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Article

A Bibliometric Analysis of the Role of Digitalization in Achieving Sustainability-Oriented Innovation

by
Laurențiu-Stelian Mihai
1,*,
Valeri Viorel Sitnikov
1,
Mirela Sichigea
1,
Laura Vasilescu
1,
Anca Băndoi
1,
Cătălina Sitnikov
1 and
Leonardo-Geo Mănescu
2
1
Faculty of Economics and Business Administration, University of Craiova, 200585 Craiova, Romania
2
Faculty of Electrical Engineering, University of Craiova, 200585 Craiova, Romania
*
Author to whom correspondence should be addressed.
Sustainability 2025, 17(13), 5822; https://doi.org/10.3390/su17135822
Submission received: 20 May 2025 / Revised: 20 June 2025 / Accepted: 20 June 2025 / Published: 24 June 2025

Abstract

In an era marked by rapid technological advancements, the relationships among organizational digitalization, innovation, and sustainability are receiving growing academic and managerial attention. This paper employs bibliometric analysis to examine the scientific literature on these interconnected terms, based on 775 relevant publications retrieved from the Web of Science database and analyzed using MS Excel, Bibliometrix, and VOSviewer software packages. The findings reveal a rapid increase in research on digital transformation and sustainability since 2017, with key themes including Industry 4.0, artificial intelligence, blockchain, and circular economy. However, the analysis also highlights notable conceptual fragmentation, emphasizing the need for a more integrated theoretical framework, especially in fields such as performance measurement and corporate social responsibility. From a practical standpoint, the study identifies research gaps—including CSR alignment, SME digitalization, and evaluation metrics—where organizations and policymakers continue to face challenges. These findings can support targeted capacity building, policy development, and strategic research funding aligned with sustainability-oriented innovation. By synthesizing key patterns from the literature, this study contributes to a deeper understanding of how digital transformation drives sustainable innovation, while suggesting several directions for further investigation in both academia and practice.

1. Introduction

In an increasingly digitalized world, organizations are undergoing profound transformations driven by technological advancements, changing market dynamics, and the growing urgency of sustainability. Digitalization, innovation, and sustainability are three interrelated forces shaping modern business environments, offering both opportunities and challenges for organizations seeking to enhance their competitiveness while addressing societal and environmental concerns. Across many sectors, digital transformation is increasingly critical for maintaining competitiveness and responding to evolving market, technological, and regulatory pressures. At the same time, several industries are beginning to rely on emerging technologies (artificial intelligence, blockchain, the Internet of Things, and big data analytics) in order to increase operational efficiency, customer engagement, and value creation. Likewise, sustainability has become a critical imperative, as organizations face increasing pressure to minimize their environmental footprint, adopt circular economy models, and align with the United Nations Sustainable Development Goals. Despite growing academic attention to the intersection of digitalization, innovation, and sustainability, there is still need for a comprehensive understanding of how these elements interact and contribute to long-term organizational success.
The rapid evolution of digital technologies has led to varying definitions and interpretations of digitalization, digital transformation, and innovation in the academic literature. Digitalization is often viewed as the process of integrating digital technologies into business operations, leading to improved efficiency and decision-making. Digital transformation, on the other hand, refers to a more profound organizational shift, encompassing cultural, strategic, and structural changes aimed at leveraging digital capabilities for competitive advantage. Innovation, as a driver of digitalization, enables organizations to develop novel business models, products, and services that foster growth and differentiation in the market. However, the role of digitalization and innovation in promoting sustainability remains an evolving discourse, with scholars and practitioners exploring how digital strategies facilitate environmental responsibility, social equity, and economic viability. Industry 4.0 technologies, for instance, hold significant potential for reducing waste, optimizing resource utilization, and enhancing transparency in supply chains, yet their implementation varies across industries and organizational contexts.
While several literature reviews have explored the intersection of digital transformation and sustainability, most have either focused on conceptual frameworks, individual technologies (e.g., AI, blockchain), or specific sectors. Few have provided a holistic bibliometric analysis that simultaneously maps the conceptual, intellectual, and social structures of this interdisciplinary field. This paper addresses this gap by integrating statistical and network-based bibliometric tools to analyze a comprehensive dataset of 775 articles. Unlike prior work, it uncovers thematic clusters and citation dynamics, while revealing underexplored links between corporate social responsibility (CSR), small and medium enterprises (SMEs), and digitalization, providing a richer basis for theory development and policy insight.
Given the growing body of research on digitalization, innovation, and sustainability, it is essential to conduct a structured analysis of the existing literature to identify key themes, research gaps, and future directions. This study aims to provide a comprehensive bibliometric analysis of the scientific literature on the relationship between these three domains. The study addresses three research questions: (RQ1) How is the relationship between organizational digitalization, innovation, and sustainability approached in the scientific literature? (RQ2) How is the existing research structured from a conceptual, intellectual, and social point of view? (RQ3) What future research directions should be pursued to advance knowledge in this field? By answering these questions, the study aims to contribute to a deeper theoretical understanding of how digital transformation and innovation strategies can drive sustainable development across various industries.
To answer these questions, the paper uses data visualization and network analysis tools such as MS Excel for Mac v. 16.66.1, the Bibliometrix package of R v. 4.3.0., and VOSviewer v. 1.6.20, which allow the systematic mapping of research trends, co-authorship networks, and thematic clusters, providing valuable insights into the evolution and impact of scientific literature. The study is based on a dataset of 775 academic publications retrieved from the Web of Science database, ensuring a high level of scholarly rigor and reliability. The analysis covers key bibliometric indicators, including citation patterns, keyword co-occurrence networks, and country-level collaborations, offering an overview of the intellectual, social, and conceptual structure of the digitalization, innovation, and sustainability research.
In addition to providing a structured overview of the literature, this study explores how the evolution of research at the intersection of digitalization, innovation, and sustainability reflects shifts in theoretical thinking, practical focus, and policy orientation. By highlighting both over- and underexplored research areas, the study aims to stimulate critical reflection on which themes are emerging due to technological, economic, or societal imperatives, and which may be overlooked yet potentially valuable to the evolution of innovation and sustainability scientific literature.
The structure of this paper is as follows: Section 2 presents a literature review that explores the theoretical aspects of digitalization, innovation, and sustainability, as well as the relationships between these three concepts. Section 3 outlines the research methodology, discussing the bibliometric analysis techniques used to identify and interpret trends in the existing literature. Section 4 presents the results and discussion, including descriptive statistics, thematic mapping, and structural analysis of the research landscape. Section 5 concludes the paper by summarizing the key findings, discussing their theoretical and practical implications, and proposing future research directions that can further advance knowledge in this domain.

2. Background and Concept Definition

2.1. Digitization, Digitalization, and Digital Transformation

In the current business environment, most companies use “traditional” digital technologies to varying degrees—such as the internet, smartphones, SEO, cloud computing, online payments—while only some of them are starting to adopt new, emerging technologies such as AI, blockchain, the Internet of Things (IoT), or big data. In order for a company to thrive in this ever-changing environment, they must leverage these technologies to digitally transform their business and management processes. This can be achieved, since many of these digital technologies have the potential to facilitate coordination, collaboration, and cooperation between the employees, enhance the service or product offering, and provide more cost-effective ways of doing business, such as optimizing logistics or reducing supply chain costs [1].
Yoo [2] states that, although no scientific consensus exists on the definition of digital technologies, they are different from earlier (analog) technologies in three key areas: their re-programmability, data homogenization, and self-referential nature, and identifies four dimensions: device, service, network, and content. Denner et al. [3], along with other earlier researchers [4,5], talk about SMAC, the social, mobile, analytics, and cloud technologies. The social aspects of digital technologies (wikis, discussion forums, social networks, chatrooms) improve the collaboration between individuals; the mobile technologies enable software that allows for new ways and communication and information sharing; analytics support companies in working with big data; and cloud computing contributes to the ease of information access.
Bican and Brem [6] state that the digital landscape is often described using three interconnected terms: digitization, digitalization, and digital transformation. Digitization denotes a technological process, namely “the integration of digital technologies into everyday life” [7] p. 62. From the perspective of information technology, digitization refers to the conversion of analog information into a digital format, such as making physical items programmable or communicative [2,8].
In contrast, digitalization is a socio-technological process that applies digitization methods to wider social and institutional settings, hence establishing the infrastructures of digital technologies [9,10]. Along the same lines, Li et al. [11] define digitalization as the use of digital technologies to develop business or management processes, while Ajigini & Chinamasa [12], Kusters [13], and Verhoef et al. [1] describe digitalization as the improvement of business or management processes through the use of digital technologies with the aim of enhancing customer or employee experiences. Several authors [14,15,16,17,18] argue that the digitalization of business and management processes has several advantages, such as better service delivery, more cost-efficient operations, faster internal communication, better resource allocation, and greater transparency—all ultimately contributing to increased value of the company’s offerings. Moreover, another study [19] has shown that companies that employ a higher degree of digitalization in their operations and internal processes generate, on average, almost 10% more revenue and are more than 25% more profitable than their less digitized competitors. This correlation between the companies’ digital capabilities and organizational performance is supported as well by Cardona et al. [20] and Abou-foul et al. [14].
On the other hand, digital transformation refers to structural changes that affect the entire organization [1,12], leading to entirely new business models and internal management processes. This concept goes beyond digitalization, which usually refers to improvements in specific business or management processes [1] with the goal of achieving competitive advantage by fundamentally changing core competencies or developing new ones [12,21]. Metselaar et al. [22] states that digital transformation changes the way a business is operated, thus leading to better performance and a more efficient environment that allows employees to thrive and perform.
While the terms digitization, digitalization, and digital transformation are often used interchangeably in academic discourse, this study adheres to the distinctions proposed by Bican and Brem [6] and Verhoef et al. [1]: digitization refers to converting analog processes into digital form; digitalization represents the broader application of digital technologies to improve processes; and digital transformation signifies a fundamental shift in business models and organizational logic. Recognizing this conceptual overlap, the three constructs were treated as analytically distinct in the interpretation of results. Despite these distinctions, inconsistencies were observed in terminology across the reviewed literature—particularly variations in spelling (e.g., “digitalization” vs. “digitalisation”) and overlapping use of related terms. Since the bibliometric software (Bibliometrix package of R v, 4.3.0 and VOSviewer v. 1.6.20) does not allow for in-depth keyword harmonization, this issue is acknowledged as a methodological limitation. These inconsistencies may have influenced the precision of keyword frequency and co-occurrence analyses and should be considered when interpreting thematic structures.

