Multi-Factor Cost Adjustment for Enhanced Export-Oriented Production Capacity in Manufacturing Firms
Round 1
Reviewer 1 Report
Comments and Suggestions for Authors1. The introduction should be improved to justify the study need, particularly in the context of Omen and the larger scientific community
2. The literature review is fine but it can be improved.
3a. The Methodology needs substantial work, consider other advanced modeling approaches besides the ordinary multiple linear regression (for instance, consider inclusion moderation, mediation, fixed effects, control variables, etc). The hypotheses can be improved on.
b. How are the predictor variables measured/quantified? Consider summarising these variables in a table format, and detail the data collection process.
c. The conceptual framework can be improved once suggestions in 3(a) are considered in the revision.
4. Analysis/Results
a. Two tables important to results interpretation should be considered. 1. The descriptive statistics and the correlation matrix tables.
c. Consider including the model robustness test/s and Goodness of fit test/s to determine model performance.
d. The graphs/diagrams seem a lot and offer no meaningful contribution. Consider minimizing, and if possible, consider eliminating them.
5 Discussion/Conclusion:
Implementation of the suggestions above will alter the discussion and conclusion sections
Comments on the Quality of English LanguageThe manuscript will benefit more from English language editing services.
Author Response
Comment.1: The introduction should be improved to justify the study need, particularly in the context of Oman and the larger scientific community
Response 1: Done. The study need is justified in the introduction, particularly in the context of Oman and the larger scientific community. We added an extra paragraph in the introduction section in red color.
Comment 2: The literature review is fine, but it can be improved.
Response.2: Done. The literature review section is extensively revised and improved. Additional paragraphs added in red color.
Comment 3: The Methodology needs substantial work, consider other advanced modeling approaches besides the ordinary multiple linear regression (for instance, consider inclusion moderation, mediation, fixed effects, control variables, etc). The hypotheses can be improved on.
Response 3. Done. Methodology is extensively revised and improved. Other approaches were performed such as moderation; control and fixed effect, which showed negative, affect the original MLRA. We added new paragraphs to the revised manuscript in red color.
Comment 4: How are the predictor variables measured/quantified? Consider summarising these variables in a table format, and detail the data collection process.
Response.4: Done. Table 1 is added, summarizing the predictor variables. We also added further details on the data collection process in red color.
Comment.5:The conceptual framework can be improved once suggestions in 3(a) are considered in the revision.
Response .5: Done. The conceptual framework is improved in the revised version. .
- Analysis/Results
Comment.6: Two tables important to results interpretation should be considered. 1. The descriptive statistics and the correlation matrix tables.
Response .6: Done. We added the descriptive statistics and the correlation matrix in Table 3 and Table 4 in the revised manuscript
Comment.7: Consider including the model robustness test/s and Goodness of fit test/s to determine model performance.
Response.7 Done. Model Robustness and Goodness of Fit are included in the analysis part in red color.
Comment.8: The graphs/diagrams seem a lot and offer no meaningful contribution. Consider minimizing, and if possible, consider eliminating them.
Response.8: We appreciate your comments. However, we believe that these visuals are essential for effectively illustrating the effects of variable adjustments on export growth, as outlined in our analysis. They contribute significantly to the comprehensibility of our findings.
5 Discussion/Conclusion:
Comment.9: Implementation of the suggestions above will alter the discussion and conclusion sections
Response.9: All suggestions are implemented in the revised manuscript.
Comments on the Quality of English Language
The manuscript will benefit more from English language editing services.
We revised the English language in the entire manuscript.
Reviewer 2 Report
Comments and Suggestions for AuthorsThis paper, adopting a corporate cost perspective, utilizes data from Omani manufacturing enterprises spanning the years 2012 to 2016. Through multivariate regression analysis, it reveals that raw material costs, labor force size, labor wages, and R&D expenditures all exert significant influences on export capabilities, which can be markedly enhanced through effective management of these factors. The conclusions drawn are practically significant; however, prior to publication, the following issues necessitate improvement:
1.To enhance the conciseness and focus of the abstract, it is advisable to reconstruct it, ensuring a clear exposition of the research background and objectives, prominently highlighting the core methodology employed, and strengthening the elaboration of key findings, thereby crafting a more succinct and theme-centric abstract.
2.The article should exhaustively elaborate on each specific contribution and is recommended to adopt an itemized approach to more fully demonstrate the profound value and unique importance of the research outcomes.
3.There exist several formatting deficiencies within the text, particularly at lines 181, 270, and 352 of the main body. Consequently, the author must rigorously adhere to academic norms and conduct a comprehensive review and revision of the manuscript to elevate the authenticity of the content and standardize the formatting.
4.Given that the data utilized in this paper covers a period from 2012 to 2016, these data have become somewhat outdated in the current academic context, posing a timeliness issue. Additionally, while the suggestions proposed at the end of the paper are highly insightful, they lack sufficient exploration and elaboration regarding their feasibility in actual policy implementation and potential cost-benefit analysis.
5.The research primarily focuses on the immediate impact of cost optimization on export capabilities, neglecting the potential long-term effects, such as those on corporate innovation, market adaptability, and sustainable development capabilities. These aspects deserve greater attention and discussion.
6.During model construction, a fundamental assumption is made that the relationships among variables are linear. However, in reality, these relationships might be more intricate, exhibiting nonlinear characteristics. For instance, increases in raw material and labor costs could lead to a decline in production efficiency through a series of complex mechanisms, ultimately exerting a profound influence on export capabilities. Therefore, the possibility of nonlinear relationships should be thoroughly considered during model development.
7.It is recommended that the author broaden the scope of references by incorporating more relevant materials from diverse fields, thereby enhancing the academic breadth and depth of the paper and ensuring comprehensive and integrated analysis. Specific literature that could be considered includes:
[1] Liu, Y., Li, Z., & Xu, M. (2020). The influential factors of financial cycle spillover: evidence from China. Emerging Markets Finance and Trade, 56(6), 1336-1350. doi: 10.1080/1540496x.2019.1658076
[2] Kamilu A. Saka, Yisau I. Bolanle. Autoregressive distributed lag estimation of bank financing and Nigerian manufacturing sector capacity utilization[J]. Quantitative Finance and Economics, 2023, 7(1): 74-86. doi: 10.3934/QFE.2023004
[3] Chong Li, Guoqiong Long, Shuai Li. Research on measurement and disequilibrium of manufacturing digital transformation: Based on the text mining data of A-share listed companies[J]. Data Science in Finance and Economics, 2023, 3(1): 30-54. doi: 10.3934/DSFE.2023003
Comments on the Quality of English LanguageMinor editing of English language required!
Author Response
Comment 1. To enhance the conciseness and focus of the abstract, it is advisable to reconstruct it, ensuring a clear exposition of the research background and objectives, prominently highlighting the core methodology employed, and strengthening the elaboration of key findings, thereby crafting a more succinct and theme-centric abstract.
Response.1: Done. Thanks for the advice.
Comment 2. The article should exhaustively elaborate on each specific contribution and is recommended to adopt an itemized approach to more fully demonstrate the profound value and unique importance of the research outcomes.
