matrices, etc.). For example, Table 2 (descriptive statistics), present some figures without the necessary context regarding sample size, time period or variable transformation (i.e., log-transformation of PATN?).

Absence of Figures:

Other than an extremely rudimentary graph of average NRR scores by country (Figure 1), the paper virtually eschews graphics (no trend lines, no scatterplots, no robustness plots). Visualizations In contemporary empirical work, visualizations are essential for both verifying outcomes and improving reader interpretation. Lack of figures Lack of informative figures reduces transparency and interpretability of the findings.

Issues regarding quality and transparency of the data:

Limited information is provided on the data sources (e.g., World Bank, Eurostat) and procedures for selecting specific data. Not a word about missing values, correction for inflation or exchange rate, exclusion of samples, data cleaning etc — which are the must for any serious empirical work.

Robustness analysis not well explored:

The data coherence is only partially cross-validated across methods, as two different methods (KRLS and quantile regressions) are adopted. Outlier tests, heteroskedasticity tests and multicollinearity tests are not presented, casting doubts over the reliability of these statistical realizations.

Accordingly, the presentation and the treatment of the data are extremely shallow, not transparent at all, way below the minimum requirements expected in a serious scientific journal.

Comments on the Quality of English Language

This article has seriously poor quality of language and it’s unprofessional:

There are also many grammatical and grammatical errors:

They are full of cumbersome expressions (such as "For performing it is necessary to use raw materials and minimize the levels of harmful to the environment waste" (sic)) and unidiomatic language, making it difficult for the reader to understand. Prepositions, articles and verb tenses are utilized interchangeably throughout the text.

Poor paragraph organization:

A great many paragraphs are too long, have no focus, and transition terribly from one idea to the next. The logical thread is rather week: for instance, Section 1 (Introduction) jumps randomly from supply chain discussion, to ICTs, to natural resources management without continuous thematic building thereon.

Excessive redundancy:

Many of the points are rehearsed almost word for word in different parts of the book (e.g. environmental impacts of transport, the role of ICT in efficiency), suggesting clumsy editing and a lack of harmony.

Technical jargon is mishandled:

There are instances of inappropriate or ambiguous use of technical terms (e.g., the “natural resources rents” are used in a rather simplistic fashion which does not correspond to their economic complexity). Additionally, key terms are variably abbreviated (e.g., SCDP and SCD; NRR and NR) resulting in both repetition and ambiguity.

Errors of the keyboard and other oversights:

There are several minor errors (eg lack of spaces, incorrect punctuation, mixed use of sing/pl) throughout the manuscript indicate that it has not been proofed well prior to submission.

The English is far below the standard required for international scientific publication and would need a substantial amount of professional editing before the paper should be put forward for review at a reputable journal.

Author Response

Dear Reviewer,

 

thank you for your valuable comments! We have addressed them as per attached response letter.

 

Best regards,

 

Authors

Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

The paper examining the effects of supply chain disruption and product exports contains a detailed analysis of the literature in the field. The authors have appropriately chosen the research methodology and the data evaluation. However, the paper does not conclude with a discussion that would appropriately complement the results of the investigation of the subject matter compared with the results of other authors.

Comments on the Quality of English Language

The paper examining the effects of supply chain disruption and product exports contains a detailed analysis of the literature in the field. The authors have appropriately chosen the research methodology and the data evaluation. However, the paper does not conclude with a discussion that would appropriately complement the results of the investigation of the subject matter compared with the results of other authors.

Author Response

Dear Reviewer,

 

Thank you for your valuable comments! We have addressed them as per attached response letter.

 

Best regards,

 

Authors

Author Response File: Author Response.pdf

Reviewer 4 Report

Comments and Suggestions for Authors

The intersection of digitalization, supply chain management, and resource sustainability is highly pertinent in the context of global environmental and logistical challenges. The KRLS and bootstrap quantile regression methods are well-suited to address non-linear relationships and cross-sectional dependence. The paper offers practical recommendations for sustainable urbanization, ICT investments, and green innovation.

The study reports multiple estimation results (KRLS and BSQREG), but does not perform a formal statistical test to determine whether observed differences in prediction accuracy are statistically significant. This would strengthen claims about model superiority.

While KRLS and BSQREG are introduced, the exact implementation (software used, cross-validation method, bandwidth/tuning choices) is vague. Provide a reproducibility appendix or at least detailed notes on Kernel selection for KRLS, number of bootstrap replications for BSQREG, and any treatment of multicollinearity.