2.2. Sustainability

According to Ghobakhloo [23], sustainability includes a wide range of elements, extending beyond environmentalism, while involving the preservation of economic and social resources [24,25,26]. The United Nations defines sustainability as a movement aimed at securing long-term well-being for everyone—including future generations—by addressing persistent global challenges such as injustice, inequality, climate change, pollution, and environmental degradation. This concept, despite being relatively new, has its origins in longstanding movements such as conservationism and socio-economic justice [27]. The literature on sustainability is extensive, with academics significantly contributing to the idea and realization of its three foundational pillars: environmental, economic, and social sustainability [28,29]
Environmental sustainability focuses on maintaining ecological integrity by balancing the use and replenishment of natural resources and preserving the earth’s environmental systems [30]. On the other hand, economic sustainability refers to the long-term development of the global economy while protecting natural and social resources. From this viewpoint, economic development must not come at the cost of reducing natural or social capital, and it should consider the balance of natural resources, ecosystems, social welfare, and income distribution [25]. Lastly, social sustainability involves identifying and addressing the beneficial and detrimental effects of corporate, environmental, economic, and technical factors on individuals, its primary objective being to establish healthy and habitable communities where all individuals are safeguarded against discrimination and have access to universal human rights and essential services [31]. Thus, the adoption of sustainable practices in the global economic development strategies is essential to preserve earth’s ecosystems and the quality of life for future generations.

2.3. Sustainability-Oriented Innovation

One effective way to pursue sustainability goals is through increased innovation, leading to significant changes in capital allocation, labor organization, business models, and technology [32,33]. Sustainability-oriented innovation (SOI) supports systematic change in terms of the organizations’ culture, philosophy, and values, with the purpose of establishing social and environmental benefits beside profit [34].
Geradts & Bocken [35] argue that sustainability-driven innovation can take multiple forms, including the creation of new or enhanced products, services, processes, and business models that provide advantages for the environment or society as a whole. Process innovation refers to the strategies used to enhance the production of goods and services [36], while also enhancing eco-efficiency and focusing on sustainable manufacturing practices. Organizational innovation refers to the restructuring of organizational processes, emphasizing personnel and organizational objectives.
Similar to sustainability itself, SOI includes several key elements male [36]: (i) operational optimization—maximizing outcomes using minimal resources with attention to regulations, eco-efficiency, and sustainability; (ii) organizational transformation—achieving positive outcomes through innovation by transcending mere sustainability; (iii) systems building—achieving positive outcomes through collaborative innovation by focusing on cooperative capabilities. Voegtlin and Scherer [37] categorize SOI into two classes: (i) Innovations that prevent harm to individuals and the environment, and (ii) Innovations that enhance conditions for individuals and the environment. This dual nature of sustainability-driven innovations implies that an innovative process positively affecting one facet of the triple bottom line may negatively impact another [37].
Goodman et al. [38] analyzed the influence of the three phases of innovation (adaptation, expansion, and transformation) on corporate performance in the pursuit of sustainability. Their analysis revealed two synergic interactions between a firm’s sustainable strategy and its dynamic capabilities: path dependence and self-reinforcement, both of which reinforce and institutionalize sustainability practices [38].

2.4. The Relationship Between Digitalization, Innovation, and Sustainability

The interdependence of digitalization, innovation, and sustainability forms the theoretical foundation for this bibliometric investigation. Digitalization acts as a technological enabler [3], innovation serves as a dynamic process of transformation [17], and sustainability functions as a normative goal toward which organizations increasingly orient their strategies [23]. These three dimensions are deeply intertwined: digital technologies foster novel forms of innovation [8] (e.g., digital business models, real-time decision systems), while innovation processes increasingly aim to address environmental and social challenges [35]. Likewise, sustainability objectives often catalyze innovation through regulatory pressure or shifting consumer expectations, prompting firms to explore and adopt digital solutions [35].
For example, technologies such as AI, the IoT, and blockchain not only optimize efficiency [3,14] but also enable traceability [20], predictive maintenance [23], and environmentally friendly process redesign [24]—all of which contribute to sustainability-oriented innovation [35]. Moreover, digital platforms facilitate stakeholder collaboration and transparency, two essential elements of sustainable governance [28]. Thus, innovation no longer occurs in isolation but within ecosystems where digitalization and sustainability shape its purpose and pathway [33]. This interrelation underscores the need for an integrated analytical approach—as employed in this bibliometric study—to reveal how the literature conceptualizes and connects these three domains.

3. Materials and Methods

To achieve the paper’s objective of exploring how organizational digitalization, innovation, and sustainability are interlinked in the scientific literature, bibliometric analysis approach was adopted. This method was chosen due to its suitability for systematically identifying patterns, conceptual structures, and research gaps within large volumes of academic publications. The methodological framework was guided by established bibliometric practices and aligned with the three research questions previously outlined in the Introduction. In order to answer these research questions and to fulfill the research objectives, the study used the Bibliometrix R package v. 4.3.0. and VOSViewer v. 1.6.20, along with MS Excel for Mac v. 16.66.1 as the main bibliometric analysis software tools. According to several authors [39,40,41,42], this method is appropriate for analyzing large amounts of scientific records, while minimizing human error and mitigating the reviewer’s bias during literature review.
Moving on, the research design was based on the framework proposed by Donthu et al. [40] and used by Brabete et al. [39]. Thus, in the first phase, the authors identified gaps in the existing literature, defined the general topic, and formulated research objectives and questions, which guided this choice of methodology.
The second phase of the research consisted of collecting the data needed for the analysis. During this phase, the Web of Science database was chosen, since it indexes only high-impact, peer-reviewed journals and conference proceedings, ensuring that the data collected is of scholarly rigor and has a comprehensive coverage of business, management, and technology fields, as well as strong citation and network analysis capabilities, advanced search and filtering options, and standardized and structured data for bibliometric software.
Although Web of Science (WoS) was selected as the sole data source for this bibliometric study, it is acknowledged that other databases such as Scopus or open-access repositories (e.g., DOAJ, Lens.org) also host a significant number of peer-reviewed English-language publications. Furthermore, to empirically validate this database choice, this phase included a test query using the same keywords in the Scopus database (on June 10, 2025), which returned only 22 documents, compared to 957 in WoS (on April 25, 2025). This difference suggests that WoS offers broader coverage for the intersection of organizational digitalization, innovation, and sustainability, reinforcing the suitability of this database for the study’s objectives.
In order to find the most relevant records regarding the relationship between organizational digitalization, innovation and sustainability, it was decided to use the following search query: TS = (“digitalization of organizations” OR “organizational digital transformation” OR “digital business transformation” OR “enterprise digitalization” OR “digitalization of healthcare organizations”) AND TS = (“innovation” OR “technological innovation” OR “digital innovation” OR “business model innovation”) AND TS=(“sustainable development” OR “sustainability” OR “corporate sustainability” OR “sustainable business practices”). Based on this string of keywords, the authors queried the Web of Science database on the 20 of February 2024, returning 957 initial records (N = 957). The publication year was not used as a refinement criterion in order to avoid excluding important works, as an arbitrary cutoff year might exclude key insights from different perspectives and limit the citation network and influence analysis, since excluding older papers may break citation chains. Thus, the 957 records spanned a period of 22 years (2004–2025).
After identifying these initial 957 records, the search results were manually refined, using Web of Science’s inclusion and exclusion refinement capabilities. This process is presented below:
  • Regarding the document type, editorials, retracted publications and book chapters, including only research articles, proceeding papers, review articles, and early access papers, were excluded (N = 926).
  • All documents not published in English were excluded (N = 926)
  • Only papers from the following Web of Science categories were included: Environmental Sciences, Green Sustainable Science Technology, Environmental Studies, Management, Business, Economics, Social Sciences Interdisciplinary, Multidisciplinary Sciences, Computer Science Interdisciplinary Applications, Operation Research Management Science, Hospitality Leisure Sports Tourism, Business Finance, Public Environment Occupational Health, Internal, Information Science Library Science, Communication (N = 775).
After refining the dataset based on inclusion/exclusion criteria, a light screening was conducted to remove duplicate records and incomplete metadata, using Web of Science’s export tools and the import validation steps in Bibliometrix package of R v. 4.3.0 and VOSviewer v. 1.6.20. However, due to software constraints, no advanced manual data cleaning (e.g., keyword consolidation, author name disambiguation, or affiliation standardization) was performed beyond what the tools offer by default. As a result, some inconsistencies—such as spelling variants (e.g., “digitalization” vs. “digitalisation”) or fragmented author identities (e.g., “Wang S” vs. “S. Wang”)—may persist in the dataset and influence results at the margin. This is acknowledged as a methodological limitation.
In terms of analysis parameters, the paper follows established practices from the recent bibliometric literature (e.g., Donthu et al. [40]; Brabete et al. [39]). The search was conducted in February 2024 on the Web of Science Core Collection using a predefined query focused on the intersection of digitalization, innovation, and sustainability. Only peer-reviewed journal articles and reviews written in English were included. Records lacking full bibliographic metadata (e.g., missing abstracts or keywords) were excluded. All analyses were performed using Bibliometrix (R version) and VOSviewer, with co-citation and co-occurrence thresholds selected based on iterative testing to balance visual clarity and network density. While advanced manual data cleaning (e.g., keyword harmonization or author disambiguation) was not possible due to software constraints, all included records were systematically screened for relevance and integrity prior to analysis. For VOSviewer, co-occurrence and co-citation thresholds were selected based on exploratory runs to balance network density and interpretability. Specifically, the analysis retained only the top 60% of nodes based on frequency or citation counts in network visualizations to avoid excessive fragmentation or noise. The Bibliometrix package was used for thematic clustering and conceptual mapping using default Louvain clustering algorithms. All figures generated were manually validated and cross-compared across tools (MS Excel, Bibliometrix, VOSviewer) to ensure consistency in interpretation.
Thus, the data collection phase yielded a final sample of 775 papers which were used in the bibliometric analysis. The next phase consisted in processing the data and visualizing the results, using Microsoft Excel for Mac version 16.66.1 for tables and chart generation, the Bibliometrix R package version 4.3.0 for the bibliometric and quantitative analysis of the Web of Science records, and VOSViewer 1.6.20 for network analysis and building bibliometric maps. By combining VOSviewer’s visualization capabilities, Bibliometrix’s advanced statistical analysis and MS Excel’s chart building functionalities, the authors aimed to gain both qualitative and quantitative depth. In order to be able to use these applications, the full record and cited references of the 775 papers were exported in the BibTex format for Bibliometrix and the tab delimited files for VOSViewer.
In the final phase of the research framework, the authors analyzed and discussed the findings, answering the three research questions and formulating the final conclusions, implications, and recommendations.

