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INTRODUCTION
The notion of Digital Twin has been developed over recent years, providing opportunities for creating virtual copies of actual systems that can be analyzed and optimized. Emerging initially from the fields of engineering and manufacturing, this innovative technology quickly gained momentum in areas including healthcare, smart cities, industrial automation, and others (Digital twin enabling technologies, Barricelli et al., 2019; Fuller et al., 2020). The development has been supported by progress in IoT, artificial intelligence, and big data analytics, which enable efficient collection, transfer, and processing of information. Digital twin research has gained considerable popularity over the last ten years due to its practical relevance. In particular, scholars have focused on the origins and potential future perspectives associated with this innovation as well as possible applications in cyber-physical systems and digital transformation (Digital twin origin to future, Singh et al., 2021; Digital twin benefits, Attaran and Celik, 2023). At the same time, researchers have recognized the importance of systematic investigation of digital twin-related knowledge considering its complex nature (Digital Twin systematic review, Jones et al., 2020).
Here, scientometrics emerges as an excellent instrument for conducting a quantitative evaluation of research tendencies, collaboration practices, and information dissemination in a specific scientific discipline. Scientific fields’ intellectual architecture and development course can be elucidated using the scientometrics technique (Ivancheva, 2008 Scientometrics methodology overview; Leydesdorff and Milojevic Scientometrics, n.d.). With the fast-growing number of scientific studies on digital twins, there is a demand to investigate their emergence and evolution, especially in less developed scientific areas like India. This study seeks to conduct scientometric analysis of digital twins research growth and dynamics, concentrating on the aspects of publication tendencies, authorship patterns, collaboration behavior, and sources’ allocation, especially that of India.
RELATED WORKS
The topic of Digital Twin has received a lot of interest from scholars owing to its immense transformational possibilities in different fields. Initial research has been concerned with the definition and conceptualization of digital twins, discussing their attributes, design considerations, and broad applicability. For example, Barricelli et al., 2019 Digital Twin review conducted a thorough review of the definitions, attributes, and applications of digital twins, creating the foundation for an understanding of this concept. Also, Jones et al., 2020 Digital Twin systematic review conducted a systematic review of the literature to define digital twin systems and their relevance in the context of cyber-physical systems. Other topics related to technological advancements and evolution of digital twin research have also been broadly addressed by scholars. Research like Fuller et al., 2020 Digital Twin enabling technologies focused on exploring enabling technologies, limitations, and future research avenues related to digital twins, whereas Singh et al., 2021 Digital twin origin to future looked at its past origin and future course.
Apart from the theoretical progress in this field, several research studies have paid attention to practical aspects related to the usage of digital twin technology. For instance, Attaran and Celik, 2023 Digital Twin benefits covered the topic of advantages, application areas, and difficulties of the digital twin implementation, whereas industry-based approaches identified important application areas and their benefits (IoT Analytics Digital Twin applications insights). In turn, specific application of digital twin technology to particular domains has also been researched, which illustrates the growth of research perspectives for this concept. For example, Zhao et al., 2024 Digital Twin measurement technology investigated the application of digital twins to measurement technologies, whereas Lam et al., 2024 Winter Simulation Conference digital twin focused on simulation technologies. Finally, the issue of organization and development of digital twins’ researches has been considered from the engineering and manufacturing point of view.
Along with technological progress, there is an increased awareness of the importance of using scientometric and bibliometric methods to analyze research trends. Scientometrics is a discipline that helps evaluate the scholarly communication process, research productivity, and collaboration practices (Ivancheva, 2008). In their foundational research, scientists stressed that quantitative metrics are used to construct the intellectual structure of research areas (Leydesdorff and Milojevic, n.d.). Also, review-based articles show the importance of research output synthesis to detect trends and research gaps (Blumel and Schniedermann, 2020). It becomes essential for researchers to conduct systematic and quantitative analysis in rapidly changing scientific disciplines, including digital twin. Although there is a considerable amount of literature dedicated to digital twin, there is still a lack of systematic scientometric research, which specifically focuses on the role of particular regions in the scientific development. Most existing works are related to studying global tendencies and technology aspects of digital twin applications. However, few studies explore the characteristics of publication process, collaboration dynamics, and research productivity in emerging communities, especially in India. Therefore, this paper aims to fill this research gap by conducting a scientometric analysis of digital twin publications with emphasis on India.
