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In recent years, supply chain research has grown at a tremendous pace. Many review papers use systematic literature reviews to describe longer-term trends and perspectives. However, many of these studies analyze a limited number of documents, which does not always guarantee representativeness of results. This paper presents a smart bibliometric literature review of supply chain research. The objectives are: (i) to identify supply chain research interest and research impact across subject areas; (ii) to capture trends of supply chain research in the last four decades; (iii) to identify research domains related to supply chain and development of these research domains over time; (iv) to explore the impact of COVID-19 on areas of supply chain research. Authors process 116,759 documents related to supply chain research, published between 1969 and 2021, retrieved from the Scopus database. After providing statistics regarding research interest and research impact, they use a corpus of abstracts to perform topic modeling. Using Latent Dirichlet Allocation (LDA) with Gibbs sampling, 13 research domains related to supply chain research are identified: Ecology; Food supply chain; IT support of supply chain; Retail-oriented supply chain; Risk and disruptive aspects of supply chain; Performance management; Value management and social aspect; Production; Sustainability & development; Models & optimization; Effective inventory management; Supply chain management systems; Supplier and logistic analytics. We also present the individual areas of supply chain research during COVID-19 pandemic. Introduction Supply chain management is becoming a priority issue and an impulse for the organization's development (Croom et al., 2000). The most important is the shift from considering the enterprise as an independent functioning entity to a more interconnected entity (Min and Mentzer, 2004). Enterprise management includes the triad: supply - production - distribution as a coherent area of management called the supply chain, which can be considered a basic module in management theory (Hitt, 2011). The supply chain is crucial for the proper functioning of businesses (Sukati et al., 2012). Today, more than ever, networks of connections are aimed at implementing innovative solutions, economizing resources, reducing costs, improving customer service, and improving the competitive position (Storey et al., 2006). The supply chain concept is widely disseminated and implemented in all business sectors (Zimon et al., 2019), for example, in the safety management standards in food supply chains or risk management (Zimon and Madzík, 2020, Dellana et al., 2020). The interest from researchers is evidenced by the significant number of publications and many recognized journals dealing with this subject (Seuring and Müller, 2008). It is influenced by increasing factors, external conditions, and the growing importance of meeting customer requirements (Mardani et al., 2020). They are subject to digitization processes, influenced by the continuous development of technologies and information systems (Seuring and Gold, 2012). Supply chain research has brought new concepts and cognitive results. Articles focusing on supply chain research are often published in the most prestigious scientific journals, and their research impact is significant (Ho et al., 2015, Seuring and Müller, 2008; Fahimnia et al., 2015; Chen et al., 2017). This research has enriched and updated existing knowledge and set new research directions (Roy et al., 2018). However, it is difficult to predict how the supply chains will change in 10 or 20 years (Melo and Saldanha-da-Gama, 2009). Therefore, it seems essential to carry out a comprehensive review of the literature, which will systematize knowledge in this field and indicate possible directions and trends of the evolution of supply chain research. The first signs of a systematic examination of the supply chain appeared in the early 1980s (Behling, 1982). However, a strong increase in the number of scientific articles on the subject was not seen until twenty years later and has been growing until now. Many studies in the past focused on defining the supply chain (Stock and Boyer, 2009, Mentzer, 2001, Gibson et al., 2005), its evolution over time (Marinagi et al., 2014), and other possible perspectives (Tang, 2006, Dainty et al., 2001, Ambrose et al., 2010). There are several approaches to conducting a literature review. The most common approaches are systematic literature reviews and bibliometric reviews. The systematic literature review is de facto a standard in performing literature reviews. This approach is concerned with organizing a topic's state of the art to consolidate individual research efforts in a single document. These types of review papers are often based on processing a selected number of scientific articles dealing with the supply chain. However, as these studies rely on in-depth analysis, the scope of processing the number of documents is limited. On the other hand, bibliometric analysis works with many more papers to understand research domains and patterns. The current