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Digital Transformation and Sustainability in Post-Pandemic Supply Chains: A Global Bibliometric Analysis of Technological Evolution and Research Patterns (2020–2024)

Sustainability 2025, 17(7), 3009; https://doi.org/10.3390/su17073009

by Gary Christiam Farfán Chilicaus¹

, Gladys Sandi Licapa-Redolfo²

, Marco Agustín Arbulú Ballesteros³

, Christian David Corrales Otazú⁴

, Sarita Jessica Apaza Miranda⁴

, Marcos Marcelo Flores Castillo⁵

, Gabriela Lizeth Castro Ijiri³

, María De los Ángeles Guzmán Valle^6,*

and Julie Catherine Arbulú Castillo³

Reviewer 1: Anonymous

Reviewer 2: Anonymous

Reviewer 3:

Mersedeh Tariverdi

Sustainability 2025, 17(7), 3009; https://doi.org/10.3390/su17073009

Submission received: 19 January 2025 / Revised: 25 March 2025 / Accepted: 25 March 2025 / Published: 28 March 2025

Round 1

Reviewer 1 Report (Previous Reviewer 3)

Comments and Suggestions for Authors

1. The abstract should avoid complex and lengthy sentences, simplifying the language to enhance reading efficiency.
2. Authors should adhere to citation norms, ensuring that square brackets with numbers are directly connected to the preceding text, and punctuation marks should follow the square brackets.
3. The introduction should follow a logical structure including research background, research questions, research objectives, research methods, and research contributions.
4. Unique contributions and innovations should be more clearly and specifically outlined and summarized.
5. The co-author citation details (lines 529-533) and the publishing institutions (lines 549-553) are recommended to be presented in tables, accompanied by relevant literature citations, in accordance with academic paper standards.

Author Response

The abstract should avoid complex and lengthy sentences, simplifying the language to enhance reading efficiency.

This systematic review examines digital transformation in post-pandemic supply chains through bibliometric analysis of literature from 2020-2024. Using the PRISMA protocol, we analyzed publications from Scopus, Web of Science, and ScienceDirect databases. Results show that sustainability has become the dominant keyword in digital transformation research, with China, the United States, and India forming the main research triangle. The most influential technologies driving transformation are big data, blockchain, artificial intelligence, and Internet of Things (IoT). Cocitation network analysis revealed three major research clusters: the green cluster led by Gunasekaran and Angappa focusing on supply chain management; the red cluster led by Rahman and Muhammad Saddiq addressing implementation aspects; and the blue cluster led by Calatayud and Rodriguez examining innovation and adaptation. Organizations are shifting from purely operational approaches to more holistic transformations that integrate strategic and organizational dimensions. We identified important research gaps in developing regions and in the integration of emerging technologies with existing systems. This review enhances understanding of post-pandemic supply chain digitization while providing a framework for future research in this rapidly evolving field

2. Authors should adhere to citation norms, ensuring that square brackets with numbers are directly connected to the preceding text, and punctuation marks should follow the square brackets.

solved in word

3. The introduction should follow a logical structure including research background, research questions, research objectives, research methods, and research contributions.

Research Background

Digital transformation in the supply chain has gained significant relevance in the post-pandemic context, driven by the need to adapt to a changing business environment and new market demands. The COVID-19 pandemic has acted as a catalyst for the adoption of digital technologies, enabling companies to optimize their operations and improve their resilience to disruptions.

Digitization has accelerated the adoption of technologies in various industries, especially those that had to quickly adapt to telework and e-commerce to survive [1][2][3]. This is how the implementation of digital tools has enabled companies to collect and analyze data in real time, facilitating informed decision-making and improving operational efficiency [4][5]. In addition, digitization has transformed the customer experience, ensuring faster and more accurate deliveries, which is crucial in a market where consumer expectations have changed dramatically [3][6].

However, the transition to digitalization has not been without challenges. Companies have faced barriers such as the digital divide, lack of resources and resistance to change, which has highlighted the importance of staff training and education for the effective use of digital technologies [7][8]. As companies continue to reinvent their business models, collaboration and innovation become essential to meet new market challenges [6].