OBJECTIVES OF THE STUDY
- To assess the number of papers published about digital twins in India annually for 2015 to 2024;
- To investigate the distribution pattern of scientific publication between national and international platforms;
- To compare the rate of growth in India’s scientific output in terms of digital twins;
- To determine the annual authorship trend for papers published;
- To analyze the collaboration rate among the authors of digital twin research;
- To measure the productivity of authors engaged in digital twin research;
- To rank the journals publishing digital twin research.
METHODOLOGY
In the current study, a scientometric method has been applied to evaluate the research trends in the field of digital twin in India. For this purpose, the data was collected from the OpenAlex database, a reliable and comprehensive resource for scientific information. Data were extracted from the OpenAlex database on 26 May 2025. Scientometric analysis involved employing the structured search process for the query: title and abstract containing "digital twin" AND country=India AND publication years=2015-2024 AND language=English. Consequently, there were 1,237 entries that comprised the dataset for the study.
The collected data included several bibliographic measures such as publication years, authors’ names, affiliations (countries), and source titles (journals). The measures were selected for analyzing publication trends, authorship trends, collaboration among the authors, and distribution of publications across sources. Upon collecting the necessary data, they were exported to Microsoft Excel, where data processing was performed. Microsoft Excel became the main software platform used for data processing, cleaning, and analysis. Scientometric measures such as annual publication output, relative growth rates, degree of collaboration, authorship trends, and author productivity were calculated according to standard methods.
FINDINGS AND DISCUSSION
Digital Twin Research Output over the Years
The sources of Digital Twin research include articles published in journals, book chapters, reviews, pre-prints, datasets etc. the study had observed a total of 18219 publications in digital twin over the 6 years (see Table 1). Out of them, articles have shown a prominent and predominant contribution. The year wise distribution also shows how research output have gradually increased over the years. The digital twin research output consisting of book chapters comes second, closely followed by preprints. Reviews and datasets hold the fourth and fifth position respectively. The other formats fail to make significant impact in the overall research output.
| Document Type | Year | Total | % | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | 2023 | 2024 | |||
| Articles | 50 | 51 | 102 | 223 | 523 | 1029 | 1866 | 2778 | 4081 | 4163 | 14866 | 81.6% |
| Book | - | - | - | - | 7 | 1 | 4 | 4 | 12 | 8 | 36 | 0.2% |
| Book chapters | - | 4 | 3 | 14 | 77 | 109 | 138 | 273 | 500 | 372 | 1490 | 8.2% |
| Dataset | 1 | - | - | - | - | 2 | 12 | 48 | 33 | 6 | 102 | 0.6% |
| Editorial | 1 | - | - | - | 2 | 2 | 9 | 14 | 30 | 23 | 81 | 5.5% |
| Other | 1 | 1 | - | - | 1 | 1 | 14 | 20 | 22 | 39 | 99 | 0.5% |
| Preprint | 1 | - | - | 8 | 19 | 56 | 99 | 140 | 357 | 319 | 999 | 5.5% |
| Report | 1 | - | - | 1 | 1 | 5 | 20 | 23 | 25 | 14 | 90 | 0.5% |
| Review | 1 | 2 | 3 | 1 | 6 | 20 | 40 | 84 | 139 | 160 | 456 | 2.5% |
| Total | 56 | 58 | 108 | 247 | 636 | 1225 | 2202 | 3384 | 5199 | 5104 | 18219 |
Digital Twin research output on International and National Output
The following Table 2 demonstrates international and national (Indian) Digital Twin research output. In 2015, out of 58 published materials, 53 were result of international publication whereas only 3 of them were published in India. The output can be seen showing gradual increase over the years and finally in 2024, out of 5104 published documents, India contributed to almost 11% of globally published Digital Twin research.