research opportunity is to enrich standard bibliometric review with other insightful information. A strong trend exists for using machine learning approaches in bibliometric literature reviews (Asmussen and Møller, 2019). Some authors even point out that manual exploratory literature reviews should be a thing of the past, and the role of machine learning literature reviews will grow (Asmussen and Møller, 2019). There are over a dozen valuable papers in which a literature review or bibliometric review was undertaken on various aspects of supply chain management and indicated possible directions of evolution and development. The following sections describe the most important of them. One of the first review studies on the supply chain was published at the end of the 90s. Cooper et al. (1997) published a review study focusing on the role of supply chain management in logistics. They noted that far-reaching changes are observed in the business management approach. Meixell and Gargeya (2005) indicated the need to develop models that show the problems of designing global supply chains practically. On the other hand, Tang (2006), based on a review of several dozen articles in the area of risk management in the supply chain (SCRM), formulated several recommendations for future research in SCM. He particularly pointed to the need to address future research issues, such as the impact of information technology and government policies on SCM. The SCRM issue was also researched by Ho et al. (2015), who reviewed 224 articles. The authors suggested that future researchers should focus primarily on case studies rather than theoretical considerations. Seuring and Müller (2008), based on a review of 192 articles in the sustainable supply chain (SSCM) area, distinguished two distinct strategies: supplier management for risks and performance and supply chain management for sustainable products. By contrast, Srivastava (2007) suggested that much research is needed to support the evolution of business practices toward greening along the entire supply chain. Effective approaches for data-sharing across the supply chain need to be developed. In the paper published by Carter and Rogers (2008) authors organized the basic concepts of SSCM. They proposed a framework for the perception of SSCM as the starting point for the common perception of this concept by various interconnections that co-create the supply chain. Gold et al. (2010) focused on studying the impact of SSCM to improve the competitive position by tightening cooperation on environmental and social issues. They stress that implementing a typical supply chain strategy is a priority while claiming that at this point, further conceptual integration of resource-oriented strategic management, SCM, and SSCM with social network theory and organizational theory seems essential. Sarkis et al. (2011) indicated a need for research on methodological developments and applications to the supply chain. In turn, Carter and Easton (2011), based on a review of articles from 20 years, noticed that the authors undertook more and more ambitious research. Still, there was a research gap in the form of a lack of papers that used conceptual theory building as a methodology to develop or expand theoretical insights. Another aspect of SCM was discussed by Govindan et al. (2015), who focused their research on reverse logistics and closed-loop supply chains. After analyzing 382 articles, they observe that much of the literature on the applications and uses of theory in GSCM research has been relatively recent. They state that there are many new directions and connections between GSCM and organization theory. De Oliveira et al. (2018) indicated insufficient research on social issues in SSCM. This thesis was confirmed by Roy et al. (2018), who analyzed 419 articles on SSCM. They proposed 13 broad themes and 34 sub-themes for further research directions. Sharma et al. (2020) conducted a systematic literature review (160 articles) to integrate lean, agile, resilient, green, and sustainable (LARGS) paradigms in the supply chain. Based on the literature review, they suggested a dozen or so future research directions. Khan et al. (2021) reviewed 362 articles covering SSCM. The research concluded that the articles published so far did not comprehensively cover the SSCM issue and focused mainly on the example of countries from highly developed economies. They also stated that future research should focus on the social aspects of sustainable development and the management of service supply chains. The suggested research gap was partially filled by an article by Nagariya et al. (2021). They reviewed 174 articles dealing with the issues of Sustainable Service Supply Chain Management (SSSCM). They proposed three future research directions: customer's perception, involvement, behavior towards sustainability in SOSC context, trade-off, incentive mechanism, and multilevel evaluation for achieving sustainability in the SOSC from various points of view. Nilsson and Göransson (2021), based on a review of 180 articles covering the issue of innovation in SCM, suggested the need for further research and modeling in the studied