Response .2: Done. We itemized our contribution and demonstrated this clearly in the discussion section.
Comment 3.There exist several formatting deficiencies within the text, particularly at lines 181, 270, and 352 of the main body. Consequently, the author must rigorously adhere to academic norms and conduct a comprehensive review and revision of the manuscript to elevate the authenticity of the content and standardize the formatting.
Response.3: Done. All formatting deficiencies are corrected in the revised manuscript.
Comment 4. Given that the data utilized in this paper covers a period from 2012 to 2016, these data have become somewhat outdated in the current academic context, posing a timeliness issue. Additionally, while the suggestions proposed at the end of the paper are highly insightful, they lack sufficient exploration and elaboration regarding their feasibility in actual policy implementation and potential cost-benefit analysis.
Response.4: We acknowledge the timeliness issue of the data from 2012-2016. The data before and after this period was patchy and missing, making it difficult to use in the analysis. We also acknowledged the issue in the study limitation and recommendations for future research.
Comment 5. The research primarily focuses on the immediate impact of cost optimization on export capabilities, neglecting the potential long-term effects, such as those on corporate innovation, market adaptability, and sustainable development capabilities. These aspects deserve greater attention and discussion.
Response .5: We appreciate your view on the potential long-term impacts of cost optimization beyond immediate export capabilities. We agree that exploring dimensions such as corporate innovation, market adaptability, and sustainable development capabilities, will enrich the discussion and provide a more comprehensive understanding of the topic. However, due to the limited space here, we acknowledge these aspects as recommendations for future work, while staying focused on the immediate impacts of cost optimization on export capabilities in the current study.
Comment 6. During model construction, a fundamental assumption is made that the relationships among variables are linear. However, in reality, these relationships might be more intricate, exhibiting nonlinear characteristics. For instance, increases in raw material and labor costs could lead to a decline in production efficiency through a series of complex mechanisms, ultimately exerting a profound influence on export capabilities. Therefore, the possibility of nonlinear relationships should be thoroughly considered during model development.
Response.6: We agree that the assumption of linear relationships among variables is a fundamental aspect of our analysis. During the preliminary stages of our study, we indeed considered the possibility of nonlinear relationships. However, based on rigorous statistical evaluation, including tests for nonlinearity, the linear model demonstrated the best fit for our dataset. Regarding the intricate nature of real-world relationships, such as the potential nonlinear effects of raw material and labor costs on production efficiency and subsequently on export capabilities, we acknowledge these complexities. While our current study focuses on linear relationships to capture the immediate impacts of cost optimization on export capabilities, we recognize the importance of exploring nonlinear dynamics as a topic for future research. This approach may provide deeper insights into the mechanisms you highlighted. Thank you.
Comment 7. It is recommended that the author broaden the scope of references by incorporating more relevant materials from diverse fields, thereby enhancing the academic breadth and depth of the paper and ensuring comprehensive and integrated analysis. Specific literature that could be considered includes:
[1] Liu, Y., Li, Z., & Xu, M. (2020). The influential factors of financial cycle spillover: evidence from China. Emerging Markets Finance and Trade, 56(6), 1336-1350. doi: 10.1080/1540496x.2019.1658076
[2] Kamilu A. Saka, Yisau I. Bolanle. Autoregressive distributed lag estimation of bank financing and Nigerian manufacturing sector capacity utilization[J]. Quantitative Finance and Economics, 2023, 7(1): 74-86. doi: 10.3934/QFE.2023004
[3] Chong Li, Guoqiong Long, Shuai Li. Research on measurement and disequilibrium of manufacturing digital transformation: Based on the text mining data of A-share listed companies[J]. Data Science in Finance and Economics, 2023, 3(1): 30-54. doi: 10.3934/DSFE.2023003
Response .7: Done. References that are more relevant from diverse fields are added in the revised manuscript in Red color.
Comment 8: Comments on the Quality of English Language - Minor editing of English language required!
Response 8: We revised the English language in the entire manuscript.
Reviewer 3 Report
Comments and Suggestions for Authors1. Is the proposed paper focused on “export capacity” (title) or “export capability” (Figure 1, p.7)? In any case, it is recommended to neatly define the concept/s upfront.
2. It is not clear if the research focus is on “export capability” (Figure 1) or “export capabilities” (hypotheses, p.7)? If the second is the case, then these capabilities should be presented.
3. Paper Abstract states that “cost components such as raw material costs, labor force size and wages, and R&D spending enhance production efficiency”. To what extent does this statement stand? Is it related or necessary to sustain the main research focus? Discussion on this issue is recommended.
4. Literature Review section mentions “production capability in a competitive market” (line 153), which is closer to R&D efforts (measured by the cost associated). Therefore, it is suggested to analyse the possible use of the syntagm “export-oriented production capability/capacity” instead of “export capability/capacity’ in the research model (as being more feasible).
5. Noteworthy, Literature Review section (2.3, lines 201, 202) underlines the role of the “skilled labor” (measured by the associated cost). It is highly recommended to make the difference between the skilled labour (either size or wages) and the generic “labor” (regardless size or wages). Simply because a higher number of employees does not necessary mean higher performance.
6. Literature review section (2.3, lines 202–203) mentions that “skilled labor can have a beneficial impact on labor productivity within firms, ultimately contributing to their export capabilities” with no documentation. If the first part of the assessment could be accepted as business common sense, the second part of the assessment should be seriously documented (as part of the conceptual model building process).
7. The data are collected from “the database of the Ministry of Commerce, Industry and Investment Promotion, Sultanate of Oman” (pp.264–265); they include “key relevant variables selected for this study as raw materials cost, labor force, labor wages, and R&D spending” (pp.269–270). Unfortunately, these data are taken non-selectively (e.g., skilled labour related numbers).
8. There are four research hypotheses (p.7; Figure 1). It is suggested to revise the Literature Review section in such a manner that these hypotheses can conclude respective sub-sections.
9. The “labour force size” and “labour wages” are among cost components considered by author/s. To what extent are they independent? How can their interdependency influence the research results? Discussion on this issue is strongly recommended.
10. The construct proposed by author/s is that “dependent variable is export capacity and independent variables are raw materials cost, labor force, labor wages, and R&D spending” (pp.270–271). To what extent is this assumption valid? Argument (counter-example): higher costs lead to lower competitiveness on international markets. Discussion in this respect is highly recommended.
11. The paper is constructed on the assumption that cost components are independent variables and export capacity/capability is the resulting dependent variable. It is strongly recommended to demonstrate this causal chain (cause to effect) because the cause-effect analysis must precede the multiple regression analysis.
12. Assuming that R&D efforts (measured in their cost) have an impact on export capacity/capability, is the time factor considered (i.e. delay, time lag)? As compared to the research period (2012–2016) the value of this time lag might significantly impact the research results. This issue should be addressed.
13. The period under scrutiny is 2012–2016. The reasons for choosing this period should be highlighted (why 2012 is the start; why until 2016, etc.)
14. Currently (2024), 2023 data are available; therefore, a longer period under proper scrutiny would probably provide more valuable results. It is suggested to consider this option.
15. Paper title declares “cost optimization” but there is no cost function to be optimized. There are five scenarios presented only. Clarification is recommended.
