Review Reports - Robotic Bricklaying Adoption in Post-Pandemic Jordan: A Resilience Framework for Construction Automation

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The study is important and holds several strengths:

1) it demonstrates how automation enhances resilience in developing economies.

2) there is strong theoretical grounding and linkage to global frameworks especially SDG 9, national modernization strategy.

However, the manuscript needs improvement. My comments and suggestions are:

1) include a concise statement of research objectives or hypotheses in the introduction.

2) add empirical or field validation to complement the simulation results.

3) there are a lot of short paragraphs which shouldn't be. It affects the presentation of the paper. For example, see: 2.2. Study Scope and Sample Justification, 2.9. Economic Analysis and Financial Modeling, 2.3. Methods Approach and Justification, 2.1. Research Paradigm and Critical Justification, 4.3. Economic Trade-offs and Lifecycle Cost Implications, 4.5. Jordan-Specific Implications and Barriers, and 5. Conclusions.

These are just few as the short paragraphs are almost all over the manuscript.

4) Why are the limitations listed? They be in narrative form and properly developed (briefly explained). Why are the limitations in section 2. Limitations would usually come towards the end of the report before the conclusion.

5) why is implication of the studies under discussion? Limitation should have a different section.

6) contribution should be narrative too. There are too many unnecessary listings in the manuscript.

6) why are there bullet points in the conclusion? Conclusion should be narrative.

Author Response

Please see the attachment.

Author Response File: Author Response.docx

Reviewer 2 Report

Comments and Suggestions for Authors

Abstract Section: The abstract lacks clarification of key assumptions, such as the specific basis for the 30% labor absenteeism rate used in the simulation and the limitations of the SAM 100 system's applicability in the Jordanian context (e.g., reliance on standardized housing designs). Limitations of the research methodology are not mentioned, such as the simulation results not being field-validated, which may affect the reliability of conclusions.

It is suggested: Briefly state the source of simulation assumptions (e.g., ILO data) in the abstract and explicitly limit the study scope to standardized housing projects. Emphasize the study's practical relevance, such as policy support for Jordan's Economic Modernization Vision (2022-2024), while exercising caution in generalizing conclusions.

Introduction: Section 1.1“Construction Under Crisis: Sectoral Fragility in Jordan”describes pre-pandemic construction sector vulnerabilities using macro data (e.g., GDP contribution, migrant labor share) without micro-level empirical support (e.g., specific project delay cases). It fails to deeply analyze pre-existing structural issues (e.g., skill shortages, technological lag), resulting in incomplete attribution of pandemic impacts.

It is suggested: Supplement with field research data or case studies, such as citing specific reports from the Jordan Contractors Association, to enhance the objectivity of the vulnerability description. Link pandemic impacts to long-term industry issues (e.g., reliance on migrant labor) to provide a more systematic contextual analysis.

In Section 1.2 “Traditional Methods Meet a Technological Wall,” the description of traditional bricklaying methods is broad and lacks detailed comparisons of efficiency differences across project scales (e.g., small vs. large projects), resulting in an insufficiently in-depth analysis of SAM 100's applicability. Citing media reports (e.g., Jordan Times) as evidence of cultural resistance lacks academic literature support, reducing the rigor of the argument.

It is suggested: Include efficiency data for traditional methods in typical Jordanian projects (e.g., small-to-medium residential buildings) and compare SAM 100's potential performance across project scales. Cite more peer-reviewed studies (e.g., Sarireh, 2020) to substantiate cultural resistance claims, reducing reliance on non-academic sources.

In Section 1.3 Robotics Through a Theoretical Lens, the application of theoretical frameworks (Disruption Theory and Resilience Theory) remains superficial. Failure to deeply integrate Jordan's local context (e.g., economic constraints or policy environment) weakens the connection between theory and practice. Omission of other relevant theories (e.g., Technology Acceptance Model or Institutional Theory) may overlook critical adoption barriers.

It is suggested: Directly link theories to Jordan-specific challenges (e.g., high equipment costs or skill shortages), such as using resilience theory to explain how SAM 100 mitigates labor disruptions. Introduce supplementary theoretical frameworks to comprehensively analyze multidimensional barriers to technology adoption (e.g., economic, social, institutional).

