Factor Identification for the Sustainable Supply Chain in Educational Construction Projects

Round 1

Reviewer 1 Report (Previous Reviewer 2)

Comments and Suggestions for Authors

Hello Editors. I would love to have a manuscript file that has all the changes made by authors wither by tracked changes or colored texts

Author Response

A highlighted [colored] version is attached with track changes.

Author Response File: Author Response.docx

Reviewer 2 Report (Previous Reviewer 1)

Comments and Suggestions for Authors

While the paper addresses an important topic and demonstrates some methodological competence, I have identified several substantial concerns that must be addressed before the manuscript can be considered suitable for publication.

My most significant concern relates to the sampling methodology, which is inadequately described throughout the manuscript. The authors state that they administered a survey to "a target sample of 100 professionals in the construction and educational sectors," yet they provide virtually no information about how these participants were identified, recruited, or selected. There is no description of the sampling frame, no discussion of inclusion or exclusion criteria beyond the broad sectoral categories mentioned, no geographic distribution specified, and no response rate reported. This lack of transparency is particularly troubling given that the paper makes repeated claims about "regional variations" in sustainable supply chain implementation. Without understanding who these 100 respondents are, where they are located, what types of projects they work on, or how they were selected, it becomes impossible to assess the representativeness of the sample or the generalizability of the findings. The distinction between convenience sampling and purposive or random sampling has profound implications for validity, yet readers are left to speculate about which approach was used.

Related to this concern is the question of sample adequacy. While the authors justify their use of Partial Least Squares Structural Equation Modeling by noting its suitability for smaller samples, a sample of 100 observations remains marginal for the complexity of their model. With five constructs measured by four to six items each, the model likely contains approximately twenty-five to thirty indicators. Standard guidelines suggest a minimum of ten observations per indicator, which would require a sample of two hundred fifty to three hundred participants. Although PLS-SEM is more forgiving than covariance-based approaches, the authors' sample size remains on the lower boundary of acceptability. This concern is reinforced by the model's R-squared value of 0.48, which indicates that only forty-eight percent of the variance in sustainable success is explained by their model. This relatively modest explanatory power may suggest that the model is underspecified or that important variables have been omitted.

The theoretical foundation for the five key drivers examined in this study also requires substantial strengthening. The authors state that their conceptual framework identifying Material Selection, Stakeholder Engagement, Waste Management, Energy Efficiency, and Digital Technologies was developed based on "an extensive review of the literature," but they provide no systematic methodology for how these specific factors were selected from among the many possible drivers of sustainable construction success. There is no discussion of alternative frameworks that were considered, no pilot testing or exploratory factor analysis to validate the proposed structure, and no clear theoretical rationale for why these five factors, as opposed to others such as cost considerations, regulatory frameworks, workforce training, or organizational culture, were chosen. The framework appears somewhat arbitrary, and readers are left uncertain about whether these factors represent a comprehensive model or merely a convenient subset of potentially relevant variables.

The methodological approach, while incorporating some elements of rigor, suffers from several important limitations. Although the authors claim to employ a "mixed-methods approach," the integration of qualitative and quantitative data appears superficial. The qualitative analysis seems to serve primarily as confirmation of the quantitative findings rather than providing genuinely new insights or exploring contradictory evidence. The interview data is presented as supporting the survey results, but there is no discussion of disconfirming cases, unexpected themes, or tensions between different data sources. This pattern suggests possible confirmation bias, where qualitative data were selectively interpreted to align with predetermined quantitative results. A truly integrated mixed-methods design would demonstrate how the different data sources inform, challenge, or refine one another in meaningful ways.

The case study component of the research is particularly problematic. While the authors include three projects from Indonesia, Singapore, and the United States, they provide no methodology for case selection, no description of data collection procedures, and no citations for the specific performance metrics presented in Table 5. The case studies read more like illustrative examples drawn from secondary sources than systematic comparative analyses conducted according to established case study methodologies. The precise figures provided for energy savings and waste reduction appear without any indication of their provenance or reliability. Furthermore, these cases are geographically distributed, yet the authors provide no evidence that their survey sample includes participants from these regions or projects, raising questions about how the case studies actually validate or extend the survey findings.

The application of Structural Equation Modeling, while technically competent in some respects, exhibits several weaknesses. Most significantly, the authors make causal claims based on cross-sectional data, using language such as "drives," "impacts," and "leads to" when describing path coefficients. Cross-sectional survey data cannot support causal inference, regardless of the analytical technique employed. The relationships identified may be associative rather than causal, and the direction of causality cannot be determined from this design. Additionally, the model specified in Equation 1 is relatively simplistic, assuming only direct linear relationships among variables without considering potential interaction effects, mediating variables, or non-linear relationships that may be theoretically plausible. The authors report standard reliability and validity metrics, which generally meet acceptable thresholds, but they omit important model fit indices such as the Standardized Root Mean Square Residual. They also rely on somewhat outdated techniques, such as Harman's single-factor test for common method bias and the Fornell-Larcker criterion for discriminant validity, when more current approaches are available and recommended.