16. Research focus is on Omani “manufacturing firms located in various industrial cities under the management of the Public Establishment for Industrial Estates” (pp.266–267). What about these firms? Some characteristics about them (essential for the study) should be provided.
17. The data collected are at macro-economic level (aggregate figures), while research discussion is at the micro-economic (company) level. This issue should be addressed.
18. In the same line of logics, essential data (number of firms analysed, number of observations, etc.) must be provided.
19. As the raw data collected are not presented, the calculations and the corresponding results displayed in sections 3 and 4 are rather difficult to be double checked.
20. Anyway, it is suggested to split section 3 (Research methodology) into Research methodology proper, and Results.
21. It is recommended to reformulate the phrases with ambiguous meaning; e.g., “It is noticed that to incrementally increase exports amount by 20%, reaching 200% …” (lines 377–378).
22. When discussing export activities, it is suggested to consider external influencing factors (export flows, demand of external markets), besides the internal factors (already discussed).
23. The author/s’ original contributions should be highlighted.
Comments on the Quality of English LanguageIt is recommended to reformulate the phrases with ambiguous meaning; e.g., “It is noticed that to incrementally increase exports amount by 20%, reaching 200% …” (lines 377–378).
Author Response
Comment 1. Is the proposed paper focused on “export capacity” (title) or “export capability” (Figure 1, p.7)? In any case, it is recommended to neatly define the concept/s upfront.
Response 1: Done. We focus mainly on export capacity. We amended the figure is amended and defined the concept in the revised manuscript.
Comment 2. It is not clear if the research focus is on “export capability” (Figure 1) or “export capabilities” (hypotheses, p.7)? If the second is the case, then these capabilities should be presented.
Response .2: Done. As stated in Q1, we amended the concept of export capability to export capacity for consistency.
Comment 3. Paper Abstract states “cost components such as raw material costs, labor force size and wages, and R&D spending enhance production efficiency”. To what extent does this statement stand? Is it related or necessary to sustain the main research focus? Discussion on this issue is recommended.
Response.3: Done. We amended the abstract. However, cost components are integral to our study, where the optimization of these costs can improve export capacity. Our research hypothesizes that optimizing cost components, namely raw material costs, labor force size and wages, and R&D spending, directly influences production efficiency, which, in turn, enhances export capacity. This hypothesis is based on economic and management theories that suggest efficient resource allocation and cost management are crucial for competitive advantage in international markets. Moreover, our findings suggest that each cost component—raw material costs, labor force size, labor wages and R&D spending—has a significant and positive impact on production efficiency and, consequently, export capacity. The statistical significance of these relationships is confirmed by low p-values and high t-statistics. Thus, optimizing these cost components can substantially enhance production efficiency, leading to improved export capacity.
Comment 4. Literature Review section mentions “production capability in a competitive market” (line 153), which is closer to R&D efforts (measured by the cost associated). Therefore, it is suggested to analyse the possible use of the syntagm “export-oriented production capability/capacity” instead of “export capability/capacity’ in the research model (as being more feasible).
Response.4. The suggestion is fully acknowledged and appreciated. To enhance the clarity and precision of the research focus, the term "export capacity" has been revised in RED colour to "export-oriented production capacity (EOPC)" throughout the manuscript. This revision aligns with the study's emphasis on optimizing cost components—specifically raw material costs, labor force size and wages, and R&D spending—to improve production efficiency and, consequently EOPC. This change is expected to provide a clearer understanding of the research scope and objectives, thereby improving the communication of the findings.
Comment 5. Noteworthy, Literature Review section (2.3, lines 201, 202) underlines the role of the “skilled labor” (measured by the associated cost). It is highly recommended to make the difference between the skilled labour (either size or wages) and the generic “labor” (regardless size or wages). Simply because a higher number of employees does not necessarily mean higher performance.
Response 5. We agree with this point. The differentiation between skilled and generic labor is crucial because merely increasing the number of employees does not necessarily lead to better performance. It's the quality, not the quantity, of labor that often drives productivity and competitiveness. This point has now been addressed in RED color in the revised literature review section.
Comment 6. Literature review section (2.3, lines 202–203) mentions that “skilled labor can have a beneficial impact on labor productivity within firms, ultimately contributing to their export capabilities” with no documentation. If the first part of the assessment could be accepted as business common sense, the second part of the assessment should be seriously documented (as part of the conceptual model building process).
Response .6. Done. This point has now been addressed in RED colour with the addition of relevant references; specifically the texts include empirical studies and theoretical foundations that substantiate the link between skilled labor and export performance.
Comment 7. The data are collected from “the database of the Ministry of Commerce, Industry and Investment Promotion, Sultanate of Oman” (pp.264–265); they include “key relevant variables selected for this study as raw materials cost, labor force, labor wages, and R&D spending” (pp.269–270). Unfortunately, these data are taken non-selectively (e.g., skilled labour related numbers).
Response 7: We appreciate your observation, but would like to stress that this database is huge and contain so many variables that are not important to our study. Thus, we confirm that we selected the data used in this study to fit with our research objectives with considerable care and accuracy.
The data underwent a particular cleaning process to ensure accuracy and relevance. This process involved rigorous validation and verification steps to guarantee that only pertinent and high-quality data were included in the study. The careful data cleaning process was crucial in aligning the dataset with the study’s objectives and ensuring that the data accurately represented the skilled labor force and other variables of interest.
The selection of variables, including raw materials cost, labor force, labor wages, and R&D spending, was guided by their relevance to the study’s objectives. Specifically, labor data included in the analysis were focused on skilled labor, as Oman, being one of the Gulf Cooperation Council (GCC) countries, is known for its distinct labor market dynamics. GCC countries often exhibit specialized labor characteristics due to their economic and developmental contexts.
To further substantiate the nature of the labor data, Oman’s labor market has been characterized by a significant emphasis on skilled labor, reflecting its investment in human capital development. This focus aligns with the broader GCC labor market trends, where skilled labor plays a crucial role in driving productivity and economic growth.
These clarifications are added in the revised manuscript in RED color.
Comment 8. There are four research hypotheses (p.7; Figure 1). It is suggested to revise the Literature Review section in such a manner that these hypotheses can conclude respective sub-sections.
Response 8. Done. The four hypotheses are now integrated in the revised Literature Review section, ensuring that each hypothesis is logically derived from the reviewed literature. In addition, a new sub-section titled "Hypothesis Development" in RED color is included.
Comment 9. The “labour force size” and “labour wages” are among cost components considered by author/s. To what extent are they independent? How can their interdependency influence the research results? Discussion on this issue is strongly recommended.
Response 9: Done. We discusses the independence and interdependency of “labour force size” and “labour wages in the revised manuscript. We also added a new paragraph to clarify the interdependency between labor force size and labor wages in RED color.
Comment 10. The construct proposed by author/s is that “dependent variable is export capacity and independent variables are raw materials cost, labor force, labor wages, and R&D spending” (pp.270–271). To what extent is this assumption valid? Argument (counter-example): higher costs lead to lower competitiveness on international markets. Discussion in this respect is highly recommended.