4. Results and Discussion

4.1. Descriptive Statistics

In order to answer RQ1 (How is the relationship between organizational digitalization, innovation and sustainability approached in the scientific literature?), the analysis began by examining the literature’s performance and highlighting the important quantitative statistical features typical to bibliometric analyses.
As Table 1 illustrates, the analysis is based on 775 papers, published in 859 different sources (795 journals and 64 conferences), between 2004 and 2025, with an annual growth rate of 21.99%, indicating growing scientific interest in the relationship between organizational digitalization, innovation, and sustainability. Moreover, the sample has an average of 16.95 citations per document, highlighting the impact of the 775 papers included in this analysis and 46,343 references (an average of almost 60 references per paper), which shows that these papers are well documented, with strong connections to other similar papers. Furthermore, the sample included 2493 author’s keywords, which were transformed into 1088 Keywords Plus by Web of Science, highlighting the topic’s complexity. Finally, Table 1 shows that the 775 papers were authored by 2483 authors, out of which 58 authors published 60 single-authored papers. The sample had an average of 3.68 co-authors per document, while about a third of the papers (34.71%) were published as a result of an international collaboration, highlighting the global interest in this topic.
Figure 1 illustrates the annual scientific production on the topic of the relationship between organizational digitalization, innovation, and sustainability. Thus, in the first 13 years, there was relatively low interest in the topic at hand, with one paper published in 2004, one in 2006, two in 2013, and two in 2016, but, starting with 2017, the trend sharply increased, peaking in 2024, with 289 papers published. While this trend reflects a surge in academic interest, it is likely to follow a logistic pattern over time, where growth rates may slow due to systemic constraints such as publication limits and saturation of research topics. As of the 20th of February 2025, 65 papers had already been published on the topic of the relationship between organizational digitalization, innovation, and sustainability; it is safe to assume that 2025 will register an even higher scientific production than all the preceding years.
The first paper published on this topic and indexed by the Web of Science database was Sherwin [43], being presented at the 3rd International Conference on Design and Manufacture for Sustainable Development, which took place between the 1st and the 4th of September 2004 in Loughborough, UK. The paper discusses the Forum for the Future, part of the UK’s largest sustainable development NGO, describing their cutting-edge research on topics such as the sustainability implications of the information and communication technology sector and digital transformation of organizations, as well as sustainable marketing and sustainable innovation. The next paper, in chronological order, is, as well, a proceeding paper [44] presented at the Fifth Wuhan International Conference on E-Business, which took place in Wuhan, PRC between the 27th and 28th of May 2006. This article examines the primary factors influencing the advancement of electronic commerce in transition economies, with a specific focus on recent developments in Lithuania.
To account for the fact that older papers naturally accumulate more citations than recent ones, this study examined not only total citations but also normalized citation indicators—specifically, average citations per citable year (per year since publication) (as shown in Table 2). This allows for a fairer comparison across publication years by considering the time elapsed since each paper’s release. While additional normalization techniques were not applied (e.g., field-weighted citation impact), this time-adjusted metric provides a useful proxy to identify high-impact papers regardless of age. Thus, the papers published in 2022 have been cited the most (2987 citations), closely followed by 2020 (2684 citations), 2023 (2517) and 2021 (2468). Somewhat surprisingly, even though 2024 is the year with the highest scientific production (289 papers published), the citations volume is relatively low, on par with 2019, which had a very modest scientific production, with only 21 papers published. This relatively low citation count for the 289 papers published in 2024 may be partially explained by the fact that only one full citable year has passed. Moreover, the average citations column is showing that 2020 has registered the average value of citations per article (68.82), and 2019 has the most average citations per citable year (11.37).
The tree map visualization shown in Figure 2 highlights the most frequently used author’s keywords in the sample of 775 papers. The prominence of “digital transformation” (13%) and “sustainability” (11%) suggests that much of the academic discourse focuses on how digital technologies drive sustainable business practices. Similarly, “digitalization” (8%) and “innovation” (6%) highlight the technological and strategic changes that organizations need to implement in order remain competitive while meeting sustainability goals. The presence of terms like “Industry 4.0”, “artificial intelligence”, “blockchain”, and “circular economy” indicates a growing interest in the role of emerging technologies in sustainable innovation. However, some inconsistencies in keyword standardization (e.g., “digitalization” vs. “digitalisation”, “digital” vs. “digitization”) suggest a need for data cleaning to enhance analytical accuracy, which was not possible due to software constraints (Bibliometrix and VOSViewer lack addvanced preprocessing capabilities for semantic consolidation). Additionally, the inclusion of “COVID-19” highlights a recent research focus on how the pandemic has influenced digital and sustainable business transformations.
The next part of the bibliometric analysis focuses on the study of the most used keywords. Web of Science offers two types of keywords: author’s keywords which are provided by the authors’ themselves and Keywords Plus, which are extracted from the titles of the cited references by Web of Science [45]. This paper focused only on the authors’ keywords, rather than Keywords Plus, since, according to Zhang et al. [45], the authors’ keywords are more comprehensive in representing a paper’s content since they are more specific and are chosen by the authors themselves to represent their research.
Figure 3 represents a word cloud visualization, highlighting the most frequently occurring terms in the abstracts of the 775 papers included in the study. The dominance of “digital”, “transformation”, “innovation”, and “sustainability” confirms the previous statement that the papers primarily explore how technological advancements drive sustainable business practices and innovation. The presence of terms like “performance”, “development”, and “business” indicates a focus on the organizational impact of digitalization, while words such as “research”, “study”, and “analysis” reflect the academic nature of the investigation. Additionally, the inclusion of “green”, “environmental”, and “sustainable” highlights an emphasis on eco-friendly business models and sustainable strategies. Similar to the author keywords tree map, the appearance of both “digitalization” and “digital” suggests potential inconsistencies in terminology, which could affect the terms’ standardization. The presence of “SMEs”, “enterprises”, “management”, and “economic” implies that the study covers both macro- and microeconomic perspectives of digital transformation.
Figure 4 illustrates the most prolific journals, showing that, by far, Sustainability is the dominant source, publishing 185 documents, which is somewhat to be expected considering the intersection between its broad focus on sustainable development and its own interest regarding digitalization, innovation, and sustainability. The Journal of Cleaner Production (23) and Business Strategy and the Environment (20) also feature prominently, indicating a strong emphasis on digitalization-driven eco-friendly business practices and corporate sustainability strategies. The presence of Technological Forecasting and Social Change (19) suggests a focus on future-oriented research, particularly on how digital transformation influences long-term sustainability trends. Other journals, such as Technology in Society (10) and the European Journal of Innovation Management (9), indicate interdisciplinary approaches, incorporating technological, managerial, and economic perspectives. While the dominance of sustainability-focused journals reflects the growing integration of digitalization and sustainability, the relatively lower presence of purely innovation-focused journals suggests an opportunity for further exploration at the intersection of digital transformation, business innovation, and environmental responsibility.
Figure 5 represents a visualization of the most locally cited sources, highlighting the key academic journals that have significantly influenced the field. The Journal of Cleaner Production (2341 citations) and Sustainability (2258 citations) are the most frequently cited sources, reinforcing the strong link between digital transformation and sustainability-oriented research. Moreover, the high citation count of the Journal of Business Research (1622 citations, 147 citations per article, highest of all sources) and Technological Forecasting and Social Change (1614 citations, 84 citations per article) suggests a focus on business strategy, future-oriented technological change, and organizational innovation. Meanwhile, Business Strategy and the Environment (939 citations, 46.95 citations per article) emphasizes the role of corporate strategy in achieving sustainability through digitalization and innovation. The presence of the Strategic Management Journal, Research Policy, and MIS Quarterly indicates that research in this area extends beyond sustainability into strategic decision-making, knowledge management, and information systems. The diversity of these journals suggests a multidisciplinary approach, integrating insights from management, economics, technology, and environmental sciences.
This bibliometric research continues with the analysis of the most productive authors on the topic of the relationship between organizational digitalization, innovation, and sustainability, as seen in Figure 6. Li Y and Wang S lead with 11 publications each, indicating their strong presence in this research domain. Following them, Li J, Li X, and Zhang H each have eight publications, suggesting that multiple researchers with similar surnames contribute actively, which might indicate a concentration of research within specific geographic regions or institutions, particularly in China. Other notable contributors, including Chen Y, Parida V, and Zhang C, have published seven papers each, reinforcing a diverse but still somewhat concentrated authorship structure. The presence of multiple authors with Chinese surnames aligns with China’s increasing emphasis on digital transformation and sustainable innovation in business and industry.
Furthermore, Figure 7 highlights the most cited authors from the sample, illustrating whether these authors’ works are highly influential or simply frequent contributors. Thus, Figure 6 shows that Li Y and Wang S were the most prolific authors, each with 11 publications, but they do not appear among the ten most cited authors in Figure 7. Instead, Ghobakhloo M (who is not in the top 10 most productive authors) stands out as the most highly cited author (54 citations), suggesting that his work is more influential per paper than those of the most prolific authors. Similarly, Ardito L, Albino V, and Bertoldi B have 29 citations each (though, again, not present in the top 10 most productive authors), indicating that while they may have published fewer papers, their research has been widely referenced within the academic community. This contrast suggests that sheer publication volume does not necessarily translate into greater impact, and instead, high-quality, widely relevant research tends to receive more citations.
The next step in this research was to analyze the most productive countries and institutions that research organizational digitalization, innovation, and sustainability. This step was crucial for understanding global research trends, regional expertise, and institutional leadership in this field. Identifying the leading countries highlights which nations are investing the most in digital transformation and sustainable innovation, often reflecting government policies, economic priorities, and technological advancements. Similarly, recognizing the top institutions allows researchers to pinpoint centers of excellence, potential collaborative opportunities, and the academic hubs driving knowledge creation. This analysis also helps reveal geographical disparities in research output, indicating where further investment, policy support, or international cooperation may be needed. Moreover, understanding country-level and institutional productivity can provide insights into research funding structures, industry-academia collaborations, and emerging innovation ecosystems, all of which are essential for shaping the future of sustainable digital transformation.
Figure 8 represents a visualization of the most productive institutions in research on organizational digitalization, innovation, and sustainability, highlighting the key academic contributors to the field. Luleå University of Technology (Sweden) leads, with 16 publications, followed by Bucharest University of Economic Studies (Romania) and the University of Aveiro (Portugal), each with 14 papers. The presence of universities from Europe (Sweden, Romania, Portugal, Italy, Finland), Asia (China), and Africa (South Africa) suggests a geographically diverse research landscape, reflecting the global importance of digitalization and sustainability in business and industry. Notably, the inclusion of the South China University of Technology and Jilin University aligns with China’s growing emphasis on technological innovation and sustainability-driven industrial policies. The School of Economics and Management and University of Turin (both with 13 papers) reinforce the role of business schools in shaping digital transformation strategies.
Table 3 compares the most productive and most cited countries, highlighting the global distribution of the scientific production as well as its volume and impact. China leads in total papers (206) but has a relatively low average citations per paper (9.80), suggesting that while it is the most prolific contributor, its research may have lower impact or broader dissemination with less influence per article. In contrast, Iran (four papers, 296.20 citations per paper) and Finland (seven papers, 95.00 citations per paper) have significantly higher average citations per paper, indicating that their fewer publications are highly influential. Italy (57 papers, 38.20 citations per paper) emerges as both a highly productive and highly cited country, suggesting a balance between volume and impact. Similarly, Germany, Sweden, and France maintain moderate productivity with strong citation impact. This contrast between quantity and quality suggests that some countries prioritize high research output, while others focus on high-impact publications. Understanding these trends is crucial for researchers seeking collaborations with institutions that excel either in volume or in influence, shaping the academic landscape of digitalization, innovation, and sustainability.
The distribution of the scientific production can also be visualized in Figure 9. The intensity of the blue color corresponds to the volume of scientific publications originating from each country. Darker shades represent higher productivity, with China being the most productive country in the analyzed sample. Countries shown in light gray have no recorded publications on this topic in the selected Web of Science dataset.

