Review Reports

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

Dear authors,

You have done a great work, and it was my pleasure to read and review your paper.

From my side, there are two key points that need to be added in order to strengthen your work.

1) Please clarify the Integration of Theoretical Framework. While the theories that have been used (RBV and DCT) are mentioned, their integration into the hypotheses and interpretation must be elaborated and be stronger.

2) There is a new publication, which highlights how organizational context and DTN drive strategic sustainability. Added this paper can enrich the discussion section. (Stroumpoulis, A., & Kopanaki, E. (2025). Examining the Relationship Between Sustainable Strategies, Digital Transformation and Organizational Context: Evidence from 3PL Companies in Greece. Sustainability, 17(19), 8846.)

Author Response

Comment 1: [Please clarify the integration of the theoretical framework. While the theories (RBV and DCT) are mentioned, their integration into the hypotheses and interpretation must be elaborated and stronger.]

Response 1: Agree. We sincerely appreciate this valuable comment. We agree that strengthening the integration between the Resource-Based View (RBV) and Dynamic Capabilities Theory (DCT) is essential for enhancing the theoretical coherence of our model. In response, we elaborated the RBV–DCT linkage throughout the theoretical framework, clarified how digital resources (DTN and SMU) evolve into dynamic capabilities (CNS, SIN, CEX, ORE), and ensured that each hypothesis is explicitly grounded in the complementary logic of resource possession (RBV) and resource reconfiguration (DCT). These revisions reinforce the causal chain and provide a clearer foundation for interpreting the study’s empirical outcomes.
Revisions Implemented:
(1) Strengthened RBV–DCT Integration in Section 2.9. 
We expanded the theoretical rationale to clarify how strategic digital resources (DTN and SMU) are transformed through DCT mechanisms (sensing, seizing, reconfiguring) into dynamic capabilities that ultimately contribute to CAE and SBP. The revisions can be found in Section 2.9, line 306-311 of the revised manuscript. 
(2) Enhanced Explanation in Discussion (Section 5.1). 
We also improved the interpretation of empirical results by emphasizing how the findings support the RBV–DCT synergy and how digital resources are orchestrated into sustainability-oriented capabilities. The updated text appears in Section 5, lines 870-872 of the revised version.  

Comment 2: [There is a new publication, which highlights how organizational context and DTN drive strategic sustainability. Adding this paper can enrich the discussion section. (Stroumpoulis & Kopanaki, 2025, Sustainability 17(19), 8846).]

Response 2:  Agree. We appreciate this excellent recommendation. The suggested study by Stroumpoulis & Kopanaki (2025) provides valuable insights into how organizational context interacts with DTN to influence sustainability outcomes, which aligns strongly with our study. 
Revisions Implemented:
(1) Added the new reference in Section 5.1 (Discussion). 
We integrated the citation to highlight how our findings complement prior evidence that DTN promotes sustainability only when combined with organizational readiness, contextual alignment, and managerial capability—consistent with DCT’s emphasis on sensing, seizing, and reconfiguring. We have incorporated these changes in Section 5, lines 876-882 of the updated manuscript. 
(2) Added conceptual linkage in Section 2.9.
We referenced the study to reinforce the importance of contextual moderators in digital transformation–sustainability pathways, further supporting the theoretical rationale of our model. This revision is now reflected in Section 2.9, lines 315–321.
(3) Added the reference to the Reference List. 
The full citation has been added according to MDPI format. The corresponding revisions have been added to Reference Section, lines 1374–1375. 

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

This manuscript presents a timely and methodologically ambitious investigation into how digital transformation and social media use jointly influence sustainable business performance in the retail sector, with a specific focus on Thailand. The integration of a dual-method design, combining a qualitative e-Delphi process with Fuzzy C-Means clustering and quantitative structural equation modeling, represents a notable methodological contribution. The theoretical grounding in the Resource-Based View and Dynamic Capabilities Theory is appropriate, and the empirical findings are robust, supported by a large and diverse sample. However, several areas require revision.

