research topics in digital transformation

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• v.9(1); 2023 Jan

Digital transformation: A meta-review and guidelines for future research

João reis.

a Industrial Engineering and Management, Faculty of Engineering, Lusofona University and EIGeS, Campo Grande, 1749-024, Lisbon, Portugal

Nuno Melão

b CISeD–Research Center in Digital Services, Polytechnic Institute of Viseu, Campus Politécnico, 3504-510, Viseu, Portugal

The emergence of digital transformation has changed the business landscape for the foreseeable future. As scholars advance their understanding and digital transformation begins to gain maturity, it becomes necessary to develop a synthesis to create solid foundations. To do so, significant steps need to be taken to critically, rigorously, and transparently examine the existing literature. Therefore, this article uses a meta-review with the support of the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) Protocol. As a result, we identified six dimensions and seventeen categories related to digital transformation. The organizational, technological, and social dimensions are still pivotal in digital transformation, while two new dimensions (sustainability and smart cities) still need to be explored in the existing literature. The need to deepen knowledge in digital transformation and refine the dimensions found is of paramount importance, as it involves some complexity due to organizational dynamics and the development of new technologies. It was also possible to identify opportunities, challenges, and future directions.

1. Introduction

In recent years, academics have provided in-depth knowledge regarding Digital Transformation (DT). These contributions were carried out in the production industry [ 1 ], service industry [ 2 ], healthcare [ 3 ], and education [ 4 ], just to name a few areas. However, these studies are dispersed across several academic fields. As the academic community realized this limitation, researchers became interested in gaining a broader view of DT through systematic literature reviews (SLR) within each field [ 5 – 7 ] and some of them about the DT phenomenon itself [ 8 ]. Although the aforementioned works have contributed to significant advances in knowledge, there are no records of articles providing a detailed holistic view of DT. To fill this gap in the literature, we followed the suggestions of notable scholars [ 9 , 10 ] and set out to undertake a meta-review. Along with this, we also identified reports of other phenomena about DT, such as the paradox of digital technologies [ 11 ]. If, on the one hand, there is a belief in the benefits of adopting DT, on the other hand, there has been some frustration with DT and its impacts on organizations. Conceptually, DT benefits organizations with better operational efficiency [ 6 , 12 ], greater innovation [ 13 ], and cost reduction [ 14 ] in the medium-long term. However, the implementation of DT is complex as it entails initial costs, requires changes, and creates resistance from workers [ 15 ]. Therefore, DT adoption may be risky without models and tools that assist its implementation across organizations. Viewed in isolation, this meta-review may be considered ambitious; however, it can become a relevant work if viewed from a holistic perspective, along with other systematic reviews. We opted for a meta-review because it can ensure reproducibility and transparency of the entire review process. To this end, we explained the methodological process in detail and included the content analysis process (see Appendix A) to make the entire process visible to readers. With DT changing rapidly, the need to identify opportunities, challenges, and future directions is critical. In this regard, we developed the following research question: What are the drivers of DT promoting scientific growth? The answer to the previous question can be achieved by addressing the following objectives: (1) identifying the most relevant thematic areas; (2) categorize the literature on DT; and (3) propose future research based on recent studies. We consider this study original and innovative because it fills an important gap in the literature. In November 22nd, 2022, after performing a search on Elsevier Scopus with the search terms “digital transforming” and “meta-review” in the title of the document, no result was found; in title-abstract-keyword only four documents were found, but they were not directly related to the theme. These results obtained in one of the most important international databases are surprising, especially considering the exponential growth of research on DT in recent years.

The next section provides a conceptualization of DT and associated terms. We then explain the PRISMA process and how the data was collected and analyzed. The results section presents a holistic theoretical-conceptual model of DT and a research agenda. Finally, the conclusions section focuses on managerial, theoretical, and original contributions.

2. Conceptual overview

In the existing literature, concepts referring to DT are still inconsistent or treated simplistically [ 16 , 17 ]. Although there is still some difficulty in accepting a consensual definition of DT, this section describes the relationship between digitation, digitalization, and DT. If it was common to find conceptual miscellanea in the past between digitization, digitalization, and DT, this issue now seems to be overcome. In that regard, Kohli & Johnson [ 18 ] stress that digitization is commonly associated with transforming traditional processes into digital ones. Loske & Klumpp [ 19 ] also consider that digitization is a “process of converting analog data into digital data sets.” Furthermore, recent research argues that digitization encodes or shifts analog tasks and information into a digital format so that computers can store, process, or transmit information without altering value-creating activities [ 20 ]. An excellent example of digitization is e-books or downloadable music, i.e., converting tangible products into products delivered digitally [ 18 ].

Digitalization, in turn, is described as digital technologies that can be used to alter existing business processes. In that regard, companies are investing in products and process innovation through new digital solutions, allowing them to deal with more data and information [ 21 ]. One example is the creation of online or mobile communication channels allowing customers to connect with companies more conveniently than through traditional interactions [ 22 ]. Thus, within the scope of digitalization, companies must apply digital technologies that allow the optimization of existing business processes, i.e., better coordination between processes and creating value for the customer. In short, the difference between digitation and digitalization lies in creating value and improving the customer experience.

Although the concept of DT has gained significant notoriety only recently, it dates back to the 90's [ 23 ]. DT goes beyond digitalization as it involves changing organizational processes and tasks, which typically lead to developing new business models [ 17 ]. Thus, DT consists of integrating information technologies in companies' operations, whether internal or external [ 24 ]. It can also be considered as a change that occurs with the implementation of technologies in a system within a company [ 19 ]. This transformation is supported by the adoption of new technologies from which new performance, new processes, and new business models emerge [ 25 , 26 ]. In addition, DT is not only linked to technology, but also to an improvement in the business model, collaboration, and culture [ 27 ]. This transformation arises with the use of digital tools in the daily activities and processes of the company, being subsequently achieved through its promotion inside and outside it [ 28 ]. For instance, DT can be employed in several domains, such as the healthcare sector; in this regard, the wide and deep use of information technologies changes how health services are delivered and processed [ 29 ]. A company that opts for DT seeks to offer a product and/or service through new digital formats, thus achieving a link between physical processes and virtual processes [ 23 ]. Some authors identify several possible contributions of DT in a company, such as: (1) optimization of physical and digital resources; (2) obtaining greater competitive advantage; (3) greater creation of value for the customer; and (4) cost reduction [ 30 , 31 ].

However, not all industries have been able to keep up with this technological pace and adopt digital technologies, either due to investment difficulties or lack of adaptation of their business model [32, p. 141]. In a digital company, success involves accepting market uncertainty and volatility, identifying opportunities and having the ambition to realize them, as well as making quick decisions taking into account innovation, customers and competitors [ 33 ]. DT has played a disruptive role in various sectors of activity. However, the retail sector was considered one of the sectors most prone to DT [ 30 , 32 ]. This is due to the emergence of new consumers called “digital natives”, who have driven the use of digital platforms and, consequently, the need for innovation in current business models [ 7 ]. The next section discusses the data collection process, the content analysis, and the research limitations.

3. Materials and methods

This article uses a meta-review, as it aims to synthesize the existing body of completed and recorded work produced by researchers [ 34 ]. Meta-reviews are methods known to be able to gather the literature and which can have a significant influence on research, practice, and policy [ 35 ]. A Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) also supports the meta-review to discover new ideas, concepts, and debates in a critical, rigorous, and transparent way. PRISMA included a checklist of 27 items and four-phase flowchart ( Fig. 1 ), enabling data extraction from two of the largest abstract and citation databases of peer-reviewed literature.

PRISMA flowchart.

The search was conducted in Elsevier's Scopus and Web of Science Core Collection (WoS) on December 8, 2021 ( Fig. 1 ). This search combined the terms “digital transformation” and “systematic literature review” in the Title-Abstract-Keywords (TITLE-ABS-KEY) to identify the manuscripts within the area of research (identification phase). Then, we applied pre-selected filters (i.e., language, source, and document type) to identify the most relevant manuscripts (screening phase). The next phase included accessibility criteria (eligibility phase), which encompassed removing duplicated articles and those that were not strictly related to the topic. Finally, articles not identified in the Scopus and WoS databases were included (inclusion phase). Incorporating additional articles allowed to justify and/or reinforce the arguments used in the results section. That is, highly cited conference papers in DT [ 17 ] can also be relevant and should not be left out. We were careful with the issue of transparency, and, for that reason, we included the flowchart ( Fig. 1 ) and their respective explanation. As mentioned earlier, data collection in the Scopus and WoS databases was carried out until the end of 2021. Both databases were selected because they are considered the largest international and multidisciplinary research databases of peer-reviewed manuscripts. This argument is also used by researchers who have published articles on DT in top-tier Journals, such as Benavides et al. [ 5 ] and Lombardi and Secundo [ 36 ], or in some cases, just one of the selected databases, such as the WoS, by Zhu [ 8 ], and Scopus by de Bem Machado et al. [ 37 ]. A more objective argument that justifies using Scopus and WoS is related to the coverage of journals in the area of Natural Sciences and Engineering [ 38 ], areas typically associated with DT. Moreover, we could have much broader data coverage [ 39 ] and free access if we selected Google Scholar. However, despite being a powerful search engine, it does not guarantee that the documents included have been peer-reviewed.

After performing the search using the terms “digital transformation” and “systematic literature review” in the TITLE-ABS-KEY, we identified 262 manuscripts. Following this, we applied the filter by full-text journal articles to obtain high-quality research articles. For readability and interpretation reasons, we selected only articles in English; otherwise, difficulties in interpretation could lead to biased results. This phase resulted in the selection of 79 scientific journal articles. The eligibility phase allowed the elimination of 17 duplicate articles and 33 articles that did not correspond to the research objectives, resulting in 29 articles. The last phase included 5 more articles, so in the end, we were left with 34 articles to analyze. The PRISMA protocol we followed uses the same process of identification, screening, eligibility, and inclusion of other relevant scientific articles published in Q1 journals, whose databases were Scopus and WoS [ 40 ].

Data were encoded twice. First, the articles were manually encoded. That is, the articles were read in full, and repeated words and text excerpts were identified ( Appendix A). Data analysis was performed using low-tech material (e.g., Excel). However, as a significant number of articles were being examined, text analysis using a computer-assisted data analysis package is recommended. Therefore, the second step included using NVivo12 [ 41 ], a qualitative data analysis software for researchers. Data were analyzed using the content analysis technique [ 42 ]. This technique allowed coding the most important phrases and words [ 43 ], making it possible to identify patterns in emerging codes and ideas. Specifically, the process was carried out in four stages: first, we read the entire texts to identify the most relevant phrases and ideas, followed by a coding process; second, we associated excerpts/codes from the selected articles with the categories and added new ones as necessary; third, we identified emerging patterns and ideas (dimensions); lastly, we revised the previous categories, making adjustments, until redundancies and contradictions were clarified and the results were easily interpreted. In short, this technique enabled to code and analyze a large volume of data. After the content analysis, we also followed a verification process: first, we compared the two analyzes, the aforementioned manual cross-analysis with NVivo12; secondly, a verification that included the analysis of the articles’ keywords. The latter step included cross-checking the categories and sub-categories (i.e., our manual categorization) with the 34 articles’ keyword statistics (i.e., authors' choice) and which can be retrieved directly from Scopus. This process allowed to identify discrepancies in the data analysis. As we found similarities, we consolidated the coding process.

Despite the advantages of meta-review, this methodology also has limitations. Applying filters may have excluded relevant documents from other databases (PubMed, etc.), search engines (e.g., Google scholar), or other forms of publication (e.g., books, chapters). However, the PRISMA technique has an advantage over traditional systematic reviews because, unlike the latter, PRISMA (last phase) allows the inclusion of relevant articles overcoming the aforementioned limitation. Lastly, this article presents a “snapshot” of the reality, as both databases are permanently being updated.

4. Results and discussion

4.1. digital transformation overview – influential topics and subject areas.

This section aims to respond to the first research objective. To transparently identify the most relevant thematic areas, we use the graphs provided directly by the Scopus database, which is the leading database for this article (similarly used by Lombardi and Secundo [ 36 ]). Compared to WoS, Scopus was selected for covering a wider range of journals, both in keyword search and citation analysis [ 16 ]. Additionally, most papers indexed in WoS are included in Scopus [ 44 ]. Indeed, when we exclude repeated articles (i.e., screening phase, Fig. 1 ), most of the selected articles come from Scopus. Therefore, for this section, the first initial terms “digital transformation” and “systematic literature review” were used in the Scopus TITLE-ABS-KEY (resulting in 157 articles), which allowed us to identify the most relevant thematic areas. This graphical analysis aims to provide the most holistic view possible in order to provide readers with an overview of the results. For example, from this analysis, the reader can easily infer that the topic is growing exponentially ( Fig. 2 ) and that only 30% of Scopus documents have been analyzed ( Fig. 3 ). For quality reasons, the content analysis had to focus only on journal articles, being therefore more restricted.

Documents by year (retrieved from Elsevier Scopus).

Documents by type (retrieved from Elsevier Scopus).

Fig. 2 shows the upward scientific interest in DT, especially from 2018 onwards. This phenomenon is probably explained by the maturity of the topic, making it possible to analyze the existing literature with some relevance. In particular, we can see that published studies have mainly focused on business model strategies [ 45 – 49 ], digital business [ 48 , 50 , 51 ], the use of disruptive technologies [ 47 , [52] , [53] , [54] ], sustainability [ 55 , 56 ], human resources [ 57 – 59 ], and smart cities [ 45 ]. In turn, Fig. 3 shows the types of documents focused on DT. The publication in conference proceedings is an indicator that DT is arousing the interest of researchers in the scope of the discussion of ideas and the search for solid knowledge on the subject. In terms of article publishing, we have seen that the appetite of top-tier indexed Journals is high, as 45% of the articles are from Q1 Journals and 31% from Q2 Journals.

Regarding the distribution of papers by country, we can see that Germany, the United Kingdom, and Brazil are the ones that stood out the most ( Fig. 4 ). Germany stands out from the other economies, as German industry is one of the main drivers of Industry 4.0 (I4.0). To do so, Germany has made a significant investment in research, which is essential for initiatives aimed at digitizing the manufacturing industry [ 56 ]. For instance, Siemens has formed a research alliance in industrial automation and digitization with the state-funded Technical University of Munich, the Ludwig-Maximilians University, the German Research Center for Artificial Intelligence, and the Fraunhofer Institute for Applied and Integrated Security Applications [ 60 ].

Documents by country or territory (retrieved from Elsevier Scopus).