4.2. The Conceptual, Intellectual, and Social Structure of the Scientific Literature Regarding the Relationship Between Organizational Digitalization, Innovation, and Sustainability

The next step of this analysis was to study the structure of the scientific literature regarding the relationship between organizational digitalization, innovation, and sustainability, in order to answer RQ2 (What is the structure of the scientific literature regarding the relationship between organizational digitalization, innovation and sustainability?).
To identify, analyze, and discuss the conceptual structure of scientific literature on the relationship between organizational digitalization, innovation, and sustainability, a content analysis was undertaken by examining the co-occurrence, frequency, and relationships between key terms within the sample. This method helps identify patterns, thematic structures, and conceptual linkages within a research field. Additionally, thematic evolution analysis can track how co-occurrence patterns change over time, providing insights into the development of new research topics.
This content analysis starts by analyzing the evolution of the keywords’ frequency over time, as seen in Figure 10. The sharp rise in occurrences of terms like “digital transformation”, “digitalization”, “Industry 4.0”, and “sustainability” after 2018 indicates a rapid acceleration in the interest for these themes, likely driven by technological advancements, policy shifts, and global sustainability goals. The dominance of “digital transformation” and “sustainability” suggests that researchers are increasingly exploring the intersection between technological change and sustainable business models. Notably, terms like “innovation” and “performance” have also seen significant growth, highlighting the focus on how digital strategies enhance business competitiveness and efficiency. The relatively slower yet steady rise of terms such as “sustainable development” and “transformation” indicates sustained interest in long-term impacts and systemic change beyond mere technological adoption. The overall trend suggests that these topics are becoming core research areas, with an expected continued rise in scholarly attention in the coming years.
Figure 11 provides a visual representation of the thematic structure in the research on organizational digitalization, innovation, and sustainability, highlighting key research areas and their interconnections. The central position of “digital transformation”, “sustainability”, and “digitalization” suggests that these are the core themes driving academic discourse in this field. The presence of distinct clusters—such as the green cluster linking “innovation”, “circular economy”, and “artificial intelligence” and the red cluster connecting “digital transformation”, “sustainable development”, and “corporate social responsibility”—indicates that research is exploring how technological advancements contribute to sustainability-driven innovation and business models. Additionally, the blue cluster, which includes “bibliometric analysis”, “systematic literature review”, and “entrepreneurship”, suggests a growing methodological focus on mapping and structuring knowledge in this domain. The strong linkage between “Industry 4.0”, “blockchain”, and “technology” indicates a focus on emerging digital technologies as enablers of sustainability and competitiveness. However, the wide dispersion of terms suggests that, although digitalization and sustainability are well-established, the interdisciplinary nature of this field is still evolving, with some subtopics being more fragmented or emerging. This network analysis reinforces the idea that digital transformation plays a pivotal role in shaping sustainable innovation strategies.
A key finding of the conceptual and co-occurrence analyses is that while digitalization, innovation, and sustainability appear as dominant and recurring themes across the literature, their interconnection is not always explicitly developed. This mirrors the broader issue of conceptual fragmentation noted in the literature and reaffirms the need for an integrative perspective. For example, while digital transformation and sustainability are often jointly discussed in relation to emerging technologies, the specific innovation pathways that link them (such as sustainable business model innovation or process innovation for ESG goals) are less consistently addressed.
The analysis shows that some clusters—such as those connecting Industry 4.0, artificial intelligence, and circular economy—implicitly reflect the convergence of the three domains. However, these connections often remain under-theorized or sector-specific, suggesting room for theoretical refinement and generalization. Likewise, the keyword corporate social responsibility appears in proximity to both digital transformation and sustainability, but without clear elaboration on the innovation mechanisms through which CSR outcomes are achieved.
These patterns suggest that future research should explicitly examine how digital capabilities drive innovation that is sustainability-oriented—not only through technology adoption but also through changes in organizational structures, stakeholder engagement, and performance measurement. The findings support the need for a more coherent theoretical architecture that recognizes digital transformation as both a driver and an outcome of innovation processes aligned with long-term sustainability objectives.
One limitation that emerged during the keyword-based analyses is the inconsistency in terminology across the reviewed literature. For example, spelling variants such as “digitalization” and “digitalisation”, or related terms like “digital” and “digitization”, were treated as distinct by the bibliometric software (Bibliometrix and VOSviewer), which lacks advanced preprocessing capabilities for semantic consolidation. As a result, some thematic fragmentation observed in the co-occurrence and clustering maps may reflect these lexical inconsistencies rather than substantive conceptual differences. Although this does not undermine the overall findings, it may have slightly affected the precision of cluster boundaries or keyword prominence. Future bibliometric studies could benefit from integrating custom preprocessing scripts or manual harmonization to better address such limitations.
The analysis continues with a thematic cluster mapping, using Bibliometrix, which classifies themes based on two axes (density/development and centrality/relevance): nice themes (high density, low centrality), motor themes (high density, high centrality), emerging or declining themes (low density, low centrality) and basic themes (low density, high centrality). Niche themes are specialized topics with strong internal development but limited connections to the broader research field; motor themes are well-developed and influential topics driving the evolution of the research field; emerging or declining themes are topics that are either in the early stages of development or losing relevance in the academic discourse; and basic themes are fundamental topics that are widely connected to multiple research areas but lack deep specialization [39].
It is important to note that the thematic classification of clusters into categories such as “motor themes”, “niche themes”, “basic themes”, and “emerging/declining themes” is not assigned manually by the authors but is derived from the output of the Bibliometrix software. This classification is based on the centrality (relevance) and density (development) of keyword clusters using the Louvain clustering algorithm. While interpretation of content within clusters does involve researcher judgment, the positioning and labeling of thematic quadrants are determined algorithmically to ensure methodological consistency and reproducibility.
The niche themes are highly specialized but not widely connected to the broader field. “Empirical evidence”, “diversity”, and “variance” indicate a focus on methodological rigor and specific research approaches, which may contribute to deep insights within specialized research communities. However, their lower centrality indicates that they are not yet widely integrated into mainstream discussions on digitalization, innovation, and sustainability.
The motor themes are highly relevant and well-developed topics that drive research on organizational digitalization, innovation, and sustainability. The presence of “innovation”, “management”, and “technology” suggests that research in this field is strongly focused on how technological advancements drive organizational change and innovation. These themes are central to the discourse, guiding theoretical and empirical studies, and are likely to shape future research directions.
The emerging or declining themes are either gaining attention or losing relevance in the scientific literature. “Augmented reality” appears as a low-density, low-centrality theme, suggesting that while it has potential applications in digital transformation, it has not yet become a major research focus within this field. Its future relevance will depend on technological advancements and industry adoption in the context of sustainability and innovation.
The basic themes are fundamental to the research field and serve as building blocks for the various studies. “Performance”, “impact”, and “dynamic capabilities” highlight the importance of measuring how digitalization and innovation contribute to organizational success and sustainability. Their high centrality suggests that they are widely referenced but still require further theoretical and empirical development.
Keywords located near the center of the map—including “China”, “corporate social responsibility”, and “determinants”—do not fall clearly into any single quadrant, indicating that they are moderately relevant (centrality) and moderately developed (density) within the research field. Their position at the intersection suggests that they are transitional themes, meaning they are connected to multiple research areas but not yet fully established as either core or niche topics. These themes may be gaining importance but still lack the depth and maturity characteristic of motor themes or the foundational role of basic themes.
This thematic mapping of 775 papers reveals that research on organizational digitalization, innovation, and sustainability is primarily driven by technological advancements and management strategies, while performance measurement remains a core but developing theme. Some specialized areas contribute valuable insights, but certain emerging technologies are yet to become mainstream research topic.
This content analysis allowed the authors to identify recurring patterns, gaps, and emerging trends, thereby answering RQ3 (What are the future directions that the research regarding the relationship between organizational digitalization, innovation and sustainability needs to focus on?). Thus, based on the findings presented in Figure 10, Figure 11 and Figure 12, four future research directions were developed, on the relationship between organizational digitalization, innovation, and sustainability, as summarized in Table 4.
While the identification of underexplored topics may suggest limited academic interest or lower relevance, this should not automatically imply a lack of research potential, but rather research opportunities for advancing theory in innovation economics and sustainability. For instance, although technologies such as blockchain, artificial intelligence, and Industry 4.0 are increasingly cited in sustainability contexts, their roles remain insufficiently conceptualized. This gap likely reflects the rapid pace of technological development compared to theoretical integration. Yet, these technologies have the potential to transform business models, supply chains, and sustainability metrics, offering the necessary context for expanding theories of digital diffusion, system innovation, and green transformation. Similarly, the limited focus on measuring the performance impact of digital transformation on sustainability objectives reflects both methodological complexity and conceptual underdevelopment. Bridging this gap through standardized metrics and integration with ESG frameworks could significantly strengthen the theoretical alignment between dynamic capabilities and long-term sustainable value creation.
Likewise, the limited presence of CSR in the digital transformation scientific literature suggests a clear division between economic and social dimensions of the triple bottom line. Moreover, the integration of CSR into digitalization research could contribute to the development of the stakeholder theory and responsible innovation models, particularly in contexts that demand transparency and accountability. Furthermore, the scarce attention to SMEs and entrepreneurial settings reveals a research bias toward large enterprises, despite the critical role of smaller firms in grassroots innovation and local sustainability transitions. Exploring how digitally enabled SMEs navigate sustainability challenges can contribute to inclusive innovation theory and foster more adaptable, context-sensitive models of sustainable economic development. Thus, rather than viewing these underdeveloped themes as marginal, this paper views them as representing high-potential pathways for advancing interdisciplinary theory and practice at the intersection of digital transformation and sustainable development.
