Agility in the Digital Era: Bridging Transformation and Innovation in Supply Chains

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

Dear authors, thank you for the opportunity to review your manuscript. I have carefully read your manuscript and I have a few suggestions and comments for your consideration. Thank you, and best regards.

1. Abstract and Introduction:
• The abstract is well-written but could benefit from a clearer statement of the practical implications of the findings.
• The introduction provides a strong overview but might benefit from a brief mention of the specific research gaps addressed.
2. Literature Review:
• Expand the literature review to include more recent sources, particularly post-2020, to strengthen the discussion of emerging trends in digital supply chains.
• Consider clarifying how your conceptual framework builds upon or diverges from existing models in the field.
3. Methodology:
• The research design is robust. These parts are well structured.
4. Results and Discussion:
• The results section is comprehensive but could be enhanced with additional visual aids (e.g., more graphs or tables) to clarify key findings.
• Discuss the implications of the weaker relationship observed between digital manufacturing and supply chain agility. This could be an opportunity for deeper theoretical exploration.
5. Limitations and Future Research:
• Expand on the limitations to discuss any potential bias introduced by the sampling method or cultural factors.
6. Clarity and Style:
• Some technical terms (e.g., "agent-based technology" or "green supply chain practices") might benefit from brief definitions for non-specialist readers.
• Revisit the manuscript for minor grammatical or typographical errors to ensure polished readability.

Comments on the Quality of English Language

This manuscript will benefit from proofreading.

Author Response

1. Add clearer practical implications of the findings in the abstract.

The practical implications of the findings have been highlighted in the abstract.

2. In the introduction, briefly mention the specific research gaps your study addresses.

The added passage “While prior studies have explored individual digital tools in supply chains, the collective impact of digital supply chain (DSC) dimensions on supply chain agility and innovation performance remains insufficiently examined (Alyasein et al., 2025; Rana et al., 2025; M. Wang et al., 2025; M. Wang & Prajogo, 2024). Moreover, the potential mediating role of agility in linking digital adoption to innovation has not been empirically tested using a multidimensional approach (Waty et al., 2022). This study addresses these gaps by evaluating six distinct DSC components and assessing their direct and indirect effects on innovation performance through the lens of supply chain agility. By doing so, it provides a more integrated understanding of how digital transformation drives innovation in volatile market contexts.”

3. Expand the literature review with more recent sources, especially post-2020, to reflect emerging trends in digital supply chains.

Thank you for your suggestion. We have expanded the literature review by incorporating recent sources published after 2020 to better reflect emerging trends in digital supply chains. The updated reference list now includes 71 sources, with 47 (approximately 66%) published from 2020 onward, ensuring the review is current and aligned with the latest research.

4. Clarify how your conceptual framework builds upon or differs from existing models.

We added this passage to clarify how your conceptual framework builds upon or differs from existing models:

The conceptual model in figure 1 offers a multidimensional framing of digital supply chain components and their joint influence on agility is more granular and comprehensive than existing models.

In contrast, many existing studies focus more narrowly on the influence of IT ca-pabilities or supply chain digitalization as a whole on agility and innovation perfor-mance. For example, Khan et al. (2023) examined the mediating role of supply chain agility between general IT capabilities and innovation performance, but did not dis-aggregate the components of digital capability into specific operational dimensions [15].

Similarly, Wang and Prajogo (2024) explored the effects of supply chain digitaliza-tion on firm performance mediated by agility and innovation capability. However, their model treats digitalization as a singular construct and does not account for the nuanced sub-dimensions like those in the current model [7].

Moreover, some models reverse the directionality, treating innovation capability as the mediator between digitalization and agility, rather than agility as a key mechanism enhancing innovation performance [6].

5. Add more visual aids (e.g., graphs or tables) to make the findings clearer.

we enhanced the visual presentation of the findings by including a total of six tables and two figures. Notably, we have added Figure 2, which presents the Structural Model Results with Path Coefficients and R² values, to clearly illustrate the relationships among constructs and improve the clarity of the results section.

6. Provide a deeper theoretical discussion on the weaker relationship found between digital manufacturing and supply chain agility.

We modified the full section related to theoretical implications and included a targeted theoretical discussion for each result based on existing literature. Specifically, for the weaker relationship observed between digital manufacturing and supply chain agility, we addressed potential theoretical explanations such as implementation complexity, integration challenges, and the time lag between adoption and agility impact. Relevant studies highlighting similar limitations in translating digital manufacturing capabilities into agile supply chain responses were also incorporated to support this discussion.