| Year | International Output | National Output | Percentage |
|---|---|---|---|
| 2024 | 4599 | 505 | 10.9% |
| 2023 | 4844 | 355 | 7.3% |
| 2022 | 3201 | 183 | 5.7% |
| 2021 | 2117 | 85 | 4% |
| 2020 | 1178 | 47 | 4% |
| 2019 | 602 | 34 | 5.6 |
| 2018 | 233 | 14 | 6.0% |
| 2017 | 98 | 7 | 7.1% |
| 2016 | 54 | 4 | 7.4% |
| 2015 | 53 | 3 | 5.7% |
| Total | 16979 | 1237 |
Relative Growth of Indian Research Output
The following Table 3 indicates the relative growth of national (India) output of Digital Twin publication as well as the doubling time for the literature. It includes all sources of publications. It can be clearly observed that the Relative Growth Rate (RGR) decreased from 2015 (0.8) to 2024 (0.5). Whereas the doubling time shows a gradual increase from 2015 (0.8) to 2024 (1.3). It can be deduced from the above table that relative growth has shown a progressive decline which means the increase rate is low in terms of proportion and this has been highlighted by doubling time for publication.
| Year | Publication output | Cumulative output | W1 | W2 | RGR | Dt |
|---|---|---|---|---|---|---|
| 2015 | 3 | 3 | 1.098612 | 1.098612 | 0.847298 | 0.817894 |
| 2016 | 4 | 7 | 1.94591 | 1.94591 | 0.693147 | 0.999788 |
| 2017 | 7 | 14 | 2.639057 | 2.639057 | 0.693147 | 0.999788 |
| 2018 | 14 | 28 | 3.332205 | 3.332205 | 0.79493 | 0.871775 |
| 2019 | 34 | 62 | 4.127134 | 4.127134 | 0.564213 | 1.228258 |
| 2020 | 47 | 109 | 4.691348 | 4.691348 | 0.57651 | 1.20206 |
| 2021 | 85 | 194 | 5.267858 | 5.267858 | 0.664387 | 1.043067 |
| 2022 | 183 | 377 | 5.932245 | 5.932245 | 0.663535 | 1.044406 |
| 2023 | 355 | 732 | 6.595781 | 6.595781 | 0.524664 | 1.320846 |
| 2024 | 505 | 1237 | 7.120444 | 7.120444 | 0.524664 | 1.320846 |
Authorship Pattern
Year-wise Authorship Pattern
The mentioned table (Table 4) clearly shows that papers with 5 authors are maximum whereas papers with more than 5 authors are minimum over the years. It also establishes the fact that when the no. of authors increases, their contribution to the paper significantly decreases.
| Year | 1 Author | 2 Authors | 3 Authors | 4 Authors | 5 Authors | >5 Authors | Total |
|---|---|---|---|---|---|---|---|
| 2015 | - | 1 | 2 | - | - | - | 3 |
| 2016 | - | 1 | 2 | - | 1 | - | 4 |
| 2017 | - | 2 | 2 | 1 | 2 | - | 7 |
| 2018 | 3 | 4 | 1 | 3 | 3 | 1 | 15 |
| 2019 | 3 | 13 | 6 | 8 | 4 | - | 34 |
| 2020 | 8 | 14 | 6 | 10 | 9 | 1 | 48 |
| 2021 | 7 | 17 | 15 | 12 | 32 | 2 | 85 |
| 2022 | 16 | 29 | 49 | 31 | 50 | 12 | 187 |
| 2023 | 15 | 60 | 72 | 72 | 127 | 8 | 354 |
| 2024 | 24 | 89 | 104 | 98 | 179 | 9 | 503 |
| Total | 76 | 230 | 259 | 235 | 407 | 33 | 1237 |
Degree of Collaboration
From the Table 5, it can be deduced that the aggregate degree of collaboration for ‘Digital Twin’ literature over 2015-2024 is 0.91 which means, out of 1237 literatures, 91% of them are product of author collaboration. This clearly brings out the high level of collaborative research for ‘Digital Twin’.