Response 10: We acknowledge your argument that higher costs can impact competitiveness in general. But, this study addresses this issue in the context of building export capacity. Our model includes raw materials cost, labor force, labor wages, and R&D spending as key independent variables because they collectively influence a firm’s ability to build, enhance and sustain its competitive edge in international markets. Higher costs can be mitigated through strategic investments in R&D and workforce development, which can lead to innovations and efficiencies that strengthen export capability. Therefore, while costs are a significant consideration, their effect on export capacity is moderated by the firm’s overall strategic approach to building and leveraging its capabilities. We believe that this understanding is crucial for accurately assessing export potential and developing effective strategies for international market success.
Comment 11. The paper is constructed on the assumption that cost components are independent variables and export capacity/capability is the resulting dependent variable. It is strongly recommended to demonstrate this causal chain (cause to effect) because the cause-effect analysis must precede the multiple regression analysis.
Response 11. We appreciating your suggestion. A causal chain analysis has been added in RED color to outlines the causal relationships between the independent variables (raw materials cost, labor force, labor wages, and R&D spending) and the dependent variable (export-oriented production capacity).
Comment 12. Assuming that R&D efforts (measured in their cost) have an impact on export capacity/capability, is the time factor considered (i.e. delay, time lag)? As compared to the research period (2012–2016) the value of this time lag might significantly impact the research results. This issue should be addressed.
Response 12. Thank you for pointing this out. The study does not account for the time lag between R&D expenditures and their impact on export performance, which could affect the results. This is a noted limitation, and future research should address this time lag to better understand the delayed effects of R&D investments on export capability.
Comment 13. The period under scrutiny is 2012–2016. The reasons for choosing this period should be highlighted (why 2012 is the start; why until 2016, etc.)
Response 13. The period 2012–2016 was determined by several factors:
(1) Oman enjoyed a relatively stable economic environment in Oman that provided a clear context for analysing the impact of selected variables on export performance.
(2) Extending the study beyond 2016 introduces potential complications due to significant changes in the economic landscape including the COVID-19 pandemic, fluctuating oil prices, fiscal reforms, and regulatory shifts that impacted on the performance of most companies.
(3) The data available between 2012 and 2016 were the most complete to use for analysis, while the data before and after this period was patchy and some statistics were missing.
(4) The Ministry did not conduct surveys in the years 2018, 2020, 2021, and 2022.
Comment 14. Currently (2024), 2023 data are available; therefore, a longer period under proper scrutiny would probably provide more valuable results. It is suggested to consider this option.
Response.14. The Ministry did not conduct surveys in the years 2018 (for technical reasons), 2020, 2021, and 2022 (due to the pandemic). Thus, our study focuses on 2012–2016 to ensure a more stable and accurate assessment. This suggest is not possible now, but further research can cover the period from 2017 onwards.
Comment 15. Paper title declares “cost optimization” but there is no cost function to be optimized. There are five scenarios presented only. Clarification is recommended.
Response 15 While the paper title refers to “cost optimization,” the study indeed employs a scenario-based approach to explore various cost strategies and identify the most effective combination for optimizing export growth. In our analysis, multiple scenarios were examined by varying individual and combined factors such as raw material costs, labor wages, labor force, and R&D spending to determine their impact on export performance. Each scenario was designed to reveal how changes in these variables influence export growth under different conditions. For instance, the results show that optimizing all variables together (Scenario 5) yields the most balanced approach for increasing exports, with cost adjustments in raw materials, labor wages, and labor force. This scenario demonstrates a significant improvement in export growth, while minimizing increases in costs compared to other scenarios (Table 6 and Figure 8). Thus, although a traditional cost function is not explicitly defined, our scenario analysis provides a practical framework for optimizing costs by identifying the best combination of variable adjustments to achieve the desired export outcomes. This approach effectively addresses the concept of cost optimization within the context of varying constraints and objectives.
Comment 16. Research focus is on Omani “manufacturing firms located in various industrial cities under the management of the Public Establishment for Industrial Estates” (pp.266–267). What about these firms? Some characteristics about them (essential for the study) should be provided.
Response 16. A summary of the characteristics of the firms investigated in this study is provided in RED into the revised manuscript under “Data collection” sub-section.
Comment 17. The data collected are at macro-economic level (aggregate figures), while research discussion is at the micro-economic (company) level. This issue should be addressed.
Response 17. All the data used are micro-economic level data as it was collected at the firm level. The ministry designed the questionnaire surveys and distributed to the manufacturing companies every year. The response of each company is individually recorded in the database. We collected the raw data, categorized, selected, cleaned, and processed it for analysis. Thus, this is a micro-economic data that fits well with our firm level analysis.
Comment 18. In the same line of logics, essential data (number of firms analysed, number of observations, etc.) must be provided.
Response18. As mentioned in the manuscript, the study analysed data from 200 manufacturing firms, with each firm contributing four annual observations (2012-2016), totaling 800 observations. The dataset includes key variables such as raw material costs, labor force, labor wages, and R&D spending. The data was meticulously cleaned to ensure accuracy and reliability in assessing export-oriented production capacity. A summary of variables and their measurements, detailing the type, measurement unit, data source, and a description of each variable was included in the text. Moreover, we added a new section titled “Descriptive Statistics of Variables” for more details.
Comment 19. As the raw data collected are not presented, the calculations and the corresponding results displayed in sections 3 and 4 are rather difficult to be double checked.
Response 19: The raw data is presented in Figure 2. Each variable versus the export capacity
Comment 20. Anyway, it is suggested to split section 3 (Research methodology) into Research methodology proper, and Results.
Response 20. Done. The Research Methodology is split into Research Methodology (section 3), and Analysis and Results (section 4).
Comment 21. It is recommended to reformulate the phrases with ambiguous meaning; e.g., “It is noticed that to incrementally increase exports amount by 20%, reaching 200% …” (lines 377–378).
Response 21. Done. All phrases with ambiguous issues were addressed.
Comment 22. When discussing export activities, it is suggested to consider external influencing factors (export flows, demand of external markets), besides the internal factors (already discussed).
Response 22. In this study, we focused on the internal factors like raw materials costs and labor wages within the manufacturing sector in Oman. We acknowledge the need to consider external factors such as export flows and market demand, which also affect export performance and suggest addressing them in future research.
Comment 23. The author/s’ original contributions should be highlighted.
Response 23. We highlighted the original contributions briefly in the introduction and more detailed in the “Discussion” section.
Comment 24. Comments on the Quality of English Language. It is recommended to reformulate the phrases with ambiguous meaning, e.g., “It is noticed that to incrementally increase exports amount by 20%, reaching 200% …” (lines 377–378).
Response 24. This point was rectified as mentioned in Answer No. 21. We revised the English language in the entire manuscript.
Reviewer 4 Report
Comments and Suggestions for AuthorsThe paper is well written with a sound research approach. However there are minor issues with concatenated text that need to be improved. For instance in Page 7 there is "Hypothesis2" that should be written as "Hypothesis 2" with a space in between the two. So, I would recommend to the authors to check these minor issues in the paper.