Considering that one of the drivers of the German economy has been I4.0, it is not surprising that the areas with the greatest scientific research are computer science (26.6%) and engineering (15.1%) in the context of the development of cyber-physical systems, cybersecurity, cloud computing, advanced robotics, just to name a few. Fig. 5 , with no surprise, also includes the subject area of business, management, and accounting (17.7%), given the impact of its coverage in different countries, industries, companies, and people. In that regard, Kraus et al. [ 61 ] argue that DT has led to considerable changes in many organizations, no longer seen as just a technological opportunity but as a way to introduce new processes that can improve the main structures of how companies do business.

Documents by subject area (retrieved from Elsevier Scopus).

4.2. Digital transformation overview – dimensions and categories

This section presents a general view of the existing literature regarding DT, thus responding to the second research objective. We focused exclusively on the analysis of the 34 articles that were selected from Scopus and WoS ( Fig. 1 ). Table 1 shows the dimensions and categories identified during data analysis. Appendix A presents a series of tables with more detailed information (including codes/phrases). Although it is not common to see tables with the complete content analysis available in scientific articles, we decided to make all the information available to the reader for transparency and reproducibility reasons.

Dimensions and categories.

4.2.1. Business models

The first dimension addresses (but not limited to) topics, such as ( Table A1 ): (1) business process innovation, which is improving the competitive position of organizations [ 45 , 54 ] and bringing disruptive DT to the global industrial value chain [ 53 , 60 , 62 ]; (2) digital business strategy that enhances productivity [ 46 , 63 , 64 ] and creates new value for customers [ 65 ].

With regard to innovation, the trend is for organizations in DT environments to implement value-added innovation by integrating social and economic dimensions from different types of innovation, such as product-service and process innovation, as well as innovation in business and organizational models [ 54 , 60 ]. Developing a digital business strategy is critical for organizations as DT involves business and technology issues, transcending organizational boundaries [ 46 ]. Furthermore, selecting technologies (i.e., tech-oriented) is vital to the business strategy and can significantly add value to the business [ 63 ]. Initially, Information Technology (IT) strategy was seen as a functional- and secondary-level strategy component; however, nowadays, DT is the central pillar of the strategy, driving the emergence of the “digital strategy” concept [ 48 ]. Thus, in the context of the digital age, the organizational environment is also more volatile, uncertain, complex, and ambiguous (VUCA), so the rapid changes in competition, demand, technology, and regulations are more challenging than ever. In that regard, the pressure on companies to align their business strategy with the changing technological environment has increased significantly with the emergence and growing importance of new disruptive digital technologies [ 60 , 64 ]. Therefore, a digital business strategy demands strong leadership, an agile and scalable core, and a clear focus on customer engagement or a digitized solutions strategy [ 65 ]. The “tech-oriented” view fails to capture the more fundamentally important role of the “procedural” character of DT, demanding a deeper and more complete “transformational” effort on vision, strategy, culture, human skills, resources and infrastructures, business model, and company's competitiveness [ 48 , 61 ].

In short, with regard to business models, we found that process innovation is changing the business landscape, increasing competitiveness through the development of new digital services and products. In that regard, the business strategy focuses on disruptive technologies. The VUCA environment pushes for a more comprehensive and transformational strategy where people and resources adapt to organizational needs.

4.2.2. Digital business

The second dimension addresses (but not limited to) topics, such as ( Table A2 ): (1) digital culture, literacy, and digital skills that are enhancing DT efforts [ 52 , 58 , 64 ]; (2) digital economy and the challenge of measuring the potential generated by digital technologies [ 65 , 66 ]; (3) innovation and socio-technological shared values, being seen as an opportunity to balance the responsibilities assigned to humans and machines [ 54 , 65 ].

When it comes to digital business, organizations wanting to benefit from their technology investments need to strengthen the digital skills of their workforce [ 58 ]. Therefore, the workforce is one of the key actors in transforming the organization, as digitally capable human resources will be managing and using technology [ 48 , 66 ]. Furthermore, employees working in digitally mature organizations describe their culture as more collaborative and innovative than traditional ones [ 64 ].

The success of the digital economy is expected to be ensured by strengthening the position of companies through the quality of corporate governance and financial structure, aligned with the latest technologies. The digital economy is seen as an economy that accelerates the DT of existing economic sectors, promotes new ecosystems enabled by digital technologies, and develops a digital industry [ 66 ]. Thus, the digital economy includes a combination of digital infrastructure, socio-technical processes, and information and communication technologies [ 56 ]. The risk of the digital economy is associated with the large-scale acceleration of the development of new technologies, which seems almost unstoppable due to the intensive innovation trend. Moreover, recent studies have also stressed that the greatest challenge many organizations face when investing in DT is finding a way for equating, reimagining and redefining the employees experience and bringing their digital literacy up to date. At this level, artificial intelligence (AI) is demanding greater skill in terms of problem solving, as it begins to outperform human performance in executing analytically complex cognitive tasks. Thus, the challenges appear to be twofold, both from the point of view of technological acceleration and the digital literacy of the workforce.

4.2.3. Technologies

The third dimension addresses (but not limited to) topics, such as ( Table A3 ): (1) technology and innovation management, which has been one of the main drivers of DT [ 48 , 52 , 61 , 64 , 65 , 67 ]; (2) AI and big data, which have been propelling significant developments in carrying out analytical-cognitive activities both in organizations and in the industry [ 55 , 56 , 58 , 62 , 64 , 68 ]; and the (3) Internet of Things (IoT) and I4.0, which involves the interconnection of computing power and intelligent data flow, enabling process control in the service and production industry [ 48 , 62 ].

Technology is one of the main drivers of DT, giving a significant boost to organizations that integrate this key factor into their strategy [ 62 ]. As mentioned earlier, technology is an enabler of DT that is causing a change in value creation, as it supports the development of new business models and a focus on acquiring new skills and competencies [ 67 ]. One of the largest consultancies, McKinsey & Company, proposed a model based on six building blocks that allows implementing a successful end-to-end transformation for industrial companies. These six blocks naturally go beyond the simple technology upgrade and are: (1) Create a business-led technology roadmap; (2) Talent development and qualification; (3) Adopt an agile delivery methodology; (4) Moving to a modern technology environment; (5) Focus on enriching data management; (6) Conduct the adaptation and scaling of digital initiatives [ 52 ]. With regard to technology, DT has aroused interest in specific digital technologies, such as AI and big data [ 65 ]. Due to VUCA pressure, companies are aligning their business strategy with digital technological change (e.g., AI, Big Data) [ 64 ]. In that regard, AI is defined as the transformation of service-product processes into automated processes, dependent on intelligent computer systems or robots that do not require human intervention to perform tasks associated with intelligence [ 6 , 47 ]. Despite the well-known advantages of AI and robotics, current discussion often covers the risks of automation. Debates have focused more on the adaptability of jobs in DT than on replacing human labor [ 69 ]. Most studies suggest that complex socioemotional tasks continue to be performed by human beings, while cognitive-analytic tasks will be increasingly migrated to machines [ 70 ]. DT has therefore led to the formation of the digital organization, whose most volatile asset is AI and computational capital, evidenced in the continuous growth of automated information and the creation of digital products [ 56 ]. Digital technologies such as AI, big data analytics, and social platforms generate positive improvements for society (smart cities) and industry (I4.0) [ 55 ]. Thus, DT has been described as the change in an organization's structure, processes, functions and business models due to the adoption of digital technologies such as IoT, AI, machine learning, augmented reality, just to mention a few [ 17 , 58 ]. Therefore, DT does not focus only on organizations, but on almost all domains of knowledge, as it radically changes the concepts traditionally defined in organizational and management science [ 68 ].

4.2.4. Sustainability

The fourth dimension addresses (but not limited to) topics, such as ( Table A4 ): (1) sustainable businesses that focus on the integration of new and disruptive technologies [ 53 , 55 , 56 ]; (2) sustainable competitive advantage by integrating these technologies into the companies’ business processes [ 47 ]; (3) sustainable development with an emphasis on the United Nations Sustainable Development Goals (SDGs) [ 56 ]; and (4) sustainable innovation with an emphasis on open innovation theory [ 53 ].

Transformation to I4.0 has involved occupational adaptations to ensure quality and sustainable business models [ 56 ], leading to carbon emissions reductions [ 55 ] and an augmented degree of social responsibility [ 53 ]. Within the scope of DT, industry-specific IT resources are valued because they reduce costs, supporting sustainable competitive advantages as a result [ 62 ]. Therefore, the objective of companies is to establish sustainable performance and competitive advantage by integrating technology in the decision-making process with corporate strategy [ 47 ]. Additionally, the open innovation paradigm suggests that a holistic and cognitive approach to corporate governance, based on a regime of cooperation between internal and external resources for value creation, opens the possibility of redefining business models in which knowledge develops horizontally. This is achieved by involving all actors in the corporate ecosystem to gain a long-term sustainable competitive advantage [ 53 ]. The interest is in understanding and presenting the impact of digitization initiatives on economic growth and the achievement of the United Nations SDG [ 56 ].

4.2.5. Human resources (HR)

The fifth dimension addresses (but not limited to) topics, such as ( Table A5 ) employee experience, career dynamics, and type of human-machine relationships [ 57 , 58 ].

Within DT, HR concerns have been about the ability of employees to establish Human-Robot Interaction and Collaboration (HRI-C) relationships. At this level, the discussion is broad and involves a change in culture, mindset, and skills required from employees [ 58 ]. However, dealing with DT and the establishment of HRI-C dynamics can be challenging, particularly if employees are not ready for them. Therefore, the pressure to create HRI-Cs can create information overload and employee anxiety [ 58 ]. On top of that, while the benefits of a diverse workforce are well known, the career dynamics of individuals with technical differences over the rest are not well understood [ 57 ]. These different levels of expertise conflict with the balance between the professional and personal lives of the workforce. Therefore, companies must find strategies to balance professional and personal life for individuals who move to more specialized fields.

Furthermore, the literature also highlights that “a change management strategy to gradually change the mindset of the workforce and senior management, and instill the idea that there is no end to change” [52, p. 15]. It is recommended that organizations should develop change management models in DT environments, similar to traditional models (e.g., Lewin's or Kotter's change management models). In that regard, Attaran and Attaran [ 63 ] go further, stating that organizations fail to change because leaders do not pay enough attention to change management, which negatively affects the companies’ HR, making the next change more challenging to implement.

4.2.6. Smart cities

The sixth dimension addresses (but not limited to) ( Table A6 ) smart manufacturing [ 45 , 55 , 60 ], in particular the use of disruptive technologies to produce high-value products and services. Smart cities are not exactly smart manufacturing; however, smart manufacturing contributes to a larger scenario, acting as an enabler of smart cities. This aspect emerges from our analysis and is in line with the arguments of Suvarna et al. [ 71 ]. According to these authors, smart manufacturing contributes to smart cities not only from a technological point of view but also because it satisfies sustainability issues, which are important indices that make up a smart city. Other authors, such as Lom et al. [ 72 ], followed the same argument when they stated that process-based I4.0 with smart city transportation systems could create very effective, demand-driven, and highly productive manufacturing companies, while contributing to the sustainable development of society.

DT has attracted increasing interest from academics and practitioners regarding sustainability and intelligence/automation, such as smart cities, smart homes, smart governments, and smart production [ 45 ]. In particular, the alliance between sustainability and intelligence is at the center of academic discussion, highlighting themes such as sustainable smart manufacturing being enabled by digital technologies, such as IoT, cloud computing, big data, cyber-physical systems, AI, etc. [ 55 ]. These disruptive technologies have been offering unprecedented opportunities to create and develop value-added products and services [ 73 ]. In that regard, we identified that smart cities work as an extensive smart ecosystem, including different value activities and specific business functions and technologies [ 60 ]. To stimulate research on smart cities, there have been numerous special issues published by top-tier journals [ 73 , 74 ]. Thus, according to our analysis, smart cities are in increasing development, being a promising research area.

4.3. Proposed research agenda

The meta-review sets the stage for a research agenda. This review documents what is already known and, using critical knowledge gap analysis, helps to refine research questions, concepts, and theories to point the way for future research [ 75 ]. The articulation between the research question and the DT dimensions allowed the definition of the research agenda. Thus, the proposed research agenda defines the research areas and priorities that guide scholars.

Early in this article, we presented four figures that allowed us to identify the publication of documents by year ( Fig. 2 ), type ( Fig. 3 ), country ( Fig. 4 ), and subject area ( Fig. 5 ). The areas of research identified with the most remarkable growth are open innovation ( Table A4 . Sustainability) and I4.0 ( Table A1 . Business Model and Table A3 . Technologies), within the scope of (1) Computer Science; (2) Business, Management, and Accounting; (3) Engineering ( vide Fig. 5 ). An example that illustrates the scientific development of the areas above (i.e., open innovation and I4.0); is given by Savastano et al. [ 60 ], referring to the case of the alliance between Siemens with the state-funded Technical University of Munich, the German Research Center for Artificial Intelligence, and the Fraunhofer Institute for Applied and Integrated Security Applications.

Some topics described above were also identified in the content analysis stage (i.e., six dimensions and respective categories), allowing us to pinpoint the research priorities for DT. Below, the reader can find the main contributions of the article that frame the research agenda:

• • According to the literature, VUCA environments are pushing for comprehensive and transformational digital strategies, changing the business landscape by increasing competitiveness in developing new services and products. To streamline research on the development of smart services and products, several special issues have been published by leading journals [ 76 ]. Therefore, disruptive technologies (AI, Big data, etc.) and innovation have been one of the main drivers of DT in building new digital services and products, and this trend is likely to continue.
• • Compared with an early DT literature review, published in 2018 by Reis et al., new dimensions have been highlighted in this article. The three dimensions identified by Reis et al. [ 17 ] are still widely explored, namely organizational ( Table A1 and A2 ), technological ( Table A3 ), and social ( Table A5 ). However, the new dimensions, namely sustainability ( Table A4 ) and smart cities ( Table A6 ) are still underdeveloped. What is new in this article is that while sustainability and smart cities are widely explored in other research domains (e.g., social sciences, engineering, etc.), within the scope of DT (i.e., business and management), it still falls far short of expectations. This argument may be also supported by a quick search in Elsevier Scopus (dated May 15th, 2022) with the keyword “sustainability” in TITLE-ABS-KEY, which indicates that the top 3 subject areas are Environmental Sciences (18.2%), Social Sciences (15.2%), and Engineering (11.3%); Business, Management, and Accounting represents only 7.5% of worldwide research. With regard to “smart cities”, a similar search shows that the top 3 subject areas are Computer Sciences (31.7%), Engineering (19.6%), and Social Sciences (11.2%); Business, Management, and Accounting represents only 2.6% of the worldwide research. This is a significant gap, considering that, in the scope of DT, the subject area Business, Management, and Accounting is in the top two with 17.7% ( Fig. 5 ).
• • From our analysis, future research may focus on the latter two dimensions (i.e., sustainability and smart cities). In that regard, researchers point out that empirical studies linking DT and sustainability are still scarce [ 77 ]. At the same time, recent growth in digital technologies is enabling cities to streamline smart services and offering new products [ 78 ]. This argument is also pointed out by some recent studies that have investigated the literature on DT in the context of meta-reviews Reis et al. [ 73 ] or meta-synthesis [ 79 ] in smart cities. Therefore, we argue that additional efforts are needed to reduce the knowledge gap between these two concepts (sustainability and smart cities) and DT.
• • During data analysis, we tried to use the MECE rule (mutually exclusive and collectively exhaustive). MECE is a framework that allows solving complex problems by dividing them into sub-problems that are mutually exclusive (they do not overlap) and comprehensively exhaustive (cover all possibilities). The application of MECE rule was impossible in this context because of the difficulty of developing mutually exclusive sub-dimensions; nevertheless, the attempt presented interesting results. We delved deeper into this issue and realized that MECE is particularly important for creating taxonomies, as vague definitions cause overlaps between dimension characteristics [ 80 ]. An example is represented by the difficulty in the past in distinguishing between digitization, digitization, and DT. Since then, DT has been extensively investigated, with a clear conceptual distinction. But DT is so comprehensive that the concept crosses several research domains and dimensions (such as those identified in this article). For instance, the HR dimension is transversal to all other dimensions, such as technology (i.e., redefinition of HR skills) or digital business (sociotechnical values). In real terms, the dimensions identified are closely related to each other, covering all possibilities (i.e., comprehensively exhaustive). The MECE rule may still be used in the future, for mixed studies that incorporate literature review and empirical research for each of the dimensions identified in this article.
• • Lastly, the research agenda includes the suggestion to analyze the impact of incorporating various technologies and how they can influence companies at different levels – individual, departmental, and organizational. In this regard, Kozanoglu and Abedin [ 58 ] argue that future studies could investigate one or several technologies to determine how their number and/or qualities can influence employees at an individual and company level. More specifically, they give the example of the article by Du et al. [ 81 ] that analyzes the use of blockchain in the business processes of a financial company.