7. Expand the limitations section to include potential biases from the sampling method or cultural factors.

We have expanded the limitations section to address potential biases associated with the sampling method and cultural context. Specifically, we acknowledge that the use of non-probabilistic sampling and the study’s confinement to Moroccan industries may introduce selection bias and cultural influences that limit the generalizability of the findings. These contextual factors may shape perceptions of digital transformation and agility differently than in other regions. This addition clarifies the need for caution in extending conclusions beyond the study’s national and cultural setting.

8. Define some technical terms (e.g., agent-based technology, green supply chain practices) for non-specialist readers.

We appreciate the reviewer’s suggestion to define technical terms for non-specialist readers. In response, we have incorporated clear and concise definitions for the following key concepts within the manuscript:

• Agent-based technology: Explained as decentralized systems in which autonomous software agents interact and make decisions independently, often used to simulate supply chain dynamics.
• Green supply chain practices: Defined as environmentally responsible strategies applied across sourcing, production, distribution, and end-of-life stages to minimize environmental impact.
• Internet-driven solutions: Clarified as cloud-based platforms and web-integrated applications that facilitate real-time connectivity, data sharing, and operational coordination.
• Environmental scanning: Introduced as the systematic process of monitoring external trends, technologies, and competitive forces to support strategic adaptability.
• Resource reconfiguration: Defined as the strategic redeployment and adjustment of internal assets and capabilities to align with changing market demands.

9. Proofread the manuscript to correct any minor grammatical or typographical errors.

The manuscript has been thoroughly proofread to correct minor grammatical and typographical errors, ensuring clarity, coherence, and overall language quality.

Reviewer 2 Report

Comments and Suggestions for Authors

1. It is suggested that an operational definition for all six dimensions of the digital supply chain be provided for clear understanding and to reduce confusion.
2. Since the present study is not embedded with a related theory, it is suggested that the hypothesis development be strengthened.
3.  Line 326, "The target population comprised supply chain management (SCM) managers and related professionals." Please specify what's 'related professionals.'
4. In line 334, please explain what a 'robust sample' is.
5. How do you justify the myriad sectors of "Agri-Food Sector, Textile, Automotive Industry, Aerospace Industry and Others" all have the same digital supply chain management perspective?

Author Response

1. Provide operational definitions for all six dimensions of the digital supply chain to ensure clarity and reduce confusion.

we have added the operational definitions for all six dimensions of the digital supply chain to ensure clarity and avoid ambiguity. These definitions are now included in Section 2.1.1: Digital Supply Chain of the revised manuscript.

2. Since the study lacks a clear theoretical foundation, strengthen the hypothesis development (possibly by linking it to existing theories or frameworks).

We have revised the manuscript to integrate established theoretical frameworks that underpin the proposed relationships.

Specifically, we have anchored the conceptual model in three core theories:

1. Resource-Based View (RBV): To support hypotheses related to internal digital capabilities (H1 and H2), we have drawn on the RBV to explain how digital performance measurement (DPM) and digital information technology (DIT) serve as strategic resources that enhance firms' agility and responsiveness.
2. Dynamic Capabilities Theory: This perspective has been incorporated to explain how firms must reconfigure digital capabilities in rapidly changing environments, supporting the mediating role of supply chain agility (H7) and the agility-enabling function of internal and external digital resources (H1 to H6).
3. Network Theory and Supply Chain Integration (SCI): To justify the influence of external actors (suppliers and clients), we have applied Network Theory and SCI literature to demonstrate how digitally enabled collaboration fosters agility across organizational boundaries (H3 and H6).

In addition, we have explicitly linked each hypothesis to these theoretical foundations within the revised text to ensure stronger coherence between theory and empirical expectations

3. Line 326: Clarify what is meant by "related professionals" alongside SCM managers.

We have clarified the term “related professionals” in the revised paragraph by adding an explanation. It refers to professionals who work closely with SCM managers, such as logistics coordinators, procurement specialists, and operations planner.

4. Line 334: Define or explain what constitutes a "robust sample" in your context.

We have replaced the term “robust sample” with “statistically representative sample” and clarified that the sample size was determined using Slovin’s formula. This ensures adequate representation of the target population and supports the generalizability of the findings across different organizational types and sizes.

5. Justify why sectors as diverse as Agri-Food, Textile, Automotive, Aerospace, and Others are assumed to share the same digital supply chain management perspective. This could require explaining commonalities or differences in digital adoption.

We appreciate the reviewer’s insightful comment regarding the justification for combining diverse sectors into a single analytical framework. To address this point explicitly, we have added the following passage in the section “3.2.  Sample and data collection” to clarify our rationale:

"Respondents from diverse sectors such as Agri-Food, Textile, Automotive, Aerospace, and Others were analyzed collectively due to their engagement with similar digital supply chain components influencing agility and innovation performance. Although sectoral differences exist, all industries rely on capabilities such as digital information technology, digital logistics, and digital manufacturing to enhance responsiveness and competitiveness. Grouping respondents thus allows identification of generalizable patterns regarding how digital supply chain elements foster agility and drive innovation outcomes."

