Scientometric Study of Digital Transformation and Human Resources: Collaborations, Opportunities, and Future Research Directions

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The article proposes a scientometric analysis of the literature on digital transformation and human resources, using data from the Web of Science. The study is well structured and contributes to the field by identifying publication trends, influential authors and collaboration networks.

The topic is current and important, relevant to researchers and practitioners in management and human resources. The study provides an overview of the existing literature but does not propose a significant theoretical contribution; instead, it summarises the current state of research.

The scientometric method used is appropriate for the proposed objectives. Data collection and filtering are clearly described, but a more detailed justification of the criteria for selecting and excluding articles would improve methodological transparency. The study relies exclusively on the Web of Science, which may lead to a linguistic and regional bias, underrepresenting literature from other relevant databases (e.g., Scopus, Google Scholar). This limitation is mentioned in the paper but is not discussed in depth.

The text is well-organised and logically structured, with a clear introduction and a coherent presentation of the results. However, the discussion and conclusions section could be better defined by highlighting the limitations and practical implications. The conclusions also do not discuss the practical implications for organisations and policymakers in depth.

The references are relevant and include recent studies, but it is unclear whether all sources have undergone a rigorous selection process based on their academic impact. A discussion of the possible omissions of important sources would be helpful.

Some passages could benefit from linguistic revision to improve the coherence and clarity of academic expression (e.g. lines 24-28, 43-49, 106-109, etc.). 

The article makes a relevant contribution, but it can be improved by:

• Specifying a clear purpose of the study in the introduction section.
• Obtaining the answer to the question “7. What are promising future research directions for digital transformation and human resources?” does not seem to be fully achieved. I consider that the research questions should be presented as explicit objectives of the research.
• If possible, the paper could include general hypotheses about the observed trends, even if these are not statistically tested.
• A more detailed justification of the methodology and limitations of the database used.
• Clearer discussion section, with better outlined theoretical and practical implications.
• Proposing a new conceptual model or a critical analysis of theories in the field.
• A reflection on the study's limitations and ways to overcome them in future research would be helpful.
• Linguistic revision for clarity.
• Adding the statements regarding author contributions, conflicts of interest, data availability, and funding.

Comments on the Quality of English Language

Some passages could benefit from linguistic revision to improve the coherence and clarity of academic expression (e.g. lines 24-28, 43-49, 106-109, etc.). The article would benefit from a linguistic revision to eliminate possible ambiguities.

Author Response

Comments 1: The scientometric method used is appropriate for the proposed objectives. Data collection and filtering are clearly described, but a more detailed justification of the criteria for selecting and excluding articles would improve methodological transparency. 

Response 1: We extend our sincere gratitude. Enhancements pertaining to the selection and exclusion criteria have been implemented in accordance with the aforementioned proposal. The limitations concerning the utilization of WoS are discussed within the discussion and conclusions section.

Data were retrieved from the Web of Science Core Collection (WoS) database, encompassing the SSCI, ESCI, SCI, BKCI-SSH, A&HCI, CPCI-SSH, BKCI-S, and CPCI-S indexes. The study focuses its search on the online database of the Web of Science (WoS), which is one of the most recognized and accepted platforms by the scientific community and by evaluation and research agencies.

The following search string was used, searching within the title, abstract, and author keywords (TS): TS=("Digital Transformation*") AND TS=("human resources" OR "people management" OR "personnel management" OR "human capital").

Within the realm of academic research on digital transformation, the application of the truncation symbol ("") to the term "Digital Transformation" is deemed essential to ensure the comprehensiveness of the search. This practice enables the inclusion of diverse terminological variations, thereby optimizing the identification of pertinent studies addressing the core concept of digital transformation (Hoods & Wilson, 2001).

Furthermore, when exploring the intersection of digital transformation and human capital management, the term "human resources" emerges as a central component. The search strategy is expanded by incorporating synonyms such as "people management," "personnel management," and "human capital," linked by the Boolean operator "OR." This measure is warranted by the terminological variations found in the literature and the necessity to cover diverse conceptual perspectives within employee management (Hoods & Wilson, 2001).

Lastly, within the context of bibliometric and scientometric studies, limiting the search to the title, abstract, and author keywords (TS) fields is grounded in their capacity to provide a succinct representation of the core content of the articles. These fields are of primary importance for indexing in academic databases, thereby ensuring a greater likelihood of identifying the literature most relevant to the research subject.