 

Introduction

1. The sectioneffectively situates the study within the broader contexts of digital transformation, social media adoption, and sustainability imperatives in retail, particularly in emerging markets. The reference to global frameworks such as the UN SDGs and Industry 5.0 strengthens the relevance of the work. However, the rationale for focusing specifically on Thailand could be more clearly articulated. The authors should elaborate on what makes Thailand a representative or unique case among emerging markets, and how the findings might be generalizable or context-specific.
2. While the dual-method approach is introduced, its necessity and advantages for addressing the research gap could be more explicitly justified.

 

Literature Review

3. The logical transitions between some constructs could be strengthened. For instance, the role of Collaboration Networks in fostering both Service Innovation and Organizational Resilience would benefit from a more nuanced theoretical explanation.
4. The review would also be enhanced by incorporating more recent studies (2024–2025) on digital transformation and sustainability, especially in retail and emerging markets.
5. while the Fuzzy C-Means theory is explained, its relevance to management and sustainability research—beyond a purely technical description—should be better emphasized.

 

Methodology

6. The expert selection process, while mentioned, should be described in more detail, including specific criteria for expertise, industry representation, and regional diversity.
7. The parameter choices for the FCM algorithm (e.g., m=2.0, initial centroids C1=4.5 and C2=6.5) should be justified with references to methodological literature.
8. The data collection procedure would benefit from greater transparency—such as response rates, timing, and measures taken to address non-response bias.
9. The authors should address potential common method bias, for example, by reporting Harman’s single-factor test results.

 

Results

10. Theanalysis would be strengthened by including formal mediation tests (e.g., using bootstrapping) to verify the indirect effects of DTN and SMU on SBP through the proposed dynamic capabilities.
11. A comparison with alternative models would also help demonstrate the superiority of the proposed framework.
12. Visually, the path model (Figure 5) could be improved by adding R² values for endogenous variables, and the tables could better distinguish between direct, indirect, and total effects.

 

Discussion

13. The discussion effectively interprets the findings in light of the theoretical framework and prior literature. However, the theoretical implications of integrating RBV and DCT in the context of digital transformation could be more explicitly articulated. The authors should elaborate on how their findings extend or refine these theories.
14. The practical recommendations, while insightful, could be more context-specific to the Thai retail environment, considering local digital infrastructure, regulatory conditions, and market characteristics.
15. Thefuture research directions is appropriate but could be more precise—for example, suggesting longitudinal designs, cross-cultural comparisons, or the inclusion of moderators such as organizational culture or digital maturity.

 

Minor revision

16. The writing is generally clear but would benefit from careful copyediting to improve sentence flow and reduce repetition (e.g., in the Limitations section).
17. Some references appear incomplete (e.g., missing volume or page numbers) and should be verified for consistency with the target journal’s style.

Author Response

Comment 1: [The section effectively situates the study within the broader contexts of digital transformation, social media adoption, and sustainability imperatives in retail, particularly in emerging markets. The reference to global frameworks such as the UN SDGs and Industry 5.0 strengthens the relevance of the work. However, the rationale for focusing specifically on Thailand could be more clearly articulated. The authors should elaborate on what makes Thailand a representative or unique case among emerging markets, and how the findings might be generalizable or context-specific.]

Response 1: Agree. We appreciate this insightful comment. In response, we expanded the Introduction to provide a clearer rationale for selecting Thailand as the empirical context. The revised section now explains Thailand’s unique digital trajectory, high social-media penetration, and strong retail modernization efforts, which make it a theoretically pertinent case among emerging markets. We also clarified how insights from the Thai retail sector may generalize to similar emerging economies while acknowledging context-specific institutional conditions. The revised material is presented in Introduction Section, lines 46–50 and 51–57 of the updated version. 

