Reshaping the Digital Economy with Big Data: A Meta-Analysis of Trends and Technological Evolution

Round 1

Reviewer 1 Report (Previous Reviewer 1)

Comments and Suggestions for Authors

Dear authors,

Thank you for resubmitting the manuscript entitled “Reshaping the Digital Economy with Big Data: A Meta-Analysis of Trends and Technological Evolution.” We acknowledge the considerable work you have done in revising the manuscript. Several aspects—such as structural organization, methodological clarity, and language use—have improved. However, a number of substantive issues remain unresolved or only partially addressed. We outline below the areas that still require attention.

The inclusion of the PRISMA diagram has enhanced transparency, but it still omits a key element: the exclusion of 47 non-English articles is not indicated in the visual flow. This step should be explicitly shown in compliance with PRISMA standards.

Figures 4, 7, and 9a–c continue to require significant refinement. Label crowding, poor resolution, and color contrast make them difficult to interpret. Improvements in scaling, font clarity, and overall visual layout are strongly recommended.

The main conceptual limitation remains the lack of representative individual citations. The issue raised was not the quantity of references, but the absence of strategically selected studies to substantiate trends, methods, or thematic claims. Including such references—particularly one per key cluster or stream—would substantially improve the analytical depth of the review.

The description of the red cluster is confusing and inconsistent with the figure. Terms like “negative upper section” are ambiguous and misleading. Keywords cited in the text do not align with their actual positions in the visual. Furthermore, the figure is too blurred to verify claims. We recommend revising the descriptive language, specifying axis orientation (Dim 1 or Dim 2), and improving figure resolution.

The discussion section is now more developed, but connections between findings and literature remain vague. The future research section, including Figure 17, lacks clear linkage between clusters and proposed research directions. More explicit integration would strengthen the impact of these sections.

Regarding author-level metrics (H-index, G-index, M-index), the manuscript still does not specify whether these are based on first, last, or corresponding authorship. This detail should be clarified to support interpretability.

The method of assigning national rankings remains vague. While full counting is mentioned, it is unclear how multi-affiliated authors or corresponding authors were handled. A clear methodological explanation is needed.

For institutional rankings, although a cautionary note on citation-based metrics is included, no normalization has been applied. Without adjustments (e.g., per-paper citation averages), the rankings are not robust. Either normalized indicators should be introduced or their limitations discussed more explicitly.

Figure 16, which aims to present the thematic evolution of keywords, is hindered by low image quality, lack of legend, and unclear criteria for transitions between time periods. The figure should be redesigned, explained in terms of methodology, and better contextualized within the text.

Some stylistic issues persist. For instance, the sentence “Bibliometric analysis gives the digital economy with this superpower…” employs rhetorical language inappropriate for a scholarly article. Such phrases should be rewritten in a neutral, evidence-based style.

The use of first-person expressions (e.g., “Our bibliometric analysis…”) is also discouraged in academic reviews. A more impersonal and objective tone is advised.

In summary, the manuscript has progressed in many areas, but several core concerns—particularly regarding methodological transparency, literature engagement, and visual presentation—are still incompletely addressed. We encourage you to revise these aspects thoroughly to bring the manuscript in line with the academic standards of the journal.

Comments on the Quality of English Language

Language-wise, the manuscript has improved. Problematic structures have been corrected, and overall fluency is better. Still, a final round of language editing would ensure polish and consistency.

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 2 Report (Previous Reviewer 3)

Comments and Suggestions for Authors

The manuscript offers a comprehensive bibliometric analysis of Big Data’s role in reshaping the digital economy between 2013 and 2024. It is grounded in solid quantitative methods (Biblioshiny via Web of Science data), well-structured, and reflects significant scholarly engagement. However, it also presents some notable areas for improvement, particularly in methodological transparency, language consistency, and analytical depth.

 Recommendations

The authors mention a Boolean search in Web of Science using "Big Data" and "Digital Economy," but do not provide the exact search string or criteria.

Provide the full search query and filtering criteria in an appendix or methods table.

The manuscript contains awkward phrasing and occasional grammatical inconsistencies (e.g., “being highlighted by bibliometric and other studies of specialists”).

Consider thorough English language editing to improve fluency and academic tone.

While citation counts and keyword frequency are reported, their theoretical or practical implications are not always explored in depth.

Discuss more explicitly why the leading journals, keywords, or authors matter in shaping the field, beyond just listing them.