Author Response
Comment 1: The paper is well written with a sound research approach. However, there are minor issues with concatenated text that need to be improved. For instance, in Page 7 there is "Hypothesis2" that should be written as "Hypothesis 2" with a space in between the two. So, I would recommend to the authors to check these minor issues in the paper.
Response 1: Thank you for your kind evaluation. The entire manuscript has been revised and all minor issues have been addressed and highlighted in red color.
Round 2
Reviewer 1 Report
Comments and Suggestions for AuthorsThere is an improvement from the previous work. However, I have the following concerns:
1. About the hypotheses, it would be beneficial to single out the type of influence [e.g. positive, negative, none, mediating, moderating, etc.]
2. The model could benefit from the inclusion of other types of variables or modifying the same. For instance, I had previously suggested considering at least one or more different variables [like a mediator, moderator, control variable, etc if more data is available] to enhance the model. If it should remain so, consider adding more predictors. (Check point 6).
3. The current regression equation is of a general form that was supposed to be built on by (a) developing a specific equation with study variables (b) The Y, Xs, alphas, betas, and noise are not assigned appropriately or explained.
4. Table 2 shows the results, however, there is no explanation of these figures in the related chapters explaining what they mean or stand for. It would make the results section better if this were to be considered.
5. There is a mix up in the results section, for instance, Table 3 on Descriptive Statistics and Correlation Matrix should come before Table 2 on the results. In addition,
(a). Table 3 results raise statistical questions on data preprocessing and analysis. For instance what/where are the VIF, multicollinearity, skewness, etc results? Was data standardized or normalized to reduce the value size? Consider revisiting multiple regression assumptions to ensure the results are statistically reliable.
(b). The correlation matrix is a mirror image of one output. Consider the diagonal format.
(c). Consider merging tables (3) and (4).
(d). Explain the output in Table 6 to avoid assumptions on the reader's part.
(e). Limit the number of graphs to the most necessary (2-3) and consider changing their presentation.
6. (a) Goodness of fit test results are detailed in the paragraphs, consider including a table to support that position and reveal fitness level.
(b). Sections (4.2.1) and (4.2.2) state that Moderating and Dummy variables are included in the regression model, respectively. The model and results output do not support the assertions. Please make this clearer by reviewing the regression model and results. I suggested the inclusion of these variables and still suggest their inclusion to make the model better.
Comments on the Quality of English Language
Minor revision but an expert or language software use is advisable.
Author Response
Comment 1: About the hypotheses, it would be beneficial to single out the type of influence [e.g. positive, negative, none, mediating, moderating, etc.]
Response 1: Thank you for this suggestion. The type of influence for each variable is assigned in Green color in the revised text.
Comment 2: The model could benefit from the inclusion of other types of variables or modifying the same. For instance, I had previously suggested considering at least one or more different variables [like a mediator, moderator, control variable, etc if more data is available] to enhance the model. If it should remain so, consider adding more predictors. (Check point 6).
Response 2: Thank you for this suggestion, moderating variables and interactions terms are considered into the revised manuscript in green color.
Comment 3: The current regression equation is of a general form that was supposed to be built on by (a) developing a specific equation with study variables (b) The Y, Xs, alphas, betas, and noise are not assigned appropriately or explained.
Response 3: Thank you for this suggestion, a specific equation includes the dependent and independent variables is developed with appropriate definition for the equation terms highlighted in green color in the revised manuscript.
Comment 4: Table 2 shows the results, however, there is no explanation of these figures in the related chapters explaining what they mean or stand for. It would make the results section better if this were to be considered.
Response 4: Thank you for this suggestion. The results are now explained in detail below Table 2 and highlighted in green color.
Comment 5: There is a mix up in the results section, for instance, Table 3 on Descriptive Statistics and Correlation Matrix should come before Table 2 on the results.
Response 5: Thank you for this suggestion. Descriptive Statistics and Correlation Matrix relocated to be before Table 2.
Comment 5a: Table 3 results raise statistical questions on data preprocessing and analysis. For instance, what/where are the VIF, multicollinearity, skewness, etc results? Was data standardized or normalized to reduce the value size? Consider revisiting multiple regression assumptions to ensure the results are statistically reliable.
Response 5a: The evaluation of Multicollinearity and Distribution Characteristics are now added in green color .
Comment 5b: The correlation matrix is a mirror image of one output. Consider the diagonal format.
Response 5b: Thank you for this suggestion. We have considered the diagonal format in the correlation matrix.
Comment 5c: Consider merging tables (3) and (4).
Response 5c: Done. thank you.
Comment 5d: Explain the output in Table 6 to avoid assumptions on the reader's part.
Response 5d: Thank you for this suggestion, Table 6 is now explained in in green color in the revised manuscript, while further explanation and discussion is presented in 5.1 “Analysis of Input Variation Scenarios”.
Comment 5e: Limit the number of graphs to the most necessary (2-3) and consider changing their presentation.
Response 5e: Thank you for this suggestion, The number of graphs are minimized to the necessary ones only.
Comment 6a: Goodness of fit test results are detailed in the paragraphs, consider including a table to support that position and reveal fitness level.
Response 6a: Thank you for this suggestion. A table included a summary of Goodness of Fit, Multicollinearity, and Residual Analysis Results was added in green color in the revised manuscript.
Comment 6b: Sections (4.2.1) and (4.2.2) state that Moderating and Dummy variables are included in the regression model, respectively. The model and results output do not support the assertions. Please make this clearer by reviewing the regression model and results. I suggested the inclusion of these variables and still suggest their inclusion to make the model better.
Response 6b: Thank you for this suggestion. We revised the model and results output in the revised manuscript in green color. The results output are shown in the preliminary MRA and Simplified MRA.
The manuscript has been revised and improved.
Thank you.
Reviewer 3 Report
Comments and Suggestions for Authors(i) The reviewer acknowledges the efforts made by the author/s, who adjusted the title of their paper (former #1 & #2); unfortunately, they failed to properly define the term “export capacity” as well as newly accepted term “export-oriented production capacity” (EOPC). In addition, they do not provide a clear conceptual model (including a graphical scheme) associated to their study.
(ii) (former #3) The author/s have turned their claim (Abstract) from “cost components such as raw material costs, labor force size and wages, and R&D spending enhance production efficiency” to “each cost component—raw material costs, labor force size, labor wages and R&D spending—has a significant and positive impact on production efficiency …”, which might be true; unfortunately, there is no cost optimization function provided (as promised in the title), and no indicator of production efficiency considered – in order to support their claim.
(iii) In addition: if the author/s prefer scenario-based analysis instead of optimization (re: former #15) then the proposed paper must acknowledge it across the board (including title, keywords, all responses and explanations provided, etc.)
(iv) (former #3 and #4) The author/s revised claim is that study's emphasis is “on optimizing cost components—specifically raw material costs, labor force size and wages, and R&D spending—to improve production efficiency and, consequently EOPC [export-oriented production capacity]”. Unfortunately, there is no optimization function provided, and no indicator of production efficiency or export-oriented production capacity considered and provided – in order to support their claim.
(v) (former #5, #6 and #7) The author/s acknowledged this point in the literature review part; unfortunately, they made no change in the data collected and their quantitative study.