Comment 2: [While the dual-method approach is introduced, its necessity and advantages for addressing the research gap could be more explicitly justified.]
Response 2: Agree. We appreciate this thoughtful suggestion. In the revised Introduction, we expanded the explanation regarding why a dual-method approach is essential for addressing the identified research gap. Specifically, we clarified that combining e-Delphi–FCM with SEM allows the study to first achieve expert-driven construct refinement and then empirically validate the proposed relationships using large-scale data. This integrated approach ensures conceptual clarity, methodological robustness, and stronger causal interpretability compared to a single-method design. The added content now articulates both the necessity and advantages of using a dual-method strategy within the context of emerging-market digital transformation research. Please see Introduction Section, lines 46-61 of the revised manuscript for the updated content.

Comment 3: [The logical transitions between some constructs could be strengthened. For instance, the role of Collaboration Networks in fostering both Service Innovation and Organizational Resilience would benefit from a more nuanced theoretical explanation.]
Response 3: Agree. We appreciate this valuable suggestion. In response, we strengthened the theoretical transitions in the Literature Review by providing a more detailed explanation of how Collaboration Networks (CNS) support both Service Innovation (SIN) and Organizational Resilience (ORE). Drawing on RBV and DCT, the revised text clarifies that collaboration enables firms to acquire external knowledge, integrate shared resources, co-create innovative solutions, and enhance adaptive capabilities—mechanisms that jointly explain why CNS function as antecedents to both SIN and ORE. These additions improve conceptual coherence and reinforce the causal pathways proposed in the framework. This revision is now reflected in Literature Review Section, lines 143-160 of the manuscript. 

Comment 4: [The review would also be enhanced by incorporating more recent studies (2024–2025) on digital transformation and sustainability, especially in retail and emerging markets.]
Response 4: Agree. We appreciate this helpful suggestion. The Literature Review has been strengthened by integrating recent studies published in 2024–2025 that address digital transformation, sustainability integration, innovation, and retail dynamics in emerging markets. These additions ensure that the review reflects the most current scholarly developments and aligns more closely with contemporary research trends. All new sources have been added to the Reference Section.

Comment 5: [While the Fuzzy C-Means theory is explained, its relevance to management and sustainability research—beyond a purely technical description—should be better emphasized.]
Response 5: Agree. We appreciate this helpful suggestion. We strengthened the Literature Review by clarifying how Fuzzy C-Means (FCM) contributes to management and sustainability research beyond its technical mechanics. The revised text now highlights FCM’s ability to capture ambiguity in expert judgment, support graded consensus, and enhance construct development—attributes that make it suitable for modeling complex organizational and sustainability-related phenomena. We emphasized the broader value of FCM by noting that it (A) models uncertainty and improves interpretive accuracy, (B) has evolved beyond engineering applications to address managerial and sustainability-focused analysis, and (C) enhances methodological rigor and interpretive depth when examining multi-dimensional organizational constructs. The corresponding revisions have been added to Section 2.10 (lines 337–339, 344–347 and 350–351) in the updated document.

Comment 6: [The expert selection process, while mentioned, should be described in more detail, including specific criteria for expertise, industry representation, and regional diversity.]
Response 6: Agree. We expanded the description of the expert-selection process by clarifying the criteria used to identify qualified participants, including academic specialization, professional experience, sector relevance, and representation across retail, digital, and sustainability domains. This revision is reflected in Section 3.1.1, lines 437-444 of the manuscript. 

Comment 7: [The parameter choices for the FCM algorithm (e.g., m=2.0, initial centroids C1=4.5 and C2=6.5) should be justified with references to methodological literature.]
Response 7: Agree. We added justification for the selected FCM parameters by referencing methodological literature supporting the use of m = 2.0 for interpretability and model stability, and we clarified the rationale for choosing initial centroids C1 = 4.5 and C2 = 6.5 based on expert consensus patterns and prior FCM applications. The modifications can be found in the revised manuscript, Section 3.1.4, lines 490–492. 

Comment 8: [The data collection procedure would benefit from greater transparency—such as response rates, timing, and measures taken to address non-response bias.]
Response 8: Agree. We expanded the description of data collection by adding the total timing, the structure of the multi-round Delphi process, and additional steps taken to ensure reliable participation. Further details regarding the response process and procedural consistency were incorporated to improve transparency. These updates have been included in Section 3.1.3, lines 462-480 of the current manuscript.