This addition underscores commonalities in digital supply chain adoption across sectors, justifying the collective analysis approach and reinforcing the study's objective to identify broader, cross-industry patterns.

Reviewer 3 Report

Comments and Suggestions for Authors

Dear Editor,

Thank you very much for allowing me to evaluate this paper. This research investigates the impact of digital supply chain elements on agility and innovation performance in Moroccan industries. Through structural equation modeling of data collected from 634 professionals, it is highlighted that agility serves as a key mediating factor in converting digital adoption into innovative outcomes. However, based on the following feedback, the paper does not deserve publication. The introduction outlines the research gap and its contribution in vague terms. The research employs a cross-sectional survey design, limiting the ability to make causal inferences or observe changes over time regarding digital adoption or supply chain agility. Collecting data with self-administered questionnaires can introduce response bias, leading participants to overstate their digital maturity and innovation levels. Additionally, the study focuses solely on Moroccan industries, which may not accurately represent global supply chain dynamics; consequently, its external validity is limited. Intriguingly, digital manufacturing shows a negative direct effect on supply chain agility and an indirect negative impact on innovation performance. This finding is neither thoroughly explained nor deeply explored within the discussion. Furthermore, digital clients and suppliers do not demonstrate a significant relationship with supply chain agility. The paper fails to thoroughly investigate or clarify the reasons for the lack of impact in these areas despite their critical consideration in the existing literature. Incorporating case studies or interviews could enhance the interpretation of the quantitative data and illuminate the organizational challenges encountered in adopting digital supply chain solutions. Although a comprehensive reference list is provided, some citations appear outdated or redundant, and there is a need for stronger cohesion between the theoretical framework and empirical findings. Curiously, digital manufacturing exhibits a negative direct impact on supply chain agility and an indirect negative effect on innovation performance. I believe the discussion lacks a thorough explanation and detailed exploration of this finding. Furthermore, no substantial correlation is found between digital clients, suppliers, and supply chain agility. The paper does not adequately analyze or explain why these factors appear to have a minimal impact, despite their significant importance in the current literature. Incorporating case studies or interviews could enhance the interpretation of the quantitative data and shed light on the organizational challenges faced in embracing digital supply chain solutions. Even though a comprehensive reference list is provided, some citations appear outdated or repetitive, and there is a need for stronger cohesion between the theoretical framework and empirical findings.

Comments on the Quality of English Language

It can be better.

Author Response

1. The research gap and contribution are described in vague terms — they need to be clearly and precisely articulated.

Thank you for this valuable remark. To address your concern, we have explicitly clarified the research gap in the revised introduction as follows:

"Previous studies have primarily focused on examining individual digital tools or generalized digital supply chain impacts without thoroughly investigating the collective influence of specific digital supply chain dimensions on supply chain agility and subsequent innovation performance (Alyasein et al., 2025; Rana et al., 2025; Wang & Prajogo, 2024). Additionally, the literature lacks empirical evidence examining the mediating role of supply chain agility in linking multiple digital dimensions—such as digital performance measurement, digital information technology, digital suppliers, digital manufacturing, digital logistics and inventory, and digital clients—to innovation performance (Waty et al., 2022). Therefore, this study specifically fills these gaps by empirically testing these precise relationships and explicitly assessing agility’s mediating role, contributing to a more nuanced understanding of digital supply chain dynamics."

We believe this revision precisely articulates our research gap and clearly highlights our study's contributions.

2. The cross-sectional survey design limits the study’s ability to make causal inferences or track changes over time.

The reviewer is correct; the cross-sectional survey design indeed limits our study's ability to establish causal relationships or to observe longitudinal changes. Recognizing this, we have explicitly acknowledged this limitation in the limitations section (section 5.3), where we clearly state that future research employing a longitudinal design would provide deeper insights into causal relationships and dynamic changes over time.

3. The use of self-administered questionnaires introduces potential response bias, especially with possible overstatements of digital maturity and innovation performance.

The reviewer’s observation is correct; using self-administered questionnaires introduces potential response bias, particularly concerning possible overstatements of digital maturity and innovation performance. However, obtaining objective or real operational data was challenging due to confidentiality concerns expressed by participating organizations. To overcome this barrier, we relied on self-reporting as the most feasible and practical approach. This limitation has been explicitly acknowledged in the limitations section (section 5.3), and we have highlighted this methodological gap clearly in the introduction to inform future research directions, encouraging alternative or complementary methodologies to reduce bias.