| Year | Single author | Multiple author | Total (Nm+Ns) | Degree of Collaboration C= Nm/(Nm+Ns) | ||
|---|---|---|---|---|---|---|
| No. of publication (Ns) | % | No. of publication (Nm) | % | |||
| 2015 | 0 | 0 | 3 | 0.26 | 3 | 1 |
| 2016 | 0 | 0 | 4 | 0.34 | 4 | 1 |
| 2017 | 0 | 0 | 7 | 0.6 | 7 | 1 |
| 2018 | 3 | 3.95 | 12 | 1.03 | 15 | 0.8 |
| 2019 | 3 | 3.95 | 31 | 2.67 | 34 | 0.9 |
| 2020 | 8 | 10.53 | 40 | 3.46 | 48 | 0.8 |
| 2021 | 7 | 9.21 | 78 | 6.72 | 85 | 0.9 |
| 2022 | 16 | 21.05 | 171 | 14.73 | 187 | 0.9 |
| 2023 | 15 | 19.74 | 339 | 29.2 | 354 | 0.9 |
| 2024 | 24 | 31.58 | 479 | 41.26 | 503 | 0.9 |
| Total | 76 | 1161 | 0.91 |
Author Productivity
The study of author productivity is an important aspect in analysing the performance of research output. Generally, research activity is carried out by one person or a group of persons depending on the nature and aim of research. It also depends on the ability and efficiency of scientists. Depending on the skill and talent, a scientist may contribute to a quite number of papers, but it may not be the case for other scientists.
The analysis of author productivity (see Table 6) examines the trend of carrying out research in any discipline. This following section will solely focus on author productivity on ‘Digital Twin’. It can be observed that, 85.3% authors have made single contributions, whereas, two and three papers contributed by authors record second (9.6%) and third (2.7%) respectively. It is an interesting factor to notice that when the number of contributions increases, the number of authors decreases. It proves that, a greater level of research performance is noted only among few authors.
| No. of contribution(s) | No. of author(s) | Percentage (%) | Cumulative percentage (%) |
|---|---|---|---|
| 1 | 3166 | 85.3 | 85.3 |
| 2 | 355 | 9.6 | 94.9 |
| 3 | 97 | 2.6 | 97.5 |
| 4 | 33 | 0.9 | 98.4 |
| 5 | 18 | 0.5 | 98.9 |
| 6 | 12 | 0.3 | 99.2 |
| 7 | 4 | 0.1 | 99.3 |
| 8 | 2 | 0.05 | 99.35 |
| 9 | 2 | 0.05 | 99.4 |
| 10 | 3 | 0.08 | 99.48 |
| >10 | 19 | 0.5 | 99.98 |
| Total | 3711 | 100 |
Lotka’s Law of Scientific Productivity
Lotka’s formula for scientific productivity is as follows:
Where,
X=Number of Publications,
Y=Relative Frequency of Authors with X publications,
C=Constants depending on the specified field.
Putting the value in above equation,
X=1, Y=3166,
We get, 3166=C/1n,
Therefore, C=3166,
Again, putting the value of X=2, Y=355,
We get,
2n=3166/355, =8.92
Taking log on both sides,
therefore, n=3.16.
Lotka’s law of scientific productivity is used to calculate the authors’ productivity in bibliometric study (see Table 7) and this law stated that- “The number of authors making n contributions is about 1/n2 of those making one and proportion of all contributors that make a single contribution is about 60 percent. This means that out of all the authors in a field, 60% will have one publication, and 15% will be two publications, 7% of authors will have three publications and so on”. The above table and figure explored the Lotka’s law of scientific productivity with the chosen dataset. It was observed that, most of the observed and expected values were same. This in fact, justifies the skewed distribution of research output that only a few highly prolific authors contribute in most of the publications and majority of authors are occasional contributors. This therefore confirms a universal bibliometric pattern that can be observed in scientific publishing, showing inequality in productivity.