Comment 9: [The authors should address potential common method bias, for example, by reporting Harman’s single-factor test results.]
Response 9: Agree. Although Harman’s single-factor test is a common diagnostic for assessing common method bias (CMB), we adopted a more rigorous approach by using Confirmatory Factor Analysis (CFA) to evaluate potential CMB. CFA-based assessments provide a stronger and more reliable indication of measurement quality than Harman’s test alone. Specifically, CFA evaluated factor loadings, CR, AVE, α, and R², and all constructs met established thresholds, confirming that no single factor dominated the variance structure. This provides evidence that CMB is unlikely to threaten the validity of our measurement model. The detailed revision is shown in Section 3.2.4, lines 610-618 of the updated manuscript.

Comment 10: [The analysis would be strengthened by including formal mediation tests (e.g., using bootstrapping) to verify the indirect effects of DTN and SMU on SBP through the proposed dynamic capabilities.]
Response 10: Agree. We have strengthened the Results section (4.2.5. Mediation Analysis) by incorporating formal mediation tests using a 5,000-sample bootstrap procedure. These analyses quantify the indirect effects of both SMU and DTN on SBP through multiple dynamic capability pathways and report the corresponding 95% confidence intervals. This provides statistical confirmation of the multi-stage mediating mechanisms proposed in the model. This adjustment is presented in the revised version under Section 4.2.5 (lines 796–819). 

Comment 11: [A comparison with alternative models would also help demonstrate the superiority of the proposed framework.]
Response 11: Agree. We added a robustness check comparing the proposed full-mediation model with two alternative specifications (direct-only and partial-mediation). The results show that the proposed model consistently achieves superior model-fit indices, demonstrating its theoretical and empirical advantage. We have added the updated explanation in Section 4.2.5, lines: 820–824. 

Comment 12: [Visually, the path model (Figure 5) could be improved by adding R² values for endogenous variables, and the tables could better distinguish between direct, indirect, and total effects.]
Response 12: Agree. We revised Figure 5 by adding R² values for all endogenous constructs and updated the tables 9 to clearly separate Specific indirect effects and mediation paths. These adjustments improve readability and allow clearer interpretation of the structural relationships. The revised material is presented in Section 4.2.3, figure 5 (lines 777) and Section 4.2.5, table 9 (lines 841) of the updated version. 

Comment 13: [The theoretical implications of integrating RBV and DCT in the context of digital transformation should be more explicitly articulated. The authors should elaborate on how their findings extend or refine these theories.]
Response 13: Agree. We strengthened the discussion by clarifying how the empirical findings extend both RBV and DCT. The revised text explains how DTN and SMU function as strategic digital assets (RBV), while dynamic capabilities (CNS, SIN, CEX, ORE) represent the mechanisms through which these resources are sensed, seized, and reconfigured (DCT) to generate CAE and SBP. We further elaborated how the RBV–DCT integration provides a multi-stage causal logic unique to digital transformation in emerging-market retail environments. These updates have been included in Section 5.1 (lines 846-854, 868-872, 876-878, and 895-904) of the current manuscript. 

Comment 14: [The practical recommendations, while insightful, could be more context-specific to the Thai retail environment, considering local digital infrastructure, regulatory conditions, and market characteristics.]
Response 14: Agree. We revised the managerial implications section to include context-specific recommendations linked to Thailand’s digital infrastructure, regulatory initiatives, and retail ecosystem. The updated discussion explains how national strategies (e.g., Thailand 4.0, DEPA, national E-commerce policies) shape digital readiness and influence how firms can translate DTN and SMU into sustainable performance. This adjustment is presented in the revised version under Section 5.2, lines 945-953.

Comment 15: [The future research directions are appropriate but could be more precise—e.g., longitudinal designs, cross-cultural comparisons, moderators such as organizational culture or digital maturity.]

Response 15: Agree. We expanded the future research section by incorporating more precise directions, including longitudinal and dynamic-panel designs, cross-cultural comparisons, and recommended moderators (organizational culture, leadership orientation, digital maturity). These enhancements clarify how future studies can extend the model and test boundary conditions across regions and time. The refined text has been inserted into Section 5.2, specifically lines 945-953.