In short, when answering the research question, we found six dimensions of DT, along with seventeen categories and sixty-six codes. Four dimensions, out of six, have already been explored in early reviews of DT literature [ 17 ]. Thus, this article is original insofar as we evidenced that “sustainability” dimension has been driven by open innovation in the context of improving new business models; and the “smart city” dimension has been driven by disruptive technologies in the context of the development of smart systems.

5. Conclusion

5.1. theoretical contributions.

To the best of our knowledge, this is the first time a meta-review on DT has been carried out. For that reason alone, this article is already original, bringing a timely contribution. From what we could extract from the analysis, there was a significant growth in literature reviews on the subject. Therefore, the academic interest in meta-reviews per se justifies publication. The article contributes to the theory as it provides clear guidance on research paths. The main contribution is, therefore, the definition of a research agenda focused on six dimensions, namely: 1) business models; 2) digital business; 3) technologies; 4) sustainability; 5) human resources; 6) smart cities. In that regard, we also provided the categories that emerged from the analysis, giving a clearer perspective of each dimension.

In general terms, it was possible to identify two new dimensions compared to previous studies – sustainability and smart cities. The existing literature points out that empirical studies link DT and sustainable business. While the most skeptical readers of this article might claim that sustainability is a widely explored dimension, it seems to fall short of expectations in the context of DT. In this context, sustainability has been driven by open innovation in terms of improving new business models. With regard to smart cities, the development of disruptive technologies has been the key driver of progress. It seems pertinent, thus, to reduce the knowledge gap on sustainability and smart cities in the context of DT.

5.2. Managerial contributions

With regard to managerial contributions, the results of this article are somewhat limited. First, because this article follows a literature review strategy; second, because the article's objective was to define a scientific agenda. Nevertheless, we were able to identify some contributions. In particular, it was possible to verify that due to the link between DT and technology, the significant areas of development are connected to computer sciences and engineering. Thus, for companies that intend to invest in DT, from the point of view of recruiting and training of HR, it may be helpful to consider investments in the areas of industrial engineering, computer engineering, and management. At the organizational level and in the context of the digital age, managers who intend to pursue a DT strategy should pay special attention to the open innovation ecosystem (e.g., n-Helix), rather than investing in company-centric innovation. From a business point of view, there are opportunities within the scope of smart cities that should be explored, namely in developing new technologies and sustainable development.

5.3. Original contributions

According to the results of the meta-review, we found that the most relevant concern is the need to reduce the gap regarding sustainability and smart cities in the context of DT. Crossing that gap in the literature and what is new and original in this article, we would like to highlight some frustration with the DT implementation, specifically with sustainable HR, a neglected dimension both empirically and theoretically. In that regard, the literature stresses that a change management strategy is essential to develop sustainable HR by instilling the idea that there is no end to change. Thus, organizations must develop management models for change in DT environments, similar to those traditional models that already exist, such as the ADKAR model or Kotter's change management model. The suggestion of developing new DT HR models is particularly relevant in digital business. Technological acceleration is forcing organizations to strengthen the digital skills of their workforce. The debates around adapting the workforce to DT contexts are not new. However, we advocate the development of HR sustainability models to adapt the workforce to Digital VUCA environments, where technological acceleration persists. Moreover, the existing literature refers the need to develop comprehensive transformational organizational efforts, particularly from a socio-technical perspective [ 48 ]. From our analysis, the smart cities dimension is very focused on smart production/manufacturing. Thus, in our view, the socio-technical approach is underdeveloped in this context. The same is not valid regarding the business model and digital model dimensions. We may have found our mutually exclusive sub-dimension in the sociotechnical issue. In other words, the socio-technical issue is a subset that still is not transversal to the different DT dimensions. However, as far as we know, there are already several articles outside the context of this research that analyze the socio-technical issue in smart cities [ 82 , 83 ] (although not focused on DT), which leads us to believe that a greater degree of scientific deepening is needed.

Appendix A. 

Business Models dimension

Digital Business Ecosystems dimension

Technological dimension

Sustainability dimension

Human Resources dimension

Smart Cities dimension

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The Essential Components of Digital Transformation

• Tomas Chamorro-Premuzic

It’s about so much more than your technology.

It’s problematic when companies decide to embark on a digital transformation agenda without having a clear definition, let alone vision, for what it means. The fundamental meaning of transformation is not about replacing old technologies with new ones, or capturing high volumes of data, or hiring an army of data scientists, or trying to copy some of the things Google or Amazon do. In fact, the essence of digital transformation is to become a data-driven organization, ensuring that key decisions, actions, and processes are strongly influenced by data-driven insights, rather than by human intuition. In other words, you will only transform when you have managed to change how people behave, and how things are done in your organization.

The digital revolution forced every organization to reinvent itself, or at least rethink how it goes about doing business. Most large companies have invested substantial cash in what is generally labelled “digital transformation.” While those investments are projected to top $6.8 trillion by 2023, they’re often made without seeing clear benefits or ROI. Although these failures have multiple causes, they are generally the result of underestimating the various steps or stages required to successfully execute a transformation agenda.

• Tomas Chamorro-Premuzic is the Chief Innovation Officer at ManpowerGroup, a professor of business psychology at University College London and at Columbia University, co-founder of  deepersignals.com , and an associate at Harvard’s Entrepreneurial Finance Lab. He is the author of  Why Do So Many Incompetent Men Become Leaders? (and How to Fix It ) , upon which his  TEDx talk  was based. His latest book is I, Human: AI, Automation, and the Quest to Reclaim What Makes Us Unique.   Find him at  www.drtomas.com . drtcp

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• Published: 12 February 2024

Education reform and change driven by digital technology: a bibliometric study from a global perspective

• Chengliang Wang 1 ,
• Xiaojiao Chen 1 ,
• Teng Yu   ORCID: orcid.org/0000-0001-5198-7261 2 , 3 ,
• Yidan Liu 1 , 4 &
• Yuhui Jing 1  

Humanities and Social Sciences Communications volume  11 , Article number:  256 ( 2024 ) Cite this article

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• Development studies
• Science, technology and society

Amidst the global digital transformation of educational institutions, digital technology has emerged as a significant area of interest among scholars. Such technologies have played an instrumental role in enhancing learner performance and improving the effectiveness of teaching and learning. These digital technologies also ensure the sustainability and stability of education during the epidemic. Despite this, a dearth of systematic reviews exists regarding the current state of digital technology application in education. To address this gap, this study utilized the Web of Science Core Collection as a data source (specifically selecting the high-quality SSCI and SCIE) and implemented a topic search by setting keywords, yielding 1849 initial publications. Furthermore, following the PRISMA guidelines, we refined the selection to 588 high-quality articles. Using software tools such as CiteSpace, VOSviewer, and Charticulator, we reviewed these 588 publications to identify core authors (such as Selwyn, Henderson, Edwards), highly productive countries/regions (England, Australia, USA), key institutions (Monash University, Australian Catholic University), and crucial journals in the field ( Education and Information Technologies , Computers & Education , British Journal of Educational Technology ). Evolutionary analysis reveals four developmental periods in the research field of digital technology education application: the embryonic period, the preliminary development period, the key exploration, and the acceleration period of change. The study highlights the dual influence of technological factors and historical context on the research topic. Technology is a key factor in enabling education to transform and upgrade, and the context of the times is an important driving force in promoting the adoption of new technologies in the education system and the transformation and upgrading of education. Additionally, the study identifies three frontier hotspots in the field: physical education, digital transformation, and professional development under the promotion of digital technology. This study presents a clear framework for digital technology application in education, which can serve as a valuable reference for researchers and educational practitioners concerned with digital technology education application in theory and practice.

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Introduction

Digital technology has become an essential component of modern education, facilitating the extension of temporal and spatial boundaries and enriching the pedagogical contexts (Selwyn and Facer, 2014 ). The advent of mobile communication technology has enabled learning through social media platforms (Szeto et al. 2015 ; Pires et al. 2022 ), while the advancement of augmented reality technology has disrupted traditional conceptions of learning environments and spaces (Perez-Sanagustin et al., 2014 ; Kyza and Georgiou, 2018 ). A wide range of digital technologies has enabled learning to become a norm in various settings, including the workplace (Sjöberg and Holmgren, 2021 ), home (Nazare et al. 2022 ), and online communities (Tang and Lam, 2014 ). Education is no longer limited to fixed locations and schedules, but has permeated all aspects of life, allowing learning to continue at any time and any place (Camilleri and Camilleri, 2016 ; Selwyn and Facer, 2014 ).

The advent of digital technology has led to the creation of several informal learning environments (Greenhow and Lewin, 2015 ) that exhibit divergent form, function, features, and patterns in comparison to conventional learning environments (Nygren et al. 2019 ). Consequently, the associated teaching and learning processes, as well as the strategies for the creation, dissemination, and acquisition of learning resources, have undergone a complete overhaul. The ensuing transformations have posed a myriad of novel issues, such as the optimal structuring of teaching methods by instructors and the adoption of appropriate learning strategies by students in the new digital technology environment. Consequently, an examination of the principles that underpin effective teaching and learning in this environment is a topic of significant interest to numerous scholars engaged in digital technology education research.

Over the course of the last two decades, digital technology has made significant strides in the field of education, notably in extending education time and space and creating novel educational contexts with sustainability. Despite research attempts to consolidate the application of digital technology in education, previous studies have only focused on specific aspects of digital technology, such as Pinto and Leite’s ( 2020 ) investigation into digital technology in higher education and Mustapha et al.’s ( 2021 ) examination of the role and value of digital technology in education during the pandemic. While these studies have provided valuable insights into the practical applications of digital technology in particular educational domains, they have not comprehensively explored the macro-mechanisms and internal logic of digital technology implementation in education. Additionally, these studies were conducted over a relatively brief period, making it challenging to gain a comprehensive understanding of the macro-dynamics and evolutionary process of digital technology in education. Some studies have provided an overview of digital education from an educational perspective but lack a precise understanding of technological advancement and change (Yang et al. 2022 ). Therefore, this study seeks to employ a systematic scientific approach to collate relevant research from 2000 to 2022, comprehend the internal logic and development trends of digital technology in education, and grasp the outstanding contribution of digital technology in promoting the sustainability of education in time and space. In summary, this study aims to address the following questions:

RQ1: Since the turn of the century, what is the productivity distribution of the field of digital technology education application research in terms of authorship, country/region, institutional and journal level?

RQ2: What is the development trend of research on the application of digital technology in education in the past two decades?

RQ3: What are the current frontiers of research on the application of digital technology in education?

Literature review

Although the term “digital technology” has become ubiquitous, a unified definition has yet to be agreed upon by scholars. Because the meaning of the word digital technology is closely related to the specific context. Within the educational research domain, Selwyn’s ( 2016 ) definition is widely favored by scholars (Pinto and Leite, 2020 ). Selwyn ( 2016 ) provides a comprehensive view of various concrete digital technologies and their applications in education through ten specific cases, such as immediate feedback in classes, orchestrating teaching, and community learning. Through these specific application scenarios, Selwyn ( 2016 ) argues that digital technology encompasses technologies associated with digital devices, including but not limited to tablets, smartphones, computers, and social media platforms (such as Facebook and YouTube). Furthermore, Further, the behavior of accessing the internet at any location through portable devices can be taken as an extension of the behavior of applying digital technology.

The evolving nature of digital technology has significant implications in the field of education. In the 1890s, the focus of digital technology in education was on comprehending the nuances of digital space, digital culture, and educational methodologies, with its connotations aligned more towards the idea of e-learning. The advent and subsequent widespread usage of mobile devices since the dawn of the new millennium have been instrumental in the rapid expansion of the concept of digital technology. Notably, mobile learning devices such as smartphones and tablets, along with social media platforms, have become integral components of digital technology (Conole and Alevizou, 2010 ; Batista et al. 2016 ). In recent times, the burgeoning application of AI technology in the education sector has played a vital role in enriching the digital technology lexicon (Banerjee et al. 2021 ). ChatGPT, for instance, is identified as a novel educational technology that has immense potential to revolutionize future education (Rospigliosi, 2023 ; Arif, Munaf and Ul-Haque, 2023 ).

Pinto and Leite ( 2020 ) conducted a comprehensive macroscopic survey of the use of digital technologies in the education sector and identified three distinct categories, namely technologies for assessment and feedback, mobile technologies, and Information Communication Technologies (ICT). This classification criterion is both macroscopic and highly condensed. In light of the established concept definitions of digital technology in the educational research literature, this study has adopted the characterizations of digital technology proposed by Selwyn ( 2016 ) and Pinto and Leite ( 2020 ) as crucial criteria for analysis and research inclusion. Specifically, this criterion encompasses several distinct types of digital technologies, including Information and Communication Technologies (ICT), Mobile tools, eXtended Reality (XR) Technologies, Assessment and Feedback systems, Learning Management Systems (LMS), Publish and Share tools, Collaborative systems, Social media, Interpersonal Communication tools, and Content Aggregation tools.

