Quality Culture, Quality Management, and Organizational Performance: A Structural Model for the Manufacturing Sector
Round 1
Reviewer 1 Report
Comments and Suggestions for AuthorsThe article deals with the impact of quality culture (QC) and quality management (QM) on organizational performance (OP) in the manufacturing sector, which is a key issue in the era of digitization and Industry 4.0. The research method - modeling of structural equations for the analysis of the relationship between QC, QM and OP - was appropriately selected. Taking into account both financial (profit margin, ROA, ROE) and non-financial (innovation, customer satisfaction) ratios allows for a holistic assessment of organizational effectiveness. It can be concluded that the article makes an important contribution to research on quality management, especially in the context of the manufacturing industry. Nevertheless, there are some shortcomings:
- Limited generalizability of the results, however, this is indicated by the authors in the final conclusions as limitations of the study.
- Failure to take into account moderation variables - g. company size, level of automation or type of industry.
- Although the article uses primary and secondary data, a significant part of the analysis is based on the subjective opinions of respondents (Likert surveys). No triangulation of results through, for example, quality audits.
- The cited literature is not always the latest – some references date back to before 2010, despite dynamic changes in the area of quality management in recent years.
- The values of the model fit indicators (CFI, RMSEA) are given, but there is no detailed interpretation of their values in the context of the study.
Recommendations:
- Consider conducting research in a broader context (other sectors, different countries).
- Supplement the literature review with the latest research, m.in. on Quality 4.0.
- Analyze the impact of additional moderation variables
Author Response
Sustainability Editor and Reviewer 1
We sincerely appreciate the opportunity to review our article and the valuable comments provided by the reviewer. Below we detail the modifications made in response to each observation:
Responses to reviewer comments
- Consider reviewing the research in a broader context (other sectors, different countries).
Response: This suggestion has been incorporated into the “Limitations and Future Research” section. We recognize the importance of expanding the analysis to other sectors and countries to improve the generalizability of the findings. Future studies will aim to validate the proposed model in different industrial and geographical contexts.
- Complement the literature review with the latest research on Quality 4.0.
Answer: The literature review has been updated to include recent studies on Quality 4.0, emphasizing its role in modern quality management practices and its impact on organizational performance. This addition strengthens the theoretical basis of the study and aligns it with current research trends.
- Analyze the impact of additional moderating variables.
Response: We recognize the relevance of this suggestion. Given the need for additional data and deeper analysis, this aspect will be considered in future research. Expanding the study to include moderating variables will require further empirical exploration, which we plan to conduct in subsequent studies.
Reviewer 2 Report
Comments and Suggestions for AuthorsDear authors,
Please find attached my comments regarding your mansucript.
All the best,
Comments for author File: Comments.pdf
English proofreading is necessary to correct a number of errors.
Author Response
Editor of Sustainability and Reviewer 2
We appreciate the opportunity to revise our article titled "Quality Culture, Quality Management, and Organizational Performance: A Structural Model for the Manufacturing Sector", as well as the valuable comments from the reviewer. Below, we provide a detailed response to each of the observations and the corresponding modifications made to the manuscript:
Responses to the Reviewer's Comments
- Avoid including R² and β values in the abstract.
Response: The R² and β values have been removed from the abstract to improve clarity and align with the journal's formatting requirements. - Modify the keywords, as 5 out of 7 are repeated from the title.
Response: The keywords have been adjusted to avoid redundancies with the title, incorporating additional relevant terms to enhance the study's visibility. - Clearly explain the research gaps and study motivation in the introduction.
Response: The introduction has been expanded to include a more detailed description of the research gaps identified in the literature and the motivation behind the study. Additionally, research questions have been incorporated to better structure the problem under analysis. - Present the theoretical framework as a separate section and move the hypotheses to that section.
Response: A new section titled "Theoretical Framework" has been created, separating it from the introduction. The hypotheses have been moved to this new section and are preceded by a theoretical justification based on previous studies. - Include sources for the measurement scales used in the study.
Response: Specific references have been added in the "Materials and Methods" section to document the sources of the measurement scales used. - Provide more details on the sampling technique and process.