The focus on educational construction specifically, while potentially valuable, is insufficiently justified. The authors mention that educational institutions serve as "living laboratories" where sustainable practices can be demonstrated and refined, but this concept is never developed beyond a passing reference. The paper does not establish what makes educational construction projects fundamentally different from other building types in terms of sustainable supply chain considerations. Without a clear articulation of the unique characteristics, constraints, or opportunities associated with educational facilities, the narrow focus appears somewhat arbitrary and may unnecessarily limit the contribution and impact of the work. A broader examination of sustainable construction supply chains, or alternatively, a deeper exploration of what makes educational projects distinctive, would strengthen the manuscript substantially.

The data preprocessing procedures described in the methods section also raise concerns. The authors mention that missing values, which represented less than three percent of the data, were imputed using mean substitution. This is a relatively crude approach that can bias parameter estimates and underestimate standard errors, particularly when more sophisticated imputation techniques are available. Similarly, they indicate that outliers beyond three standard deviations were "winsorized," but they provide no justification for this threshold or discussion of how many observations were affected. These preprocessing decisions can meaningfully impact results, yet they receive only cursory mention.

The thematic analysis of qualitative data, while appropriate in principle, lacks sufficient methodological detail. The authors state that they used NVivo software to systematically identify recurring themes, but they provide no description of the coding process, no information about whether multiple coders were involved, and no assessment of inter-rater reliability. The four themes that emerged appear to align perfectly with the quantitative findings, which, while potentially valid, may also indicate that the coding was influenced by prior knowledge of the survey results. More transparency about the analytical process and evidence of systematic, rigorous qualitative analysis would strengthen confidence in these findings.

The manuscript also suffers from limited discussion of alternative explanations or contradictory evidence. For instance, the finding that Waste Management showed a somewhat weaker effect than in some previous studies is acknowledged but not deeply explored. The authors suggest this may be due to limited adoption of modular and prefabricated construction methods, but they provide no data to support this interpretation. More generally, the comparison with previous literature in Table 6 appears selective, highlighting studies that align with the current findings while providing limited engagement with work that might challenge or complicate the conclusions.

Several transparency and replicability concerns also deserve mention. The survey instrument itself is not provided, either in the main text or in supplementary materials, making it impossible for readers to assess the face validity of the items or for future researchers to build on this work. The raw data are not made available, and insufficient methodological detail is provided to allow for true replication of the study. There is no mention of ethical approval or informed consent procedures, which are increasingly expected in survey research involving human participants. The manuscript would benefit significantly from greater openness and transparency in these regards.

The paper's contribution to knowledge, while potentially valuable, is overstated in places. The authors use terms such as "comprehensive analysis," "robust," and "holistic" to describe their approach, but these characterizations are not fully supported by the methodology employed. A sample of one hundred participants of unknown representativeness, analyzed using cross-sectional methods that cannot support causal inference, with case studies that lack methodological rigor, does not constitute a comprehensive or definitive examination of sustainable supply chain practices in educational construction. The findings may represent useful preliminary evidence, but they should be presented with appropriate epistemic humility regarding their scope and limitations.

The limitations section of the manuscript is notably brief and fails to adequately acknowledge the most significant constraints of the study. Rather than engaging seriously with questions of sampling, causality, generalizability, and measurement, the discussion of limitations is largely confined to noting that some factors showed different effect sizes than expected. A more honest and thorough treatment of the study's boundaries and constraints would demonstrate greater scholarly rigor and would actually enhance rather than diminish the credibility of the work.

Despite these concerns, the manuscript does possess some strengths that should be acknowledged. The topic is unquestionably important, as sustainable construction practices represent a critical component of addressing climate change and environmental degradation. The construction sector's contribution to global carbon emissions and waste generation makes research in this area valuable and timely. The authors demonstrate familiarity with relevant literature and engage with key concepts in sustainable supply chain management. The writing is generally clear and well-organized, making the paper accessible to readers. The attempt to combine multiple methods and data sources, even if imperfectly executed, reflects an appropriate recognition that complex phenomena benefit from multiple perspectives.