Comment 16: The writing is generally clear but would benefit from careful copyediting to improve sentence flow and reduce repetition (e.g., in the Limitations section).
Response 16: Agree. We performed careful copyediting across the manuscript to improve sentence flow, reduce redundancy, and refine clarity—particularly in the Limitations section. Wording, transitions, and repetitive expressions were streamlined to enhance readability. Please see Limitations and Suggestions Section, lines 1059-1068 of the revised manuscript for the updated content. 

Comment 17: [Some references appear incomplete (e.g., missing volume or page numbers) and should be verified for consistency with the target journal’s style.]
Response 17: Agree. All references were checked and corrected for completeness, including volume numbers, issue numbers, page ranges, and DOIs. We also ensured consistency with the MDPI reference style throughout the entire reference list. The detailed revision is shown in Reference Section 

Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

The manuscript presents an ambitious and timely investigation. However, improvements are required as follows:

• The manuscript integrates the Resource-Based View (RBV) and Dynamic Capabilities Theory (DCT) but does not clearly explain how these perspectives jointly operate. The discussion remains descriptive rather than explanatory.
• The authors should explicitly articulate the causal mechanisms linking DTN and SMU to SBP through the mediating capabilities. For instance: How do specific digital resources (SMU, DTN) translate into specific dynamic capabilities (SIN, ORE, etc.)? What boundary conditions might limit these effects (e.g., organizational culture, digital literacy, infrastructure)?
• The theoretical contribution should move beyond restating RBV and DCT assumptions to demonstrating a new integrative logic or framework (e.g., “digital resource orchestration for sustainable competitiveness”).
• The proposed model includes multiple mediators (CNs, SIN, CEX, ORE, CAE) but lacks theoretical parsimony. It appears as a chain of constructs without clear hierarchical logic.
• While the dual-method design (e-Delphi + FCM + SEM) is innovative, the methodological details are insufficient: The process for selecting the 23 experts in the e-Delphi should be elaborated (criteria, expertise fields, sampling strategy). In addition, the link between Delphi/FCM results and SEM constructs should be clarified. How did FCM outputs refine measurement indicators for the survey?
• The results are briefly summarized but lack in-depth interpretation: Which mediators exerted the strongest effects? How do these findings advance our understanding of digital sustainability in emerging markets? Are there context-specific insights (Thailand’s retail digital maturity, institutional constraints, consumer behavior)? The discussion should explicitly connect results to previous literature, highlighting both theoretical advancement and practical significance.
• Although the title and abstract emphasize Sustainable Business Performance, the discussion of sustainability (economic, social, environmental pillars) is limited. The authors should elaborate on how digital and social media strategies contribute to the triple bottom line. Discuss alignment with UN SDGs more concretely (e.g., SDG 9—Industry, Innovation, and Infrastructure; SDG 12—Responsible Consumption and Production). Integrate sustainability indicators into the measurement model or discussion.
• The discussion lacks managerial insights and policy implications. The authors should: Explain how retail managers can strategically integrate DTN and SMU for sustainable advantage. Provide actionable recommendations for emerging-market policymakers on supporting digital sustainability ecosystems.

 

Author Response

Comment 1: [The manuscript integrates RBV and DCT but does not clearly explain how these perspectives jointly operate. The discussion remains descriptive rather than explanatory.]
Response 1: Agree. We appreciate this insightful comment. In the revised manuscript, we enhanced the theoretical explanation of how RBV and DCT jointly operate by clarifying that DTN and SMU function as strategic digital resources (RBV) that are sensed, seized, and reconfigured through DCT mechanisms into higher-order dynamic capabilities (CNS, SIN, CEX, ORE). We also incorporated an explicit articulation of the multistage causal chain—digital resources → dynamic capabilities → CAE → SBP—and added contextual boundary conditions such as organizational culture, digital literacy, and infrastructure maturity to explain when these mechanisms strengthen or weaken. These refinements collectively shift the discussion from a descriptive presentation to a clearer explanatory framework grounded in RBV–DCT integration. These revisions are located in Section 2.9 (lines 306-314), and Section 5.1 (lines 870-874) of the revised manuscript.