Methodology and materials

Research method: bibliometric.

The research on econometric properties has been present in various aspects of human production and life, yet systematic scientific theoretical guidance has been lacking, resulting in disorganization. In 1969, British scholar Pritchard ( 1969 ) proposed “bibliometrics,” which subsequently emerged as an independent discipline in scientific quantification research. Initially, Pritchard defined bibliometrics as “the application of mathematical and statistical methods to books and other media of communication,” however, the definition was not entirely rigorous. To remedy this, Hawkins ( 2001 ) expanded Pritchard’s definition to “the quantitative analysis of the bibliographic features of a body of literature.” De Bellis further clarified the objectives of bibliometrics, stating that it aims to analyze and identify patterns in literature, such as the most productive authors, institutions, countries, and journals in scientific disciplines, trends in literary production over time, and collaboration networks (De Bellis, 2009 ). According to Garfield ( 2006 ), bibliometric research enables the examination of the history and structure of a field, the flow of information within the field, the impact of journals, and the citation status of publications over a longer time scale. All of these definitions illustrate the unique role of bibliometrics as a research method for evaluating specific research fields.

This study uses CiteSpace, VOSviewer, and Charticulator to analyze data and create visualizations. Each of these three tools has its own strengths and can complement each other. CiteSpace and VOSviewer use set theory and probability theory to provide various visualization views in fields such as keywords, co-occurrence, and co-authors. They are easy to use and produce visually appealing graphics (Chen, 2006 ; van Eck and Waltman, 2009 ) and are currently the two most widely used bibliometric tools in the field of visualization (Pan et al. 2018 ). In this study, VOSviewer provided the data necessary for the Performance Analysis; Charticulator was then used to redraw using the tabular data exported from VOSviewer (for creating the chord diagram of country collaboration); this was to complement the mapping process, while CiteSpace was primarily utilized to generate keyword maps and conduct burst word analysis.

Data retrieval

This study selected documents from the Science Citation Index Expanded (SCIE) and Social Science Citation Index (SSCI) in the Web of Science Core Collection as the data source, for the following reasons:

(1) The Web of Science Core Collection, as a high-quality digital literature resource database, has been widely accepted by many researchers and is currently considered the most suitable database for bibliometric analysis (Jing et al. 2023a ). Compared to other databases, Web of Science provides more comprehensive data information (Chen et al. 2022a ), and also provides data formats suitable for analysis using VOSviewer and CiteSpace (Gaviria-Marin et al. 2019 ).

(2) The application of digital technology in the field of education is an interdisciplinary research topic, involving technical knowledge literature belonging to the natural sciences and education-related literature belonging to the social sciences. Therefore, it is necessary to select Science Citation Index Expanded (SCIE) and Social Science Citation Index (SSCI) as the sources of research data, ensuring the comprehensiveness of data while ensuring the reliability and persuasiveness of bibliometric research (Hwang and Tsai, 2011 ; Wang et al. 2022 ).

After establishing the source of research data, it is necessary to determine a retrieval strategy (Jing et al. 2023b ). The choice of a retrieval strategy should consider a balance between the breadth and precision of the search formula. That is to say, it should encompass all the literature pertaining to the research topic while excluding irrelevant documents as much as possible. In light of this, this study has set a retrieval strategy informed by multiple related papers (Mustapha et al. 2021 ; Luo et al. 2021 ). The research by Mustapha et al. ( 2021 ) guided us in selecting keywords (“digital” AND “technolog*”) to target digital technology, while Luo et al. ( 2021 ) informed the selection of terms (such as “instruct*,” “teach*,” and “education”) to establish links with the field of education. Then, based on the current application of digital technology in the educational domain and the scope of selection criteria, we constructed the final retrieval strategy. Following the general patterns of past research (Jing et al. 2023a , 2023b ), we conducted a specific screening using the topic search (Topics, TS) function in Web of Science. For the specific criteria used in the screening for this study, please refer to Table 1 .

Literature screening

Literature acquired through keyword searches may contain ostensibly related yet actually unrelated works. Therefore, to ensure the close relevance of literature included in the analysis to the research topic, it is often necessary to perform a manual screening process to identify the final literature to be analyzed, subsequent to completing the initial literature search.

The manual screening process consists of two steps. Initially, irrelevant literature is weeded out based on the title and abstract, with two members of the research team involved in this phase. This stage lasted about one week, resulting in 1106 articles being retained. Subsequently, a comprehensive review of the full text is conducted to accurately identify the literature required for the study. To carry out the second phase of manual screening effectively and scientifically, and to minimize the potential for researcher bias, the research team established the inclusion criteria presented in Table 2 . Three members were engaged in this phase, which took approximately 2 weeks, culminating in the retention of 588 articles after meticulous screening. The entire screening process is depicted in Fig. 1 , adhering to the PRISMA guidelines (Page et al. 2021 ).

The process of obtaining and filtering the necessary literature data for research.

Data standardization

Nguyen and Hallinger ( 2020 ) pointed out that raw data extracted from scientific databases often contains multiple expressions of the same term, and not addressing these synonymous expressions could affect research results in bibliometric analysis. For instance, in the original data, the author list may include “Tsai, C. C.” and “Tsai, C.-C.”, while the keyword list may include “professional-development” and “professional development,” which often require merging. Therefore, before analyzing the selected literature, a data disambiguation process is necessary to standardize the data (Strotmann and Zhao, 2012 ; Van Eck and Waltman, 2019 ). This study adopted the data standardization process proposed by Taskin and Al ( 2019 ), mainly including the following standardization operations:

Firstly, the author and source fields in the data are corrected and standardized to differentiate authors with similar names.

Secondly, the study checks whether the journals to which the literature belongs have been renamed in the past over 20 years, so as to avoid the influence of periodical name change on the analysis results.

Finally, the keyword field is standardized by unifying parts of speech and singular/plural forms of keywords, which can help eliminate redundant entries in the knowledge graph.

Performance analysis (RQ1)

This section offers a thorough and detailed analysis of the state of research in the field of digital technology education. By utilizing descriptive statistics and visual maps, it provides a comprehensive overview of the development trends, authors, countries, institutions, and journal distribution within the field. The insights presented in this section are of great significance in advancing our understanding of the current state of research in this field and identifying areas for further investigation. The use of visual aids to display inter-country cooperation and the evolution of the field adds to the clarity and coherence of the analysis.

Time trend of the publications

To understand a research field, it is first necessary to understand the most basic quantitative information, among which the change in the number of publications per year best reflects the development trend of a research field. Figure 2 shows the distribution of publication dates.

Time trend of the publications on application of digital technology in education.

From the Fig. 2 , it can be seen that the development of this field over the past over 20 years can be roughly divided into three stages. The first stage was from 2000 to 2007, during which the number of publications was relatively low. Due to various factors such as technological maturity, the academic community did not pay widespread attention to the role of digital technology in expanding the scope of teaching and learning. The second stage was from 2008 to 2019, during which the overall number of publications showed an upward trend, and the development of the field entered an accelerated period, attracting more and more scholars’ attention. The third stage was from 2020 to 2022, during which the number of publications stabilized at around 100. During this period, the impact of the pandemic led to a large number of scholars focusing on the role of digital technology in education during the pandemic, and research on the application of digital technology in education became a core topic in social science research.

Analysis of authors

An analysis of the author’s publication volume provides information about the representative scholars and core research strengths of a research area. Table 3 presents information on the core authors in adaptive learning research, including name, publication number, and average number of citations per article (based on the analysis and statistics from VOSviewer).

Variations in research foci among scholars abound. Within the field of digital technology education application research over the past two decades, Neil Selwyn stands as the most productive author, having published 15 papers garnering a total of 1027 citations, resulting in an average of 68.47 citations per paper. As a Professor at the Faculty of Education at Monash University, Selwyn concentrates on exploring the application of digital technology in higher education contexts (Selwyn et al. 2021 ), as well as related products in higher education such as Coursera, edX, and Udacity MOOC platforms (Bulfin et al. 2014 ). Selwyn’s contributions to the educational sociology perspective include extensive research on the impact of digital technology on education, highlighting the spatiotemporal extension of educational processes and practices through technological means as the greatest value of educational technology (Selwyn, 2012 ; Selwyn and Facer, 2014 ). In addition, he provides a blueprint for the development of future schools in 2030 based on the present impact of digital technology on education (Selwyn et al. 2019 ). The second most productive author in this field, Henderson, also offers significant contributions to the understanding of the important value of digital technology in education, specifically in the higher education setting, with a focus on the impact of the pandemic (Henderson et al. 2015 ; Cohen et al. 2022 ). In contrast, Edwards’ research interests focus on early childhood education, particularly the application of digital technology in this context (Edwards, 2013 ; Bird and Edwards, 2015 ). Additionally, on the technical level, Edwards also mainly prefers digital game technology, because it is a digital technology that children are relatively easy to accept (Edwards, 2015 ).

Analysis of countries/regions and organization

The present study aimed to ascertain the leading countries in digital technology education application research by analyzing 75 countries related to 558 works of literature. Table 4 depicts the top ten countries that have contributed significantly to this field in terms of publication count (based on the analysis and statistics from VOSviewer). Our analysis of Table 4 data shows that England emerged as the most influential country/region, with 92 published papers and 2401 citations. Australia and the United States secured the second and third ranks, respectively, with 90 papers (2187 citations) and 70 papers (1331 citations) published. Geographically, most of the countries featured in the top ten publication volumes are situated in Australia, North America, and Europe, with China being the only exception. Notably, all these countries, except China, belong to the group of developed nations, suggesting that economic strength is a prerequisite for fostering research in the digital technology education application field.

This study presents a visual representation of the publication output and cooperation relationships among different countries in the field of digital technology education application research. Specifically, a chord diagram is employed to display the top 30 countries in terms of publication output, as depicted in Fig. 3 . The chord diagram is composed of nodes and chords, where the nodes are positioned as scattered points along the circumference, and the length of each node corresponds to the publication output, with longer lengths indicating higher publication output. The chords, on the other hand, represent the cooperation relationships between any two countries, and are weighted based on the degree of closeness of the cooperation, with wider chords indicating closer cooperation. Through the analysis of the cooperation relationships, the findings suggest that the main publishing countries in this field are engaged in cooperative relationships with each other, indicating a relatively high level of international academic exchange and research internationalization.

In the diagram, nodes are scattered along the circumference of a circle, with the length of each node representing the volume of publications. The weighted arcs connecting any two points on the circle are known as chords, representing the collaborative relationship between the two, with the width of the arc indicating the closeness of the collaboration.

Further analyzing Fig. 3 , we can extract more valuable information, enabling a deeper understanding of the connections between countries in the research field of digital technology in educational applications. It is evident that certain countries, such as the United States, China, and England, display thicker connections, indicating robust collaborative relationships in terms of productivity. These thicker lines signify substantial mutual contributions and shared objectives in certain sectors or fields, highlighting the interconnectedness and global integration in these areas. By delving deeper, we can also explore potential future collaboration opportunities through the chord diagram, identifying possible partners to propel research and development in this field. In essence, the chord diagram successfully encapsulates and conveys the multi-dimensionality of global productivity and cooperation, allowing for a comprehensive understanding of the intricate inter-country relationships and networks in a global context, providing valuable guidance and insights for future research and collaborations.

An in-depth examination of the publishing institutions is provided in Table 5 , showcasing the foremost 10 institutions ranked by their publication volume. Notably, Monash University and Australian Catholic University, situated in Australia, have recorded the most prolific publications within the digital technology education application realm, with 22 and 10 publications respectively. Moreover, the University of Oslo from Norway is featured among the top 10 publishing institutions, with an impressive average citation count of 64 per publication. It is worth highlighting that six institutions based in the United Kingdom were also ranked within the top 10 publishing institutions, signifying their leading position in this area of research.

Analysis of journals

Journals are the main carriers for publishing high-quality papers. Some scholars point out that the two key factors to measure the influence of journals in the specified field are the number of articles published and the number of citations. The more papers published in a magazine and the more citations, the greater its influence (Dzikowski, 2018 ). Therefore, this study utilized VOSviewer to statistically analyze the top 10 journals with the most publications in the field of digital technology in education and calculated the average citations per article (see Table 6 ).

Based on Table 6 , it is apparent that the highest number of articles in the domain of digital technology in education research were published in Education and Information Technologies (47 articles), Computers & Education (34 articles), and British Journal of Educational Technology (32 articles), indicating a higher article output compared to other journals. This underscores the fact that these three journals concentrate more on the application of digital technology in education. Furthermore, several other journals, such as Technology Pedagogy and Education and Sustainability, have published more than 15 articles in this domain. Sustainability represents the open access movement, which has notably facilitated research progress in this field, indicating that the development of open access journals in recent years has had a significant impact. Although there is still considerable disagreement among scholars on the optimal approach to achieve open access, the notion that research outcomes should be accessible to all is widely recognized (Huang et al. 2020 ). On further analysis of the research fields to which these journals belong, except for Sustainability, it is evident that they all pertain to educational technology, thus providing a qualitative definition of the research area of digital technology education from the perspective of journals.

Temporal keyword analysis: thematic evolution (RQ2)

The evolution of research themes is a dynamic process, and previous studies have attempted to present the developmental trajectory of fields by drawing keyword networks in phases (Kumar et al. 2021 ; Chen et al. 2022b ). To understand the shifts in research topics across different periods, this study follows past research and, based on the significant changes in the research field and corresponding technological advancements during the outlined periods, divides the timeline into four stages (the first stage from January 2000 to December 2005, the second stage from January 2006 to December 2011, the third stage from January 2012 to December 2017; and the fourth stage from January 2018 to December 2022). The division into these four stages was determined through a combination of bibliometric analysis and literature review, which presented a clear trajectory of the field’s development. The research analyzes the keyword networks for each time period (as there are only three articles in the first stage, it was not possible to generate an appropriate keyword co-occurrence map, hence only the keyword co-occurrence maps from the second to the fourth stages are provided), to understand the evolutionary track of the digital technology education application research field over time.

2000.1–2005.12: germination period

From January 2000 to December 2005, digital technology education application research was in its infancy. Only three studies focused on digital technology, all of which were related to computers. Due to the popularity of computers, the home became a new learning environment, highlighting the important role of digital technology in expanding the scope of learning spaces (Sutherland et al. 2000 ). In specific disciplines and contexts, digital technology was first favored in medical clinical practice, becoming an important tool for supporting the learning of clinical knowledge and practice (Tegtmeyer et al. 2001 ; Durfee et al. 2003 ).