The paper could benefit from a stronger theoretical underpinning linking SCD, ICT, and NRR. While the literature review is broad, it lacks a conceptual framework that explains why and how these variables interact. You can consider including a conceptual figure or table summarizing hypothesized causal paths.

Although the paper mentions CO₂ emissions and environmental degradation qualitatively, it does not empirically measure or control for environmental outcomes such as emissions per capita or carbon intensity. If feasible, incorporate environmental indicators (such as CO₂ emissions) as additional dependent or control variables to enhance the sustainability framing.

Clearly differentiate and explain the relationship between supply chain disruption and the supply chain distribution (SCDP) index. Elaborate on the interpretation of the positive impact of a strong SCDP on NRR in the context of resource utilization.

Discuss the potential limitations of analyzing European countries as a homogenous group. Consider mentioning potential regional variations or suggest avenues for future research exploring sub-regional analyses.

Provide a more detailed discussion on the specific mechanisms through which ICT goods exports contribute to the reduction of natural resource rents. Link the empirical findings more directly to the theoretical arguments and examples from the literature review.

Expand the discussion on the impact of urbanization on natural resource rents by considering alternative or complementary explanations, such as the shift towards service-based economies.

Ensure all abbreviations (e.g., FIE, PATN) are clearly defined when first introduced.

The references are current and relevant but require consistent formatting (some links are repeated or split).

There are many issues related to the tables and figures such as:

• Tables are dense and not reader-friendly. It's difficult to quickly interpret key findings due to the lack of visual cues (e.g., bold for significant results, shaded rows).
• Table formatting (Tables 6 & 7) could be improved for readability.
• Column alignment (e.g., variable names, quantiles) is occasionally misaligned.
• Table captions are too short and do not explain what the table shows in full detail.
• Add clear, concise notes under each table (“Standard errors in parentheses”, “* p<0.05, ** p<0.01”).
• There is no summary table comparing model performance (RMSE, AIC) across estimation strategies.
• Consider adding a model evaluation table to help readers assess predictive fit across methods.
• The figures are low-resolution and appear slightly pixelated. This can affect readability in the published version.
• Axes on some figures lack units or full variable names.
• Add legends or captions that help interpret the plotted effects, especially for readers unfamiliar with the methods.
• No confidence intervals or shading to show uncertainty around kernel estimates.

Consider adding confidence bands to kernel regression plots if possible.

Comments on the Quality of English Language

The manuscript suffers from awkward phrasing, grammatical inconsistencies, and occasionally imprecise terminology. Substantially revise the manuscript for English clarity, preferably with assistance from a native speaker or professional editing service. (CSD vs. CDS in Table 4, missing column headers, “3.2 Metedology in page 6”…)

Carefully proofread the manuscript to correct any typographical errors, inconsistencies in acronyms, and ensure clarity in presentation.

Author Response

Dear Reviewer,

 

thank you for your valuable comments! We have addressed them as per attached response letter.

 

Best regards,

 

Authors

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

The revised manuscript presents substantial improvements and offers meaningful insights into the effects of supply chain distribution and ICT product exports on natural resource rents. The topic is both timely and relevant, and the study contributes to the growing body of empirical research in this field. Nevertheless, a few minor issues remain that should be addressed to further strengthen the manuscript and prepare it for publication:

1.Baseline Regression Model: The manuscript still lacks a clearly defined baseline regression model, which is essential for establishing a foundational framework for the subsequent empirical analysis. It is strongly recommended that the author incorporate such a model to improve the methodological rigor and clarity of the study.

2.Section Numbering: There is a formatting issue with the section numbering—both “4. Findings and Discussion” and “4. Conclusion and Recommendations” are labeled as Section 4. The author should carefully review the manuscript to ensure consistent and correct section numbering throughout.

3.Table Formatting: Several tables display inconsistencies in formatting. The author is advised to conduct a thorough review to ensure all tables adhere to a uniform style in terms of layout, alignment, and presentation.

Author Response

Dear Reviewers,

 

Thank ou for your valuale comments! We have addressed them as per the uploaded response letter. All changes are marked in yellow into the revised paper.

Best regards,

Authors

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

Research Question and Framing

Reviewer Comment: Construct Definition (problem with concept: was not well-defined, was not explicitly stated, and was not set in a framework).

Author’s Reply: / Claims to have reorganized the introduction, refined the research question, and added post-COVID sources to the literature.

Evaluation:

Partially addressed. New version of Introduction: Statement of the question The introduction has been altogether rewritten (now in a clear version of the purpose), but the novelty is at issue in the reviewer's opinion regarding the wide coverage of the topic.