area. From the above brief overview, we conclude that systematic literature reviews supply chain research are usually carried out on a specific aspect or component of the supply chain. Such studies thus provide a deep insight into a narrowly defined issue. Studies of the bibliometric review type, whose popularity has grown in recent years, offer a more generic view of the broader issue. The analytical possibilities brought by information technology increased the implementation of bibliometric review studies (Zupic and Čater, 2015). Bibliometric studies aim to analyze a much larger number of studies and thus provide a more general overview of the state of science in the selected field. This also applies to the supply chain research area, where increased bibliometric review articles can also be observed. While in 2013, only two bibliometric reviews on the supply chain were published, in 2021, there were already 31, and in September 2022, up to 41. Bibliometric studies within the supply chain also, in this case, focused on various subfields such as green supply chain (Fahimnia et al., 2015), supply chain finance (Xu et al., 2020), digitalization in the supply chain (Muñoz-Villamizar et al., 2019), agri-food supply chain (Hisjam and Sutopo; 2017), big data in supply chain management (Mishra et al., 2018), supply chain in healthcare (Maheshwari et al., 2020), sustainability (Nimsai et al., 2020), supply chain 4.0 risk management (Zekhnini et al., 2021) or vaccines supply chain management (Santos and Martins; 2021). Although these studies processed a relatively large number of papers, their focus did not cover the entire supply chain research but only some of its aspects. However, some bibliometric studies also tried covering the entire supply chain research field. Several have been published in recent years, while some have worked with a relatively large number of analyzed documents. For example, Tsai and Chi (2011) analyzed 2,558 papers, Hu et al. (2013) analyzed up to 52,680 papers, the study by Kumar and Kushwaha (2015) included the analysis of 458 papers, Oliveira et al. (2018) developed a study based on a review of 23,584 papers, Wen et al. (2020) published the results of the analysis of 4,687 papers, Amirbagheri et al. (2020) published study with 35,497 papers analyzed, Benedetto (2020) analyzed 9525 papers and Hariharasudan et al. (2021) analyzed 1,454. The focus of these studies was more general and oriented to catching current trends in supply chain research. There are quite a lot of articles that try to capture current trends in individual aspects of supply chain research. The above overview of these studies can be displayed graphically - Fig. 1. The figure shows an overview of studies focused on supply chain research from 1995 to 2021. The size of the bubbles represents the number of analyzed documents. The study's authors and the number of analyzed documents are indicated for each bubble. The number of published studies retrieved from the Scopus database up to the given year is marked in gray. The systematic literature review studies are marked in blue color. Bibliometric studies focused on specific aspects of the supply chain (not the entire supply chain area) are marked in orange. Bibliometric studies focused on the entire supply chain area are marked in green. Several findings can be made based on the image. Systematic literature review studies (blue color bubbles) work with a limited amount of documents. The growth of bibliometric studies that analyze many papers has been significant in recent years. While studies focused on an individual aspect of the supply chain (orange color) usually process up to 2000 papers, bibliometric studies covering the entire supply chain research can reach several thousands of analyzed papers. The more papers the bibliometric study analyzes, the higher the probability that the results will be representative. Only a few bibliometric studies analyze several thousand documents - we briefly characterize the three most extensive studies. Armibagheri, Merigó, and Yang (2019) published a study to understand the trends among the countries over three decades. Although this study processed many documents (20,616), it is relatively brief and mainly contains the number of published papers in the given countries and the bibliometric coupling of countries. Another study is by Benedetto (2018), in which the author analyzed 9,525 papers. In addition to standard bibliometric information such as the most frequented journals, number of articles in years, and authors, this study was one of the first to identify topics related to supply chain research. Six major clusters or streams of research have been identified: Green Supply Chain, SCM Practice, SCRM, Information Sharing, Dyadic Relationship, and Analytical Models. The third study was developed by Wen et al. (2020), in which the authors analyzed 4,687 papers related to supplier management. Wen's study offers an overview of the so-called “hot research themes”, which were identified based on keywords and co-occurrence analysis. The systematic literature reviews and bibliometric reviews analyzed above differ mainly in two fundamental