2006.1–2011.12: initial development period

Between January 2006 and December 2011, it was the initial development period of digital technology education research. Significant growth was observed in research related to digital technology, and discussions and theoretical analyses about “digital natives” emerged. During this phase, scholars focused on the debate about “how to use digital technology reasonably” and “whether current educational models and school curriculum design need to be adjusted on a large scale” (Bennett and Maton, 2010 ; Selwyn, 2009 ; Margaryan et al. 2011 ). These theoretical and speculative arguments provided a unique perspective on the impact of cognitive digital technology on education and teaching. As can be seen from the vocabulary such as “rethinking”, “disruptive pedagogy”, and “attitude” in Fig. 4 , many scholars joined the calm reflection and analysis under the trend of digital technology (Laurillard, 2008 ; Vratulis et al. 2011 ). During this phase, technology was still undergoing dramatic changes. The development of mobile technology had already caught the attention of many scholars (Wong et al. 2011 ), but digital technology represented by computers was still very active (Selwyn et al. 2011 ). The change in technological form would inevitably lead to educational transformation. Collins and Halverson ( 2010 ) summarized the prospects and challenges of using digital technology for learning and educational practices, believing that digital technology would bring a disruptive revolution to the education field and bring about a new educational system. In addition, the term “teacher education” in Fig. 4 reflects the impact of digital technology development on teachers. The rapid development of technology has widened the generation gap between teachers and students. To ensure smooth communication between teachers and students, teachers must keep up with the trend of technological development and establish a lifelong learning concept (Donnison, 2009 ).

In the diagram, each node represents a keyword, with the size of the node indicating the frequency of occurrence of the keyword. The connections represent the co-occurrence relationships between keywords, with a higher frequency of co-occurrence resulting in tighter connections.

2012.1–2017.12: critical exploration period

During the period spanning January 2012 to December 2017, the application of digital technology in education research underwent a significant exploration phase. As can be seen from Fig. 5 , different from the previous stage, the specific elements of specific digital technology have started to increase significantly, including the enrichment of technological contexts, the greater variety of research methods, and the diversification of learning modes. Moreover, the temporal and spatial dimensions of the learning environment were further de-emphasized, as noted in previous literature (Za et al. 2014 ). Given the rapidly accelerating pace of technological development, the education system in the digital era is in urgent need of collaborative evolution and reconstruction, as argued by Davis, Eickelmann, and Zaka ( 2013 ).

In the domain of digital technology, social media has garnered substantial scholarly attention as a promising avenue for learning, as noted by Pasquini and Evangelopoulos ( 2016 ). The implementation of social media in education presents several benefits, including the liberation of education from the restrictions of physical distance and time, as well as the erasure of conventional educational boundaries. The user-generated content (UGC) model in social media has emerged as a crucial source for knowledge creation and distribution, with the widespread adoption of mobile devices. Moreover, social networks have become an integral component of ubiquitous learning environments (Hwang et al. 2013 ). The utilization of social media allows individuals to function as both knowledge producers and recipients, which leads to a blurring of the conventional roles of learners and teachers. On mobile platforms, the roles of learners and teachers are not fixed, but instead interchangeable.

In terms of research methodology, the prevalence of empirical studies with survey designs in the field of educational technology during this period is evident from the vocabulary used, such as “achievement,” “acceptance,” “attitude,” and “ict.” in Fig. 5 . These studies aim to understand learners’ willingness to adopt and attitudes towards new technologies, and some seek to investigate the impact of digital technologies on learning outcomes through quasi-experimental designs (Domínguez et al. 2013 ). Among these empirical studies, mobile learning emerged as a hot topic, and this is not surprising. First, the advantages of mobile learning environments over traditional ones have been empirically demonstrated (Hwang et al. 2013 ). Second, learners born around the turn of the century have been heavily influenced by digital technologies and have developed their own learning styles that are more open to mobile devices as a means of learning. Consequently, analyzing mobile learning as a relatively novel mode of learning has become an important issue for scholars in the field of educational technology.

The intervention of technology has led to the emergence of several novel learning modes, with the blended learning model being the most representative one in the current phase. Blended learning, a novel concept introduced in the information age, emphasizes the integration of the benefits of traditional learning methods and online learning. This learning mode not only highlights the prominent role of teachers in guiding, inspiring, and monitoring the learning process but also underlines the importance of learners’ initiative, enthusiasm, and creativity in the learning process. Despite being an early conceptualization, blended learning’s meaning has been expanded by the widespread use of mobile technology and social media in education. The implementation of new technologies, particularly mobile devices, has resulted in the transformation of curriculum design and increased flexibility and autonomy in students’ learning processes (Trujillo Maza et al. 2016 ), rekindling scholarly attention to this learning mode. However, some scholars have raised concerns about the potential drawbacks of the blended learning model, such as its significant impact on the traditional teaching system, the lack of systematic coping strategies and relevant policies in several schools and regions (Moskal et al. 2013 ).

2018.1–2022.12: accelerated transformation period

The period spanning from January 2018 to December 2022 witnessed a rapid transformation in the application of digital technology in education research. The field of digital technology education research reached a peak period of publication, largely influenced by factors such as the COVID-19 pandemic (Yu et al. 2023 ). Research during this period was built upon the achievements, attitudes, and social media of the previous phase, and included more elements that reflect the characteristics of this research field, such as digital literacy, digital competence, and professional development, as depicted in Fig. 6 . Alongside this, scholars’ expectations for the value of digital technology have expanded, and the pursuit of improving learning efficiency and performance is no longer the sole focus. Some research now aims to cultivate learners’ motivation and enhance their self-efficacy by applying digital technology in a reasonable manner, as demonstrated by recent studies (Beardsley et al. 2021 ; Creely et al. 2021 ).

The COVID-19 pandemic has emerged as a crucial backdrop for the digital technology’s role in sustaining global education, as highlighted by recent scholarly research (Zhou et al. 2022 ; Pan and Zhang, 2020 ; Mo et al. 2022 ). The online learning environment, which is supported by digital technology, has become the primary battleground for global education (Yu, 2022 ). This social context has led to various studies being conducted, with some scholars positing that the pandemic has impacted the traditional teaching order while also expanding learning possibilities in terms of patterns and forms (Alabdulaziz, 2021 ). Furthermore, the pandemic has acted as a catalyst for teacher teaching and technological innovation, and this viewpoint has been empirically substantiated (Moorhouse and Wong, 2021 ). Additionally, some scholars believe that the pandemic’s push is a crucial driving force for the digital transformation of the education system, serving as an essential mechanism for overcoming the system’s inertia (Romero et al. 2021 ).

The rapid outbreak of the pandemic posed a challenge to the large-scale implementation of digital technologies, which was influenced by a complex interplay of subjective and objective factors. Objective constraints included the lack of infrastructure in some regions to support digital technologies, while subjective obstacles included psychological resistance among certain students and teachers (Moorhouse, 2021 ). These factors greatly impacted the progress of online learning during the pandemic. Additionally, Timotheou et al. ( 2023 ) conducted a comprehensive systematic review of existing research on digital technology use during the pandemic, highlighting the critical role played by various factors such as learners’ and teachers’ digital skills, teachers’ personal attributes and professional development, school leadership and management, and administration in facilitating the digitalization and transformation of schools.

The current stage of research is characterized by the pivotal term “digital literacy,” denoting a growing interest in learners’ attitudes and adoption of emerging technologies. Initially, the term “literacy” was restricted to fundamental abilities and knowledge associated with books and print materials (McMillan, 1996 ). However, with the swift advancement of computers and digital technology, there have been various attempts to broaden the scope of literacy beyond its traditional meaning, including game literacy (Buckingham and Burn, 2007 ), information literacy (Eisenberg, 2008 ), and media literacy (Turin and Friesem, 2020 ). Similarly, digital literacy has emerged as a crucial concept, and Gilster and Glister ( 1997 ) were the first to introduce this concept, referring to the proficiency in utilizing technology and processing digital information in academic, professional, and daily life settings. In practical educational settings, learners who possess higher digital literacy often exhibit an aptitude for quickly mastering digital devices and applying them intelligently to education and teaching (Yu, 2022 ).

The utilization of digital technology in education has undergone significant changes over the past two decades, and has been a crucial driver of educational reform with each new technological revolution. The impact of these changes on the underlying logic of digital technology education applications has been noticeable. From computer technology to more recent developments such as virtual reality (VR), augmented reality (AR), and artificial intelligence (AI), the acceleration in digital technology development has been ongoing. Educational reforms spurred by digital technology development continue to be dynamic, as each new digital innovation presents new possibilities and models for teaching practice. This is especially relevant in the post-pandemic era, where the importance of technological progress in supporting teaching cannot be overstated (Mughal et al. 2022 ). Existing digital technologies have already greatly expanded the dimensions of education in both time and space, while future digital technologies aim to expand learners’ perceptions. Researchers have highlighted the potential of integrated technology and immersive technology in the development of the educational metaverse, which is highly anticipated to create a new dimension for the teaching and learning environment, foster a new value system for the discipline of educational technology, and more effectively and efficiently achieve the grand educational blueprint of the United Nations’ Sustainable Development Goals (Zhang et al. 2022 ; Li and Yu, 2023 ).

Hotspot evolution analysis (RQ3)

The examination of keyword evolution reveals a consistent trend in the advancement of digital technology education application research. The emergence and transformation of keywords serve as indicators of the varying research interests in this field. Thus, the utilization of the burst detection function available in CiteSpace allowed for the identification of the top 10 burst words that exhibited a high level of burst strength. This outcome is illustrated in Table 7 .

According to the results presented in Table 7 , the explosive terminology within the realm of digital technology education research has exhibited a concentration mainly between the years 2018 and 2022. Prior to this time frame, the emerging keywords were limited to “information technology” and “computer”. Notably, among them, computer, as an emergent keyword, has always had a high explosive intensity from 2008 to 2018, which reflects the important position of computer in digital technology and is the main carrier of many digital technologies such as Learning Management Systems (LMS) and Assessment and Feedback systems (Barlovits et al. 2022 ).

Since 2018, an increasing number of research studies have focused on evaluating the capabilities of learners to accept, apply, and comprehend digital technologies. As indicated by the use of terms such as “digital literacy” and “digital skill,” the assessment of learners’ digital literacy has become a critical task. Scholarly efforts have been directed towards the development of literacy assessment tools and the implementation of empirical assessments. Furthermore, enhancing the digital literacy of both learners and educators has garnered significant attention. (Nagle, 2018 ; Yu, 2022 ). Simultaneously, given the widespread use of various digital technologies in different formal and informal learning settings, promoting learners’ digital skills has become a crucial objective for contemporary schools (Nygren et al. 2019 ; Forde and OBrien, 2022 ).

Since 2020, the field of applied research on digital technology education has witnessed the emergence of three new hotspots, all of which have been affected to some extent by the pandemic. Firstly, digital technology has been widely applied in physical education, which is one of the subjects that has been severely affected by the pandemic (Parris et al. 2022 ; Jiang and Ning, 2022 ). Secondly, digital transformation has become an important measure for most schools, especially higher education institutions, to cope with the impact of the pandemic globally (García-Morales et al. 2021 ). Although the concept of digital transformation was proposed earlier, the COVID-19 pandemic has greatly accelerated this transformation process. Educational institutions must carefully redesign their educational products to face this new situation, providing timely digital learning methods, environments, tools, and support systems that have far-reaching impacts on modern society (Krishnamurthy, 2020 ; Salas-Pilco et al. 2022 ). Moreover, the professional development of teachers has become a key mission of educational institutions in the post-pandemic era. Teachers need to have a certain level of digital literacy and be familiar with the tools and online teaching resources used in online teaching, which has become a research hotspot today. Organizing digital skills training for teachers to cope with the application of emerging technologies in education is an important issue for teacher professional development and lifelong learning (Garzón-Artacho et al. 2021 ). As the main organizers and practitioners of emergency remote teaching (ERT) during the pandemic, teachers must put cognitive effort into their professional development to ensure effective implementation of ERT (Romero-Hall and Jaramillo Cherrez, 2022 ).

The burst word “digital transformation” reveals that we are in the midst of an ongoing digital technology revolution. With the emergence of innovative digital technologies such as ChatGPT and Microsoft 365 Copilot, technology trends will continue to evolve, albeit unpredictably. While the impact of these advancements on school education remains uncertain, it is anticipated that the widespread integration of technology will significantly affect the current education system. Rejecting emerging technologies without careful consideration is unwise. Like any revolution, the technological revolution in the education field has both positive and negative aspects. Detractors argue that digital technology disrupts learning and memory (Baron, 2021 ) or causes learners to become addicted and distracted from learning (Selwyn and Aagaard, 2020 ). On the other hand, the prudent use of digital technology in education offers a glimpse of a golden age of open learning. Educational leaders and practitioners have the opportunity to leverage cutting-edge digital technologies to address current educational challenges and develop a rational path for the sustainable and healthy growth of education.

Discussion on performance analysis (RQ1)

The field of digital technology education application research has experienced substantial growth since the turn of the century, a phenomenon that is quantifiably apparent through an analysis of authorship, country/region contributions, and institutional engagement. This expansion reflects the increased integration of digital technologies in educational settings and the heightened scholarly interest in understanding and optimizing their use.

Discussion on authorship productivity in digital technology education research

The authorship distribution within digital technology education research is indicative of the field’s intellectual structure and depth. A primary figure in this domain is Neil Selwyn, whose substantial citation rate underscores the profound impact of his work. His focus on the implications of digital technology in higher education and educational sociology has proven to be seminal. Selwyn’s research trajectory, especially the exploration of spatiotemporal extensions of education through technology, provides valuable insights into the multifaceted role of digital tools in learning processes (Selwyn et al. 2019 ).

Other notable contributors, like Henderson and Edwards, present diversified research interests, such as the impact of digital technologies during the pandemic and their application in early childhood education, respectively. Their varied focuses highlight the breadth of digital technology education research, encompassing pedagogical innovation, technological adaptation, and policy development.

Discussion on country/region-level productivity and collaboration

At the country/region level, the United Kingdom, specifically England, emerges as a leading contributor with 92 published papers and a significant citation count. This is closely followed by Australia and the United States, indicating a strong English-speaking research axis. Such geographical concentration of scholarly output often correlates with investment in research and development, technological infrastructure, and the prevalence of higher education institutions engaging in cutting-edge research.

China’s notable inclusion as the only non-Western country among the top contributors to the field suggests a growing research capacity and interest in digital technology in education. However, the lower average citation per paper for China could reflect emerging engagement or different research focuses that may not yet have achieved the same international recognition as Western counterparts.

The chord diagram analysis furthers this understanding, revealing dense interconnections between countries like the United States, China, and England, which indicates robust collaborations. Such collaborations are fundamental in addressing global educational challenges and shaping international research agendas.

Discussion on institutional-level contributions to digital technology education

Institutional productivity in digital technology education research reveals a constellation of universities driving the field forward. Monash University and the Australian Catholic University have the highest publication output, signaling Australia’s significant role in advancing digital education research. The University of Oslo’s remarkable average citation count per publication indicates influential research contributions, potentially reflecting high-quality studies that resonate with the broader academic community.

