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Market competition has gradually shifted from enterprises to their supply chains in the context of globalization (Christopher, 2000). Hence, supply chain management (SCM) can play a significant role in determining a company's competitive advantage, to a certain extent. With the development of a new generation of information technologies such as Radio Frequency Identification (RFID), the Internet of Things (IoT), cloud computing, blockchain, 3D-printing, and so on, traditional supply chain efforts would not be enough to meet the industry requirements of today (Wu et al., 2006). Thus, the utilization of information technologies into SCM has gained significant attention over last two decades (Subramani, 2004). In addition, the concept of Digital Supply Chain Management (DSCM) has been proposed in both industry and academic SCM research areas (Agrawal & Narain, 2018; Butner, 2010; Büyüközkan & Göçer, 2018; Garay-Rondero et al., 2019; Liu et al., 2023).
There has been a notable increase in the number of studies pertaining to DSCM in recent years. Some of this literature has conducted various overviews for the development process of SCM to DSCM (Agrawal & Narain, 2018; Iddris, 2018). Furthermore, others have concentrated on certain niche areas such as digital supply chain dynamic capabilities, which illustrates the changes of capability in digital transformation context (Queiroz et al., 2019), firm performance evaluation under the influence of digital transformation (Aimulhim, 2021), data-driven innovation in DSCM (Nica, 2019), security and trust problem in DSCM (Zhang et al., 2019), digital supply chain finance (Banerjee, 2021), and DSCM resilience and agility during the COVID-19 period (Ivano, 2021). It should be emphasized that the global supply chain suffered a serious breakdown at the beginning of the pandemic, identifying the importance of supply chain resilience. Experts in both the academic and industrial arenas are seeking ways to improve the stability of the supply chain through digital solutions (Wang, Xue, et al., 2023). The studies have illustrated deep insight into the relevance of the supply chain field. However, there is a lack of comprehensive analysis by using bibliometric tools which could provide a deeper understanding of DSCM. Bibliometric analysis refers to using mathematical and statistical methods to quantitatively identify and analyze an emerging research area (Martinez-Lopez et al., 2018). It is a comprehensive knowledge system which integrates mathematics, statistics, and quantification. It could identify researcher, affiliation, and keywords statistics. In addition, it can also conduct network analysis such as citation, co-citation, and cluster analysis, which help to explore significant research areas and major specialties with DSCM (Chen, 2017).
The rest of this paper is organized as follows. The second section illustrates the concept of DSCM and reviews related literature. The third section introduces the methodology used in this research, defines search terms, and refines literature scope. The fourth section makes a general analysis of author, affiliation, and keyword. A deep observation is conducted by CiteSpace and Hiscite tools to analyze citation, PageRank, and co-citation statistics. The fifth section explains analysis results, investigates research limitations, and proposes some directions for future studies.