(vi) (former #9 and #10) The author/s acknowledged that two variables (labour force size and wages) are inter-dependent; unfortunately, they persist in their construct of “independent variables”.
(vii) (former #12, #13 and #14) The author/s have provided valid arguments for the relatively short and outdated scrutinized period (2012–2016). Nevertheless, the failure to consider the natural delay (time-lag) significantly influences the value of their study as well as the readership’s interest.
(viii) Overall comment (including former #8, #11, #17, #18, #19 and other related): The proposed paper is based on a confusing assumption:
While (export-oriented) production capacity can be the reflection of internal factors (counted by author/s), the exported amounts hardly could - because they are mostly the consequence of external factors (international markets demand, etc.) Direct consequence: failure to conduct proper cause effect analysis.
Comments on the Quality of English LanguageFair English language quality
Author Response
Comment 1: The reviewer acknowledges the efforts made by the author/s, who adjusted the title of their paper (former #1 & #2); unfortunately, they failed to properly define the term “export capacity” as well as newly accepted term “export-oriented production capacity” (EOPC). In addition, they do not provide a clear conceptual model (including a graphical scheme) associated to their study.
Response 1: Thank you for this comment, The definition of both terms “export capacity” and “export-oriented production capacity” (EOPC) are stated defined and explained in the introduction and highlighted in green color in the Revised Manuscript. Also, the revised conceptual model with graphical scheme is added in the text.
Comment 2: (former #3) The author/s have turned their claim (Abstract) from “cost components such as raw material costs, labor force size and wages, and R&D spending enhance production efficiency” to “each cost component—raw material costs, labor force size, labor wages and R&D spending—has a significant and positive impact on production efficiency …”, which might be true; unfortunately, there is no cost optimization function provided (as promised in the title), and no indicator of production efficiency considered – in order to support their claim.
Response 2: Thank you for this suggestion. This is addressed as the scenario-based analysis is considered in the manuscript instead of optimization; accordingly, adjust rather than optimize is added in green color in the revised manuscript.
Comment 3: In addition: if the author/s prefer scenario-based analysis instead of optimization (re: former #15) then the proposed paper must acknowledge it across the board (including title, keywords, all responses and explanations provided, etc.)
Response 3:: Thank you for this comment. The scenario-based analysis is acknowledged in the entire manuscript instead of optimization, as suggested. We used word "Adjustment" instead if "optimization" in green color in the revised manuscript.
Comment 4: (former #3 and #4) The author/s revised claim is that study's emphasis is “on optimizing cost components—specifically raw material costs, labor force size and wages, and R&D spending—to improve production efficiency and, consequently EOPC [export-oriented production capacity]”. Unfortunately, there is no optimization function provided, and no indicator of production efficiency or export-oriented production capacity considered and provided – in order to support their claim.
Response 4: Thank you for this comment. As explained above, this has been addressed, with scenario-based analysis replacing optimization in the entire manuscript, as suggested.
The current analysis considered production efficiency and export-oriented production capacity through five different scenarios. Each scenario explored specific cost adjustments to achieve a 20% increase in exports, reflecting varying levels of efficiency and capacity under different market conditions.
Among these scenarios, the fifth scenario was identified as the most balanced and favourable approach. This scenario involved a combined increase in Raw Material Cost (RMC) by 15%, Labor Wages (LW) by 13%, Labor Force (LF) by 20%, and Research and Development (R&D) spending by 30% under neutral market conditions. This balanced mix of cost adjustments indicates an efficient use of resources to enhance production capacity and support export growth.
Under favorable conditions, the required increases are significantly lower: 5% for RMC, 4% for LW, 10% for LF, and 14% for R&D. This reflects improved production efficiency, where smaller investments can yield substantial export growth. Conversely, under unfavorable conditions, the required increases are much higher: 35% for RMC, 24% for LW, 50% for LF, and 50% for R&D, highlighting the challenges in maintaining efficiency and capacity in adverse markets.
The fifth scenario demonstrates a strategic approach to cost management, optimizing resource allocation to achieve sustainable export growth across various market conditions.
The revised analysis is added in green color the revised manuscript.
Comment 5: (former #5, #6 and #7) The author/s acknowledged this point in the literature review part; unfortunately, they made no change in the data collected and their quantitative study.
Response 5: We appreciate your concern. However, as mentioned earlier that the data underwent rigorous cleaning and validation to ensure accuracy and relevance, focusing on SKILLED LABOR, raw material costs, labor wages, and R&D spending, pertinent to our study's objectives. Given the high quality and thorough validation of the data, no changes are needed in the collected data or the quantitative analysis. The current dataset provides a robust foundation for our conclusions.
Comment 6: (former #9 and #10) The author/s acknowledged that two variables (labour force size and wages) are inter-dependent; unfortunately, they persist in their construct of “independent variables”.
Response 6: Thank you for this comment. This is now addressed. The inter-dependency is considered into the model as an interaction term between the Labor wage and Labor force (LW x LF) in the revised model in green color in the Revised Manuscript.
Comment 7: (former #12, #13 and #14) The author/s have provided valid arguments for the relatively short and outdated scrutinized period (2012–2016). Nevertheless, the failure to consider the natural delay (time-lag) significantly influences the value of their study as well as the readership’s interest.
Response 7: We acknowledged this limitation at the study limitation section and that we do not account for the time lag between R&D expenditures and their impact on export performance. We do not believe that this issue would influence the value of the study. Future research can address this gap by incorporating the delayed effects of R&D investments and considering external factors such as export flows and market demand to provide a more comprehensive analysis of export growth dynamics.
Comment 8: Overall comment (including former #8, #11, #17, #18, #19 and other related): The proposed paper is based on a confusing assumption: While (export-oriented) production capacity can be the reflection of internal factors (counted by author/s), the exported amounts hardly could - because they are mostly the consequence of external factors (international markets demand, etc.) Direct consequence: failure to conduct proper cause effect analysis.
Response 8: We appreciate the mentioned feedback and understand the concerns regarding the analysis. We would like to confirm that our argument and framework primarily focuse on internal factors—such as raw materials cost, labor force, labor wages, and R&D spending—and their impact on export-oriented production capacity. We also recognize that export amounts could be influenced by other external factors like international market demand.
In response to the reviewer's comment, we have expanded our analysis to include the moderating role of market conditions (as external factor). We now discuss how varying market conditions can influence the effectiveness of internal factors on export-oriented production capacity. For instance, in favorable market conditions, the positive effects of a large labor force, competitive labor wages, and R&D spending might be magnified, leading to greater export capacity. Conversely, in less favorable market conditions, these effects might be diminished.
This approach highlights the varying impact of internal factors under different market conditions and aligns with empirical evidence suggesting that firms with lower raw material costs, higher R&D investment, and competitive labor wages tend to exhibit better export performance.
We agree that a comprehensive view of export performance would benefit from incorporating both internal and external factors. Therefore, the revised manuscript includes a the external factor (market condition) as well as a recommendation for future research to address more external factors .
English language has been revised and improved.
Thank you for the feedback.
Round 3
Reviewer 1 Report
Comments and Suggestions for AuthorsAs authors, you have put in so much based on the previous suggestions.