Comments 2: The scientometric method used is appropriate for the proposed objectives. Data collection and filtering are clearly described, but a more detailed justification of the criteria for selecting and excluding articles would improve methodological transparency. The study relies exclusively on the Web of Science, which may lead to a linguistic and regional bias, underrepresenting literature from other relevant databases (e.g., Scopus, Google Scholar). This limitation is mentioned in the paper but is not discussed in depth.

Response 2: We extend our sincere gratitude. Enhancements pertaining to the selection and exclusion criteria have been implemented in accordance with the aforementioned proposal. The limitations concerning the utilization of WoS, including an enhanced explanation of the inherent constraints of relying solely on this database, are discussed within the discussion and conclusions section.

Comments 3: The text is well-organised and logically structured, with a clear introduction and a coherent presentation of the results. However, the discussion and conclusions section could be better defined by highlighting the limitations and practical implications. The conclusions also do not discuss the practical implications for organisations and policymakers in depth.

Response 3: We extend our sincere gratitude. Enhancements pertaining to the selection and exclusion criteria have been implemented in accordance with the aforementioned proposal. The limitations concerning the utilization of WoS, including an enhanced explanation of the inherent constraints of relying solely on this database, are discussed within the discussion and conclusions section, which has been further improved by integrating both the limitations and practical implications.

Regarding the limitations of this study, it is acknowledged that bibliometrics, with its inherent focus on quantitative metrics, often overlooks qualitative contributions and nuanced interpretations of research quality. Consequently, future research may benefit from exploring systematic reviews of the literature, which would facilitate an objective and systematic integration of empirical study results to determine the current state of knowledge within a specific research domain (Cabrerizo et al., 2010).

Furthermore, the Web of Science (WoS) has historically demonstrated a pronounced focus and robust coverage in the domains of natural sciences, engineering, and biomedical research. This has resulted in the underrepresentation of the social sciences and humanities (SSH) within WoS coverage. Notably, certain disciplines within the humanities rely heavily on formats such as books and book chapters, which are not as comprehensively indexed by WoS. Similarly, the breadth and depth of thematic coverage for journals in SSH may be comparatively limited within this database (Garfield, 2002). Additionally, WoS coverage exhibits a clear dominance of English-language journals, which are overrepresented at the expense of other languages. This linguistic bias may disadvantage research produced in non-English speaking regions and distort the representation of global research output (Ammon, 2001). Moreover, both WoS and Scopus present accuracy issues concerning the assignment of corresponding authorship. Inaccurately indexed author names or affiliations can result in the erroneous attribution of publications and citations, potentially skewing metrics such as the h-index or institutional rankings. Finally, a systematic increase in the number of citations over time is observed due to the expanding length of reference lists. Consequently, recently published works may accumulate a higher number of citations simply due to the increased volume of publications and citations, rather than an inherently greater impact compared to older works (Leydesdorff & Ivanova, 2021).

The concentration of citations among a limited number of authors may inadvertently exclude valuable perspectives. Therefore, it is essential to promote the dissemination of less visible works through increased methodological rigor, content specificity, or publication in lower-impact journals, as suggested by Chawla and Goyal (2021). Furthermore, given this concentration of influence, the integration of junior researchers and the incorporation of less explored geographical contexts are crucial. The significant influence of certain institutions raises questions about their collaboration networks and resource availability, warranting further investigation. Similarly, the prominent role of certain countries necessitates a deeper analysis of the impact of public policies on digital transformation (DT) research.

This research delves into the intersection of DT and human resources (HR), revealing significant theoretical and practical contributions to the field. Although the observed exponential growth in publications is encouraging, it does not guarantee practical application within organizations, particularly in developing regions. This growth aligns with previous findings that highlight the positive impacts of DT on profits, cost reduction, and efficiency (Valderrama, 2019; Hanelt et al., 2021; Tomaszewski, 2021). This study reveals limited participation by Spanish-speaking authors in DT and HR research, suggesting a need for increased theoretical and practical development in Spanish-speaking contexts. This research contributes by summarizing existing theoretical and practical advancements, enabling an analysis of DT challenges within the social, economic, and political context of these regions. The incorporation of data from additional databases could provide a more comprehensive representation of Spanish-language research on DT.