In conclusion, while this manuscript addresses an important topic and demonstrates some methodological competence, it requires substantial revision before it can be considered suitable for publication in a peer-reviewed journal. The most critical issues that must be addressed include: first, a complete and transparent description of the sampling methodology, including how participants were recruited, selection criteria, geographic distribution, and response rates; second, either a substantial increase in sample size or a simplification of the analytical model to match the available data; third, a stronger theoretical justification for the selection of the five key drivers examined in the study; fourth, either genuine integration of the mixed methods components with evidence of how different data sources inform one another, or a clearer acknowledgment that the study employs parallel rather than integrated methods; fifth, either a rigorous case study methodology with clear data collection and analysis procedures, or removal of the case study component in favor of a focus on the survey data; sixth, more cautious language regarding causality and recognition of the limitations of cross-sectional data for causal inference; seventh, provision of the survey instrument and greater transparency about data collection and analysis procedures; and eighth, a substantially expanded limitations section that honestly acknowledges the study's boundaries and constraints.

With these revisions, the manuscript could make a meaningful contribution to the literature on sustainable construction supply chains. In its current form, however, the gap between the claims made and the evidence provided is too large to recommend publication. I therefore recommend that the manuscript be returned to the authors for major revision, with the understanding that addressing these concerns will require significant additional work and potentially new data collection.

Author Response

Thank you very much for your thorough and constructive review of our manuscript. Your comments were highly valuable in identifying methodological, theoretical, and reporting gaps that required substantial improvement. We deeply appreciate the level of detail and care reflected in your critique.

In response, we have undertaken a comprehensive revision of the manuscript, including a full restructuring and expansion of the Materials and Methods section, enhanced transparency regarding sampling and data collection, strengthened theoretical justification for the selected drivers, improved integration of the mixed-methods components, revised case study methodology, and significant refinement of the Discussion and Limitations sections.

We have addressed each of your comments individually and in detail. Please find our point-by-point response document attached, outlining exactly how every comment has been incorporated into the revised manuscript.

Thank you again for your insightful feedback and for helping us improve the rigor and clarity of this work.

Author Response File: Author Response.pdf

Reviewer 3 Report (New Reviewer)

Comments and Suggestions for Authors

Dear Authors,

the manuscript does present an interesting problem and is well structured and well written. The smaller issues I found is in why specifically focus on educational projects. Your explanations from the text are also applicable to almost any other publicly funded projects. Additionally there are some minor formatting issues.

But the largest problem I found is the research design itself. Why did you decide to do three different things in one paper? And none of them are sufficiently methodologically described. What were the questions for the survey? Sure, they might relate to table 1, but what exactly was asked? Who were the respondents? And I don't mean in percentages what you stated already (35% project managers etc.). The same goes for the interviews. 

What did you hope to achieve with interviews, atop of the survey? Because they are used for different things.

Finally, the case studies are described in 10 lines in the text. Why even mention them then?

All in all, the methods are not clearly and sufficiently defined and moreover the reasoning behind such choice. It seems that you tried to do everything at once and in the end did nothing.

Further comments are in the attached pdf.

Best,
Reviewer

Comments for author File: Comments.pdf

Author Response

We sincerely thank you for your thoughtful and constructive review of our manuscript. Your feedback helped us recognize important areas that required clearer methodological justification, stronger motivation for focusing on educational construction, and more transparent reporting of our research design.

In revising the manuscript, we have expanded and clarified the rationale for concentrating on the educational sector, substantially improved the description of the survey, interview, and case study procedures, and streamlined the structure of the mixed-methods design to avoid overlap and ambiguity. We also enhanced the transparency of our research instruments by providing full appendices and methodological documentation.

We have carefully addressed each of your comments in the point-by-point response document attached, detailing the modifications made throughout the manuscript.

Thank you again for your valuable feedback and for helping us significantly strengthen the contribution and rigor of this study.

Author Response File: Author Response.pdf

Round 2

Reviewer 2 Report (Previous Reviewer 1)

Comments and Suggestions for Authors

I believe the manuscript has improved due to the revisions done by the authors.

There are a few issues which require major editing:

Darko et al., 2019  which is cited in the text is missing from the References. Same issue for Etikan et al. (2016), which is cited but not included in the References. This makes me think that there might be more like this.

Something seems to be missing here: . Measurement Items for SSC Constructs

Author Response

Dear Reviewer,
We appreciate your constructive feedback. Please find the detailed point-by-point responses to all your comments in the attached document.
Sincerely.

Author Response File: Author Response.pdf

Reviewer 3 Report (New Reviewer)

Comments and Suggestions for Authors

Dear Authors, you have addressed most of the concerns, however a few minor details remain. Please consult the comments in the attached pdf.

Comments for author File: Comments.pdf

Author Response

Dear Reviewer,
We appreciate your constructive feedback. Please find the detailed point-by-point responses to all your comments in the attached document.
Sincerely.

Author Response File: Author Response.pdf

This manuscript is a resubmission of an earlier submission. The following is a list of the peer review reports and author responses from that submission.