The digital transformation in supply chains has undergone a significant evolution between the pre- and post-pandemic periods, transitioning from an optional strategic initiative to a business survival imperative. Empirical evidence documents fundamental changes in the way organizations approach digitization of their operations. Before the pandemic, companies followed a pattern of gradual and selective technology adoption, with digital initiatives often isolated and fragmented [31]. However, the global health crisis acted as an unprecedented catalyst that radically transformed this landscape.

Longitudinal studies reveal that during and after the pandemic, there was a dramatic acceleration in the implementation of digital solutions, with approximately two-thirds of organizations significantly increasing their investments in digital transformation [33]. This change manifested itself not only in the speed of adoption but also in the implementation approach. While the prepandemic period was dominated by isolated digital initiatives [35], the post pandemic era has driven a more holistic and integrated approach, characterized by the adoption of complete digital ecosystems that simultaneously incorporate multiple technologies such as blockchain, IoT, and data analytics [29].

Strategic priorities have also undergone a substantial transformation. Research by [30] shows that before 2020, digitization was primarily oriented toward operational efficiency. In contrast,[32] identifies that in the post-pandemic period, resilience and adaptability have become the main drivers of digital transformation, with more than 78% of organizations prioritizing responsiveness to disruptions. This paradigm shift is clearly reflected in the [36] study, which documents how companies that had initiated their digital transformation prior to the pandemic demonstrated 2.5 times greater resilience than those that had not.

The relevance of the 2020-2024 period as a time frame for this analysis lies precisely in the fact that it captures this critical phase of acceleration and maturation of digital initiatives catalyzed by the pandemic. During this period, there has been evidence not only of an intensification in the adoption of digital technologies but also an evolution in the understanding of their strategic role within organizations. Companies have moved from a view of digitalization as a tool for operational optimization to a deeper understanding of its role as an enabler of organizational resilience and business continuity in contexts of high uncertainty.

This comparative analysis of the impact of the pre- and post-pandemic on the digital transformation of supply chains provides a critical context for understanding the relevance and timeliness of the present research. The selection of the 2020–2024-time frame allows for an examination of how organizations have responded and adapted to this new paradigm, offering valuable lessons for the future of supply chain management in an increasingly digitized and volatile environment.

The existing literature on digital transformation in the supply chain has examined a number of theories and conceptual frameworks. The deployment of emerging technologies, such as the Internet of Things (IoT) and artificial intelligence (AI), has been widely discussed as a potential means to optimize decision-making processes and improve visibility within the supply chain [9]. However, a significant number of studies focus on the application of these technologies alone, without adequately addressing their integration into the broader supply chain context [10][11]. Despite the growing interest in the topic, significant research gaps have been observed, as the long-term implications of digitization on inter-firm relationships and supply chain sustainability have not been considered [12]. This justifies the need for a comprehensive review that synthesizes and critiques the existing literature.

Research Questions

The research questions that will guide this review focus on critical aspects of the digital transformation of supply chains. First, it asks: What are the most effective digital technologies that have been shown to improve the agility and resilience of post-pandemic supply chains? It also seeks to understand the obstacles companies face in implementing these technologies in their logistics operations. In addition, it explores integration strategies by asking: How can organizations effectively integrate digital strategies into their business models to optimize their response to future disruptive events? The aim of these questions is not only to deepen current understanding of the topic, but also to contribute to business practice and academic research in a context that continues to evolve rapidly.

Research Objectives

The objectives of this review of the literature are clear and are intended to make a significant contribution to the field of supply chain management in the context of digital transformation post-pandemic. First, it aims to take a detailed look at the current state of research on digital transformation in the supply chain, identifying key trends, technologies, and strategies that have emerged in response to the challenges imposed by the pandemic. Second, it aims to identify and discuss existing literature gaps, specifically those areas that require more attention and could benefit from more in-depth and systematic research. Finally, the aim is to propose an integrative theoretical framework that facilitates the understanding of digital transformation in the supply chain and serves as a basis for future research and practice in this area.

Research Methods

The methodology of this review is based on a systematic approach that includes the collection of relevant academic articles and case studies. To identify literature published between 2020 and 2024, databases such as Scopus, ScienceDirect, and Web of Science will be used. Selection criteria will include relevance of the topic, methodological quality, and diversity of approaches.