Response: The description of the sampling process has been expanded, specifying the type of sampling used, the criteria for selecting the sample, and the justification for its representativeness. - In the discussion section, provide a more comprehensive interpretation of the results, compare them with previous studies, and emphasize their theoretical and managerial implications.
Response: The discussion section has been strengthened with a more detailed analysis of the findings in relation to previous studies. Additionally, theoretical and managerial implications have been added, highlighting how the study contributes to the field of quality management and organizational performance. - Expand on the study's limitations and suggestions for future research.
Response: A more extensive section on study limitations and potential future research directions has been added, including the need to replicate the model in other sectors and regions. - Update Figure 5 to improve its visibility.
Response: Figure 5 has been enhanced with higher resolution and formatting adjustments for better readability. - Standardize the in-text citation format.
Response: The formatting of all in-text citations has been reviewed and corrected to align with the journal's guidelines. - Avoid including R², β, and p values in the discussion.
Response: The R², β, and p values have been removed from the discussion, ensuring that the interpretation of results focuses on their theoretical and practical significance. - Remove the optional note regarding the conclusions section (lines 506-508).
Response: The unnecessary note about the conclusions section has been removed. - Review and correct the manuscript's English.
Response: A thorough language review has been conducted, correcting errors and improving the fluency of the text.
We sincerely appreciate the valuable feedback from the reviewer, which has significantly improved our article. We remain available for any further comments and hope that the revised version meets the journal's standards.
Reviewer 3 Report
Comments and Suggestions for AuthorsFirst of all, I would like to thank the editor of the journal for giving me the opportunity to review this work, and secondly, I would like to congratulate the authors for their work on such an interesting topic. Below, I will present several suggestions to improve the paper for its possible publication in the journal:
- Regarding the use of the abbreviations QC, QM, and OP, I advise the authors that once each concept is explained in the theoretical framework, they could use the abbreviation throughout the rest of the text.
- The hypotheses appear in the introduction section, but the SEM model appears in the discussion section. My recommendation is to modify the structure so that the model to be tested is included in section 2 of the theoretical framework.
- Section 3 should be the materials and methods section, where there is repeated information that the authors should eliminate (lines 129-139) and rewrite that part. In the same section, KMO and Bartlett are mentioned, but the numbers that corroborate what is said in the text are missing.
- Table 1 is the correlation matrix of the variables that characterize the sample. It might be necessary to include a characterization of the sample in a table, not necessarily the correlations, as they do not provide much information for characterizing the sample.
- In Figures 2, 3, and 4, the information is illegible and in Spanish. As the figures are currently, we cannot know which indicators are being referred to, and in addition, in Figure 3, the data in the text do not match the mean values shown in the table. The same issue occurs with Figure 5, which is unreadable.
- In the section on the methodologies used (3.6), it is recommended that the authors rewrite it to present it in a more organized and easy-to-follow manner. It is advisable to explain in the EDA what the factorial analysis is used for and what is done with the factors afterward. The same applies to the relational analysis: what is it for? Does it complement the model you are conducting with SEM? Is it an additional analysis?
- The model used for SEM is in Spanish and appears in the Discussion section. It should appear in a Results section.
- The authors need to restructure the methodology section of the work so that they can present a good discussion of the results obtained and a conclusion that also includes limitations and future lines of research.
- Finally, I would like to reiterate my congratulations to the authors because it is a very interesting work that, with some modifications, can be publishable in the journal.
Author Response
We sincerely appreciate the opportunity to revise our article and the valuable feedback provided by the reviewer. Below, we present the modifications made to the manuscript in response to the observations:
The manuscript has been revised to ensure that the first mention of Quality Culture (QC), Quality Management (QM), and Organizational Performance (OP) includes the full terms in the Theoretical Framework section. After this initial definition, abbreviations are consistently used throughout the text.
The SEM model is now introduced in the Theoretical Framework section (Section 2), ensuring coherence in the theoretical development before moving to methodology and results. The hypotheses have also been moved to this section to provide a clearer justification based on previous literature.
The redundant information in Section 3 has been eliminated to improve clarity and conciseness. Additionally, numerical values for the KMO and Bartlett's tests have been included to provide proper statistical justification for the adequacy of the sample.
