# Agile and Digital Transformation in Manufacturing: A Bibliometric Review, Current Research Trends and Future Avenue

Milena Savkovic, Danijela Ciric Lalic, Bojan Lalic, Maja Miloradov, Jelena Curcic, Nenad Simeunovic

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Milena Savkovic, Danijela Ciric Lalic, Bojan Lalic, Maja Miloradov, Jelena Curcic, et al. Agile and Digital Transformation in Manufacturing: A Bibliometric Review, Current Research Trends and Future Avenue. IFIP International Conference on Advances in Production Management Systems (APMS), Sep 2022, Gyeongju, South Korea. pp.380-388, 10.1007/978-3-031-16407-1_45. hal-05386103

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# Agile and Digital Transformation
in Manufacturing: A Bibliometric Review,
Current Research Trends and Future Avenue

Milena Savkovic✉, Danijela Ciric Lalic✉, Bojan Lalic✉, Maja Miloradov✉, Jelena Curcic✉, and Nenad Simeunovic✉

Faculty of Technical Sciences, University of Novi Sad, 21000 Novi Sad, Serbia
milena.savkovic@uns.ac.rs

**Abstract.** Digital transformation has become commonplace in the manufacturing industry, forcing companies to abide by the “laws” established by Industry 4.0. The term adaptability could relate to agility, which brings us to the link between agile manufacturing and digital transformation. This posed a question: do these two concepts affect each other’s success and implementation? Likewise, does their relationship affect other factors in the manufacturing industry? This article aims to study the connection between agility and digital transformation in manufacturing. Based on the relationship between these two concepts, the authors tented to map current research and establish new research avenues through bibliometric analysis of all articles indexed in Scopus’s bibliographic database. We identified the most relevant and productive authors, countries, and institutions researching the relation between agile and digital transformation in manufacturing. Trend analysis and thematic evaluation were performed to indicate respect for the research terms and their effect on other topics.

**Keywords:** Agility · Manufacturing · Digital transformation · Industry 4.0 · Bibliometric analysis

## 1 Introduction

The fourth industrial revolution can be seen in the digital transformation in all industries and the consumer market [1]. Today’s manufacturing firms are forced into agility and digital business transformation to maintain market success and operate sustainably [1, 2].

A dynamic and uncertain business environment provokes manufacturing companies to be agile and thrives in digital transformation simultaneously. Agile manufacturing, the 21st-century manufacturing paradigm [3], could be explained as a methodology that fosters high-quality products and provides high value to the customer at its core. Some authors claim that agile manufacturing support socially and environmentally responsible business and responds to uncertainty and change [3–8]. The all-encompassing way agile
manufacturing could be defined in a strategic context is a “business-wide mindset that emphasizes routinely flexible structures and infrastructures” [9].

Some of the topics of the APMS 2022 conference are “Industrial Digital Transformation”, “Sustainable Production Management”, “Smart Manufacturing & Industry 4.0”, “AI & Data-driven Production Management”, etc. All topics can be linked to Industry 4.0. And the struggle of companies to adapt to new paradigms. The key topics this conference has been covering in the last few years (e.g. Industry 4.0, Lean manufacturing, Flexibility, Sustainability, Smart manufacturing, etc. [10]) indicate that the APMS is one of the research drivers in digital and agile manufacturing.

This article aims to study the scientific production around digital transformation and agility in manufacturing through bibliographic data analysis of all articles indexed in Scopus, containing the terms “agile/agile methods/agile methodology/agile manufacturing”, “manufacturing” and “digital transformation/digitalization/digitization” in all article title, abstract and keywords. Scopus is the largest, multidisciplinary database consisting of peer-reviewed scientific content. Based on the relationship between these two concepts, the authors tented to map current research and establish new research avenues through bibliometric analysis of all articles indexed in Scopus’s bibliographic database. The bibliometric study was conducted using the “bibliometrics” R Package. VOSviewer software was used for graphical analysis and representation of the bibliographic data. We contribute to manufacturing literature by evaluating the publication of digital transformation and agile in this field to comprehend research trends through bibliometric analysis.