The strong showing of UK institutions, including the University of London, The Open University, and the University of Cambridge, reinforces the UK’s prominence in this research field. Such institutions are often at the forefront of pedagogical innovation, benefiting from established research cultures and funding mechanisms that support sustained inquiry into digital education.

Discussion on journal publication analysis

An examination of journal outputs offers a lens into the communicative channels of the field’s knowledge base. Journals such as Education and Information Technologies , Computers & Education , and the British Journal of Educational Technology not only serve as the primary disseminators of research findings but also as indicators of research quality and relevance. The impact factor (IF) serves as a proxy for the quality and influence of these journals within the academic community.

The high citation counts for articles published in Computers & Education suggest that research disseminated through this medium has a wide-reaching impact and is of particular interest to the field. This is further evidenced by its significant IF of 11.182, indicating that the journal is a pivotal platform for seminal work in the application of digital technology in education.

The authorship, regional, and institutional productivity in the field of digital technology education application research collectively narrate the evolution of this domain since the turn of the century. The prominence of certain authors and countries underscores the importance of socioeconomic factors and existing academic infrastructure in fostering research productivity. Meanwhile, the centrality of specific journals as outlets for high-impact research emphasizes the role of academic publishing in shaping the research landscape.

As the field continues to grow, future research may benefit from leveraging the collaborative networks that have been elucidated through this analysis, perhaps focusing on underrepresented regions to broaden the scope and diversity of research. Furthermore, the stabilization of publication numbers in recent years invites a deeper exploration into potential plateaus in research trends or saturation in certain sub-fields, signaling an opportunity for novel inquiries and methodological innovations.

Discussion on the evolutionary trends (RQ2)

The evolution of the research field concerning the application of digital technology in education over the past two decades is a story of convergence, diversification, and transformation, shaped by rapid technological advancements and shifting educational paradigms.

At the turn of the century, the inception of digital technology in education was largely exploratory, with a focus on how emerging computer technologies could be harnessed to enhance traditional learning environments. Research from this early period was primarily descriptive, reflecting on the potential and challenges of incorporating digital tools into the educational setting. This phase was critical in establishing the fundamental discourse that would guide subsequent research, as it set the stage for understanding the scope and impact of digital technology in learning spaces (Wang et al. 2023 ).

As the first decade progressed, the narrative expanded to encompass the pedagogical implications of digital technologies. This was a period of conceptual debates, where terms like “digital natives” and “disruptive pedagogy” entered the academic lexicon, underscoring the growing acknowledgment of digital technology as a transformative force within education (Bennett and Maton, 2010 ). During this time, the research began to reflect a more nuanced understanding of the integration of technology, considering not only its potential to change where and how learning occurred but also its implications for educational equity and access.

In the second decade, with the maturation of internet connectivity and mobile technology, the focus of research shifted from theoretical speculations to empirical investigations. The proliferation of digital devices and the ubiquity of social media influenced how learners interacted with information and each other, prompting a surge in studies that sought to measure the impact of these tools on learning outcomes. The digital divide and issues related to digital literacy became central concerns, as scholars explored the varying capacities of students and educators to engage with technology effectively.

Throughout this period, there was an increasing emphasis on the individualization of learning experiences, facilitated by adaptive technologies that could cater to the unique needs and pacing of learners (Jing et al. 2023a ). This individualization was coupled with a growing recognition of the importance of collaborative learning, both online and offline, and the role of digital tools in supporting these processes. Blended learning models, which combined face-to-face instruction with online resources, emerged as a significant trend, advocating for a balance between traditional pedagogies and innovative digital strategies.

The later years, particularly marked by the COVID-19 pandemic, accelerated the necessity for digital technology in education, transforming it from a supplementary tool to an essential platform for delivering education globally (Mo et al. 2022 ; Mustapha et al. 2021 ). This era brought about an unprecedented focus on online learning environments, distance education, and virtual classrooms. Research became more granular, examining not just the pedagogical effectiveness of digital tools, but also their role in maintaining continuity of education during crises, their impact on teacher and student well-being, and their implications for the future of educational policy and infrastructure.

Across these two decades, the research field has seen a shift from examining digital technology as an external addition to the educational process, to viewing it as an integral component of curriculum design, instructional strategies, and even assessment methods. The emergent themes have broadened from a narrow focus on specific tools or platforms to include wider considerations such as data privacy, ethical use of technology, and the environmental impact of digital tools.

Moreover, the field has moved from considering the application of digital technology in education as a primarily cognitive endeavor to recognizing its role in facilitating socio-emotional learning, digital citizenship, and global competencies. Researchers have increasingly turned their attention to the ways in which technology can support collaborative skills, cultural understanding, and ethical reasoning within diverse student populations.

In summary, the past over twenty years in the research field of digital technology applications in education have been characterized by a progression from foundational inquiries to complex analyses of digital integration. This evolution has mirrored the trajectory of technology itself, from a facilitative tool to a pervasive ecosystem defining contemporary educational experiences. As we look to the future, the field is poised to delve into the implications of emerging technologies like AI, AR, and VR, and their potential to redefine the educational landscape even further. This ongoing metamorphosis suggests that the application of digital technology in education will continue to be a rich area of inquiry, demanding continual adaptation and forward-thinking from educators and researchers alike.

Discussion on the study of research hotspots (RQ3)

The analysis of keyword evolution in digital technology education application research elucidates the current frontiers in the field, reflecting a trajectory that is in tandem with the rapidly advancing digital age. This landscape is sculpted by emergent technological innovations and shaped by the demands of an increasingly digital society.

Interdisciplinary integration and pedagogical transformation

One of the frontiers identified from recent keyword bursts includes the integration of digital technology into diverse educational contexts, particularly noted with the keyword “physical education.” The digitalization of disciplines traditionally characterized by physical presence illustrates the pervasive reach of technology and signifies a push towards interdisciplinary integration where technology is not only a facilitator but also a transformative agent. This integration challenges educators to reconceptualize curriculum delivery to accommodate digital tools that can enhance or simulate the physical aspects of learning.

Digital literacy and skills acquisition

Another pivotal frontier is the focus on “digital literacy” and “digital skill”, which has intensified in recent years. This suggests a shift from mere access to technology towards a comprehensive understanding and utilization of digital tools. In this realm, the emphasis is not only on the ability to use technology but also on critical thinking, problem-solving, and the ethical use of digital resources (Yu, 2022 ). The acquisition of digital literacy is no longer an additive skill but a fundamental aspect of modern education, essential for navigating and contributing to the digital world.

Educational digital transformation

The keyword “digital transformation” marks a significant research frontier, emphasizing the systemic changes that education institutions must undergo to align with the digital era (Romero et al. 2021 ). This transformation includes the redesigning of learning environments, pedagogical strategies, and assessment methods to harness digital technology’s full potential. Research in this area explores the complexity of institutional change, addressing the infrastructural, cultural, and policy adjustments needed for a seamless digital transition.

Engagement and participation

Further exploration into “engagement” and “participation” underscores the importance of student-centered learning environments that are mediated by technology. The current frontiers examine how digital platforms can foster collaboration, inclusivity, and active learning, potentially leading to more meaningful and personalized educational experiences. Here, the use of technology seeks to support the emotional and cognitive aspects of learning, moving beyond the transactional view of education to one that is relational and interactive.

Professional development and teacher readiness

As the field evolves, “professional development” emerges as a crucial area, particularly in light of the pandemic which necessitated emergency remote teaching. The need for teacher readiness in a digital age is a pressing frontier, with research focusing on the competencies required for educators to effectively integrate technology into their teaching practices. This includes familiarity with digital tools, pedagogical innovation, and an ongoing commitment to personal and professional growth in the digital domain.

Pandemic as a catalyst

The recent pandemic has acted as a catalyst for accelerated research and application in this field, particularly in the domains of “digital transformation,” “professional development,” and “physical education.” This period has been a litmus test for the resilience and adaptability of educational systems to continue their operations in an emergency. Research has thus been directed at understanding how digital technologies can support not only continuity but also enhance the quality and reach of education in such contexts.

Ethical and societal considerations

The frontier of digital technology in education is also expanding to consider broader ethical and societal implications. This includes issues of digital equity, data privacy, and the sociocultural impact of technology on learning communities. The research explores how educational technology can be leveraged to address inequities and create more equitable learning opportunities for all students, regardless of their socioeconomic background.

Innovation and emerging technologies

Looking forward, the frontiers are set to be influenced by ongoing and future technological innovations, such as artificial intelligence (AI) (Wu and Yu, 2023 ; Chen et al. 2022a ). The exploration into how these technologies can be integrated into educational practices to create immersive and adaptive learning experiences represents a bold new chapter for the field.

In conclusion, the current frontiers of research on the application of digital technology in education are multifaceted and dynamic. They reflect an overarching movement towards deeper integration of technology in educational systems and pedagogical practices, where the goals are not only to facilitate learning but to redefine it. As these frontiers continue to expand and evolve, they will shape the educational landscape, requiring a concerted effort from researchers, educators, policymakers, and technologists to navigate the challenges and harness the opportunities presented by the digital revolution in education.

Conclusions and future research

Conclusions.

The utilization of digital technology in education is a research area that cuts across multiple technical and educational domains and continues to experience dynamic growth due to the continuous progress of technology. In this study, a systematic review of this field was conducted through bibliometric techniques to examine its development trajectory. The primary focus of the review was to investigate the leading contributors, productive national institutions, significant publications, and evolving development patterns. The study’s quantitative analysis resulted in several key conclusions that shed light on this research field’s current state and future prospects.

(1) The research field of digital technology education applications has entered a stage of rapid development, particularly in recent years due to the impact of the pandemic, resulting in a peak of publications. Within this field, several key authors (Selwyn, Henderson, Edwards, etc.) and countries/regions (England, Australia, USA, etc.) have emerged, who have made significant contributions. International exchanges in this field have become frequent, with a high degree of internationalization in academic research. Higher education institutions in the UK and Australia are the core productive forces in this field at the institutional level.

(2) Education and Information Technologies , Computers & Education , and the British Journal of Educational Technology are notable journals that publish research related to digital technology education applications. These journals are affiliated with the research field of educational technology and provide effective communication platforms for sharing digital technology education applications.

(3) Over the past two decades, research on digital technology education applications has progressed from its early stages of budding, initial development, and critical exploration to accelerated transformation, and it is currently approaching maturity. Technological progress and changes in the times have been key driving forces for educational transformation and innovation, and both have played important roles in promoting the continuous development of education.

(4) Influenced by the pandemic, three emerging frontiers have emerged in current research on digital technology education applications, which are physical education, digital transformation, and professional development under the promotion of digital technology. These frontier research hotspots reflect the core issues that the education system faces when encountering new technologies. The evolution of research hotspots shows that technology breakthroughs in education’s original boundaries of time and space create new challenges. The continuous self-renewal of education is achieved by solving one hotspot problem after another.

The present study offers significant practical implications for scholars and practitioners in the field of digital technology education applications. Firstly, it presents a well-defined framework of the existing research in this area, serving as a comprehensive guide for new entrants to the field and shedding light on the developmental trajectory of this research domain. Secondly, the study identifies several contemporary research hotspots, thus offering a valuable decision-making resource for scholars aiming to explore potential research directions. Thirdly, the study undertakes an exhaustive analysis of published literature to identify core journals in the field of digital technology education applications, with Sustainability being identified as a promising open access journal that publishes extensively on this topic. This finding can potentially facilitate scholars in selecting appropriate journals for their research outputs.

Limitation and future research

Influenced by some objective factors, this study also has some limitations. First of all, the bibliometrics analysis software has high standards for data. In order to ensure the quality and integrity of the collected data, the research only selects the periodical papers in SCIE and SSCI indexes, which are the core collection of Web of Science database, and excludes other databases, conference papers, editorials and other publications, which may ignore some scientific research and original opinions in the field of digital technology education and application research. In addition, although this study used professional software to carry out bibliometric analysis and obtained more objective quantitative data, the analysis and interpretation of data will inevitably have a certain subjective color, and the influence of subjectivity on data analysis cannot be completely avoided. As such, future research endeavors will broaden the scope of literature screening and proactively engage scholars in the field to gain objective and state-of-the-art insights, while minimizing the adverse impact of personal subjectivity on research analysis.

Data availability

The datasets analyzed during the current study are available in the Dataverse repository: https://doi.org/10.7910/DVN/F9QMHY

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Acknowledgements

This research was supported by the Zhejiang Provincial Social Science Planning Project, “Mechanisms and Pathways for Empowering Classroom Teaching through Learning Spaces under the Strategy of High-Quality Education Development”, the 2022 National Social Science Foundation Education Youth Project “Research on the Strategy of Creating Learning Space Value and Empowering Classroom Teaching under the background of ‘Double Reduction’” (Grant No. CCA220319) and the National College Student Innovation and Entrepreneurship Training Program of China (Grant No. 202310337023).

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Wang, C., Chen, X., Yu, T. et al. Education reform and change driven by digital technology: a bibliometric study from a global perspective. Humanit Soc Sci Commun 11 , 256 (2024). https://doi.org/10.1057/s41599-024-02717-y

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Unlocking success in digital transformations

As digital technologies dramatically reshape industry after industry, many companies are pursuing large-scale change efforts to capture the benefits of these trends or simply to keep up with competitors. In a new McKinsey Global Survey on digital transformations, more than eight in ten respondents say their organizations have undertaken such efforts in the past five years. 1 The online survey was in the field from January 16, 2018, to January 26, 2018, and garnered responses from 1,793 participants representing the full range of regions, industries, company sizes, functional specialties, and tenures. Of them, 1,521 have been part of at least one digital transformation in the past five years at either their current or previous organizations. To adjust for differences in response rates, the data are weighted by the contribution of each respondent’s nation to global GDP. Yet success in these transformations is proving to be elusive. While our earlier research has found that fewer than one-third of organizational transformations succeed at improving a company’s performance and sustaining those gains, the latest results find that the success rate of digital transformations is even lower.

The results from respondents who do report success point to 21 best practices, all of which make a digital transformation more likely to succeed . These characteristics fall into five categories: leadership, capability building, empowering workers, upgrading tools, and communication. These categories suggest where and how companies can start to improve their chances of successfully making digital changes to their business.

Transformations are hard, and digital ones are harder

Years of research on transformations has shown that the success rate for these efforts is consistently low: less than 30 percent succeed . 2 We define a successful transformation as one that, according to respondents, was very or completely successful at both improving performance and equipping the organization to sustain improvements over time. In our 2016 survey, the rate of success was 20 percent; in 2014, 26 percent; and in 2012, 20 percent. This year’s results suggest that digital transformations are even more difficult. Only 16 percent of respondents say their organizations’ digital transformations have successfully improved performance and also equipped them to sustain changes in the long term. An additional 7 percent say that performance improved but that those improvements were not sustained.