While this study does not directly analyze empirical barriers to digital transformation, the bibliometric patterns examined allowed the identification of areas where challenges to adoption and integration may persist. For example, the lack of standardized performance metrics in the literature suggests a practical difficulty in measuring the sustainability outcomes of digital strategies, which may impede evidence-based policy or management decisions. Similarly, the limited representation of CSR, SMEs, and entrepreneurial ecosystems in the existing research points toward structural gaps in both scholarly attention and practical uptake. These are not barriers per se, but underdeveloped domains where theoretical guidance and practical frameworks are still maturing. The analysis thus supports the prioritization of these topics in future research, as addressing them can help clarify pathways through which digitalization supports sustainability goals, particularly in contexts with constrained resources or regulatory uncertainties.
The analysis continues with an examination the intellectual structure of the research on the relationship between organizational digitalization, innovation, and sustainability. Analyzing the intellectual structure is essential for identifying key theories, foundational works, influential scholars, and emerging trends. Mapping co-citation networks, bibliographic coupling, and the impact of research, aimed to uncover how knowledge has evolved over time, the main thematic clusters, and gaps in the literature.
Figure 13 provides a visual representation of the most frequently cited academic journals in research on organizational digitalization, innovation, and sustainability, providing additional insights into the intellectual landscape of the field. The three main clusters—red (sustainability and environmental management), green (corporate social responsibility and business strategy), and blue (management and technological innovation)—suggest that research on digital transformation and sustainability is inherently interdisciplinary, integrating environmental sciences, business strategy, and management innovation. The prominence of “Journal of Cleaner Production” and “Sustainability” in the red cluster indicates a strong emphasis on sustainable business practices and resource efficiency, while the green cluster, led by “Business Strategy and the Environment” and “Corporate Social Responsibility and Environmental Management”, reflects the connection between digitalization and corporate sustainability strategies. Meanwhile, the blue cluster, featuring “Strategic Management Journal” and “Technological Forecasting and Social Change”, highlights the role of innovation and digital transformation in shaping sustainable business models. The strong connections between clusters indicate that sustainability, digital transformation, and innovation are highly interrelated topics, though some areas remain less integrated.
The paper continues with the study of bibliographic coupling by sources, which supports the analysis by identifying journals that share common references, helping to map thematic relationships and research clusters. Unlike co-citation analysis, which traces historical intellectual influences, bibliographic coupling is particularly valuable for understanding current and emerging research trends in organizational digitalization, innovation, and sustainability. By linking journals based on their shared reference lists, this method highlights which sources contribute to similar knowledge domains, allowing researchers to detect interdisciplinary connections, dominant publication venues, and gaps in the literature.
Figure 14 provides a visual representation of how journals are interconnected based on shared references, offering valuable insights into the intellectual structure of the research on organizational digitalization, innovation, and sustainability. The centrality of “Sustainability” as the most strongly connected journal suggests that it serves as a key publication venue for studies at the intersection of digital transformation and sustainability. The strong connections to “Journal of Cleaner Production”, “Business Strategy and the Environment”, and “Journal of Business Research” indicate that research in this field integrates environmental management, corporate strategy, and innovation-driven business models. The presence of “IEEE Transactions on Engineering” and “Technology in Society” highlights the role of technological advancements in driving sustainable digitalization efforts, while the linkage to entrepreneurship and business process management journals suggests that new business models and organizational strategies are emerging as critical components of this discourse. The multicolored network clusters reflect the multidisciplinary nature of the field, connecting insights from engineering, environmental science, business, and technological innovation.
Figure 15 illustrates the most globally (a) and locally (b) cited documents from the sample of 775 papers. Locally cited references are those that are cited within the specific dataset and help identify key works that shape the intellectual structure of a specific research field, while globally cited references refer to works that have been cited across all scientific literature, regardless of their relevance to the dataset, indicating widely influential studies that have had a broader impact across multiple disciplines.
Figure 15a highlights works with widespread academic impact across multiple research fields, with Ghobakhloo [23] leading at 913 citations, indicating that his work on digital transformation and sustainability is influential beyond the specific dataset analyzed. Other highly cited studies, such as those by Kohtamäki et al. [46] and Chauhan et al. [48], suggest a strong academic focus on the intersection of digitalization, business strategy, and technological innovation. In contrast, Figure 15b identifies studies that are highly relevant within the sample, meaning they shape the discourse specifically on digital transformation, innovation, and sustainability. Ghobakhloo [23] is again the most cited, reinforcing his centrality in the field, but other studies, such as Ardito et al. [53] emerge as influential within this particular research scope. The gap between global and local citation rankings suggests that while some works have broad, cross-disciplinary impact, others are highly specialized and deeply integrated into this research domain. This distinction is essential for understanding which studies serve as foundational theoretical works versus those driving niche advancements in the literature.
This analysis of the intellectual structure of this sample concludes with Figure 16, which highlights the most cited references in the dataset of 775 papers on the relationship between organizational digitalization, innovation, and sustainability. The most frequently cited reference, Vial [61], suggests that his work on digital transformation serves as a key conceptual framework in the field. Other highly cited sources, such as Verhoef et al. [1] and Warner & Wäger [62], emphasize the role of strategic business adaptation and long-term digitalization planning, reinforcing the managerial and innovation aspects of digital transformation. The presence of Barney [63] and [64,65] indicates that resource-based and dynamic capability theories are central to understanding how organizations leverage digital transformation for competitive advantage and sustainability. Additionally, works like Nambisan et al. [66] on digital innovation and Bharadwaj et al. [67] on IT capabilities suggest that technological advancements are key enablers of sustainable business strategies.
The last part of this analysis deals with the study of the social structure of the research on the relationship between organizational digitalization, innovation, and sustainability. Analyzing the social structure of research helps uncover the collaborative dynamics, influential researchers, and institutional or geographic networks that shape the topic at hand. By examining co-authorship networks, institutional affiliations, and country collaborations, the study aimed to identify key contributors, leading research groups, and patterns of scientific cooperation in the field of organizational digitalization, innovation, and sustainability. This analysis reveals how knowledge is generated and disseminated, highlighting strong collaborative clusters, isolated research groups, and emerging academic partnerships. In the context of this topic, understanding the social structure helped the authors identify which researchers or institutions drive the conversation, facilitate cross-disciplinary collaborations, and identify potential gaps in global or industry–academia cooperation.
The social structure analysis starts with a discussion of the co-authorship patterns in the data set, aiming to identify collaborative relationships, influential researchers, and research clusters within a field. By visualizing connections between authors, this analysis revealed which scholars frequently collaborate, which research teams or institutions dominate the field, and how knowledge is shared across different geographical regions or disciplines. It helps detect highly influential researchers, potential research silos, and opportunities for new collaborations. In the context of this topic, co-authorship networks can highlight interdisciplinary partnerships, track the globalization of research efforts, and identify gaps where more cross-institutional or cross-country cooperation is needed.
Figure 17 provides a visual representation of collaboration patterns among researchers in the field of organizational digitalization, innovation, and sustainability. Given that the dataset includes 2483 authors, but the network map displays only 24, this indicates that many researchers work independently or in isolated teams. While the authors shown in the map exhibit strong collaboration, forming a well-connected sub-network, it does not represent the overall research landscape. The presence of a few highly connected nodes (e.g., Cimmino, Andrea; Salinas, Diego; Wagner, Martin) suggests that certain researchers act as collaboration hubs, fostering teamwork among select groups. However, the absence of a larger, more integrated structure indicates that the field may be highly fragmented, with many researchers not engaged in extensive co-authorship networks.
Figure 18 highlights the research the institutional partnerships in the field of organizational digitalization, innovation, and sustainability. The presence of multiple clusters suggests that research in this area is geographically diverse, with universities from Europe, Asia, and the Americas forming distinct yet interconnected collaboration networks. Some institutions, such as Luleå University of Technology, Zhejiang Shuren University, and Shanghai University, appear as central hubs, indicating their key role in fostering international academic cooperation. The structure of the network suggests that while some institutions collaborate extensively across regions, others remain more isolated, highlighting potential gaps in global research integration. Strengthening cross-institutional and interdisciplinary collaborations could enhance knowledge exchange and lead to more impactful research on the intersection of digital transformation and sustainability. This analysis underscores the importance of academic partnerships in advancing sustainable innovation through shared expertise and resources.
This bibliometric analysis concludes with the country collaboration network map (Figure 19), which illustrates the global research partnerships in the field of organizational digitalization, innovation, and sustainability, highlighting the most active nations and their international connections. The central position and large node size of China suggest that it is a key player in the field, forming extensive collaborations with countries like South Korea, Australia, and Iran, indicating strong regional and intercontinental partnerships. European countries, including Italy, Spain, Germany, and England, also form dense collaboration clusters, showing a strong intra-European research network. The USA appears connected but less central, suggesting that while it engages in international research, its collaboration patterns may be more selective. The presence of multiple smaller clusters, such as India’s connections to the Middle East and Southeast Asia, suggests regional research hubs that contribute to the field but are not yet fully integrated into the global network. The diverse nature of these collaborations highlights the multidisciplinary and international efforts required to address the challenges of digital transformation and sustainability, yet the network also suggests potential gaps in cross-regional partnerships.
The analysis reveals significant fragmentation among institutions and countries, with several regions (Thailand, Morocco, Slovenia, etc.) and universities (Technology University Kosice, Zhejiang Shuren University, etc.) operating in relative isolation. This suggests the need for targeted strategies to foster broader, more inclusive collaboration networks. For example, international research funding programs (e.g., Horizon Europe, Erasmus+, or cross-border university alliances) can serve as platforms to promote joint projects between high-output and lower-participation regions. Additionally, thematic research clusters or digitally supported knowledge hubs could facilitate access to best practices, methods, and data resources. Journals and conferences may also consider encouraging multi-country co-authorship by introducing incentives or thematic calls aimed at global collaboration. Ultimately, addressing these gaps requires coordinated efforts at the policy, institutional, and individual researcher levels.