This article is organized into four chapters. The introductory part defined the problem, need and aim of the paper. The methodology then explains how the research was conducted and why we use the bibliometric R tool. The third section presents the key research findings and a brief discussion. Finally, the paper is summarized in conclusion, and directions for future research are also suggested.

For this research, we consider the following questions to be answered to help identify the dynamics of manufacturing literature and provide future research avenues in the era of digital and agile industrial enterprise challenges. The authors proposed research questions as follows:

1. What is the evolutionary path of scientific documents on agile and digital manufacturing to date?

2. What are the most productive countries, authors and affiliations in this field?

3. Exploring the link between agile and digital in the manufacturing industry, what are the main trends and key themes?

## 2 Research Methodology

This article proceeds with standard “bibliometric workflow”, suggested by Zupic and Čater [11, 12]. The first step is (1) a *Scheme of study* where we defined research questions and identified tools and techniques for accessing bibliometric analysis. This step is described in the introductory section. Then we performed the second step – (2) *Data collection*, which included source selection, filter and export data. In order to determine the research trend in this area of publications, the dataset was obtained from
the Scopus database, which is widely used in bibliometric studies [13]. The data were downloaded from the Scopus core collection for the period 2006–2022 using the following search query: (TITLE-ABS-KEY(agile) OR TITLE-ABS-KEY("agile manufacturing") OR TITLE-ABS-KEY("agile methods") OR TITLE-ABS-KEY("agile methodology") AND TITLE-ABS-KEY(manufacturing) AND TITLE-ABS-KEY("digital transformation") OR TITLE-ABS-KEY(digitalization) OR TITLE-ABS-KEY(digitization)) AND (LIMIT-TO(DOCTYPE,"cp") OR LIMIT-TO(DOCTYPE,"ar")) AND (LIMIT-TO(LANGUAGE,"English")). A filter was used to find documents containing any search terms in the title, abstract, and keyword. The search was restricted to English-language articles. Document types observed were only conference proceedings and articles. (3) *Bibliometric analysis* was the third step, including software selection and analysis. The bibliometric analysis was conducted using the “bibliometrix” R Package tool. This analysis enables scientists to get an overview in one place, identify gaps in knowledge, extract new research ideas and set out their intended contribution to the field [14]. Firstly, annual scientific production, the most productive countries, authors and relevant affiliations were analyzed. After that, we performed trend analysis and thematic evaluation. (4) *Visualization* was the fourth step, which refers to selecting tools and techniques for appropriate visualization [15]. VOSviewer software was used for the graphical analysis of the bibliographic data [16]. Finally, the fifth step – (5) *Interpretation*, refers to the explanation of findings.

# 3 Results and Discussion of Findings

## 3.1 The Main Information About the Database

The final sample consisted of 154 documents published in 107 sources (44 articles and 110 conference papers) during the timespan 2006:2022. These documents were (co)authored by 447 people, out of which there were only ten single-authored documents and 467 multi-authored documents, with the average number of authors per document at 3.1. Records are concentrated around main research areas: engineering, computer science, business, management and accounting and decision sciences. Scopus assigns indexed articles to one or more research areas.

Figure 1 shows the annual production, and Fig. 2 shows the average citation per year for a relation between the terms agile, agile methodology/methods, agile manufacturing and at the other hand digital transformation, digitalization and digitization, observed in the manufacturing sector. Figure 1 clearly emphasizes increased literature production over time, especially in 2018, with 26 documents per year. Only 20 papers were published in the first 11 years in the observed time frame, increasing the number of published works already in 2017. The year 2018 can be considered the first relevant year for the scientific community because more papers were published than in the previous 11. However, after 2018, the number of published documents was constant and, then again, in 2021 – an increasing trend in the publication. Figure 2 indicates a significant increase in the annual citation rate of publications linking agile and digital transformation topics in the manufacturing domain from 2016 to 2021. The first significant growth in average citations is observed in 2016 and the second in 2021. The decline in average citations can be seen in 2019 and a substantial increase in 2020. These results may be related to
the beginning COVID 19 pandemic and thus the growing need for digital and flexible ways of doing business.