From a theoretical perspective, this study analyzes the development and evolution of specialized literature. In practical terms, it highlights the strategic role of digital competencies as key facilitators in DT processes. This approach enables the understanding of how the implementation of change management plans, aimed at aligning organizational culture with strategic objectives of innovation and agility, is directly influenced by these competencies.

The analysis of publication trends reveals a growing interest in the role of soft skills within DT-driven change processes, as well as the importance of digital competencies for successful adoption of new technologies. The most influential studies provide practical guidelines to facilitate these processes, emphasizing the relevance of individual, group, and organizational factors from a systemic perspective, and identifying existing research gaps related to employee-related factors. Among the most prominent journals identified in this study are Sustainability, Frontiers in Psychology, and Finance Research Letters.

In the global context, countries with higher scientific production in this area tend to have strategies that link public policies with technology-based productive efficiency, reflected in higher R&D spending. These countries, characterized by their focus on innovation and the production of high value-added goods and services, perceive DT as a competitive advantage. Scientific collaboration networks, predominantly among industrialized countries, reflect this concentration of efforts and resources.

The findings of this research have significant practical implications for organizations. Firstly, the identification of the most relevant digital competencies enables the design of specific training programs for employees, optimizing the DT process. These plans seek to align organizational culture with the strategic objectives of innovation and agility, essential elements in the current organizational context. Secondly, this study highlights the need to develop a validated psychometric instrument to measure the development of digital competencies in Spanish-speaking contexts, overcoming the limitations of existing qualitative assessments.

Finally, the literature review provides guidance for articulating DT processes with a focus on aligning personnel competencies with organizational strategy. Additionally, it emphasizes the importance of public policies that promote research and knowledge transfer, driving efficiency and the retraining of human capabilities in both the public and private sectors. It is recommended that future research explore the impact of DT on various dimensions of work-life quality, such as wage compensation, occupational safety and health, interpersonal relationships, work climate, workload, and technostress (Wang et al., 2023). Furthermore, the findings of this study should be interpreted considering the temporal framework of its analysis, given the dynamic nature of this field.

Organizations can utilize the findings of this study to identify the most relevant digital competencies for their needs and to design specific training programs to develop these competencies in their employees. The findings of this study should be interpreted in consideration of the analyzed timeframe, given that the field of digital transformation and human resources is in constant evolution.

Comments 4: The references are relevant and include recent studies, but it is unclear whether all sources have undergone a rigorous selection process based on their academic impact. A discussion of the possible omissions of important sources would be helpful.

Response 4: We extend our sincere gratitude. The majority of the citations utilized are from publications indexed in the WOS database. With respect to potential omissions, these are discussed within the discussion section.

Comments 5: Some passages could benefit from linguistic revision to improve the coherence and clarity of academic expression (e.g. lines 24-28, 43-49, 106-109, etc.). 

Response 5: We extend our sincere gratitude. Improvements have been made regarding the coherence and clarity of academic expression.

Comments 6: The article makes a relevant contribution, but it can be improved by: Specifying a clear purpose of the study in the introduction section. Obtaining the answer to the question “7. What are promising future research directions for digital transformation and human resources?” does not seem to be fully achieved. I consider that the research questions should be presented as explicit objectives of the research.

Response 6: We extend our sincere gratitude. Improvements have been made in the introduction to clarify the purpose of the study.

Digital transformation (DT) is a multidimensional phenomenon that has been addressed by disciplines such as mathematics, engineering, computer science, social sciences, economics, and also by behavioral sciences (Li, 2022).

For the purposes of this publication, we will focus on the approach to DT from the perspective of human resources, highlighting the role of individuals in the technological changes occurring in the workplace.

In this context, digital transformation drives performance through strategic innovations that create value (Hess et al., 2016). These strategic innovations empower organizations to respond to constantly evolving global demands (Mat et al., 2015; Hess et al., 2016; Correani et al., 2020).

There is a consensus that DT is as much about people as it is about technology (Erceg et al., 2022; He, 2023) in a change process that requires teams to move beyond habitual practices (Teece et al., 2016).

The change process demands a significant effort from the entire company, making the formulation of business strategy fundamental for success (Sebastian et al., 2017; Erceg & Zoranović, 2022).