5. Conclusions

The bibliometric analysis conducted in this study has provided a comprehensive overview of the scientific literature on the relationship between organizational digitalization, innovation, and sustainability. By addressing three key research questions, the study has shed light on how this relationship is conceptualized, the structure of the existing research landscape, and the potential directions for future studies. The findings indicate a significant and growing academic interest in this intersection, particularly since 2017, with a marked increase in research output in the last five years. While this growth has been rapid, it should not be interpreted as exponential in the strict mathematical sense. Rather, it is more likely to follow a logistic trend, where initial acceleration is followed by a plateau as systemic constraints such as journal capacity, researcher availability, and topic saturation come into play. The thematic analysis revealed that digital transformation plays a critical role in driving sustainable innovation, with Industry 4.0 technologies such as artificial intelligence, blockchain, and the Internet of Things (IoT) emerging as core enablers. However, the study also identified conceptual fragmentation, with varying definitions and perspectives on how digitalization contributes to sustainability. This suggests the need for a more integrated theoretical framework that connects digital transformation strategies with long-term sustainability objectives. Moreover, these findings may also serve as a lens through which one could assess theoretical consolidation and fragmentation in this emerging research domain. Identifying gaps is not merely an observation of low frequency but a call for theoretical development where concepts such as dynamic capabilities, responsible innovation, and stakeholder theory can intersect more meaningfully with digital and sustainability scientific literature.
The structural analysis of the literature highlighted the key intellectual, conceptual, and social elements shaping this research domain. Co-occurrence analysis of keywords demonstrated that while some themes, such as innovation management and technology, are well-developed motor themes, others, such as digitalization’s impact on corporate social responsibility, remain underexplored. The co-authorship and institutional collaboration networks indicated that while research in this field is expanding, collaboration patterns remain uneven, with a few dominant countries and institutions leading the discourse. China, Italy, and Germany emerged as the most productive countries; however, the collaboration network reveals persistent fragmentation. The citation analysis further revealed a distinction between highly productive authors and highly cited ones, reinforcing the idea that research impact is not solely determined by publication volume but also by the theoretical and empirical contributions made.
The theoretical implications of this study are significant, as they reinforce the idea that digitalization is not merely a technological trend but a transformative force that reshapes business models, value chains, and sustainability practices. The findings suggest that future research should integrate digital transformation theories with sustainability frameworks, bridging the gap between technological adoption and environmental, social, and governance concerns. However, this study does not test or evaluate specific causal mechanisms linking digitalization, innovation, and sustainability. As a bibliometric analysis, this approach is primarily exploratory and descriptive, aimed at mapping the intellectual and conceptual landscape of the field. While the results highlight thematic clusters and underexplored connections, they do not provide explanatory models or validate existing theoretical frameworks. Future research could build upon these findings by employing qualitative or quantitative empirical methods to test causal relationships, develop integrative models (e.g., dynamic capabilities for sustainability-oriented innovation), or assess sector-specific mechanisms in depth. The identification of performance and impact as key but underdeveloped themes indicates that there is still a need to understand how digital transformation contributes to measurable sustainability outcomes. Additionally, the presence of niche themes such as empirical diversity suggests that different regions and industries may have unique perspectives on the interplay between digitalization and sustainability, warranting further comparative studies.
From a practical perspective, the study offers valuable insights for businesses seeking to align digital transformation strategies with sustainability goals. Organizations can benefit from digital transformation to improve sustainability outcomes, yet the fragmented research coverage identified in this study—particularly regarding SMEs, CSR integration, and performance evaluation—indicates persistent challenges in both theory and practice. Rather than diagnosing these barriers directly, these findings suggest that these areas warrant further investigation and support to enable more effective digital sustainability transitions. As sustainability becomes a competitive advantage, businesses must develop comprehensive digital sustainability strategies that integrate long-term environmental and social considerations into their core operations. Managers should also focus on performance measurement, as the study suggests a lack of standardized metrics for assessing the impact of digitalization on sustainability goals.
Policymakers play a crucial role in fostering ecosystems where digital transformation and sustainability advance together. The collaboration analysis suggests that while certain countries dominate research in this field, cross-regional partnerships remain limited, indicating the need for policies that encourage international cooperation. Governments should provide incentives for businesses to adopt green digital technologies, such as tax breaks for companies implementing AI-driven energy management systems or blockchain-based sustainable supply chains. Moreover, regulatory frameworks should be updated to ensure that digitalization efforts align with broader sustainability goals, including the United Nations Sustainable Development Goals. Funding for interdisciplinary research should be prioritized, bridging the gap between technology-focused and sustainability-driven studies to promote more holistic solutions.
Future research should address several gaps identified in this study. First, the role of emerging technologies in driving sustainable innovation needs further exploration, particularly in understanding how AI, the IoT, and blockchain can be leveraged to achieve environmental and social benefits. Second, researchers should develop standardized methodologies for measuring the sustainability impact of digital transformation, ensuring that businesses and policymakers can track progress effectively. Third, the link between digitalization and corporate social responsibility remains an underdeveloped area, requiring more research on how digital technologies can enhance transparency, stakeholder engagement, and ethical business practices. Fourth, SMEs face unique challenges in adopting digital sustainability strategies, and future research should explore tailored solutions that consider financial, regulatory, and operational constraints.
Despite the valuable insights provided by this study, several limitations must be acknowledged. The reliance on the Web of Science database means that relevant research indexed in other databases, such as Scopus or Google Scholar, was not included. This may have resulted in the omission of relevant studies—especially from interdisciplinary or emerging domains—and may have introduced some selection bias. Additionally, the study focused exclusively on English-language publications, potentially overlooking important contributions from non-English sources. The bibliometric approach, while effective in mapping research trends and structures, has inherent limitations in capturing the depth and qualitative nuances of the literature and in harmonizing terminology across diverse sources. In particular, the inability to merge spelling variants or semantically similar keywords (e.g., “digitalisation” vs. “digitalization”) or fragmented author identities (e.g., “Wang S” vs. “S. Wang”) may have introduced some analytical noise in results of this bibliometric analysis. Future studies should complement bibliometric analysis with systematic literature reviews or meta-analytical approaches to provide a more comprehensive understanding of the field. Given the rapid evolution of this field, the trends identified here may shift in the coming years, necessitating continuous updates to bibliometric analyses. Lastly, although normalized citation counts were normalized by publication year, other adjustments, such as field-specific citation norms or journal-level impact, were not used, which could influence visibility and citation behavior.
In conclusion, this study has provided a structured overview of the scientific literature examining the relationship between organizational digitalization, innovation, and sustainability. The findings indicate that digital transformation is a critical enabler of sustainable innovation, yet significant gaps remain in understanding its full impact. While research in this field is expanding, there is a need for greater interdisciplinary collaboration, standardization of sustainability metrics, and policy support to ensure that digitalization contributes to long-term sustainability objectives. Despite its limitations, this study serves as a valuable foundation for academics, practitioners, and policymakers seeking to navigate the evolving landscape of digital transformation and sustainability. By fostering collaboration and integrating technological advancements with sustainability principles, organizations and societies can work towards a more innovative and environmentally responsible future.

Author Contributions

Conceptualization, L.-S.M. and C.S.; Data curation, L.V. and A.B.; Methodology, V.V.S. and M.S.; Software, V.V.S. and L.-G.M.; Supervision, C.S.; Writing—original draft, L.-S.M., V.V.S. and L.-G.M.; Writing—review & editing, A.B. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data available upon demand.