The trend line is shown in red on both charts, pointing to a specific pattern that can be seen from the behavioral observation of the set of data. From 2016 to 2021, there is a steady increase in the average citation of documents per year. From 2006 to 2015, citations did not exceed 0.5%, considered a weak scientific contribution in this area. Also, most of the papers were published from 2017 until the end of the observed period.

<figure><img src="image_3.png" /><figcaption>Fig. 1. Annual scientific production</figcaption></figure>

<figure><img src="image_4.png" /><figcaption>Fig. 2. Average articles citation per year</figcaption></figure>

## 3.2 Most Productive Countries, Authors and Affiliations

This section provides information regarding core countries, authors and relevant affiliations of manufacturing literature in the field of digital and agile. Table 1 shows the
top ten most productive countries, observing the total citations (TC) and frequency (F) over a time span. Country productivity was measured by two indicators - total citation of each country and distribution of publication frequencies according to country. The most productive countries, by total citation, were Sweden, followed by New Zealand, Norway, Portugal, Turkey, etc. Germany was in the first place, perceived by country frequency in the scientific world, followed by Norway, the United States, the United Kingdom, France, etc. According to both observed indicators, countries that appear in the top ten were Sweden, Germany, Norway, and China. It can be seen from the table that Germany (TC = 44, F = 78) was in a high position on both lists, which makes this country the most productive in this research field. The following most productive country was Norway (TC = 38, F = 22).

<table><caption>**Table 1.** Top ten most productive countries</caption><thead><tr><td>Country and Regions</td><td>Total Citations</td><td>Country and Regions</td><td>Frequency</td></tr></thead><tbody><tr><td>Sweden</td><td>95</td><td>Germany</td><td>78</td></tr><tr><td>New Zealand</td><td>59</td><td>Norway</td><td>22</td></tr><tr><td>Germany</td><td>44</td><td>USA</td><td>21</td></tr><tr><td>Norway</td><td>38</td><td>UK</td><td>14</td></tr><tr><td>Portugal</td><td>35</td><td>France</td><td>12</td></tr><tr><td>Turkey</td><td>23</td><td>Italy</td><td>12</td></tr><tr><td>China</td><td>12</td><td>Finland</td><td>11</td></tr><tr><td>Morocco</td><td>11</td><td>Switzerland</td><td>11</td></tr><tr><td>Malaysia</td><td>9</td><td>China</td><td>9</td></tr><tr><td>Romania</td><td>7</td><td>Sweden</td><td>7</td></tr></tbody></table>

Table 2 shows the ten most productive authors. The indicators that influenced the ranking were the number of published documents due to the observed period and the local impact measured by the h-index. From the list of authors, we can conclude that six authors come from Germany, and the other countries mentioned were Sweden, Norway, USA and Mexico. These facts confirmed that Germany contributed to the development of science in the domain observed in this paper. The local impact by h-index shows the scientific productivity of the authors based on the number of published research papers and their citations in the observed database of documents in this research. An author who stands out from others on this list was Vinit Parida from Luleå University of Technology, Sweden. His research interests were innovation, manufacturing, digitalization, entrepreneurship, high tech, sustainable industry, etc.

The top ten most relevant affiliations were shown in Table 3, according to the number of documents published during the timespan. The most pertinent affiliation was Reutlin-gen University with seven published documents from 2006 - to 2022 in the field of agile and digital manufacturing, one of Germany's leading universities offering international
<table><caption>**Table 2.** Top ten most productive authors</caption><thead><tr><td>Authors</td><td>Authors Country</td><td>Local Impact by h-index</td><td>Number of Documents</td></tr></thead><tbody><tr><td>V. Parida</td><td>Sweden</td><td>4</td><td>4</td></tr><tr><td>D. J. Powell</td><td>Norway</td><td>2</td><td>4</td></tr><tr><td>A. Zimmermann</td><td>Germany</td><td>3</td><td>4</td></tr><tr><td>J. Bogner</td><td>Germany</td><td>3</td><td>3</td></tr><tr><td>S. Bondar</td><td>Germany</td><td>2</td><td>3</td></tr><tr><td>J. C. Hsu</td><td>USA</td><td>2</td><td>3</td></tr><tr><td>D. Jugel</td><td>Germany</td><td>3</td><td>3</td></tr><tr><td>M. Möhring</td><td>Germany</td><td>3</td><td>3</td></tr><tr><td>A. Pfouga</td><td>Germany</td><td>2</td><td>3</td></tr><tr><td>D. Romero</td><td>Mexico</td><td>2</td><td>3</td></tr></tbody></table>