aspects. While systematic literature reviews are narrowly oriented and go relatively in-depth into the investigated issue, bibliometric reviews are generally broader, and their goal is to understand research domains and patterns. Considering the current possibilities offered by bibliometric databases, in combination with the rapid development of machine learning algorithms, there is a considerable potential for the implementation of the so-called “smart literature review”, which currently represents a new trend in working with big data research (Asmussen and Møller, 2019). It is a type of bibliometric analysis complemented by using text mining procedures to identify latent topics or research domains. According to some sources (Ozansoy Çadlrcl, 2022, Talafidaryani, 2021), the implementation of this type of analysis is a relatively effective way to identify not only the research domain (bibliometric review) but also the state of the art of a given topic or field (systematic literature review). We can see a massive increase in interest in the supply chain in Scopus. Approximately as many articles have been published in the last six years (2015–2021) as in the previous 35 years (1979–2014). The growing interest in supply chain research makes the need for systematic and comprehensive capture of current trends critical. As the number of articles focused on the supply chain has constantly been growing, it is practically impossible to process them into one review paper in the usual way. However, machine learning methods can represent robust research potential combined with bibliometric and citation databases data. As seen in Fig. 1, we can see that no bibliometric study has examined more than a quarter of all available studies. Our study aims to implement a smart bibliometric literature review from all available documents related to the issue of supply chain research. In addition to standard bibliometric analyses, we use a novel machine learning approach to identify latent topics (named “research domains”) in the whole area of supply chain research. The reason for deploying this approach is to use the huge potential of text data in bibliometric databases using algorithms based on machine learning. This study aims to obtain answers to the following four research questions, which have so far only been partially or not elaborated: ● RQ1: What is the distribution of research interest and research impact of supply chain theme in particular subject areas? ● Supply chain research is becoming a multidisciplinary field, the application of which can be seen in various subject areas. This research question will allow a better understanding of the position of the supply chain and the scientific interest in this topic in individual subject areas. ● RQ2: What are the trends of supply chain research in the last four decades? ● Due to the dynamics of the company's development and globalization, the role of the supply chain in the world is changing. The aim is to examine how the role and applications of the supply chain have changed over time. ● RQ3: What are the research domains related to supply chain research, and what is their development over time? ● Bibliometric data hides a great informational value, which has been hidden until now and has not been the subject of extensive research. Extracting topics through a machine learning text mining approach can reveal a lot of insightful information. ● RQ4: Which areas of supply chain research have been affected by the Covid-19 pandemic the most? ● Covid-19 has had a significant impact on the supply chain all over the world. We tried to examine which areas of supply chain research have seen the greatest research interest. By focusing on these research questions, we will be able to update previous results of review studies related to the supply chain and offer a comprehensive picture of their evolution. In addition, a bibliometric analysis capturing such a large amount of data, which would additionally use a machine learning approach to identify latent topics in supply chain research, has never been published until now. Our study focuses on presenting metadata processing results from more than 116,000 documents. We combine standard bibliometric literature review with a machine learning textmining approach to: (i) identify supply chain research interest and research impact across subject areas; (ii) to capture trends of supply chain research in the last four decades; (iii) to identify research domains related to supply chain and development of these research domains over time; (iv) to explore the impact of COVID-19 on areas of supply chain research. Section snippets Data We used data from the Scopus database to answer the research questions. Scopus is one of the two most respected scientific databases. The database indexes more than one million records of 76 and 39,000 serial titles. Every year, three million documents are added to the database (Baas et al., 2020). The basis for our analysis was formed by all records indexed in the Scopus database on November, 24, 2021, i.e. 116,759 records. We did not explicitly limit our search to any specific language or type Results Data were collected on