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

I haven't seen any changes in this version other than an addition that now says, Institutional Review Board (IRB) of [University Name] under protocol 228 number [XXXX], which does not add an value. My initial review and opinion remain the same.

Reviewer 2 Report

Comments and Suggestions for Authors

Abstract
1) “surveys with 100 industry professionals” is fine, but specify if these were contractors, project managers, or policymakers—since “industry professionals” is broad.
2) You say “Structural Equation Modeling (SEM-PLS)”—better phrasing is “Partial Least Squares Structural Equation Modeling (PLS-SEM)”
3) You mention material selection, digital technologies, stakeholder engagement as strongest, but you don’t report the weaker ones (waste management, energy efficiency). Adding a clause like “while waste management and energy efficiency showed weaker but still significant effects” improves completeness.

Introduction
1) Use “Partial Least Squares Structural Equation Modeling (PLS-SEM)” consistently rather than “Structural Equation Modeling (SEM-PLS).”
2) 7th paragraph - Unlike previous studies that focus on isolated factors,  this research adopts a systems perspective to analyze how these dimensions interact to 114 shape sustainable project success.....what are those previous studies....list them...

Methods
1) You justify PLS-SEM well (small/moderate sample, predictive modeling), but don’t mention why CB-SEM was not chosen. We need to know why.
2) You study Egypt, Singapore, and the U.S.—but the introduction earlier mentioned Bali, Singapore, and U.S. (inconsistent).
3) The Likert scale description is fine, but you should clarify whether it was translated/back-translated (if used across multiple countries).
4) Did you check item-level discriminant validity beyond Fornell–Larcker (e.g., HTMT ratio)? Many reviewers expect HTMT in 2025.
5) Common method bias: You only used Harman’s single-factor test (criticized as weak). A marker variable test or full collinearity VIFs would be stronger.
6) You mention saturation after 18 interviews, but reviewers may ask: how was saturation operationalized? Was it judged by recurring codes or lack of new themes?
7) For case studies, why Egypt/Singapore/U.S. (or Bali earlier)? Was it because of diverse policy/regulatory frameworks?

Results
1) Some contradictions (e.g., stakeholder engagement strong statistically but tokenistic qualitatively) are identified but not reconciled or theorized. This needs to be addressed.
2) Patterns like “cost vs. sustainability trade-offs” or “policy as an enabler” could be presented as overarching themes but remain scattered.

Reviewer 3 Report

Comments and Suggestions for Authors

This study investigates five key drivers of sustainable supply chain management in educational construction projects: material selection, stakeholder engagement, waste management, energy efficiency, and digital technologies. Using a mixed-methods approach combining surveys with 100 industry professionals, 20 semi-structured interviews, and three international case studies, the authors employed Structural Equation Modeling (SEM-PLS) to test hypothesized relationships. The research found that stakeholder engagement, material selection, and digital technologies exerted the strongest influence on overall sustainable success, while waste management showed unexpectedly weak effects. The study contributes both theoretical insights and practical recommendations for implementing sustainable supply chain practices in educational infrastructure.

Overall manuscript structure is ok, however manuscript contribution is not for publication, so author needs rejection, however author can have one chance to improve the quality of manuscript: some comments are given below:

In the abstract there are **critical inconsistencies** in the reported beta coefficients between the abstract and results sections:

Abstract reports: material selection (β = 0.65), digital technologies (β = 0.62), stakeholder engagement (β = 0.58)

Results section reports: stakeholder engagement (β = 0.31), material selection (β = 0.28), digital technologies (β = 0.23)

This is a major error that undermines credibility and suggests inadequate proofreading.

The introduction has several key issues: Excessive length (that dilutes focus on the specific research gap), Unclear transition (between literature streams - the organization jumps between material selection, stakeholder engagement, and digital technologies without clear logical flow), Insufficient justification (for why educational construction specifically requires different analysis from general construction projects).

Several methodological concerns arise:

Purposive and snowball sampling may not provide representative samples, particularly given the geographic concentration in only three regions

While 100 respondents is mentioned, there's no power analysis or justification for this sample size for SEM analysis

Table 1 provides only single example items per construct, making it impossible to assess content validity

No information on survey administration method, response rates, or non-response bias assessment

The IRB protocol number is listed as "[XXXX]" suggesting incomplete documentation

The results section contains several issues:

As noted above, major discrepancies between abstract and results

Claims "good overall fit" but SRMR of 0.061 is borderline, and NFI of 0.92 is adequate but not excellent

Claims of regional variations are mentioned but not systematically analyzed or reported

Interview quotes feel cherry-picked rather than systematically integrated with quantitative findings

Claims about paradigm shifts and fundamental changes seem overstated given the study's scope

Insufficient comparison with existing literature on construction sustainability

The claimed theoretical contributions are not clearly distinguished from existing knowledge