Acknowledgments

The research within this paper was conducted within and with the support of the Interdisciplinary Research Center for Economics and Social Sciences, INCESA (Research Infrastructure in Applied Sciences), University of Craiova, a part of the project “HUB-UCv—Support Center for International CD Projects for the Oltenia” project code POC/80/1/2/107885, cofinanced by the European Social Fund within the Sectorial Operational Program COMPETITIVENESS 2014–2020.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Annual scientific production. Source: the authors’ own processing of Web of Science bibliometric data, using MS Excel for Mac V. 16.66.1.
Figure 1. Annual scientific production. Source: the authors’ own processing of Web of Science bibliometric data, using MS Excel for Mac V. 16.66.1.
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Figure 2. Tree map of the author’s keywords. Source: the authors’ own processing of Web of Science bibliometric data, using Bibliometrix package of R v. 4.3.0.
Figure 2. Tree map of the author’s keywords. Source: the authors’ own processing of Web of Science bibliometric data, using Bibliometrix package of R v. 4.3.0.
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Figure 3. Word cloud of the most used words in the 775 abstracts. Source: the authors’ own processing of Web of Science bibliometric data, using Bibliometrix package of R v. 4.3.0.
Figure 3. Word cloud of the most used words in the 775 abstracts. Source: the authors’ own processing of Web of Science bibliometric data, using Bibliometrix package of R v. 4.3.0.
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Figure 4. Most prolific journals. Source: the authors’ own processing of Web of Science bibliometric data, using Bibliometrix package of R v. 4.3.0.
Figure 4. Most prolific journals. Source: the authors’ own processing of Web of Science bibliometric data, using Bibliometrix package of R v. 4.3.0.
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Figure 5. Most local cited journals. Source: the authors’ own processing of Web of Science bibliometric data, using Bibliometrix package of R v. 4.3.0.
Figure 5. Most local cited journals. Source: the authors’ own processing of Web of Science bibliometric data, using Bibliometrix package of R v. 4.3.0.
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Figure 6. Most productive authors. Source: the authors’ own processing of Web of Science bibliometric data, using Bibliometrix package of R v. 4.3.0.
Figure 6. Most productive authors. Source: the authors’ own processing of Web of Science bibliometric data, using Bibliometrix package of R v. 4.3.0.
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Figure 7. Most cited authors. Source: the authors’ own processing of Web of Science bibliometric data, using Bibliometrix package of R v. 4.3.0.
Figure 7. Most cited authors. Source: the authors’ own processing of Web of Science bibliometric data, using Bibliometrix package of R v. 4.3.0.
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Figure 8. Most productive institutions. Source: the authors’ own processing of Web of Science bibliometric data, using Bibliometrix package of R v. 4.3.0.
Figure 8. Most productive institutions. Source: the authors’ own processing of Web of Science bibliometric data, using Bibliometrix package of R v. 4.3.0.
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Figure 9. Global distribution of scientific output on the relationship between digitalization, innovation, and sustainability. Source: the authors’ own processing of Web of Science bibliometric data, using Bibliometrix package of R v. 4.3.0.
Figure 9. Global distribution of scientific output on the relationship between digitalization, innovation, and sustainability. Source: the authors’ own processing of Web of Science bibliometric data, using Bibliometrix package of R v. 4.3.0.
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Figure 10. Keywords frequency over time. Source: the authors’ own processing of Web of Science bibliometric data, using Bibliometrix package of R v. 4.3.0.
Figure 10. Keywords frequency over time. Source: the authors’ own processing of Web of Science bibliometric data, using Bibliometrix package of R v. 4.3.0.
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Figure 11. Keyword co-occurrence map. Source: the authors’ own processing of Web of Science bibliometric data, using VOSViewer v. 1.6.20.
Figure 11. Keyword co-occurrence map. Source: the authors’ own processing of Web of Science bibliometric data, using VOSViewer v. 1.6.20.
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Figure 12. Thematic clustering map of the author’s keywords. Source: the authors’ own processing of Web of Science bibliometric data, using Bibliometrix package of R v. 4.3.0.
Figure 12. Thematic clustering map of the author’s keywords. Source: the authors’ own processing of Web of Science bibliometric data, using Bibliometrix package of R v. 4.3.0.
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Figure 13. Co-citation by sources network map. Source: the authors’ own processing of Web of Science bibliometric data, using VOSViewer v. 1.6.20.
Figure 13. Co-citation by sources network map. Source: the authors’ own processing of Web of Science bibliometric data, using VOSViewer v. 1.6.20.
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Figure 14. Bibliographic coupling by sources network map. Source: the authors’ own processing of Web of Science bibliometric data, using VOSViewer v. 1.6.20.
Figure 14. Bibliographic coupling by sources network map. Source: the authors’ own processing of Web of Science bibliometric data, using VOSViewer v. 1.6.20.
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Figure 15. Most cited documents: (a) globally [23,46,47,48,49,50,51,52,53,54]; (b) locally [23,49,51,53,55,56,57,58,59,60]. Source: the authors’ own processing of Web of Science bibliometric data, using Bibliometrix package of R v. 4.3.0.
Figure 15. Most cited documents: (a) globally [23,46,47,48,49,50,51,52,53,54]; (b) locally [23,49,51,53,55,56,57,58,59,60]. Source: the authors’ own processing of Web of Science bibliometric data, using Bibliometrix package of R v. 4.3.0.
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Figure 16. Most locally cited references [1,61,62,63,64,65,66,67,68,69]. Source: the authors’ own processing of Web of Science bibliometric data, using Bibliometrix package of R v.4.3.0.
Figure 16. Most locally cited references [1,61,62,63,64,65,66,67,68,69]. Source: the authors’ own processing of Web of Science bibliometric data, using Bibliometrix package of R v.4.3.0.
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Figure 17. Co-authorship network map. Source: the authors’ own processing of Web of Science bibliometric data, using VosViewer v.1.6.20.
Figure 17. Co-authorship network map. Source: the authors’ own processing of Web of Science bibliometric data, using VosViewer v.1.6.20.
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Figure 18. Institutional collaboration network map. Source: the authors’ own processing of Web of Science bibliometric data, using VOSViewer v.1.6.20.
Figure 18. Institutional collaboration network map. Source: the authors’ own processing of Web of Science bibliometric data, using VOSViewer v.1.6.20.
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Figure 19. Country collaboration network map. Source: the authors’ own processing of Web of Science bibliometric data, using VOSViewer v. 1.6.20.
