Statistical Predictors of Project Management Maturity

Round 1

Reviewer 1 Report

Minor comments
Line 33: 5,702 instead of 5,692
line 200: -3 instead of +3
line 301: add that each level has four questions
Figure 3: give also the proportions of Brazilian and Multinational companies for Manufacturing and Service
Line 353: explanation rate of 72% and eigenvalue equal to 0.95 (as given in line 361)

Major Comment
The survey is from 2010. Is it possible to fall back to a newer survey to compare it with the existing one? I would recommand to carry out a new survey and include the results of this survey in the paper.

 

Author Response

Dear Reviewer 1,

Thank you for your comments. All minor points have been addressed. Attending to the main point, a new survey was started, and as commented in the new last line of Conclusions, we hope to present the results of the new survey in a future work.

Reviewer 2 Report

Reject. Paper titled "Statistical Predictors of Project Management Maturity." Need an improvement in future submission, based on the following issues: lack of information in the methodology section, ambiguity in the comparison between PLS and other regression models, unconventional and uninformative graphical presentation of coefficients, unexplained principal component analysis and cluster analysis, and inadequate contextualization of the dendrogram and cluster analysis results.

 Maintaining a high standard of quality in scientific research articles is of utmost importance. However, the provided article exhibits several weaknesses that diminish its clarity and reliability. This comment critically evaluates these weaknesses and highlights the necessity for improvement in subsequent submissions.

Lack of Information in Methodology Section: The article lacks sufficient information in the methodology section, particularly in lines 286-288 where the comparison between PLS and other regression models is not adequately explained. This ambiguity raises doubts about the chosen methodology and weakens the validity of the comparison. It is crucial to provide a clear and comprehensive explanation of the methodology employed. There are no measures of the relevance of the model (R-squared measures, Predictive Accuracy, Variable Importance in Projection (VIP) Scores)

Unconventional and Uninformative Graphical Presentation of Coefficients: The article's graphical presentation of coefficients in the PLS model deviates from conventional practices and fails to provide informative value. A graphical representation should aid readers in understanding and interpreting the results. However, the unconventional approach adopted in this article hinders comprehension and diminishes the effectiveness of the graphical presentation.

Unexplained Principal Component Analysis and Cluster Analysis:The article briefly mentions principal component analysis and cluster analysis without providing adequate explanations in the methodology section. This omission creates confusion and prevents readers from understanding the rationale behind these analytical techniques. It is crucial to provide a comprehensive and clear explanation of these methodologies.

Inadequate Contextualization of Dendrogram and Cluster Analysis Results:The article lacks proper contextualization of the dendrogram and cluster analysis results, particularly in line 356-357. This omission makes it challenging to comprehend the significance of the results. Additionally, the coherence and contextualization of the mentioned information are unclear and need improvement.

 In conclusion, the provided article exhibits several weaknesses, including a lack of information in the methodology section, ambiguity in the comparison between PLS and other regression models, unconventional graphical presentation of coefficients, unexplained principal component analysis and cluster analysis, and inadequate contextualization of the dendrogram and cluster analysis results. Addressing these weaknesses and providing more clarity and transparency in future submissions is crucial to enhance the overall quality and impact of the research presented in the article.

Author Response

Dear Reviewer 2, 

Thank you very much for your comments. 

On the "lack of information in the methodology section, ambiguity in the comparison between PLS and other regression models", three new paragraphs and the new Table 6 were added to Section 3. 

On the "Unexplained Principal Component Analysis and Cluster Analysis" and "Inadequate Contextualization of Dendrogram and Cluster Analysis Results" new paragraphs and the new Table 7 were added to Section 4.2. 

Round 2

Reviewer 1 Report

The paper has been improved considerably and the critical remarks of the referees are addressed. Especially the research design is clearly stated and presented.
The referee suggests the publication of the paper.

Author Response

Thank you for your valuable comments and for your support of our work. 

Reviewer 2 Report

I would like to clarify my position regarding the manuscript's recent revision and my reservations about accepting the decision to reject it outright. While I wholeheartedly acknowledge the considerable improvements made to the manuscript, I remain uncertain about accepting the rejection without further consideration from a third reviewer.

The revisions made by the authors have undeniably demonstrated a significant effort in addressing the reviewers' comments and concerns. The explanations provided have been thorough and comprehensive, and I commend the authors for their hard work in this regard.

However, I still have reservations regarding the clustering technique employed in the study. Specifically, my main concern lies in the use of only clustering four variables which, I believe, is not a logical procedure for clustering.

Additionally, I would like to express my uncertainty regarding the aggregation method and distance measure used for clustering in the manuscript. Moreover, while I acknowledge the theoretical development presented in this second version, I believe that the primary focus should be placed on elucidating the rationale behind the chosen clustering methods, as other methods.

I kindly request that the manuscript be reconsidered for further evaluation by a third reviewer. 

Author Response

Thank you for your comments. In attendance to your suggestions, we added a new Table 8 on the clustering methods. With the new text, two new references wereradded: Dudoit & Fridlyand (2003) and Gelbard et al. (2007).