Originality and Contribution

Reviewer critique: Lack of novelty; does not provide any new theoretical or methodological insight.

Response: We take into consideration the existing literature, and our contribution is to specifically address the European regional context.

Evaluation:

Lacking. The argument for regional focus does not quite vindicate the weight. The results simply confirmatory as opposed to exploratory or groundbreaking.

Methodological Rigor

Reviewer Issue: Model and question don't match, inadequately addressed endogeneity, multicollinearity and omitted variable.

Author’s Response: I added a methodology section addressing these problems, and justified KRLS and quantile regression.

Evaluation:

Better, but still not quite there. Although there were technical extensions, explanation for the models selected for estimation was very poor and no more work on causal inference is reported. The robustness is handled better though not more complex.

Transparency of Results and Data Treatment

Reviewer 1 Concern: No documentation; missing treatment of data; no details on the transformation - no visualizations to understand the data.

Author's Response: Revised the tables, with additional explanations and figures for the variableAdded data cleaning.

Evaluation:

Adequately addressed. The presentation has been enhanced, however, a more detailed appendix or data description (e.g. STROBE like table or data dictionary) would improve transparency.

Interpretation and Policy Implications

Reviewer Critique: The policy implications were very vague and not rooted in the results. For the paradoxical results (eg urbanisation) not mentioned.

Author's Reply: Elaboration and new analysis of paradoxes.

Evaluation:

Improved. There is a more explicit connection between econometric results and policy recommendations now, even though some recommendations are still general in nature.

Reviewers’ comment: Outdated references and weak integration, a lot of repited reference, the format of reference was bad.

Author’s Correction: References updated, formatting corrected - new sources added.

Evaluation:

Partially addressed. A few references are newer, yet thematic literature synthesis remains limited. Most references are listed like books with no consideration to concept or system building.

Visulization and Reporting

Reviewer Issue: Missing graphs, poorly explained tables missing variable data.

Author's Response: Incorporated figures and table notes.

Evaluation:

Partially addressed. But there's still little in the way of visualisation beyond summary statistics and model outputs.

Comments on the Quality of English Language

Language quality and structure

Reviewer Comment: Very poor English including serious grammar, arrangement of text and repetition.

Author’s Reply: A professional editing had been provided.

Evaluation:

Improved but not flawless. The resubmitted manuscript is clearer, although some weird wording remains and the issues are repeated.

Citations and Literature Integration..2...2.. Reference Baader, F., Brewka, G., & Tel- kamps, V.

Author Response

Dear reviewers,

 

Thank you for your valuable comments! We have addressed them as per the attached response letter. All changes are marked in yellow into the revised paper.

 

Best regards,

Authors

Author Response File: Author Response.pdf

Reviewer 4 Report

Comments and Suggestions for Authors

Despite some improvements, some critical issues remain partially addressed or unresolved:

Authors compare KRLS and BSQREG descriptively but do not provide formal statistical tests (Diebold-Mariano for predictive accuracy or RMSE/AIC comparisons). Include statistical performance metrics across models to justify claims of robustness.

Tables are denser, and although labeled better, some column headers, captions, and notes are still missing or unclear. Figures are still low resolution. Improve table formatting, align columns, bold significance stars, and provide full-resolution figures with legends and confidence intervals.

Terminology inconsistency remains (SCD, SCP, SCDP used interchangeably). Consistently use one abbreviation and define it clearly.

Authors did not add a visual conceptual framework to illustrate hypothesized relationships. A figure summarizing causal paths between SCD, ICT, NRR, and mediators like patents and urbanization would strengthen coherence.

No discussion on regional variation within Europe or the limitations of treating it as homogeneous. Add a paragraph in the limitations section noting this assumption and suggesting future regional studies.

No appendix or clear detail on: Kernel type used for KRLS (Gaussian? Polynomial?), number of bootstrap replications, software and packages used (R, Stata, Python), treatment of multicollinearity or outliers.

Add a reproducibility note or appendix to support transparency.

Comments on the Quality of English Language

Despite some improvement, the manuscript still suffers from grammatical errors, awkward phrasing, and occasional mistranslations (e.g., “Metedology”, “SPCH”, “Inangible Flow”). Requires professional proofreading or native speaker editing to ensure readability and scholarly tone.

Author Response

Dear reviewers,

 

Thank you for your valuable comments! We have addressed them as per the attached response letter. All changes are marked in yellow into the revised paper.

 

Best regards,

Authors

Author Response File: Author Response.pdf