Comment 2: [The authors should explicitly articulate the causal mechanisms linking DTN and SMU to SBP through the mediating capabilities. For instance: How do specific digital resources (SMU, DTN) translate into specific dynamic capabilities (SIN, ORE, etc.)? What boundary conditions might limit these effects (e.g., organizational culture, digital literacy, infrastructure)?]
Response 2: Agree. We clarified the causal mechanisms by explaining how DTN and SMU operate as strategic digital resources (RBV) that are sensed, seized, and reconfigured into dynamic capabilities (DCT), including CNS, SIN, CEX, and ORE. The revised discussion outlines a unified multistage pathway—digital resources → dynamic capabilities → CAE → SBP—showing how each resource triggers specific capability formation and contributes to sustainable performance. We also added contextual boundary conditions, such as organizational culture, digital literacy, and infrastructure maturity, to explain when these mechanisms may strengthen or weaken. We have incorporated these changes in Section 5.1, lines 868-875 and 883-887 of the updated manuscript. 

Comment 3: [The theoretical contribution should move beyond restating RBV and DCT assumptions to demonstrating a new integrative logic or framework (e.g., “digital resource orchestration for sustainable competitiveness”).]
Response 3: Agree. We clarified the theoretical contribution by articulating a clearer integrative logic that links RBV and DCT into a unified framework of digital resource orchestration for sustainable competitiveness. The revised discussion explains how SMU and DTN operate as foundational digital assets that are transformed—through sensing, seizing, and reconfiguring—into higher-order capabilities that drive sustainable performance. This positions the study not only as an application of RBV and DCT, but as an advancement that demonstrates how digital resources evolve into sustainability-oriented capability systems. The corresponding revisions have been added to Section 5.1 (lines 888-891).

Comment 4: [The proposed model includes multiple mediators (CNs, SIN, CEX, ORE, CAE) but lacks theoretical parsimony. It appears as a chain of constructs without clear hierarchical logic.]
Response 4: Agree. We clarified the theoretical structure of the model by articulating a more coherent hierarchical logic across the mediating capabilities. The revised explanation distinguishes foundational relational capabilities (CNS), innovation-oriented capabilities (SIN), adaptive and experiential capabilities (CEX, ORE), and outcome-oriented strategic capabilities (CAE). This layered structure enhances theoretical parsimony and demonstrates how the mediators operate as an interconnected capability progression rather than a simple chain of constructs. These updates have been included in Section 2.11 (lines 387–392) and Section 5.1 (lines 872-875) of the current manuscript. 

Comment 5: [While the dual-method design (e-Delphi + FCM + SEM) is innovative, the methodological details are insufficient: The process for selecting the 23 experts in the e-Delphi should be elaborated (criteria, expertise fields, sampling strategy). In addition, the link between Delphi/FCM results and SEM constructs should be clarified. How did FCM outputs refine measurement indicators for the survey?]
Response 5: Agree. We expanded the methodological explanation by clarifying the criteria for selecting the 23 e-Delphi experts, including domain expertise in retail, digital transformation, sustainability, and managerial experience. We also outlined the sampling strategy to ensure balanced representation across academic, industry, and executive groups. In addition, we clarified how FCM outputs were used to refine the measurement indicators—specifically by translating expert consensus patterns into validated item centroids and membership strengths, which were subsequently incorporated into the SEM survey instrument to improve construct clarity and content validity. The relevant updates are now included in Section 2.10 (lines 347-353), and Section 3.1.1 (lines 434-444) of the revised manuscript. 