The growing body of literature on digital transformation (DT) highlights the significant interest in its impact (Vial, 2019; Baiyere et al., 2020; Broz et al., 2020; Chawla, 2022).

The objective of this review is to map the academic landscape, to provide insights into the challenges and opportunities, and to identify future directions for both researchers and practitioners in the field of digital transformation and human resource management.

To this end, this article addresses the following research questions:

• What are the key publication trends in the field of digital transformation and human resource management?
• What are the most influential studies on digital transformation and human resource management based on citation analysis, and what are their main contributions and theoretical findings?
• Which countries and institutions host the leading researchers in this field?
• In which research networks do the main authors participate?
• Which scientific journals contribute most significantly to the body of knowledge on this topic?
• What are the promising future research avenues for digital transformation and human resources?
• What are the practical implications of current research on digital transformation and human resource management for HR professionals and organizational leaders when informing their strategies, decision-making, and implementation efforts?

Comments 7: What are promising future research directions for digital transformation and human resources?” does not seem to be fully achieved. I consider that the research questions should be presented as explicit objectives of the research.

Response 7: We extend our sincere gratitude. Possibilities for future research have been incorporated.

Future research should explore the impact of DT on various dimensions of quality of work life, such as wage compensation, occupational safety and health, interpersonal relationships, work climate, workload, and technostress (Wang et al., 2023).

Finally, there is a need for a validated psychometric instrument to measure the maturity of DT in organizations within Spanish-speaking contexts. Current assessments rely heavily on qualitative methods, such as interviews with management, which can introduce bias. A standardized instrument would provide a more objective and reliable measure of DT maturity.

Organizations can utilize the findings of this study to identify the most relevant digital competencies for their needs and to design specific training programs to develop these competencies in their employees.

Comments 8: A more detailed justification of the methodology and limitations of the database used.

Response 8: We extend our sincere gratitude. The discussion section has been improved as suggested.

Data were retrieved from the Web of Science Core Collection (WoS) database, encompassing the SSCI, ESCI, SCI, BKCI-SSH, A&HCI, CPCI-SSH, BKCI-S, and CPCI-S indexes. The study focuses its search on the online database of the Web of Science (WoS), which is one of the most recognized and accepted platforms by the scientific community and by evaluation and research agencies.

The following search string was used, searching within the title, abstract, and author keywords (TS): TS=("Digital Transformation*") AND TS=("human resources" OR "people management" OR "personnel management" OR "human capital").

Within the realm of academic research on digital transformation, the application of the truncation symbol ("") to the term "Digital Transformation" is deemed essential to ensure the comprehensiveness of the search. This practice enables the inclusion of diverse terminological variations, thereby optimizing the identification of pertinent studies addressing the core concept of digital transformation (Hoods & Wilson, 2001).

Furthermore, when exploring the intersection of digital transformation and human capital management, the term "human resources" emerges as a central component. The search strategy is expanded by incorporating synonyms such as "people management," "personnel management," and "human capital," linked by the Boolean operator "OR." This measure is warranted by the terminological variations found in the literature and the necessity to cover diverse conceptual perspectives within employee management (Hoods & Wilson, 2001).

Lastly, within the context of bibliometric and scientometric studies, limiting the search to the title, abstract, and author keywords (TS) fields is grounded in their capacity to provide a succinct representation of the core content of the articles. These fields are of primary importance for indexing in academic databases, thereby ensuring a greater likelihood of identifying the literature most relevant to the research subject.

The search, conducted on February 5, 2024, encompassed the period from 1975 to 2023. This initial search yielded 279 records. Subsequently, the dataset was refined to include only peer-reviewed articles published in indexed journals up to December 31, 2023, to ensure a consistent timeframe for analysis. This refinement excluded 8 articles under review, 2 book chapters, 1 editorial, 1 meeting abstract, and 1 retraction. The final dataset comprised 266 documents, which have collectively garnered 1,938 citations.

Comments 9: Clearer discussion section, with better outlined theoretical and practical implications.

Response 9: We extend our sincere gratitude. The discussion section has been improved as proposed.

Comments 10: A reflection on the study's limitations and ways to overcome them in future research would be helpful.

Response 10: We extend our sincere gratitude. The suggested improvements have been incorporated into the discussion and conclusions section, taking into account the corresponding observation made in point No. 2.

Comments 11: Adding the statements regarding author contributions, conflicts of interest, data availability, and funding.