November, 24, 2021. The “supply chain” query entered for document search returned us a total of 116,759 results, which fall under the period 1969 to 2022. The most significant part of these papers was represented by articles (58.8%), conference papers (27.3%), reviews (5.0%), book chapters (4.8%), and other types (4.1%). At the time of data collection, 1,886,837 citations were registered on these papers. The number of articles and the number of citations were the basis Summary of main findings In this study, we present the results of processing a large number of scientific documents related to supply chain research. In this section, main highlights are summarized. RQ1: What is the distribution of research interest and research impact of supply chain theme in particular subject areas? Main findings: ● The most represented areas of research interest in supply chain research include BUSI (19.5%), ENGI (18.7%), DECI (12.0%), COMP (11.3%), SOCI (5.4%), and ENVI (5.0%) - which include almost Research implications The results presented in this study offer several implications of both theoretical and practical nature. Despite decades of research, BUSI subject area is still one of the top domains in supply chain research. In BUSI, aspects of the supply chain relate primarily to the organization and managerial use of information for the organization's smooth running. The role of management is still an essential domain for supply chain efficiency, as evidenced by the sharp increase in research in the BUSI Research limitations and future research In our research, it is possible to identify several research limitations that need to be considered when presenting research questions RQ1 to RQ4. Several research limitations apply to the dataset which we worked with. We created the dataset using the Scopus database. However, it is clear that although the Scopus database indexes a huge number of articles, it does not index all articles related to supply chain issues. This could have a partial effect on representativeness. However, as the Conclusion Review studies with different scopes focus on capturing main scientific directions related to supply chain research. Although many of them refer to the most renowned studies, it has been almost impossible to capture the overall development of tens of thousands of individual studies. Our study processed abstracts of more than 116,000 scientific papers related to supply chain research. Our goal was to capture research impact and research interest, development, and main RDs related to supply chain Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. References (112) A. Cappelli et al. Will the COVID-19 pandemic make us reconsider the relevance of short food supply chains and local productions? Trends in Food Science and Technology (2020) S. Croom et al. Supply chain management: An analytical framework for critical literature review European Journal of Purchasing and Supply Management (2000) U.R. de Oliveira et al. A systematic literature review on green supply chain management: Research implications and future perspectives Journal of Cleaner Production (2018) B. Fahimnia et al. 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Research article Joint location optimization of charging stations and segments in the space-time-electricity network: An augmented Lagrangian relaxation and ADMM-based decomposition scheme Computers & Industrial Engineering, Volume 183, 2023, Article 109517 Show abstract Electric vehicles that contribute to better air quality, less noise, and low-carbon emissions are a promising selection for sustainable transportation. However, the development of electric vehicles is impeded by various factors, including driving range anxiety, long recharging period, and insufficient charging facilities. As the charging-while-driving techniques gradually mature, electric vehicles can recharge on charging stations stationarily or charging lanes (segments) dynamically. Additional charging facilities should be constructed to improve the level of charging services. Under a predefined construction budget, the difficulty is how to determine their numbers and distributions. This study jointly locates charging stations and segments by maximizing the accessibility of electric vehicles. In space-time-electricity networks, we formulate a multi-commodity network flow model with location and routing. A decomposition scheme based on augmented Lagrangian relaxation and alternating direction method of multipliers is developed to tackle this problem. The standard and augmented Lagrangian relaxed problems are decomposed into many solvable subproblems. Numerical experiments are conducted in three transportation networks, showing that the proposed method can achieve good integrality gaps. View full text © 2023 Elsevier Ltd. All rights reserved. About ScienceDirect Remote access Shopping cart Advertise Contact and support Terms and conditions Privacy policy We use cookies to help provide and enhance our service and tailor content and ads. By continuing you agree to the use of cookies . Copyright © 2023 Elsevier B.V. or its licensors or contributors. 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