Even digitally savvy industries , such as high tech, media, and telecom, are struggling. Among these industries, the success rate does not exceed 26 percent. But in more traditional industries, such as oil and gas, automotive, infrastructure, and pharmaceuticals, digital transformations are even more challenging: success rates fall between 4 and 11 percent.

Success rates also vary by company size. At organizations with fewer than 100 employees, respondents are 2.7 times more likely to report a successful digital transformation  than are those from organizations with more than 50,000 employees.

The anatomy of digital transformations

Whether a change effort has succeeded or not, the results point to a few shared traits of today’s digital transformations. For one, organizations tend to look inward when making such changes. The most commonly cited objective for digital transformations is digitizing the organization’s operating model, cited by 68 percent of respondents. Less than half say their objective was either launching new products or services or interacting with external partners through digital channels. Digital transformations also tend to be wide in scope. Eight in ten respondents say their recent change efforts involved either multiple functions or business units or the whole enterprise. Additionally, the adoption of technologies plays an important role across digital transformations. On average, respondents say their organizations are using four of 11 technologies we asked about, with traditional web tools cited most often and used in the vast majority of these efforts.

At the same time, the results from successful transformations show that these organizations deploy more technologies than others do (Exhibit 1). This might seem counterintuitive, given that a broader suite of technologies could result in more complex execution of transformation initiatives and, therefore, more opportunities to fail. But the organizations with successful transformations are likelier than others to use more sophisticated technologies, such as artificial intelligence, the Internet of Things, and advanced neural machine-learning techniques.

The keys to success

Having these technologies on hand is only one part of the story. The survey results indicate how, exactly, companies should make the technology-supported changes that differentiate successful digital transformations from the rest (Exhibit 2).

Our research points to a set of factors that might improve the chances of a transformation succeeding (see sidebar, “Twenty-one keys to success”). 3 The survey tested for best practices in a digital transformation by using different types and structures of questions. To make commensurate comparisons of each practice’s impact on the likelihood of transformation success, Total Unduplicated Reach and Frequency (TURF) and Shapley value analyses were run. TURF analysis was conducted among respondents reporting successful transformations to identify the most common combinations of the 83 practices tested in the survey. This analysis was carried out by determining the proportion of respondents agreeing with or selecting at least one practice, then calculating the incremental value of including or excluding each practice. Shapley value analysis was then applied to the TURF output to rank the practices by their average expected marginal contribution to the likelihood of a successful transformation. The 21 keys to transformation success are the practices with the highest Shapley values. These factors fall into five categories:

Twenty-one keys to success

Out of 83 practices that were tested in the survey, 1 The survey tested for best practices in a digital transformation by using different types and structures of questions. To make commensurate comparisons of each practice’s impact on the likelihood of transformation success, Total Unduplicated Reach and Frequency (TURF) and Shapley value analyses were run. TURF analysis was conducted among respondents reporting successful transformations to identify the most common combinations of the 83 practices tested in the survey. This analysis was carried out by determining the proportion of respondents agreeing with or selecting at least one practice, then calculating the incremental value of including or excluding each practice. Shapley value analysis was then applied to the TURF output to rank the practices by their average expected marginal contribution to the likelihood of a successful transformation. The 21 keys to transformation success are the practices with the highest Shapley values. the following are those that best explain the success of an organization’s digital transformation:

• Implement digital tools to make information more accessible across the organization.
• Engage initiative leaders (leaders of either digital or nondigital initiatives that are part of the transformation) to support the transformation.
• Modify standard operating procedures to include new digital technologies.
• Establish a clear change story (description of and case for the changes being made) for the digital transformation.
• Add one or more people who are familiar or very familiar with digital technologies to the top team.
• Leaders engaged in transformation-specific roles encourage employees to challenge old ways of working (processes and procedures).
• Senior managers encourage employees to challenge old ways of working (processes and procedures).
• Redefine individuals’ roles and responsibilities so they align with the transformation’s goals.
• Provide employees with opportunities to generate ideas of where digitization might support the business.
• Establish one or more practices related to new ways of working (such as continuous learning, open physical and virtual work environments, and role mobility).
• Engage employees in integrator roles (employees who translate and integrate new digital methods and processes into existing ways of working to help connect traditional and digital parts of the business) to support the transformation.
• Implement digital self-serve technology for employees’ and business partners’ use.
• Engage the leader of a program-management office or transformation office (full-time leader of the team or office dedicated to transformation-related activities) to support the transformation.
• Leaders in transformation-specific roles get more involved in developing the digital transformation’s initiatives than they were in past change efforts.
• Leaders in transformation-specific roles encourage their employees to experiment with new ideas (such as rapid prototyping and allowing employees to learn from their failures).
• Senior managers get more involved in digital initiatives than they were in past change efforts.
• Leaders in transformation-specific roles ensure collaboration between their units and others across the organization when employees are working on transformation initiatives.
• Senior managers ensure collaboration between their units and others across the organization.
• Engage technology-innovation managers (managers with specialized technical skills who lead work on digital innovations, such as development of new digital products or services) to support the transformation.
• Senior managers encourage their employees to experiment with new ideas.
• Senior managers foster a sense of urgency within their units for making the transformation’s changes.
• having the right, digital-savvy leaders in place
• building capabilities for the workforce of the future
• empowering people to work in new ways
• giving day-to-day tools a digital upgrade
• communicating frequently via traditional and digital methods

Having the right, digital-savvy leaders in place

Change takes place at all levels during a digital transformation, especially when it comes to talent and capabilities. Nearly 70 percent of all respondents say their organizations’ top teams changed during the transformation—most commonly when new leaders familiar with digital technologies joined the management team.

Indeed, adding such a leader is one of the keys to transformation success. So is the engagement of transformation-specific roles—namely, leaders of individual initiatives and leaders of the program-management or transformation office who are dedicated full time to the change effort. Another key to success is leadership commitment. When people in key roles (both the senior leaders of the organization and those in transformation-specific roles) are more involved in a digital transformation than they were in past change efforts, a transformation’s success is more likely.

Other results indicate that when companies achieve transformation success, they are more likely to have certain digital-savvy leaders in place. Less than one-third of all respondents say their organizations have engaged a chief digital officer (CDO) to support their transformations. But those that do are 1.6 times more likely than others to report a successful digital transformation.

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Building capabilities for the workforce of the future.

The survey results confirm that developing talent and skills throughout the organization—a fundamental action for traditional transformations —is one of the most important factors for success in a digital change effort. Of our 21 keys to success, three relate to the workforce’s digital capabilities. First is redefining individuals’ roles and responsibilities so they align with a transformation’s goals, which can help clarify the roles and capabilities the organization needs. Respondents are 1.5 times more likely to report a successful digital transformation when this practice is in place.

Two other keys relate to engaging the specific roles of integrators and technology-innovation managers, who bridge potential gaps between the traditional and digital parts of the business. People in these roles help foster stronger internal capabilities among colleagues. Integrators are employees who translate and integrate new digital methods and processes into existing ways of working. Because they typically have experience on the business side and also understand the technical aspects and business potential of digital technologies, integrators are well equipped to connect the traditional and digital parts of the business. For their part, technology-innovation managers possess specialized technical skills and lead work on a company’s digital innovations.

Beyond these three keys for success, we found that companies with winning transformations have a better-funded and more robust approach to talent than others do. Transformation success is more than three times likelier when respondents say their organizations have invested the right amount in digital talent .

Success is also more likely when organizations scale up their workforce planning and talent development (Exhibit 3). For example, 27 percent of respondents report successful transformations when their companies set cross-functional or enterprise-wide hiring goals based on specific skill needs—nearly twice the share of respondents whose organizations do not.

During recruitment, using a wider range of approaches also supports success. Traditional recruiting tactics, such as public job postings and referrals from current employees, do not have a clear effect on success, but newer or more uncommon methods do. Success is at least twice as likely at organizations that run innovative recruiting campaigns (such as having recruits play games or find hidden messages in source code as part of the recruiting process) or host technology conferences or “hackathons.”

Empowering people to work in new ways

Digital transformations require cultural and behavioral changes such as calculated risk taking, increased collaboration, and customer centricity, as our previous research has shown . In this survey, the results suggest two primary ways in which companies with successful transformations are empowering employees to embrace these changes.

The first is reinforcing new behaviors and ways of working through formal mechanisms, long proved as an action that supports organizational change. One related key to transformation success is establishing practices related to working in new ways. Respondents who say their organizations established at least one new way of working, such as continuous learning or open work environments, as part of their change efforts are more likely than others to report successful transformations. Another key is giving employees a say on where digitization could and should be adopted. When employees generate their own ideas about where digitization might support the business, respondents are 1.4 times more likely to report success.

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A second approach to empowering workers is ensuring that people in key roles play parts in reinforcing change. Success depends on both senior leaders and those engaged during the transformation. 4 The survey asked which of the following roles were engaged by the organization to support the execution of the digital transformation: initiative leaders, integrator roles, leaders of the program-management or transformation office, technology-innovation managers, chief digital officers, and coaches. One related factor is encouraging employees to challenge old ways of working. Respondents who say their senior leaders and the people engaged in transformation-specific roles do this are more likely than their peers to report success (1.5 times more for senior leaders and 1.7 times more for those in key transformation roles). Another factor for success relates to risk taking. Success is more likely when senior leaders and leaders who are engaged in the transformation all encourage employees to experiment with new ideas—for example, through rapid prototyping and allowing employees to learn from their failures. A third key to success is people in key roles ensuring that their own units are collaborating with others when working on transformations. When respondents say their senior leaders and those in transformation-related roles have done so, they are 1.6 and 1.8 times, respectively, more likely than others to report success.

Giving day-to-day tools a digital upgrade

For organizations to empower employees to work in new ways, the survey findings show how, and by how much, digitizing tools and processes can support success. We asked respondents about seven structural changes their organizations had made since the transformations began (Exhibit 4). Three of these changes—each of which involves making the use of digital tools a new organizational norm—emerged as keys to success.

The first key is adopting digital tools to make information more accessible across the organization, which more than doubles the likelihood of a successful transformation. The second is implementing digital self-serve technologies for employees, business partners, or both groups to use; transformation success is twice as likely when organizations do so. A third key, focused on technology in company operations, is organizations modifying their standard operating procedures to include new technologies. Beyond these factors, an increase in data-based decision making and in the visible use of interactive tools can also more than double the likelihood of a transformation’s success.

Communicating frequently via traditional and digital methods

We also found that using remote and digital communications to convey the transformation’s vision does a much better job of supporting success than in-person or traditional channels. When senior managers and initiative leaders use new digital channels to reach employees remotely, the rate of success is three times greater.

Looking ahead

While respondents say that many digital transformations fall short in improving performance and equipping companies to sustain changes, lessons can be learned from those who report success. The survey results suggest steps companies can take to increase their chances of success during a transformation:

• Reimagine your workplace. The results show that success requires both digital-savvy leaders and a workforce with the capabilities to make a digital transformation’s changes happen, which other McKinsey research also confirms. 5 For more, see James Manyika and Kevin Sneader, “ AI, automation, and the future of work: Ten things to solve for ,” McKinsey Global Institute, June 2018; Jacques Bughin, Peter Dahlström, Eric Hazan, Susan Lund, Amresh Subramaniam, and Anna Wiesinger, “ Skill shift: Automation and the future of the workforce ,” McKinsey Global Institute, May 2018; and Pablo Illanes, Susan Lund, Mona Mourshed, Scott Rutherford, and Magnus Tyreman, “ Retraining and reskilling workers in the age of automation ,” McKinsey Global Institute, January 2018. The workforce implications of digitization, automation, and other technological trends are significant, and companies will need to invest in and hire for radically different skills and capabilities. Whether or not an organization has already begun a digital transformation, it is important for all companies to think critically about the ways in which digitization could affect their businesses, in the near and longer term, and the skills they will need to keep up. One critical step is for organizations to develop clear workforce strategies to help determine the digital skills and capabilities that they currently have—and will need—to meet their future goals.
• Upgrade the organization’s “hard wiring.” As digital requires new ways of working as well as changes to the organization’s overall culture, employees must be empowered to work differently and keep up with the faster pace of business. The implementation of digital tools and upgrading of processes, along with the development of a nimbler operating model—that is, the hard wiring of the organization—will support these changes. Of course, leaders have important roles to play, too, by letting go of old practices (command-and-control supervision, for example). Since not all leaders will have the experience to support or enact such changes, dedicated leadership-development programs could help leaders and employees alike to make the necessary shifts in mind-sets and behaviors.
• Change the ways you communicate. Good communication has always been a key success factor in traditional change efforts, and it is just as important in a digital transformation. In a digital context, companies must get more creative in the channels they are using to enable the new, quicker ways of working and the speedier mind-set and behavior changes that a digital transformation requires. One change is to move away from traditional channels that support only one-way communication (company-wide emails, for example) and toward more interactive platforms (such as internal social media) that enable open dialogues across the organization. Another key to better communication is developing more concise—and even tailored—messages for people in the organization, rather than lengthier communications.

Stay current on your favorite topics

The contributors to the development and analysis of this survey include Hortense de la Boutetière , a partner in McKinsey’s Paris office, and Alberto Montagner and Angelika Reich , an associate partner and partner, respectively, in the Zurich office.

They wish to thank Cristy Chopra, Carolyn Dewar, Julie Goran, and Michael Krüsi for their contributions to this work.

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• Published: 15 April 2024

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• Javid Zare   ORCID: orcid.org/0000-0002-2947-8046 1 &
• Ajax Persaud   ORCID: orcid.org/0000-0002-2846-681X 1  

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Digital technologies, which are fundamentally different from traditional technologies, are driving radical changes across all industries, supply chains, consumer preferences, competition, and more. These radical shifts create challenges and opportunities for firms to create and capture value from business model innovation. The challenge goes beyond simply implementing advanced digital technologies such as artificial intelligence (AI), machine learning (ML), and Internet of Things (IoT) to developing business model innovations to create and capture value. Essentially, there is a complementary, mutually reinforcing relationship between digital transformation (DT) and business model innovation (BMI). However, the current understanding of the relationship between DT and BMI remains unclear, despite growing academic interest in this relationship. We endeavor to map the intellectual structure of this emerging research field at the intersection of DT and BMI over a 24-year period (from January 1999 to December 2023). The goal is to harness the fragmented literature, thereby creating a coherent basis for understanding its separate perspectives and issues. Using bibliometric analysis, we identified several key themes around which the extant literature can be organized. We also identified several areas where further research is warranted.