Response 11: We extend our sincere gratitude. The required section has been incorporated.

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

The manuscript explores the intersection between digital transformation and human resources, shedding light on the implications for organizational structure and employee capabilities. However, several aspects require significant revision to enhance clarity, coherence, and academic rigor.

Firstly, while the introduction discusses the complexity of digital transformation, it lacks a comprehensive review of existing literature and pertinent references that would better contextualize the research within the current academic landscape. A stronger foundation is critical for framing the study’s significance and relevance.

Secondly, the research design, while interesting, appears to lack specificity regarding the methodologies employed. The manuscript would benefit from a more detailed description of the bibliometric analysis methods, including the parameters used for data selection and filtering (lines 92-100). This approach will help strengthen the validity of the research design and allow readers to assess the reliability of the findings.

Further, the conclusions in the final section do not convincingly stem from the results presented. The connection between the results and the conclusions must be articulated more explicitly to facilitate a robust understanding (lines 340-353).

Lastly, I recommend discussing potential limitations and implications for future research more thoroughly. Addressing these aspects will lend depth to the analysis and propose valuable avenues for other scholars interested in this intersection. Additionally, revisiting the reference list to include more recent developments in the field can provide a broader and more contemporary perspective.

Summarizing, while the manuscript offers a promising contribution to the literature on digital transformation and human resources, it must undergo substantial revisions in these key areas. The article can significantly increase its impact and scholarly contribution by refining the introduction, enhancing methodological clarity, improving result presentation, and ensuring logical coherence between findings and conclusions.

Author Response

Comments 1: Firstly, while the introduction discusses the complexity of digital transformation, it lacks a comprehensive review of existing literature and pertinent references that would better contextualize the research within the current academic landscape. A stronger foundation is critical for framing the study’s significance and relevance.

Response 1: We extend our sincere gratitude. The articulation of the literature has been enhanced by incorporating key scholars, with consideration given to the impact of their contributions as indexed in WoS.

Given that competencies are an inherent attribute of individuals, it is crucial to examine the perceptions and responses of individuals regarding digital transformation (Teichert, 2019; Martínez-Peláez et al., 2023), including leaders and managers, who face the chal lenge of developing strategies that align with the evolving digital landscape (Berghaus y Back, 2016). Organizations that design flexible structures to achieve their strategy are better positioned to adapt to digital transformation (Teece et al., 2016; Verhoef et al., 2021).

In practical terms, one of the primary consequences is the automation of repetitive tasks, which implies prioritizing human capabilities such as creativity, empathy, judgment, intuition, interpersonal sensitivity, and problem-solving skills (Soto-Acosta, 2020).

Digital transformation entails a fundamental shift in how companies generate value, driven by a cultural change aligned with the organizational strategy, with the aim of pro viding agility to the organizational structure to respond effectively and efficiently to environmental challenges (Rogers, 2016).

In summary, the following authors have made significant contributions to the study of DT:

 

Author	Main Findings
Vial, et al., 2019	Digital transformation (DT) has become recognized as a strategic phenomenon, wherein technology constitutes only a component of a complex process enabling organizations to respond to potentially instantaneous environmental shifts, thereby generating alterations in value creation. This necessitates modifications to the organizational structure, organizational culture, leadership, and the competencies of personnel.
Hanelt et al.,2020	Ambiguity persists regarding the precise definition and scope of DT, although a clear correlation exists between DT and organizational change. These authors posit that DT is initiated by the integration of digital technology, thereby facilitating the evolution towards flexible organizational structures.
Hess et al., 2020	Strategy is paramount to the success of DT, thereby necessitating the engagement of managers. Managers are tasked with overseeing the application of DT strategies through the analysis of technology utilization, alterations in value creation, structural modifications, and financial considerations. The authors assert that the initial phases of DT implementation are characterized by a significant degree of uncertainty.
Verhoeff et al., 2021	Digital transformation (DT) is not an intrinsic objective but rather a multidisciplinary phenomenon occurring in response to changes induced by technology, encompassing three distinct stages: typification, digitization, and digital transformation. Each stage necessitates specific conditions with respect to digital resources, organization, structure, and metrics. Organizations that undertake DT enhance agility, establish networks, and facilitate information management.
Nadkarni et al., 2020	Digital transformation (DT) is a phenomenon underpinned by diverse theoretical foundations, for which there is limited quantitative empirical evidence. DT is enabled by technology but not determined by it. It is a construct comprising two primary dimensions: technology and actor. Furthermore, each dimension consists of several sub-dimensions. Within the technology dimension: change environment, technological capacity, value creation and capture, and market environment. Within the actor dimension: transformative leadership, managerial and organizational skills, culture, and work environment.
Ogrean et al., (2021)	Digital transformation (DT) encompasses the domain of digital technologies and their applications. Consequently, DT is not an ultimate goal but rather a means to attain digital economies, foster economic growth, enhance the quality of life, promote sustainable development, and ensure sustainability.