| No. of papers (X) | No. of authors (Y) observed values | When n=3.16, expected values |
|---|---|---|
| 1 | 3166 | 3166 |
| 2 | 355 | 354.2 |
| 3 | 97 | 98.4 |
| 4 | 33 | 39.6 |
| 5 | 18 | 19.6 |
| 6 | 12 | 11 |
| 7 | 4 | 6.8 |
| 8 | 2 | 4.4 |
| 9 | 2 | 3.1 |
| 10 | 3 | 2.2 |
Ranking of Journals
Journals is one of the primary sources of information. A higher rate of periodicals can be a measure of growth in the field of knowledge. It is an established fact that in the field of science, there is apparently an increased rate of birth of journals to meet the rapid explosion of information. The following table shows the ranking of journals according to their productivity. For ‘Digital Twin’, a total no. of 3289 journals published 18219 articles (see Table 8).
| Serial No. | Title of the journal | No. of Articles | % | Rank |
|---|---|---|---|---|
| 1 | IEEE Transactions on Industrial Informatics | 211 | 8.0% | 1 |
| 2 | The International Journal of Advanced Manufacturing Technology | 190 | 7.2% | 2 |
| 3 | Springer eBooks | 183 | 7% | 3 |
| 4 | CIRP journal of manufacturing science and technology | 181 | 6.9% | 4 |
| 5 | IEEE Access | 171 | 6.4% | 5 |
| 6 | Procedia Manufacturing | 169 | 6.4% | 6 |
| 7 | IFAC-PapersOnLine | 159 | 6% | 7 |
| 8 | Journal of Manufacturing Systems | 136 | 5.2% | 8 |
| 9 | International Journal of Production Research | 124 | 4.7% | 9 |
| 10 | CIRP Annals | 121 | 4.6% | 10 |
| 11 | IEEE Multimedia | 118 | 4.5% | 11 |
| 12 | Procedia CIRP | 110 | 4.2% | 12 |
| 13 | Systems | 108 | 4.1% | 13 |
| 14 | Automation in Construction | 104 | 4% | 14 |
| 15 | Computers in Industry | 103 | 3.9% | 15 |
| 16 | Nature | 100 | 3.8% | 16 |
| 17 | Robotics and Computer-Integrated Manufacturing | 98 | 3.7% | 17 |
| 18 | IEEE Internet of Things Journal | 87 | 3.3% | 18 |
| 19 | Engineering | 82 | 3.1% | 19 |
| 20 | Manufacturing Letters | 81 | 3.1% | 20 |
| Total | 2636 |
Scope of the Study
The current research is limited to a scientometric analysis of the existing literature on digital twin published in the OpenAlex database. The literature review is limited to those publications which have used the keyword “digital twin” in their titles and abstracts and are in the English language during the period 2015-2024. Regionally, the literature review focuses on the studies conducted by the researchers from India while at the same time making comparisons with global trends in order to see where India stands regarding digital twin research.
The literature reviewed includes a wide range of scholarly writings including journal papers, book chapters, reviews, preprints, and data sets among others. However, it is important to note that the research is limited to only the literature found in the OpenAlex database.
CONCLUSION
In this scientometric research, it is shown how the number of digital twins and its scope have rapidly grown and evolved during the time span of 2015-2024. As one can see, the number of research outputs has significantly increased on a global level. Moreover, journal articles have become the most prevalent type of scholarly publication within this topic. The constant growth of scientific publications shows how significant and diverse the use of digital twins has become across different spheres. When analyzing the distribution of national and international research contributions, it becomes evident that even though the number of global research outputs has rapidly increased, India’s contribution has been growing consistently and reached a significant level lately. Nevertheless, one can note that its growth rate tends to stabilize. Moreover, an analysis of authorship patterns and collaboration among authors shows that there is a trend of collaboration between scholars. In particular, the results show that many researchers tend to co-author their papers in digital twins’ field. The analysis of multi-authorship demonstrates a high level of cooperation, which is expected in digital twins’ sphere because it is an interdisciplinary topic. The authorship productivity analysis proves that the number of publications written by authors.
The above trend is reinforced by Lotka’s Law, which highlights the skewed distribution of scientific output. Additionally, journal ranking shows that a few key journals play an important role in disseminating knowledge on digital twin technology. Generally speaking, the findings of this research provide a good picture of the research status in the domain of digital twin, which is gaining importance due to the collaborative nature of the work done. The results of this research can be very helpful for policy makers, academics, and professionals who want to understand new trends in the field.