4. The study’s focus on only Moroccan industries limits its external validity — the findings may not be generalizable to global contexts.

Thank you for the valuable comment. We fully acknowledge that the study’s focus on Moroccan industries may limit the generalizability of the findings to broader, global contexts. In response, this concern has been explicitly addressed in the "Research Limitations" section of the paper, where we highlight that cultural, infrastructural, and economic specificities could influence digital adoption and supply chain agility outcomes differently across regions. To build on this limitation, we are currently exploring opportunities to conduct future studies in other geographical and industrial contexts to examine whether similar patterns emerge and to strengthen the external validity of our model.

5. The negative direct effect of digital manufacturing on supply chain agility, and its indirect negative impact on innovation performance, is:

• Not thoroughly explained, and
• Not deeply explored in the discussion.

We have expanded the discussion to more thoroughly explain the unexpected negative direct effect of digital manufacturing on supply chain agility and its indirect negative impact on innovation performance. Specifically, in the "Research Discussion" section, we address how the complexity and rigidity of digital manufacturing systems—such as standardized processes, high integration requirements, and dependency on stable infrastructure—can constrain flexibility and slow responsiveness, which are core to agility. We also highlight that overemphasis on technological sophistication without aligning dynamic capabilities may create operational bottlenecks. Furthermore, institutional pressures and compliance standards in certain sectors may hinder quick adaptation. These explanations were added to provide a deeper and more nuanced understanding of this counterintuitive finding and to lay the groundwork for future investigation into the contextual and implementation-related factors that may moderate this relationship.

6. The lack of significant relationships between digital clients/suppliers and supply chain agility is:

• Not adequately investigated,
• Not clearly explained, despite being highlighted in existing literature.

We have taken care to address the lack of significant relationships between digital clients and suppliers and supply chain agility in both the discussion and limitations sections of the paper. Specifically, we explain that while digital clients and suppliers are important for broader supply chain integration, their impact on agility may be indirect or context-dependent. For example, the discussion notes that digital supplier contributions to agility often rely on complementary capabilities such as trust, strategic sourcing, or integration mechanisms—factors that may not be captured through direct linear relationships. Similarly, the limited impact of digital clients is attributed to the gap between front-end digitalization and the back-end internal coordination required for true agility. These points are supported by relevant literature and framed as areas for deeper exploration in future research.

7. Incorporate case studies or interviews to:

• Better interpret the quantitative data
• Illuminate the organizational challenges related to digital adoption.

While the current study is based on a quantitative, cross-sectional design using data from 634 supply chain professionals, we recognize the added value that qualitative methods such as case studies or interviews could bring. This point is acknowledged in the limitations section, particularly regarding the reliance on self-reported data and the potential for perception bias. We agree that incorporating qualitative insights would provide a richer understanding of the organizational challenges tied to digital adoption and help interpret the quantitative results more deeply. As a next step, we are planning a follow-up qualitative phase involving interviews with selected industry professionals to explore the contextual factors and implementation barriers in more depth, thereby complementing and extending the findings of this study.

8. Strengthen the connection between the theoretical framework and the empirical findings — there is a lack of cohesion.

We have addressed this point by reinforcing the alignment between the theoretical foundations—namely the Resource-Based View (RBV), Dynamic Capabilities Theory, Network Theory, and Lean and Agile Manufacturing principles—and the empirical results throughout the discussion section. For instance, the strong impact of Digital Performance Measurement (DPM) on supply chain agility is tied back to the RBV and Dynamic Capabilities perspectives, emphasizing its role as a strategic internal resource enabling adaptability. Similarly, the non-significant effects of Digital Suppliers and Digital Clients are explained through Network Theory and Supply Chain Integration literature, noting that without internal integration, external digitalization may not lead to agility. These connections ensure that our empirical insights are not isolated but grounded in and interpreted through established theoretical lenses, enhancing cohesion between theory and findings.

9. Update the references:

• Remove outdated or redundant citations,
• Ensure the literature reflects current discussions in the field.

In response, we conducted a thorough review and update of the reference list to ensure alignment with recent discussions in the field. Outdated or redundant citations were removed or replaced with more recent and relevant sources. As a result of this revision, the final reference list now includes 71 sources, with 47 (approximately 66%) published from 2020 onward.

Round 2

Reviewer 2 Report

Comments and Suggestions for Authors

The authors have addressed the reviewer's concerns and are ready to proceed to the next step.

Reviewer 3 Report

Comments and Suggestions for Authors

Dear Editor,

The authors have addressed all of my comments. Wishing them good luck.