Comment 6: [The results are briefly summarized but lack in-depth interpretation: Which mediators exerted the strongest effects? How do these findings advance our understanding of digital sustainability in emerging markets? Are there context-specific insights (Thailand’s retail digital maturity, institutional constraints, consumer behavior)? The discussion should explicitly connect results to previous literature, highlighting both theoretical advancement and practical significance.]
Response 6: Agree. We expanded the interpretation of results by clarifying which mediators exerted the strongest influence and how each capability contributes to sustainable performance. The revised discussion highlights that collaboration networks (CNS) and service innovation (SIN) form the most influential pathways for SMU, while customer experience (CEX) and organizational resilience (ORE) play a central role in translating DTN into CAE and SBP. We also incorporated context-specific insights reflecting Thailand’s retail digital maturity, institutional constraints, and evolving consumer behavior to explain why certain mediators are more prominent in an emerging-market setting. In addition, the findings were explicitly connected to recent literature to demonstrate how the study advances theoretical understanding of digital sustainability and provides meaningful practical implications. The detailed revisions are shown in Section 4.2.5 (lines 804-811), and Section 5.2 (lines 967-972) of the updated manuscript.

Comment 7: [Although the title and abstract emphasize Sustainable Business Performance, the discussion of sustainability (economic, social, environmental pillars) is limited. The authors should elaborate on how digital and social media strategies contribute to the triple bottom line. Discuss alignment with UN SDGs more concretely (e.g., SDG 9—Industry, Innovation, and Infrastructure; SDG 12—Responsible Consumption and Production). Integrate sustainability indicators into the measurement model or discussion.]

Response 7: Agree. We strengthened the sustainability dimension by clarifying how DTN and SMU contribute to all three pillars of the triple bottom line. The revised discussion explains that digital technologies enhance operational efficiency and innovation (economic), enable inclusive engagement and knowledge-sharing across stakeholders (social), and support environmentally responsible practices through data-driven processes (environmental). We also integrated a clearer alignment with UN SDGs—particularly SDG 9 (Industry, Innovation, and Infrastructure) and SDG 12 (Responsible Consumption and Production)—to demonstrate how digital and social media strategies advance sustainable development objectives. These enhancements situate the model within a comprehensive sustainability perspective and clarify how digital transformation translates into measurable economic, social, and environmental outcomes. The refined text has been inserted into Section 5.1, specifically lines 905-918. 

Comment 8: [The discussion lacks managerial insights and policy implications. The authors should: Explain how retail managers can strategically integrate DTN and SMU for sustainable advantage. Provide actionable recommendations for emerging-market policymakers on supporting digital sustainability ecosystems.]
Response 8: Agree. We enriched the discussion by adding more concrete managerial guidance on how retail managers can strategically integrate DTN and SMU—for example, by aligning social media analytics with service innovation, using DTN to redesign customer journeys, and embedding resilience and sustainability metrics into digital initiatives to build long-term competitive advantage. We also expanded the policy implications to provide actionable recommendations for emerging-market policymakers, emphasizing the need to invest in digital infrastructure, promote interoperable data and regulatory frameworks, support SME capability-building, and incentivize digital solutions that advance sustainable business performance and broader sustainability goals. The detailed revision is shown in Section 6, lines 1043-1050 of the updated manuscript.

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

I would like to thank you for addressing the comment.

Author Response

Thank you very much for your thoughtful review. We appreciate your positive assessment and confirm that no further revisions were required based on your comments.

Reviewer 2 Report

Comments and Suggestions for Authors

While the manuscript is strong in its current form, the following revisions would further needed.

1. The introduction of the DROSC framework is a highlight, but it would benefit from deeper engagement with existing digital transformation theories, such as digital capability models or IT-enabled organizational capabilities. Clarifying how DROSC extends or differs from these established frameworks would strengthen its theoretical contribution and boundary conditions.
2. The exclusive focus on Thailand’s retail sector provides valuable context-specific insights but limits the generalizability of findings. The authors should explicitly acknowledge this in the "Limitations and Future Research" section and recommend cross-national or cross-industry replications to validate the framework.
3. The rationale for setting the FCM consensus threshold at ≥6.0 should be briefly justified—whether it is based on prior studies, pilot testing, or sensitivity analysis.
4. The relatively weak direct effect of DTN on competitive advantage (β = 0.260) warrants further discussion. The authors could explore whether this is due to the predominance of mediation pathways, the time-lagged nature of digital transformation benefits, or contextual factors in emerging markets.