(How is MC quantified/measured as it is not explicitly indicated in Table 1? A reader may think it is the predictors under it in the Conceptual Framework)
1. The hypotheses should be stated once and if possible, each with its related literature review (as with the first hypothesis). Consider removing the second set of hypotheses after the conceptual framework (probably it may be beneficial to check on the CF positioning).
2. Consider revising your conceptual framework. Given that MC is the moderator based on your hypotheses and Table 4 output, it has to be between (LF, LW, RMC, R&D) and the dependent variables (explained in subsequent points). LF and LW then influence the output variable in two ways (a) Each separately & directly influences the dependent variable (b) Each separately and indirectly influences the EC through moderation by MC [first level moderation], (b) the LF & LW interaction influences EC through MC moderation [second level moderation] or (c) LF & LW interaction influences EC without the intervention of MC.
4. Standardize the descriptive statistics to make the values comparable and meaningful (standardize/normalize/transform/scale). For instance, the Mean has a high of [24,000,000] and a low of [8047] leaves several questions on the statistical soundness of the model. The correlation matrix values are well put.
5. Combine tables with related statistics 3, 4 & 6 (except Goodness of fit test). For the Goodness of Fit tests, there are quite a number, choose one that best suits your study.
5. Table 4 results, MC (coefficient & Std error), (MC * LF) has a high Std error. Could this be addressed by variable standardization/normalization etc previously raised?
6. Table 7 is unnecessary, these are best discussed in a paragraph format.
Comments on the Quality of English Language
Minor to moderate editing required
Author Response
As authors, you have put in so much based on the previous suggestions.
(How is MC quantified/measured as it is not explicitly indicated in Table 1? A reader may think it is the predictors under it in the Conceptual Framework)
Market Condition (MC) is a moderator in our study, not a predictor.
Comment 1: The hypotheses should be stated once and if possible, each with its related literature review (as with the first hypothesis). Consider removing the second set of hypotheses after the conceptual framework (probably it may be beneficial to check on the CF positioning).
Response 1: the second set of hypotheses after the conceptual framework was removed
Comment 2: Consider revising your conceptual framework. Given that MC is the moderator based on your hypotheses and Table 4 output, it has to be between (LF, LW, RMC, R&D) and the dependent variables (explained in subsequent points). LF and LW then influence the output variable in two ways(a) Each separately & directly influences the dependent variable (b) Each separately and indirectly influences the EC through moderation by MC [first level moderation], (b) the LF & LW interaction influences EC through MC moderation [second level moderation] or (c) LF & LW interaction influences EC without the intervention of MC.
Response 2: The conceptual framework was totally revised as suggested
Comment 3: Standardize the descriptive statistics to make the values comparable and meaningful (standardize/normalize/transform/scale). For instance, the Mean has a high of [24,000,000] and a low of [8047] leaves several questions on the statistical soundness of the model. The correlation matrix values are well put.
Response 3: The data has been standardized in blue color in the revised manuscript
Comment 4: Combine tables with related statistics 3, 4 & 6 (except Goodness of fit test). For the Goodness of Fit tests, there are quite a number, choose one that best suits your study.
Response 4: While I understand the suggestion to combine tables 3, 4, and 6, I believe that keeping these tables separate is important for maintaining the clarity and flow of the study's output. Each table addresses distinct aspects of the analysis, and presenting them separately ensures that each aspect is highlighted appropriately and supports a comprehensive understanding of the results. Regarding the Goodness of Fit tests, all the tests conducted are relevant to our study, as each provides valuable insights into different aspects of the data. Given that they all align with the study's objectives, it is crucial to present the results from each test to offer a complete picture of the model's fit.
Comment 5: Table 4 results, MC (coefficient & Std error), (MC * LF) has a high Std error. Could this be addressed by variable standardization/normalization etc previously raised?
Response 5: Since the terms Market Condition (MC) and MC×LF are not significant in the analysis and excluded from the final model, standardizing these variables may not be beneficial. The focus is on the significant variables and interactions, as outlined in the revised model. Simplifying the model by excluding non-significant terms provides a clearer understanding of the key factors affecting export capacity.
Comment 6: Table 7 is unnecessary; these are best discussed in paragraph format.
Response 6: The discussion of the hypotheses is indeed covered in the paragraph format in section 4.6. However, the inclusion of Table 7 was requested by other reviewers for clarity and ease of reference. To accommodate both preferences, we will retain Table 7 alongside the paragraph discussion to ensure comprehensive coverage and accessibility of the results.
Thank you very much.
Reviewer 3 Report
Comments and Suggestions for Authors1. Despite making clear differentiation between EC (export capacity) and EOPC (export-oriented production capacity)–per 1. Introduction (p.2, lines 38–51)–the confusion persists: the title displays “EC”, while Abstract and content keep up with “EOPC”. This ambiguity continues to remain unaddressed.
2. In addition, these definitions and statements associated have no references associated. It is suggested to have.
3. The author/s’ arguments that “model's adjusted R² value indicates a strong fit, showing that the independent variables account for a substantial proportion of the variance in production capacity” (Abstract, lines 21–22) might be true for “production capacity” BUT NOT for “export capacity” unless all production is exported (which is not the case, anyway). Reconsidering the logics of conceptual model is highly recommended.
4. The author/s agreed with the reviewer’s comment that labour force size and labour wages are not independent. However, Table 1 declares them–erroneously–as independent variables. Coherent formulations are recommended.
5. The assertion that MC (market conditions) is a moderator that “affect the relationship between these [cost] factors and export-oriented production capacity” (pp.10–11, lines 488–490) is in contradiction with Figure 1 (where MC looks like an independent variable that impacts cost factors). Coherence is highly recommended across the paper.
6. In addition, the newly introduced variable MC (p.10, lines 460–472) is too complex (although author/s admits it in sub-section 2.3) to be considered as a unique variable in the model. It is too general (not specific) and an extreme simplification for such complex international environment, both in space and time. Reconsideration is strongly recommended.
7. The author/s rightly acknowledged that “lack of detailed understanding obstructs the ability to develop a comprehensive model for production capacity improvement and export capacity building” (p.8, lines 349–351), and may be right to claim that their study “aims to address this gap by focusing on the specific impact of each cost component on production capacity” (ibidem, lines 351–352). Unfortunately, extending this conclusion over “export capacity” (“thereby providing a strong insight into how these factors contribute to export capacity”, lines 352–353) is dubitable. Coherent logic is necessary.
8. The time lag (delay) is acknowledged by author/s but it is not considered at all, which is a critical shortcoming. This phenomenon considerably impacts the validity of the research results for multiple reasons: it is significant in case of R&D efforts/costs, at least; it varies case-by case, R&D project-by-project; it may be comparable with the relatively short period under scrutiny (2012–2016).
9. It is recommended to reconsider and redesign Figure 1, because there are unexplained and/or confusing box contents (e.g., production efficiency, production cost, export-oriented production capacity; export volumes, competitive pricing, export capacity).
10. There are many referenced paragraphs which are not much connected to the research topic (e.g., several sentences in section 1. Introduction; p.5, lines 206–2012, etc.); filtering the references, and keeping only ones strictly related to the research topic is suggested.