Add a conceptual diagram or section that integrates findings into a cohesive theoretical model of Big Data’s evolution in the digital economy.

Acknowledge the potential bias more explicitly and suggest how future studies could triangulate findings using Scopus or Dimensions databases.

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 3 Report (Previous Reviewer 4)

Comments and Suggestions for Authors

Thank you for resubmitting and inviting me to review the manuscript again. I recently reviewed the original version, "The Evolution and Emerging Trends of Big Data in the Digital Economy: A Meta-Analysis Study."

The manuscript was previously rejected pending revisions based on its weaknesses and some scientific concerns. I have reviewed it again, and it is well-structured and demonstrates scholarly knowledge with innovation. I recommend that the manuscript be ready for publication, and I appreciate the authors' efforts to improve the scientific quality.

Congratulations to the authors!

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report (Previous Reviewer 1)

Comments and Suggestions for Authors

The authors have carefully implemented all the requested changes. We acknowledge and appreciate their effort in revising the manuscript. We understand that, due to software limitations, further improvements to some figures are not feasible. Overall, the paper is now clear and well-structured.

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

Dear Authors,

Thank you for the opportunity to review your manuscript titled “The Evolution and Emerging Trends of Big Data in Digital Economy: Meta-Analysis Study.” The subject matter is timely and aligns with the scope of Electronics, particularly as it relates to the application of Big Data in contemporary economic systems. While the manuscript presents an interesting premise and the ambition to map a decade of research is commendable, the current version presents several methodological, interpretive, and structural limitations that substantially affect the clarity, rigor, and reproducibility of the study. I have outlined below detailed comments and suggestions intended to support a potential revision and strengthen the contribution of this work.

 

General Comments

The introduction touches on key themes but could benefit from a more focused structure and consolidation of references.

The six research questions appear overly granular and partially overlapping. Consider merging them into broader thematic categories or framing them as objectives.

The methods section requires greater transparency—particularly regarding the exact search string, filtering criteria, and parameter settings used in Biblioshiny.

The PRISMA protocol flow is confusing. Clarify how the final sample of 584 documents was derived and ensure consistency in reported numbers.

 

Results and Figures

Several figures (e.g., Figure 2, 5, 7, and 9c) are difficult to interpret due to visual clutter or lack of legibility. Improving resolution, simplifying visual elements, and enhancing captions are recommended.

The repetition of numeric data already visible in tables/figures adds verbosity. Emphasize trends and comparisons instead.

Introduce bibliometric indices like G-Index and M-Index when first mentioned. Define “local impact” more precisely.

Clarify whether author-level metrics are based on first, last, or corresponding authorship.

 

Geographic and Institutional Data

Some results—such as Russia far outperforming the USA and the underrepresentation of India and Germany—raise concerns. These trends do not align with global publication patterns on Big Data.

Clarify the query used for affiliation attribution and provide justification for the national rankings.

Rankings of institutions based solely on citation counts should be normalized or interpreted with caution.

 

Discussion and Thematic Analysis

The discussion section mostly restates earlier results without deeper synthesis or engagement with existing literature.

The formation of thematic clusters in Section 4.2 is not explained adequately. Specify how clusters were generated, thresholds used, and parameters applied in VOSviewer.

Future directions (Section 4.3) are built around the keywords disclosure, performance, and transformation—yet these are not grounded in a clear methodological explanation or figure reference.

 

Scholarly Rigor and Language

The manuscript does not cite any individual studies from the 500+ articles reviewed. This weakens the depth of analysis. Incorporating key representative papers would enhance insight.

Several typos and awkward expressions affect readability. A thorough language review is advised.

 

I hope these comments prove helpful in revising and strengthening your manuscript. The study has potential, but substantial improvements in methodological transparency, data interpretation, and analytical depth are necessary to support its contributions to the field.

Comments on the Quality of English Language

The manuscript would benefit from a comprehensive language revision. While the general meaning is understandable, the text contains numerous instances of awkward phrasing, redundancies, and grammatical inconsistencies that detract from clarity and readability. Several terms are vague or imprecise (e.g., “subtleties,” “local impact”), and some sections (e.g., repeated H-index definitions, discussion of figures) are verbose or poorly structured.

Improving sentence structure, eliminating redundancy, and ensuring consistent use of academic terminology would significantly enhance the overall quality of the manuscript.

A thorough revision by a native English speaker or professional editing service is recommended.