In Section 1.4 Study Focus and Methodological Overview, the research focus is clear but lacks sufficient justification for selecting SAM 100 over other automation technologies (e.g., 3D printing), with no comparative argumentation. The methodological overview omits limitations of the simulation tool (e.g., AnyLogic's capability to simulate complex on-site logistics).

It is suggested: Briefly discuss SAM 100's comparative advantages over other automation technologies (e.g., operational simplicity) in the introduction to highlight research value. Clearly state the assumptions and limitations of simulation tools in the Methods section to enhance transparency.

Research Methodology Section: In Section 2.1 Research Paradigm and Critical Justification, the adoption of an empiricist paradigm without considering qualitative factors (such as contractor attitudes or cultural resistance) may lead to results that are disconnected from reality. The validation process for simulation parameters (e.g., 30% absenteeism rate) is not detailed, and there is a lack of triangulation with local data.

It is suggested: Future research should adopt mixed methods, such as incorporating questionnaires or interviews, to balance quantitative and qualitative approaches. Provide detailed parameter validation information, e.g., comparisons with Jordanian Ministry of Labor data, to enhance the reliability of hypotheses.

In Section 2.2 Study Scope and Sample Justification, the sample is based on 10 standardized residential buildings, but the representativeness of the sample (e.g., whether it covers urban-rural differences or different project types) is not discussed, limiting the generalizability of conclusions. The statistical basis for the sample size (80 units) (e.g., power analysis) is not explained, potentially affecting the robustness of results.

It is suggested: Expand the sample scope to include diverse building types (e.g., commercial or public buildings) or demonstrate the representativeness of the current sample. Cite statistical methods (e.g., sample size calculation formulas) to justify the sample size.

In Section 2.3 Methods Approach and Justification, the simulation methodology lacks detailed calibration procedures (e.g., comparison with historical project data), undermining model credibility. The selection of tools (e.g., Python and AnyLogic) is not justified as superior to alternatives (e.g., BIM or discrete event simulation software).

It is suggested: Add calibration details, such as validation using actual Jordanian project data, and report error margins. Briefly justify tool selection (e.g., AnyLogic's advantages for dynamic systems) to enhance methodological transparency.

In Section 2.4 Data Collection, reliance on secondary sources (e.g., literature and media) without primary data (e.g., contractor interviews) may introduce bias. The data collection timeframe (e.g., pandemic peak vs. later stages) remains undiscussed, affecting data timeliness.

It is suggested: Supplement with primary data collection, such as structured interviews with Jordanian contractors, to validate simulation parameters. Specify the data timeframe and discuss its impact on results (e.g., labor force changes across pandemic phases).

In Section 2.5 Simulation Scenarios and Parameters, parameter settings (e.g., daily output of SAM 100) are based on international standards without adaptation to local Jordanian conditions (e.g., worker skills or material variations). No comprehensive sensitivity analysis was conducted to test how key parameter changes (e.g., absenteeism rates or material costs) affect outcomes.

It is suggested: Localize parameter settings, e.g., adjust SAM 100 output efficiency through local pilot studies. Add sensitivity analysis including multi-scenario testing (e.g., absenteeism rates from 20% to 50%) to assess result robustness.

In Section 2.6-2.9 Time, Cost, and Financial Analysis, cost analysis excludes implicit costs (e.g., training, maintenance, software updates), potentially leading to overly optimistic ROI estimates. Financial models (e.g., NPV) do not account for Jordan-specific economic risks (e.g., currency fluctuations or policy changes).

It is suggested: Include all relevant expenses in cost analysis and discuss their impact on payback periods. Extend the financial model to incorporate risk factors, such as using Monte Carlo simulations to assess uncertainty.

In Section 2.10 Methodological Limitations, the list of limitations is comprehensive but does not discuss how these limitations specifically impact conclusions (e.g., implications of limited generalizability on what is it suggested for policy recommendations). No specific measures to mitigate limitations are proposed (e.g., design for future research).

It is suggested: Conduct a detailed analysis of how limitations affect results and advise caution when interpreting conclusions. Propose targeted measures, such as field trials or expanded samples, to address current limitations.

Results Section: In 3.1 Simulation Outcomes: Time Efficiency, time efficiency results are based on simulations but lack empirical validation through comparison with field data. The performance degradation of SAM 100 in non-standard projects (e.g., irregular geometries) is not discussed.