Figure 19. Country collaboration network map. Source: the authors’ own processing of Web of Science bibliometric data, using VOSViewer v. 1.6.20.
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Table 1. Descriptive statistics.
Table 1. Descriptive statistics.
DescriptionResults
MAIN INFORMATION ABOUT DATA
Timespan2004:2025
Sources290
Documents775
Annual Growth Rate %21.99
Document average age2.21
References46,343
DOCUMENT CONTENTS
Keywords Plus (ID)1088
Author’s Keywords (DE)2493
AUTHORS
Authors2483
Authors of single-authored docs58
AUTHORS COLLABORATION
Single-authored docs60
Co-authors per doc3.68
International co-authorships %34.71
DOCUMENT TYPES
Article579
Article; early access75
Proceedings paper64
review56
Review; early access1
Source: the authors’ own processing of Web of Science bibliometric data, using Bibliometrix package of R v. 4.3.0.
Table 2. Average number of citations per year.
Table 2. Average number of citations per year.
YearNumber of Articles PublishedTotal
Citations
Number of Articles PublishedAverage
Citations
Per Article
Average
Citations Per Citable Year
Citable
Years
20041010.000.0022
20061010.000.0020
2013230215.001.1513
20162120.500.0510
20177105715.001.679
2018112751125.003.128
2019219342144.486.357
20203926843968.8211.476
20215524685544.878.985
2022103298710329.007.254
2023179251717914.064.693
202428910972893.801.902
20256538650.580.601
Source: the authors’ own processing of Web of Science bibliometric data, using MS Excel for Mac v. 16.66.1 and Bibliometrix package of R v. 4.3.0.
Table 3. Most productive and most cited countries.
Table 3. Most productive and most cited countries.
CountryTotal CitationsTotal PapersAverage Article Citations
Italy21795738.20
China20152069.80
Iran11854296.20
Germany8253027.50
Finland665795.00
United Kingdom5482422.80
Sweden4711531.40
France4381725.80
Spain4243213.20
Portugal2972312.90
Source: the authors’ own processing of Web of Science bibliometric data, using MS Excel for Mac V. 16.66.1.
Table 4. Future directions of research on the relationship between organizational digitalization, innovation, and sustainability.
Table 4. Future directions of research on the relationship between organizational digitalization, innovation, and sustainability.
Research DirectionDescription
Exploring the causal mechanisms through which emerging technologies are driving sustainability-oriented innovationThe keyword co-occurrence network (Figure 11) highlights “blockchain”, “artificial intelligence”, and “Industry 4.0” as connected to sustainability, but their role in sustainable business models remains underdeveloped. Thus, future researchers should move beyond conceptual associations and examine how specific digital technologies (e.g., blockchain, AI, the IoT) influence sustainability outcomes through concrete innovation pathways (such as circular economy adoption, sustainable product design, or green supply chain management). At the same time, future researchers should explore the ethical and environmental implications of integrating digital technologies in corporate sustainability strategies, as well as conduct comparative case studies on organizations leveraging AI-driven decision-making and IoT solutions for enhancing sustainability performance. Mixed-method approaches are recommended, such as multiple case studies in key sectors (manufacturing, logistics, agri-food) or structural equation modeling (SEM) based on organizational survey data.
Measuring the performance impact of digital transformation on sustainability goalsThe thematic mapping (Figure 12) identified “performance”, “impact”, and “dynamic capabilities” as basic themes, suggesting they are fundamental but still evolving. Thus, rather than treating digitalization as a binary variable, future research could quantify the level of digital maturity and link it to sustainability KPIs (such as carbon emissions, resource efficiency, waste reduction), as well as examine the long-term financial and environmental trade-offs of digital sustainability strategies in different industries and regions and use big data and machine learning to analyze how digital initiatives affect ESG performance. Studies can use survey-based digital capability indexes, matched with firm-level sustainability performance data, or econometric modeling across industries.
Strengthening the link between digitalization and corporate social responsibility (CSR)The co-occurrence analysis (Figure 11) links “corporate social responsibility” (CSR) with “digital transformation” and “sustainable development”, yet CSR remains less central. There is a need to empirically assess how digital tools—such as data analytics, blockchain, and AI-based transparency platforms—contribute to CSR implementation and ESG accountability. Research should investigate how digital technologies (e.g., big data analytics, AI-powered transparency tools) can enhance CSR and ESG reporting, examine the role of digital platforms in enabling stakeholder engagement and ethical decision-making in sustainable business practices, and explore how companies can use blockchain for transparent supply chain management, reducing fraud and improving corporate accountability. Suggested methods include longitudinal studies on CSR reporting evolution pre-/post-digitalization, panel data analysis using ESG performance indices, or sentiment/content analysis of CSR disclosures.
Investigating barriers and enablers of digital sustainability strategies among SMEs and entrepreneursThe blue cluster in Figure 12 links “entrepreneurship” and “SMEs” with sustainability and digitalization, but this relationship is less explored compared to larger corporations. Thus, future scholars should focus on identifying context-specific challenges (financial constraints, digital skill gaps) and enabling factors (policy incentives, digital ecosystems) that affect SMEs’ ability to implement digitally driven sustainable innovations. Recommended methods include qualitative interviews with entrepreneurs, regional comparative studies, or scenario-based design workshops.
Source: the authors’ own conclusions.
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Mihai, L.-S.; Sitnikov, V.V.; Sichigea, M.; Vasilescu, L.; Băndoi, A.; Sitnikov, C.; Mănescu, L.-G. A Bibliometric Analysis of the Role of Digitalization in Achieving Sustainability-Oriented Innovation. Sustainability 2025, 17, 5822. https://doi.org/10.3390/su17135822

AMA Style

Mihai L-S, Sitnikov VV, Sichigea M, Vasilescu L, Băndoi A, Sitnikov C, Mănescu L-G. A Bibliometric Analysis of the Role of Digitalization in Achieving Sustainability-Oriented Innovation. Sustainability. 2025; 17(13):5822. https://doi.org/10.3390/su17135822

Chicago/Turabian Style

Mihai, Laurențiu-Stelian, Valeri Viorel Sitnikov, Mirela Sichigea, Laura Vasilescu, Anca Băndoi, Cătălina Sitnikov, and Leonardo-Geo Mănescu. 2025. "A Bibliometric Analysis of the Role of Digitalization in Achieving Sustainability-Oriented Innovation" Sustainability 17, no. 13: 5822. https://doi.org/10.3390/su17135822

APA Style

Mihai, L.-S., Sitnikov, V. V., Sichigea, M., Vasilescu, L., Băndoi, A., Sitnikov, C., & Mănescu, L.-G. (2025). A Bibliometric Analysis of the Role of Digitalization in Achieving Sustainability-Oriented Innovation. Sustainability, 17(13), 5822. https://doi.org/10.3390/su17135822

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