Reviewer 2 Report

Comments and Suggestions for Authors

This meta-analysis explores the evolution and thematic development of Big Data research within the digital economy from 2013 to 2024, using bibliometric methods (notably Biblioshiny) on 584 selected publications from Web of Science.

The paper offers a comprehensive longitudinal analysis of Big Data research over a 12-year span, employing robust bibliometric techniques, leveraging both performance and conceptual structure metrics. The authors identify and visually represent key trends, such as "disclosure," "performance," and "transformation" as pivotal themes. Another strength of the paper is that it highlights institutional and national contributions with clarity, revealing dominant actors like China and Russia.

Please find below some comments that might improve the quality of the manuscript:

1. Although PRISMA and Biblioshiny are mentioned, essential methodological steps—such as precise inclusion/exclusion criteria, database query logic, and reproducibility measures—are only briefly described. This affects the replication and evaluation of reliability.
2. The study leans heavily on frequency counts and co-occurrence analysis without providing deeper qualitative interpretation or cross-validation from external sources.
3. The paper does not adequately relate bibliometric findings to theoretical frameworks in digital economy or Big Data adoption. For example, concepts like innovation diffusion or digital transformation models are only implied but not integrated.
4. Several sections reiterate the same points, especially about China and Russia's dominance, and thematic terms like "performance" and "transformation" are repeated without sharpening their meaning.
5. There are numerous instances of awkward phrasing (e.g., "China emergence as the most cited country") and inconsistent grammar throughout the manuscript, which detracts from its professional tone.
6. Figures and tables are informative but often appear with minimal captioning or discussion in the text. Consider aligning interpretations more tightly with visuals. Also, most of the figures are quite difficult to read (especially figures 7, 9 and 11).
7. Consider consolidating redundant findings (e.g., citation trends, co-authorship maps) where they do not provide new insights.
8. The use of "Plus Keywords" and technical terms (e.g., MCA, thematic evolution, RPYS) should be accompanied by clearer explanations for non-specialist readers.

Reviewer 3 Report

Comments and Suggestions for Authors

The article entitled "The Evolution and Emerging Trends of Big Data in Digital Economy: Meta-Analysis Study" presents an extensive bibliometric review of the application of Big Data in the digital economy, covering publications from 2013 to 2024 using data from Web of Science (WoS) and the Biblioshiny tool.

The article is timely and relevant, especially considering the acceleration of digital transformation in various sectors worldwide. The use of quantitative bibliometric techniques is appropriate for the objectives stated.

 

For two of the authors, please use their institutional email addresses.

The BiblioShiny application is interesting, but it is not among the main bibliometric tools.

I searched WoS and the list of journals addressing the concept of "Big Data" is much larger.

In WoS a special account is needed to query a certain number of records via API depending on the chosen/payed plan according to https://developer.clarivate.com/apis/wos

What to improve:

-no clear statement of novelty in the Abstract.

-streamlining the Introduction, 

-the figures are not of good quality.

- enhancing critical analysis in Results and Discussion

Comments on the Quality of English Language

"China emergence as the most cited country" → "China emerges as the most cited country."

"Thei study analyzed..." → "This study analyzed..."

I did not find the word 'thei' in https://www.oxfordlearnersdictionaries.com/.

Use professional language editing before resubmission.

Reviewer 4 Report

Comments and Suggestions for Authors

Manuscript ID: electronics-3676215

Title: The Evolution and Emerging Trends of Big Data in Digital Economy: Meta-Analysis study

Summary: The study reviews 12 years of Big Data research in the digital economy, analyzing 584 documents. It identifies three key trends: disclosure, performance, and transformation. China leads in citations, with notable contributions from major journals and St. Petersburg Polytechnic University.

The research article is a perfect example of a study based on big data. It utilizes data, figures, and tables alongside theoretical work; however, I noted that the manuscript still needs careful revision. Suggested follow-up comments addressed

The manuscript title is too simple; please write it as unique and academic with refinement.

I suggest the authors add every section to the end of the introduction to make it more straightforward.

The authors used many figures, some of which are unclear in the results and are not explained in the text and figures. Please carefully revise them.

The paper has structural issues; the authors have used figures throughout. I suggest that they create a separate section called 'Results' and include all figures in that section.

Please follow the recently published articles, check their structure, and add them as citations in the literature review of your research paper.

https://doi.org/10.3390/su16146025,  https://doi.org/10.3390/electronics14030504

Please rewrite the Conclusions section. I noted that the Conclusions and Introduction sections are similar. After the Conclusions section, include the primary findings and add future research directions.