It is suggested: Cite actual data from local or international comparable projects to validate the credibility of simulation results. Expand the analysis of SAM 100's applicability boundaries in the discussion, such as limitations in complex designs.

In Section 3.2 Cost Analysis and Per-Unit Cost Structure, the cost structure analysis is brief and lacks detailed explanation of cost allocation methods (e.g., the logic for allocating equipment rental fees). The impact of different leasing models (e.g., short-term vs. long-term) on costs is not compared.

It is suggested: Provide complete cost calculation formulas and assumptions, e.g., by detailing the allocation process in an appendix. Analyze the economics of different leasing strategies to support decision-making.

In Section 3.3 Indirect Savings, estimates for indirect savings (e.g., reduced management fees) are based on assumptions without specifying data sources or calculation details. Risks associated with accelerated timelines (e.g., quality compromises or supply chain pressures) are not discussed. Clarify the methodology for indirect savings calculations and reference industry standards (e.g., Jordan Construction Management Cost Benchmarks). Balance efficiency and risk in the discussion, it is suggested that accelerated project management be adopted.

In Section 3.4 Benchmarking SAM 100 vs. Regional Alternatives, the comparison with 3D printing is superficial, failing to consider technological maturity, local supply chain support, or long-term sustainability. The potential of other automation technologies (e.g., prefabricated components) in Jordan is not discussed.

It is suggested: Expand the comparative framework to include additional dimensions (e.g., environmental impact or skill requirements). Future research should systematically evaluate multiple automation options to provide comprehensive guidance.

Discussion Section: In 4.1 Interpretation of Key Findings, the interpretation of results lacks sufficient connection to theoretical frameworks (e.g., resilience theory) and fails to provide in-depth analysis of how “resilience” is concretely achieved. The findings are not discussed in terms It is suggested: Directly map findings to theory, e.g., using SAM 100 stability to illustrate resilience theory application. Add literature comparisons to highlight innovation or consistency. In Section 4.2 Implications for Jordan’s Construction Sector, policy recommendations remain broad (e.g., training programs) without specifying implementing entities, timelines, or resource requirements. Potential negative labor market impacts of SAM 100 adoption. (e.g., unemployment).

It is suggested: Propose a concrete policy roadmap, such as a design in collaboration with Jordanian vocational training centers. Discuss automation’s impact on social sustainability and suggest strategies for an inclusive transition.

In Section 4.3 Economic Trade-offs and Lifecycle Cost Implications, the economic analysis excludes lifecycle costs (e.g., equipment maintenance or disposal costs), resulting in incomplete ROI estimates. The NPV model lacks scenario testing (e.g., economic downturns or cost overruns).

It is suggested: Expand cost analysis to cover the full lifecycle and provide financial simulations under different scenarios. Detail NPV model inputs and outputs in appendices to enhance reproducibility.

In Section 4.4 Addressing Cultural Resistance and Contractor Skepticism, the analysis of cultural resistance relies on secondary sources and lacks empirical data (e.g., contractor surveys). It does not discuss how to measure resistance levels or evaluate intervention effectiveness.

It is suggested that future research include quantitative surveys (e.g., Likert scales) to quantify resistance factors. Propose a pilot project evaluation framework to test the effectiveness of awareness-raising measures.

In Section 4.5 Jordan-Specific Implications and Barriers, the analysis of local barriers (e.g., import dependency) fails to delve into root causes (e.g., regulatory or infrastructure issues). No specific strategies to address these barriers (e.g., local manufacturing partnerships) are proposed.

It is suggested: Develop tailored solutions aligned with Jordan's policy environment (e.g., National Robotics Strategy). Consider researching the feasibility of import substitution or localized supply chains.

Conclusion Section: The conclusion repeats the results summary without highlighting the study's theoretical contributions (e.g., extensions to resilience theory) or practical innovations. Future directions remain vague (e.g., “mixed-method research”) without specifying research questions or methodologies. It is suggested: Clearly summarize the study's unique contributions to construction management theory and Jordanian policy. Propose concrete future research agendas, such as piloting SAM 100 in non-residential projects or conducting long-term performance evaluations.

Other Sections (e.g., Appendix): The NPV model in the appendix lacks detailed explanations of parameter sources (e.g., rationale for discount rate selection), reducing replicability. The data availability statement links to a repository but fails to describe data quality control processes.