We have carefully reviewed this suggestion and believe that the correlation matrix provides essential information for understanding the relationships between key variables in our study. Given its relevance to the statistical analysis and findings, we have decided to retain the correlation matrix in the manuscript. Additionally, we considered including a separate table for the characterization of companies; however, since this characterization is based on Colombian legislation, we believe that it might not provide the same level of generalizable insights for an international audience. We hope that this decision will be accepted.
All figures have been updated to improve readability and resolution. Additionally, labels and captions have been translated into English to align with the journal’s guidelines. The inconsistencies between Figure 3 and the mean values in the table have been corrected. Figure 5 has been improved for better visualization.
Section 3.6 has been restructured to provide a more logical and organized explanation of the methodology. The role of Exploratory Data Analysis (EDA), relational analysis, and SEM has been clarified, specifying their purpose and contribution to the study. The relationship between these methods and the research objectives is now explicitly stated.
The SEM model figure has been translated into English, and its placement has been corrected. It now appears in the Results section, ensuring consistency in the manuscript structure.
The methodology section has been reorganized for better coherence, facilitating a stronger discussion of the results. Additionally, the conclusion has been expanded to explicitly address study limitations and propose future research directions, as suggested.
Round 2
Reviewer 2 Report
Comments and Suggestions for AuthorsThe authors have put significant effort into improving the manuscript; however, a few issues still need to be addressed:
A thorough interpretation of the study's findings is essential in the discussion section. The authors should clarify the implications of these findings and highlight their contributions to the field. Additionally, comparing the current results with previous research would help illustrate how this study advances existing knowledge.
Best regards,
Comments on the Quality of English LanguageEnglish proofreading is necessary to correct a number of errors.
Author Response
Dear Editor and Reviewer,
We sincerely appreciate the detailed and constructive feedback you have provided for our manuscript. Based on your comments, we have carefully revised the Discussion section to improve the interpretation of our findings, align them more explicitly with previous research, and emphasize their theoretical and managerial implications. Below, we describe the specific modifications made in response to the reviewer’s suggestions:
Improved Interpretation of Findings:
- We have expanded our analysis of financial and non-financial indicators, further explaining the implications of differences in profitability, operational efficiency, innovation, customer satisfaction, and organizational climate among manufacturing companies.
- Additional discussion has been included on the impact of structural challenges on business competitiveness, reinforcing how differentiated quality management strategies can address these disparities.
Comparison with Previous Research:
- We have strengthened the literature comparison by integrating recent studies that support our findings on the role of culture and quality management in organizational performance (1,8,5,4,16).
- The analysis now explicitly contextualizes our results within the framework of general systems theory (13), further highlighting how the integration of quality culture (CC), quality management (MG), and organizational performance (DES) aligns with previous empirical research (10,25,29).
Theoretical Contributions:
- We have placed greater emphasis on the role of quality control as a mediating variable, demonstrating how it amplifies the relationship between quality management and functional optimization. A more detailed explanation has been included on how our findings contribute to advancing the literature on quality management, particularly by validating the use of structural equation modeling (SEM) in this context.
- Our analysis now clarifies how our study extends previous works that have examined these constructs in isolation, providing a comprehensive empirical model that integrates them (18,25).
Managerial Implications:
- We have expanded the practical implications for manufacturing companies, detailing how Quality 4.0 technologies (big data, IoT, and AI) can be leveraged to improve decision-making, process optimization, and competitiveness (31,36-37).
- The analysis now includes a clearer explanation of how companies can implement quality control through structured quality management systems, in line with international standards such as ISO 9001:2015.
Clarification of Hypothesis Testing Results:
- The significance of hypotheses H1 to H4 has been further contextualized, linking them more explicitly with previous empirical findings and reinforcing their managerial relevance (17,34,32).
- Additional comments have been provided on the variance explained by quality management in OP (89.8%), highlighting its fundamental role in achieving sustainable organizational success.
We believe these revisions significantly enhance the clarity, depth, and impact of the Discussion section, addressing the reviewers' concerns regarding the interpretation of findings, alignment with previous research, and theoretical and practical contributions.
We sincerely appreciate the time and effort invested in reviewing our manuscript. Your valuable feedback has been instrumental in refining our study, and we hope that the revised version meets the journal’s expectations.
Please do not hesitate to let us know if any further modifications are required.
Best regards,
Author Response File: Author Response.pdf