Author Response

Comment 1: [The introduction of the DROSC framework is a highlight, but it would benefit from deeper engagement with existing digital transformation theories, such as digital capability models or IT-enabled organizational capabilities. Clarifying how DROSC extends or differs from these established frameworks would strengthen its theoretical contribution and boundary conditions.]

Response 1: Agree. We sincerely thank you for this constructive and insightful feedback. In response, we substantially strengthened both the theoretical foundations and comparative positioning of DROSC in Sections 2.9 and 5.1.
1. In Section 2.9 (lines 332-342) of the updated manuscript, we expanded the RBV–DCT integration to explicitly introduce the need for a process-oriented view of digital capability development, emphasizing emerging scholarship that moves beyond static digital capability or IT-enabled capability models. This enhancement clarifies the theoretical motivation for an orchestration-based perspective. 
2. In Section 5.1 (lines 932-940), we formally articulated how DROSC extends existing frameworks by conceptualizing DTN and SMU not as stable capability bundles but as dynamic, sequential, and orchestrated processes that unfold through sensing, seizing, and reconfiguring mechanisms. We further clarified how DROSC differs from traditional models and identified relevant boundary conditions within emerging-market retail environments. 
These revisions collectively strengthen the theoretical contribution of the study and provide a clearer articulation of how DROSC advances digital transformation research.

Comment 2: [The exclusive focus on Thailand’s retail sector provides valuable context-specific insights but limits the generalizability of findings. The authors should explicitly acknowledge this in the ‘Limitations and Future Research’ section and recommend cross-national or cross-industry replications to validate the framework.]

Response 2: Agree. We appreciate this insightful comment. In response, we explicitly acknowledged the limited generalizability arising from the Thailand-only retail context and incorporated your recommendation into both the “Future Research Directions” and “Limitations and Suggestions” sections. These revisions clarify that the proposed framework should be validated through cross-national and cross-industry replications to strengthen its external applicability. The updated text now highlights how differences in institutional environments, digital readiness, and cultural orientation may influence the DROSC-related capability pathways. These revisions are located in Section 5.4 (lines 1038-1041,1061-1063), and Section 5.1 (lines 947-961) and in the section of Limitations and Suggestions (lines 1107-1110,1117-1120, and 1127-1130) of the revised manuscript.

Comment 3: [The rationale for setting the FCM consensus threshold at ≥6.0 should be briefly justified—whether it is based on prior studies, pilot testing, or sensitivity analysis.]

Response 3: Agree. Thank you for this important methodological observation. We have now clarified the rationale for the ≥6.0 FCM consensus threshold in Section 3.1.2 (Line. 471-476) of the current manuscript. The revision explains that this cutoff aligns with established Delphi–FCM consensus practices and is supported by our pilot sensitivity checks, which showed that lower thresholds admitted items with high dispersion, while ≥6.0 consistently retained indicators demonstrating stable expert agreement suitable for SEM measurement.

Comment 4: [The relatively weak direct effect of DTN on competitive advantage (β = 0.260) warrants further discussion. The authors could explore whether this is due to the predominance of mediation pathways, the time-lagged nature of digital transformation benefits, or contextual factors in emerging markets.]

Response 4: Agree. The observation regarding the relatively modest direct effect of DTN on CAE is well taken. We have now clarified this point in Section 4.2.3 (Line. 773-780) by explaining that the model is structurally designed such that DTN exerts its primary influence through Customer Experience (CEX), the only downstream capability directly shaped by DTN. As a result, the indirect pathway (DTN → CEX → CAE) accounts for a substantial share of the total effect, which inherently lowers the direct coefficient. This interpretation aligns with established findings in digital transformation research, where competitive advantages typically emerge after digital capabilities are progressively absorbed, reconfigured, and aligned with strategic objectives—particularly in emerging-market settings.

Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

No further improvements needed!

Author Response

We sincerely appreciate your insightful feedback and are grateful that no additional changes were requested. No further revisions were needed in response to your comments.