Research Contributions

This review aims to contribute to the field of supply chain management by providing a critical analysis that summarizes existing findings and offers a theoretical framework that facilitates understanding of digital transformation in the post-pandemic context. It is hoped that this review will serve as a guide for researchers and practitioners seeking to implement effective strategies in their logistics operations

4. Unique contributions and innovations should be more clearly and specifically outlined and summarized.

Unique Contributions and Innovations

This research offers several unique contributions to the field of digital transformation in post-pandemic supply chains. Our bibliometric analysis provides the first comprehensive examination specifically capturing the 2020-2024 period, allowing us to precisely document how the pandemic catalyzed fundamental changes in technological adoption and strategic approaches to digitization. One of our most significant findings is the emergence of sustainability as the dominant keyword in the network of terms related to digital transformation. This discovery documents a paradigm shift where organizations are increasingly integrating sustainability objectives with their digitization initiatives, establishing an empirical foundation for future research at this critical intersection. Through rigorous analysis of the identified bibliometric clusters, we've established an innovative taxonomy characterizing the temporal evolution in digital technology adoption. The early pandemic period (2020-2021) was dominated by terms related to resilience and immediate pandemic response; the middle period (2022-2023) saw the emergence of concepts related to sustainability, blockchain, and IoT; while the most recent period (2023-2024) shows consolidation of terms related to circular economy and AI integration. This temporal characterization helps understand the field's maturation toward more strategic transformations.

Our research also uncovers a significant methodological gap in blockchain technology literature, where surprisingly only 15% of analyzed research presents empirical evidence of verifiable implementations, while 85% focuses predominantly on conceptual frameworks and theoretical proposals. This identified methodological gap points to a critical direction that future research must address. In response to these gaps, we propose an innovative conceptual framework synthesizing our findings into three fundamental and interrelated dimensions: technological (addressing technology adoption and integration), organizational (contemplating change management and competency development), and sustainable (incorporating impact metrics and resource optimization). This framework provides not only an original conceptual foundation but also establishes a solid structure for future research and practical applications.

From a methodological perspective, we've implemented a standardized evaluation rubric integrating four key components: methodological rigor (30%), thematic relevance (25%), data quality (25%), and contribution to the field (20%). This evaluation tool represents a significant advancement by providing a systematic and reproducible method for assessing studies in digital transformation of supply chains. Finally, our analysis of international collaboration networks identifies the China-United States-India triangle as the main core of scientific production, revealing significant geographical imbalances in research that should be addressed for a truly global understanding of this phenomenon.

Collectively, these innovative contributions not only expand the horizon of theoretical knowledge in the field but also provide concrete guidelines for future research and practical applications, laying a solid foundation for the future development of digital transformation in post-pandemic supply chains.

5. The co-author citation details (lines 529-533) and the publishing institutions (lines 549-553) are recommended to be presented in tables, accompanied by relevant literature citations, in accordance with academic paper standards.

Table 1. Most cited author pairs in digital transformation of post-pandemic supply chains.

Author Pairs	Number of Co-citations	Key Research Area
Benitez G.B. and Frank A.G.	4	Digital transformation and sustainability in supply chains
Caiado R.G.G. and Scavarda L.F.	4	Integration of digital technologies in supply chain operations
Xu J. and Zhao Z.	4	Digital supply chain modeling and optimization
De la Poza E. and Barykin S.E.	3	Transformation strategies in logistics operations
Lerman L.V. and Benitez G.B.	3	Implementation of Industry 4.0 technologies

Note: Data obtained from bibliometric analysis of publications in Scopus, Web of Science, and ScienceDirect databases, 2020-2024.

Table 2. Most frequently cited institutions in digital transformation research.

Institution	Country	Citations	Research Focus
School of Computer Science and Applications, IIMT University	India	6	AI applications in supply chain management
Eastern International University	Vietnam	5	Digital transformation in emerging markets
University of Southern Denmark	Denmark	4	Sustainable digital solutions
University of Hamburg	Germany	4	Industry 4.0 implementation frameworks
Southwest Jiaotong University	China	4	Smart logistics and IoT integration

Note: Based on institutional affiliations from bibliometric analysis of publications between 2020-2024. Citation counts represent frequency of institutional appearances in the analyzed literature

Author Response File: Author Response.docx

Reviewer 2 Report (Previous Reviewer 2)

Comments and Suggestions for Authors

My comments have been addressed, the authors made a substantial revision, therefore an accept is recommended.