Table 1. Leading Authors in DT Research

There is a consensus that DT is as much about people as it is about technology (Erceg et al., 2022; He, 2023) in a change process that requires teams to move beyond habitual prac tices (Teece et al., 2016).

Comments 2: Secondly, the research design, while interesting, appears to lack specificity regarding the methodologies employed. The manuscript would benefit from a more detailed description of the bibliometric analysis methods, including the parameters used for data selection and filtering (lines 92-100). This approach will help strengthen the validity of the research design and allow readers to assess the reliability of the findings.

Response 2: We extend our sincere gratitude. The articulation of the literature has been enhanced by incorporating key scholars, with consideration given to the impact of their contributions as indexed in WoS. Furthermore, the justification for the methodology has been strengthened as previously suggested.

Data were retrieved from the Web of Science Core Collection (WoS) database, encompassing the SSCI, ESCI, SCI, BKCI-SSH, A&HCI, CPCI-SSH, BKCI-S, and CPCI-S indexes. The study focuses its search on the online database of the Web of Science (WoS), which is one of the most recognized and accepted platforms by the scientific community and by evaluation and research agencies.

The following search string was used, searching within the title, abstract, and author keywords (TS): TS=("Digital Transformation*") AND TS=("human resources" OR "people management" OR "personnel management" OR "human capital").

Within the realm of academic research on digital transformation, the application of the truncation symbol ("") to the term "Digital Transformation" is deemed essential to ensure the comprehensiveness of the search. This practice enables the inclusion of diverse terminological variations, thereby optimizing the identification of pertinent studies addressing the core concept of digital transformation (Hoods & Wilson, 2001).

Furthermore, when exploring the intersection of digital transformation and human capital management, the term "human resources" emerges as a central component. The search strategy is expanded by incorporating synonyms such as "people management," "personnel management," and "human capital," linked by the Boolean operator "OR." This measure is warranted by the terminological variations found in the literature and the necessity to cover diverse conceptual perspectives within employee management (Hoods & Wilson, 2001).

Lastly, within the context of bibliometric and scientometric studies, limiting the search to the title, abstract, and author keywords (TS) fields is grounded in their capacity to provide a succinct representation of the core content of the articles. These fields are of primary importance for indexing in academic databases, thereby ensuring a greater likelihood of identifying the literature most relevant to the research subject.

The search, conducted on February 5, 2024, encompassed the period from 1975 to 2023. This initial search yielded 279 records. Subsequently, the dataset was refined to include only peer-reviewed articles published in indexed journals up to December 31, 2023, to ensure a consistent timeframe for analysis. This refinement excluded 8 articles under review, 2 book chapters, 1 editorial, 1 meeting abstract, and 1 retraction. The final dataset comprised 266 documents, which have collectively garnered 1,938 citations.

Comments 3: Further, the conclusions in the final section do not convincingly stem from the results presented. The connection between the results and the conclusions must be articulated more explicitly to facilitate a robust understanding (lines 340-353).

Response 3: We extend our sincere gratitude. The rationale for the conclusion has been enhanced based on the aforementioned points.

Comments 4: Lastly, I recommend discussing potential limitations and implications for future research more thoroughly. Addressing these aspects will lend depth to the analysis and propose valuable avenues for other scholars interested in this intersection. Additionally, revisiting the reference list to include more recent developments in the field can provide a broader and more contemporary perspective.

Response 4: We extend our sincere gratitude. A more comprehensive account of the study's limitations has been incorporated, based on the aforementioned points.

Author Response File: Author Response.pdf

Round 2

Reviewer 2 Report

Comments and Suggestions for Authors

The paper can be published in the current form.