11. Conversely, there are statements which are not documented (e.g., p.10, lines 473–476), if not plainly wrong (e.g., “our investigation is essential to contribute to the creation of new frameworks and methods that help firms […] overcome trade barriers” (p.3, lines 135–137). Reformulations are recommended.
12. Overall comment: It is regrettable that newly inserted paragraphs not only fail to solve all conceptual and methodological shortcomings (repeatedly signaled in previous review rounds), but also display new (truly, minor) inadequacies: e.g., “statical” (Abstract, line 15); acronym EOPC (Abstract, line 16) not defined upfront; etc.
Comments on the Quality of English LanguageMinor spelling errors.
Author Response
Comment 1: Despite making clear differentiation between EC (export capacity) and EOPC (export-oriented production capacity)–per 1. Introduction (p.2, lines 38–51)–the confusion persists: the title displays “EC”, while Abstract and content keep up with “EOPC”. This ambiguity continues to remain unaddressed.
Response 1: Thank you. The inconsistency between the title and the terminology used in the abstract and content has been addressed. We revised the title to use "Export-Oriented Production Capacity" (EOPC) instead of "Export Capacity" (EC) and consistency maintained throughout the manuscript.
Comment 2: In addition, these definitions and statements associated have no references associated. It is suggested to have.
Response 2: We added references to support the definitions.
Comment 3: The author/s’ arguments that “model's adjusted R² value indicates a strong fit, showing that the independent variables account for a substantial proportion of the variance in production capacity” (Abstract, lines 21–22) might be true for “production capacity” BUT NOT for “export capacity” unless all production is exported (which is not the case, anyway). Reconsidering the logics of conceptual model is highly recommended.
Response 3: Thank you. We understand the concern regarding the use of “production capacity” versus “export capacity” in our arguments. Since the study exclusively focuses on export-oriented production capacity, we clarified in the abstract that the model’s adjusted R² value reflects the fit for export capacity, as all production analyzed in this study is EXPORT-ORIENTED. We also revisited the conceptual model to ensure that the discussion was accurately represented.
Comment 4: The author/s agreed with the reviewer’s comment that labour force size and labour wages are not independent. However, Table 1 declares them–erroneously–as independent variables. Coherent formulations are recommended.
Response 4: Thank you. We have agreed with the reviewer that labor force size (LF) and labor wages (LW) may not be fully independent in a theoretical or logical sense. To address this concern, we conducted a correlation matrix analysis between LF and LW to assess their level of interdependency. The correlation coefficient was found to be 0.6, which indicates no significant correlation between these variables. Therefore, the statistical output should be followed, not the logical sense.
For further exploration, we included an interaction term between LF and LW in our model to capture any combined effects these variables might have on the outcome. However, the results indicated that the interaction term did not significantly impact the model's output, suggesting that while LF and LW are related, their combined effect does not introduce meaningful interdependency within the context of our analysis. Consequently, LF and LW should remain in Table 2 as independent variables, supported by the correlation matrix results.
Comment 5: The assertion that MC (market conditions) is a moderator that “affect the relationship between these [cost] factors and export-oriented production capacity” (pp.10–11, lines 488–490) is in contradiction with Figure 1 (where MC looks like an independent variable that impacts cost factors). Coherence is highly recommended across the paper.
Response 5: Thank you. The conceptual model framework was totally revised to address this comment.
Comment 6: In addition, the newly introduced variable MC (p.10, lines 460–472) is too complex (although author/s admits it in sub-section 2.3) to be considered as a unique variable in the model. It is too general (not specific) and an extreme simplification for such complex international environment, both in space and time. Reconsideration is strongly recommended.
Response 6: We appreciate the concern about the complexity of the Market Condition (MC) variable. However, we believe that the MC variable effectively captures the moderating effects of external factors on export capacity in a manageable and interpretable way. The scale (1-10) is designed to reflect varying market conditions without overcomplicating the model. Importantly, this assumption was validated by the statistical analysis output, which supports the inclusion of MC in our model. That said, we acknowledged the complexity of market conditions and recommended that this is an area worthy of further exploration in future research.
Comment 7: The author/s rightly acknowledged that “lack of detailed understanding obstructs the ability to develop a comprehensive model for production capacity improvement and export capacity building” (p.8, lines 349–351), and may be right to claim that their study “aims to address this gap by focusing on the specific impact of each cost component on production capacity” (ibidem, lines 351–352). Unfortunately, extending this conclusion over “export capacity” (“thereby providing a strong insight into how these factors contribute to export capacity”, lines 352–353) is dubitable. Coherent logic is necessary.
Response 7: The paragraph was rephrased in blue color in the revised manuscript. The logical flow is improved by clearly distinguishing between the study's primary contributions and its exploratory insights.
Comment 8: The time lag (delay) is acknowledged by author/s but it is not considered at all, which is a critical shortcoming. This phenomenon considerably impacts the validity of the research results for multiple reasons: it is significant in case of R&D efforts/costs, at least; it varies case-by case, R&D project-by-project; it may be comparable with the relatively short period under scrutiny (2012–2016).
Response 8: We stated clearly that the time lag was not considered in our analysis due to the short period under examination. We also believe that this does not affect our results. However, we acknowledged this concern and suggested incorporating the time lag between R&D expenditures and export performance in future research to address this gap.
Comment 9: It is recommended to reconsider and redesign Figure 1, because there are unexplained and/or confusing box contents (e.g., production efficiency, production cost, export-oriented production capacity; export volumes, competitive pricing, export capacity).
Response 9: Figure 1 is revised, as suggested.
Comment 10: There are many referenced paragraphs which are not much connected to the research topic (e.g., several sentences in section 1. Introduction; p.5, lines 206–2012, etc.); filtering the references, and keeping only ones strictly related to the research topic is suggested.
Response 10: The introduction was reviewed again, and any irrelevant parts were removed.
Comment 11: Conversely, there are statements which are not documented (e.g., p.10, lines 473–476), if not plainly wrong (e.g., “our investigation is essential to contribute to the creation of new frameworks and methods that help firms […] overcome trade barriers” (p.3, lines 135–137). Reformulations are recommended.
Response 11: Thank you. , After revising the manuscript by including moderator and interaction term, this part at p.10 lines 473-476 should be removed. Therefore, we removed this part from the casual chain analysis part. Regarding p.3 lines 135-137, the context was reformulated in blue color in the revised manuscript.
Comment 12: Overall comment: It is regrettable that newly inserted paragraphs not only fail to solve all conceptual and methodological shortcomings (repeatedly signaled in previous review rounds), but also display new (truly, minor) inadequacies: e.g., “statical” (Abstract, line 15); acronym EOPC (Abstract, line 16) not defined upfront; etc.
Response 12: Thank you. We corrected typographical errors e.g. "statical," to "statistical." The acronym "EOPC" has been defined as "export-oriented production capacity" at its first occurrence to ensure clarity. We also addressed all conceptual and methodological aspects, as suggested by the four reviewers, in the revised manuscript. Of course, we are committed to ensuring that all concerns are adequately addressed in this round of review. Any further investigations are suggested in future work.
Thank you very much.