Author Response

Thank you very much. Your reviews were very helpful in improving the quality of the article.

Author Response File: Author Response.docx

Reviewer 3 Report (Previous Reviewer 1)

Comments and Suggestions for Authors

I have skimmed the resubmission and it looks good with significant changes

Author Response

I thank the reviewer for his valuable contributions, which the reviewer has already considered to have been lifted.
Thank you very much.

Author Response File: Author Response.docx

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 want to thank the authors for picking up this important topic for systematic review and a very clear manuscript.

Please do consider reflecting different key findings (or gaps) in the abstract. I think better points have been discussed in the text and discussion. I also suggest working to make the results more concise and targeted and think about how each part can inform next researches or if there is any insights, expand on the proposed linkage and what does it mean for the industry. It helps to provide more info on the context of top papers to help readers navigating claimed trends.

Please consider some of my suggestions below:

would supply-chain capture articles that for example discuss medical supply deliveries? medical shortages? is it possible to provide a line or two to clarify the scope and common use of term "supply-chain" in medical journals.

line 263, consider table format.

Figure 338: translate the graph to English

paragraph of line 411: a lot of citations come at introductions and it would be quiet hard to know why specific groups have been cited more to draw any solid conclusions. I suggest the focus on geographic (as mentioned in line 437) and thematic dice of the results rather than by specific school or research teams based on number of citations. Please disregard if this is a common practice in this very particular field for systematic reviews.

on the same note, it would be very useful to have few paragraphs on why highly cited papers have been mentioned .i.e. new implementation technology, new framework?

Please consider complimentary evidence for cased in which maybe the studies only suggesting the possibility of using blockchain technologies for secure transactions, but not actually be on the blockchain implementation.

I suggest highlighting the gaps (such as line 641) while providing more context on the score of the word (sustainability in supply chain can be very broad).

Reviewer 2 Report

Comments and Suggestions for Authors

1. Search Strategy: While the authors claimed to follow the PRISMA protocol, the description of search strategies was overly generic. Specific search strings and the rationale behind database selection were insufficiently detailed.

• Recommendation: Provide explicit search strings, include justification for excluding specific studies, and clarify why Scopus, Web of Science, and ScienceDirect were selected.

2. Selection Criteria: The inclusion and exclusion criteria lacked sufficient detail and failed to ensure reproducibility.

• Recommendation: Detail how studies were assessed for quality and relevance using a standardized scoring system.

3. Bibliometric Analysis: Although bibliometric tools were used, the clustering thresholds and data normalization methods were not sufficiently justified, leading to potential biases in the network visualization.

• Recommendation: Include sensitivity analysis to validate the robustness of clustering methods.

4. Lack of Thematic Depth: While bibliometric clusters were identified, the manuscript lacks an in-depth analysis of how these clusters contribute to understanding post-pandemic digital transformation.

• Recommendation: Enhance the discussion of each bibliometric cluster, connecting key works to the broader supply chain management field.

5. Missing Critical Literature: Several foundational works on digital transformation, sustainability, and resilience in supply chains are absent.

• Recommendation: Incorporate recent high-impact studies and provide a comprehensive theoretical background.

6. Co-Citation Analysis: While prominent authors and research networks were highlighted, their theoretical or practical contributions were not discussed.

• Recommendation: Expand on the specific contributions of key authors and explain their relevance to supply chain digital transformation.

7. Keyword Co-Occurrence: The paper mentions dominant themes such as sustainability and Industry 4.0 but does not analyze how these themes interconnect or evolve over time.

• Recommendation: Conduct a temporal analysis of keyword trends to illustrate the evolution of research themes.

8. Result Interpretation: The manuscript offers descriptive statistics but fails to provide actionable insights or a framework for practical application.

• Recommendation: Propose a conceptual framework based on findings to guide future research and practice.

Comments on the Quality of English Language