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84 Digital Transformation Essay Topic Ideas & Examples

🏆 best digital transformation topic ideas & essay examples, 📃 good research topics about digital transformation, 🎓 interesting topics to write about digital transformation, ❓ digital transformation research questions.

• Bossard Company’s Digital Transformation As the size of the clients grew to industrial companies and factories, the demands for parts increased. The SmartBin technology was innovative and has become the centerpiece of Bossard’s business model and approach to customers.
• Digital Transformation in the Oil and Gas Industry The functions of modern digital devices that support the work of the oil and gas industry serve as the tolls reducing people’s participation in the monitoring process, thereby automating the monitoring of activities and allowing […] We will write a custom essay specifically for you by our professional experts 808 writers online Learn More
• General Electric Company’s Digital Transformation Strategy The introduction of digital products is something that should be supported by the current business model. Such an initiative required a superior business model to make the company competitive and successful.
• American Entertainment Industry: Digital Transformation The purpose of this paper is to examine the aspects of the current competition between streaming companies and television networks with the focus on observed digital transformations in sharing information and to discuss what further […]
• The Automobile Company’s Digital Transformation As a result, the primary objective of the project is to discuss how the company can move from the first level of the maturity model to the second level.
• Digital Transformation Strategies for Organizations The first success factor in digital transformation is the company’s preparedness to make bold moves in the digital realm to explore and anticipate customers’ expectations.
• The Digital Transformation and Innovation Nexus The practical orientation of the study ensures its applicability in the current economic environment characterized by the increasing complexity of the organizational landscape.
• Information Governance and Digital Transformation By involving information technology, innovations in technology, and data, organizations must oversee the right implementation of digital transformation to address security and privacy concerns.
• Digital Transformation: Job Satisfaction among Academic Family Physicians Some stakeholders may resist the application of Industry 4 in the manufacturing sector based on the concerns raised above. This study aims to investigate the relevance of digital transformation, specifically focusing on Industry 4, in […]
• Extending Supply Chain Digital Transformation with Analytics, Simulation, and Optimization There is a need for digital transformation in the supply chain to streamline operations, reduce costs, and improve the employees’ working environment.
• Supply Chain Digital Transformation To improve the present system, it is essential to utilize analytics, simulation, and optimization approach as a digitalization extension means.
• Sadara Company’s Digital Transformation The digital transformation and the transition to the online environment used to be seen as the prerogative of the organizations that provided solely the services that could be easily translated into the online context due […]
• Electric Utility Companies’ Digital Transformation Electric utility companies have faced the problem of decentralization in the past due to the underdevelopment of the service market in this area and the centralization of the system.
• Business and Its Digital Transformation However, if a company wants to be ahead of competitors, it needs to invest in advanced digital technologies regularly. Nonetheless, individuals should analyze the possible reasons for the deployment of NIT to their unique business […]
• Digital Transformation: E-Services in the UAE In the United Arabs Emirates, there has been a major transformation in the adoption of electronic services aimed to improve the quality of service delivery.
• Digital Transformation in the UAE’s National Policy As a result, the changes taking place in various sectors correspond to the state plan for the reorganization of different sectors and the promotion of modern digital opportunities to improve life in the country.
• How Digital Transformation Is Affecting the Oil and Gas Industry The research will assess the contributions of digital transformation in the oil and gas industry. What is the impact of digital transformation in the oil and gas industry?
• Organizational Capabilities and Digital Transformation A digital strategy entails using big data and business intelligence to acquire a competitive advantage in the industry. Data indexing, quality evaluation, and aggregation are some of the procedures that may be complex and costly […]
• Digital Transformation: Hyper-Connectedness and Collaboration The guiding principles for E2E economy formulated by the authors include the ability of organizations to provide optimal customer experiences through the right partnerships, capacity to use contextual and predictive analytics to generate customer value, […]
• Digitalization and the Future of Work: Macroeconomic Consequences
• Does Enterprise Architecture Support the Digital Transformation Endeavors?
• Digital Transformation and Lean Management: Challenges in the Energy Industry
• The Process of Digital Transformation of Airline Companies
• Digital Transformation Beyond the Digital Age
• Paving the Way Towards Digital Transformation and Sustainable Societies
• Digital Transformation, Digital Dividends, and Entrepreneurship
• The Impact of Digital Transformation on Finance Sector Competition
• Digital Transformation And Its Effect On A Business
• Linking Digital Transformation and Localizing the Sustainable Development Goals
• Digitalization Changing the Economy and the Labor Market
• The Relations Between Digital Transformation and Technological Advancements
• Digital Transformation and the Performance of Micro and Small Enterprises
• Correlation Between Digital Transformation and the Provision of Legal Services
• The Relationship Between Digital Transformation and the Renewal of Social Theory
• Digital Transformation and Value Creation: Sea Change Ahead
• Linking Digital Transformation, International Competition, and Specialization
• Does Digital Transformation Mean the End of Marketing?
• Engineering the Digital Transformation of Marketing
• How Information Systems Enable Digital Transformation: Focus on Business Models
• Predicting the Future Work Change Due to Digital Transformation
• Government Digital Transformation Strategy: High-Level Themes
• How Does the Digital Transformation Affect Organizations?
• Composing the Plan and Budget for a Digital Transformation Project
• Products’ Digital Transformation Effect on Perceived Luxury Level and Brand Authenticity
• How the Internet Drove the Digital Transformation of Products and Services
• The Digital Transformation of Healthcare: Current Status and the Road Ahead
• Retail Digital Transformation Market: Global Industry Analysis, Share, Growth, and Forecast
• The Productivity and Unemployment Effects of the Digital Transformation
• Analysis of the Key Elements of Digital Transformation
• How the Digital World May Influence Teaching
• Data, Measurement and Initiatives for Inclusive Digitalization, and Future of Work
• Digitalization and Smartening Public Governance of the European High North Regions
• Fiscal Pressures From Digital Transformation and Immigration
• How Decarbonization, Digitalization, and Decentralization Are Changing Key Power Infrastructures
• Digitalization, Multinationals, and Employment: An Empirical Analysis of Their Causal Relationships
• How Digital Transformation Has Reshaped the Mass Media
• Managing Digitalization: Challenges and Opportunities for Business
• Organizing for Digitalization Through Mutual Constitution: The Design Firm Case
• Innovative and Sustainable eMaintenance: Capabilities for Digital Transformation of Maintenance
• How Does Digital Transformation Impact Marketing?
• Why Is Digital Transformation a Never-Ending Process?
• What Is the Biggest Barrier to Digital Transformation?
• Is Digital Marketing Part of Digital Transformation?
• Which Industry Is Leading in Digital Transformation?
• What Is the Future of Digital Transformation?
• How Is Digital Transformation Affecting the Industry or Work?
• What Is the End Goal of Digital Transformation?
• How Does Digital Transformation Improve Organizational Resilience?
• What Is the Outcome of Digital Transformation?
• Does Digital Transformation Require Coding?
• Why Do People Fear Digital Transformation?
• Does Information Management Play a Critical Role in Digital Transformation?
• What Are the Biggest Digital Transformation Challenges Organizations Face?
• Why Is Digital Transformation Important for Organizations?
• How Has Technology Impacted Digital Transformation?
• Why Is Digital Transformation Critical to Business Growth?
• How Effective Is Digital Transformation?
• What Is the Negative Impact of Digital Transformation?
• Is Technology Important in Digital Transformation?
• What Are the Key Effective Strategies for Digital Transformation?
• How Do Companies Implement Digital Transformation?
• Why Is Digital Transformation Important in Retail?
• Does Digital Transformation Ever End?
• Is Digital Transformation a Business Model?
• Chicago (A-D)
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How Lufthansa Shapes Data-Driven Transformation Leaders

The airline created a program to educate leaders all across the organization and turn a sky filled with data into accelerated change.

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Up in the air, a modern plane generates 1 terabyte of data every 24 hours of flight. For airlines like the Lufthansa Group, this data can be used to create valuable business outcomes, from improved operational efficiency to higher customer satisfaction. On top of this rich data set, Lufthansa has invested substantially in deploying artificial intelligence technologies, improving data quality processes, and hiring data engineers and data scientists. However, in 2023, it recognized that it had to do more to become a truly data-driven company. The industry incumbent faced not a mechanical problem but a human one: Organizational resistance to change stood in the way of transformational efforts. Lufthansa’s data experts felt like they were operating as lone wolves, without the business support and use cases that would get the whole company behind its transformation goals.

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In its quest to beat these challenges and speed transformation, Lufthansa recognized that a crucial ingredient had been overlooked: the leadership circle. Leaders can not only motivate and inspire but also coach their employees to drive exciting data and AI use cases and turn their own business units into front-runners of data-driven change. However, internal analysis confirmed that there was a huge shortage of data and AI literacy among Lufthansa’s leadership ranks, from the C-suite to team leaders. Lufthansa felt that turning its leaders into data leaders would be a key success factor for the whole organization.

So Lufthansa created a data leadership program, and along the way, its team learned valuable insights about the roles that people could play in data-driven change. The company’s approach has lessons for other organizations facing the same need.

Data Leadership Is Not Just for Tech Leaders

What is data leadership? At Lufthansa, it means accompanying and supporting one’s team to achieve data-driven transformation together. Lufthansa knew that its future data leaders would not just be tech leads, like chief data officers (CDOs), who drive the implementation of data and AI use cases and corresponding policies, standards, and programs. Especially in data-driven digital transformations, business leaders need to take an active role. 1

To operationalize the concept, Lufthansa defined six different roles for effective data leaders (see “Data Leadership: Six Key Roles”) and shaped a corresponding data leadership development program to bring those roles to life.

About the Authors

Christian Haude is senior data strategy and innovation manager at Lufthansa Group. Ivo Blohm is associate professor for information systems and business analytics at the Institute of Information Systems and Digital Business at the University of St. Gallen in Switzerland. Xavier Lagardère is managing director of the Lufthansa Innovation Hub and head of data and innovation at Lufthansa Group.

1. T.H. Davenport and J. Foutty, “ AI-Driven Leadership ,” MIT Sloan Management Review, Aug. 10, 2018, https://sloanreview.mit.edu; and T.H. Davenport, N. Mittal, and I. Saif, “ What Separates Analytical Leaders From Laggards? ” MIT Sloan Management Review, Feb. 3, 2020, https://sloanreview.mit.edu.

2. E.A. Teracino, “ Data and Analytics as a Key Business Capability in Focus at the 2nd Annual Chief Data Officer and Information Quality (CDOIQ) European Symposium ,” CDO Magazine, Sept. 18, 2023, www.cdomagazine.tech.

3. G. Vial, J. Jiang, T. Giannelia, et al., “ The Data Problem Stalling AI ,” MIT Sloan Management Review 62, no. 2 (winter 2021): 47-53.

4. “ Successful Experiment to Detect Hand Luggage Using Computer Vision ,” Lufthansa Group, accessed March 28, 2024, https://innovation-runway.lufthansagroup.com.

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A roadmap for digital neuroscience: Researchers summarize current status and further developments

Neuroscience has entered a new, digital phase. The combination of brain research with supercomputing in large-scale, multi-disciplinary research collaborations has enabled an innovative approach to deciphering the brain, using powerful scientific technologies and data resources.

These developments open up new possibilities for brain research, medicine and technology. A position paper by over 100 authors, now published in the journal Imaging Neuroscience , summarizes the current status and identifies the key points for further developments in digital neuroscience .

Digital technologies have fundamentally changed neuroscience in recent years. The challenges posed by increasingly large and complex data have been met with innovative shared platforms and novel tools for scientific investigation.

Large-scale research initiatives within Europe and worldwide have shaped these developments and enabled synergies in scientific efforts. Examples include the EU Flagship Human Brain Project (HBP), and its digital research infrastructure EBRAINS, which enable scientists to integrate data from different scales according to FAIR principles, use models and software at EBRAINS for gaining new insights and working collaboratively on a larger scale. This change has led to significant progress and offers the opportunity to advance neuroscience, medicine and brain-inspired technologies.

Against this background, the position paper titled " The coming decade of digital brain research—A vision for neuroscience at the intersection of technology and computing " is primarily intended as a roadmap for digital neuroscience over the next ten years.

"It is crucial that we assess, anticipate and shape the changes occurring in neuroscience and its related fields. The position paper identifies points of convergence and common goals, and provides a scientific framework for current and future developments in digital brain research based on a structured process of discussion with the research community at large," says lead author Prof. Katrin Amunts, Director at the Jülich Institute of Neuroscience and Medicine and Joint CEO of EBRAINS.

The position paper lists a total of eight key areas for digital neuroscience research. Near-term, middle-term and long-term goals are discussed, as well as novel developments like "digital twin"-approaches, with their applicability, potential and limitations in brain science.

A "digital twin" is a type of personalized computational brain model that can be continuously updated with measured data obtained from its real-life counterpart, i.e., the patient. While not aimed at being an exact replica , the increasing sophistication and predictive power of these models is bringing new clinical and research applications into reach.

Further key areas described in the paper include ultra-high-resolution digital atlases and models of the brain that integrate multiple scales and modalities, neuro-derived artificial intelligence (AI) and computing innovations.

EBRAINS has a key role in in the interaction between brain research and computing, offering scientists access to the most powerful European supercomputers via the computing network Fenix and to the brain-inspired computing systems BrainScaleS and SpiNNaker. An Executive Summary of the paper has been published on the website of the EBRAINS research infrastructure.

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ORIGINAL RESEARCH article

This article is part of the research topic.

Digital Governance, Ecological Resilience and Resident Well-Being

Digital Transformation, Green Innovation, and Audit Fees Provisionally Accepted

• 1 Zhengzhou Business University, China
• 2 Yunnan Minzu University, China

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Under the trend of synergistic development of digitalization and greening, this paper investigates the impact of enterprise digital transformation on audit fees and its mechanism, by using textual analysis and performing empirical tests on the data of Chinese listed companies from 2007 to 2021. It is found that enterprise digital transformation significantly increases audit fees, and green innovation partially mediates this process. The study results are robust, even after a series of robustness tests. When financing constraints and environmental regulations are low, the mediating role of green innovation between digital transformation and audit fees is more significant. In addition, green innovation has a stronger mediating role between the use of underlying technology and audit fees, while green substantive innovation has a stronger mediating role between digital transformation and audit fees. This study investigates the effect of enterprise digital transformation on audit fees from the standpoint of green innovation. It offers a new perspective on how accounting firms make audit pricing decisions, provides guidance for enterprise digital transformation and green innovation, and gives an opportunity for China to promote the synergistic transformation and development of digitalization and greening to achieve the dual-carbon goal.

Keywords: digital transformation, Audit fees, green innovation, Financing constraint, environmental regulation

Received: 19 Oct 2023; Accepted: 22 Apr 2024.

Copyright: © 2024 Lou and Zhou. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: PhD. Xiaohui Zhou, Yunnan Minzu University, Kunming, China

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