academic programs with close ties to industry and commerce. Besides Reutlingen University, this list included three more affiliates recognized as important in the scientific community. Affiliates from Norway, Sweden and the United States are in the most relevant affiliation, which confirms they are one of the leading countries researching this topic.

<table><caption>**Table 3.** Top ten most relevant affiliation</caption><thead><tr><td>Affiliations</td><td>Country</td><td>Number of Documents</td></tr></thead><tbody><tr><td>Reutlingen University</td><td>Germany</td><td>7</td></tr><tr><td>Norwegian University of Science and Technology</td><td>Norway</td><td>5</td></tr><tr><td>Aalen University</td><td>Germany</td><td>3</td></tr><tr><td>California State University</td><td>USA</td><td>3</td></tr><tr><td>Luleå University of Technology</td><td>Sweden</td><td>3</td></tr><tr><td>RWTH Aachen University</td><td>Germany</td><td>3</td></tr><tr><td>University of Rostock</td><td>Germany</td><td>3</td></tr><tr><td>Aalborg Universitet</td><td>Denmark</td><td>2</td></tr><tr><td>Delft University of Technology</td><td>Netherlands</td><td>2</td></tr><tr><td>University of St. Gallen</td><td>Switzerland</td><td>2</td></tr></tbody></table>

It is interesting to mention Denmark, the Netherlands and Switzerland as part of this list, then only Switzerland being on the list of the most productive countries in Table 1 in terms of frequency. None of the authors from these countries were on the list of the most productive authors (Table 2).
All universities shown in Table 3 have a strong connection with the industry, and their relevance in the research field of agile and digital manufacturing industry signified the importance of this topic and the challenges facing manufacturing companies.

## 3.3 Trend Analysis and Thematic Evaluation

This section presents trend analysis and thematic evaluation of the research topic. Trend analysis, shown in Fig. 3, explains the evolution of keyword plus from 2008 to 2022. The observed parameter was keyword plus, which can tell us about the content and scientific concepts presented in the documents in the database. The most frequent terms in the last three years were virtual manufacturing, information system, systems engineering (2018.), agile manufacturing system, digital transformation, automotive industry, software design (2019), internet of things, embedded systems, industry 4.0, digital technologies (2020), agile, manufacturing companies, digitization, lean manufacturing, industrial research (2021).

<figure><img src="image_5.png" /><figcaption>Fig. 3. Trend analysis</figcaption></figure>

Figure 4 presents the historical development of agile and digital manufacturing literature. Thematic evolution depicts the history of themes and how these themes evolved, using the authors keywords. The first segment is from 2006–2020 and the second is from 2021–2022. Themes have evolved with time. Today, the concepts of agility and manufacturing are mentioned in the context of digitalization, which can be seen from the figure.
<figure><img src="image_6.png" /><figcaption>Fig. 4. Thematic evaluation</figcaption></figure>

## 4 Conclusions and Further Research

To remain in a dynamic market and stay concurrent, companies are adopting agile and adaptive management methods and changing existing business models, i.e., operating more agile and digitally. This paper presents the scientific production of manufacturing literature about agile and digital transformation using bibliometric analysis. The research covers annual scientific production and citation per year to point out the topic's relevance, the most productive countries, authors and affiliations researching agile and digital manufacturing areas, and trend analysis and evolution of themes to show the current topics and future direction. The results of this research provide the directions for future research in sustainable and competitive manufacturing. This research is limited to analyzing only the Scopus database. Further works can be developed by analyzing databases such as Web of Science, Science Direct, among others.

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