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Review

What Have We Learned? A Bibliometric Review of a Three-Decade Investigation into the Supply Chain Uncertainty and a Revised Framework to Cope with the Challenges

by
Asma-Qamaliah Abdul-Hamid
1,2,
Lokhman Hakim Osman
1,
Ahmad Raflis Che Omar
1,
Mara Ridhuan Che Abdul Rahman
1,2,* and
Mohd Helmi Ali
2,*
1
Faculty of Economics and Management, Universiti Kebangsaan Malaysia, Bandar Baru Bangi 43000, Malaysia
2
UKM-Graduate School of Business, Universiti Kebangsaan Malaysia, Bandar Baru Bangi 43000, Malaysia
*
Authors to whom correspondence should be addressed.
Sustainability 2023, 15(22), 15911; https://doi.org/10.3390/su152215911
Submission received: 2 June 2023 / Revised: 11 September 2023 / Accepted: 12 September 2023 / Published: 14 November 2023
(This article belongs to the Section Sustainable Management)
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Abstract

:
Three decades ago, supply chain uncertainty was recognized as a significant conceptual problem that must be resolved to successfully satisfy supply and demand activities. For this reason, firms have developed several workable approaches and techniques (including lean, agility, and resilient framework) in response to the need to maintain such activities in the face of uncertainty. Despite this, the current pandemic’s onset has hampered supply chain management, indicating that current solutions fall short of being sufficient to shield firms from being impacted. Therefore, it raises the question of what we have learned from decades of research and studies to prepare us for such adversities. And what plans must the firms have put in place to address this disaster? To focus on this, the current study intends to explore supply chain uncertainty trends and patterns, to emphasize the future orientation. Using the PRISMA 2020 (Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020) protocol, 884 peer-reviewed journal articles were selected from the Web of Science database and analyzed using bibliometric analysis through MS Excel and VOSviewer software (version 1.6.18). There are two ways the results are presented. First, performance analysis revealed that 2335 writers had written 884 publications (1993–2022), which had an average 32.2 citation level across 176 journals. Second, the science mapping analysis included well-known methods, such as citation analysis, co-citation analysis, bibliographic coupling, co-word analysis, and co-authorship analysis. The original contribution of this study lies in the identification of four clusters through the analysis, namely, overall impact of uncertainty, demand uncertainty, challenges uncertainty, and uncertain strategy. This led to recommendations for future research that practitioners could use.

1. Introduction

Climate change, demographic developments, and habitat destruction have all contributed to the world’s rising outbreaks, including severe acute respiratory syndrome (SARS) (2002), H1N1 flu (2009), Middle East respiratory syndrome (MERS) (2012), Ebola virus (2013), and COVID-19 (2019) pandemic, which has wreaked havoc on global supply chains. Not only that, but this pandemic’s economic and social consequences have had a significant impact too [1,2]. Even though supply chain disruptions are typical, the pandemic’s speed, intensity, and scope took businesses off unprepared and exposed the covert limitations of their supply chain management practices [3]. In the literature, over the past few decades, firms have prepared several practical strategies (such as lean, agility, and resilient framework) in response to maintaining supply and demand processes. Nonetheless, regardless of readiness, the emergence of the current pandemic has disrupted the supply chain management process, demonstrating that current strategies are insufficient to protect firms from being affected by these uncertainties. Concerning the uncertainty in the supply chain, it raises the question of what strategy the firms have established to deal with this phenomenon.
Uncertainty in the supply chain is a significant research topic, and many papers in the literature investigate these concepts [4,5,6]. For instance, literature [7] seeks to answer the research question of how environmental uncertainty in a firm’s supply chain affects financial performance. Although there are multiple dimensions to uncertainty, it is typically only thought to have one: the environmental dimension [8]. Albeit to varying degrees, as the supply chain becomes complex, uncertainties are inherent in all economic activities [9]. According to Yang et al. [10], globalization and challenges in the global supply chain have created global uncertainty. Moreover, unpredictable lead times and supplier exchange contributed to supply chain uncertainty and complexity [11]. Likewise, supply chains are vulnerable to supply chain disruption and uncertainties, especially when a crisis occurs [12,13]. In short, chaotic situations that are overlooked or not initially considered may arise, and these unexpected events can cause uncertainty, which can be a source of risk. Considering this perspective, firms have no choice but to close the bridge by suggesting a systemic, strategic supply chain framework for future benefits.
Although many scholars have emphasized the importance of a strategic framework for supply chain systems, existing research has focused on concepts rather than practice [14,15]. Highlighting this issue, Weisz et al. [16] argue that periodic inventory issues like stockout and bullwhip effect are also associated with disruptions. Furthermore, firms are under time constraints during the outbreak to respond to extremely high demand for certain categories of products and services [17]. Unlike in normal circumstances, the pandemic required firms to accelerate their operations and products faster than usual [18]. To this note, supply chain uncertainty refers to the unpredictability and risk factors that can affect the smooth flow of goods, services, and information from suppliers to consumers [15]. Various elements in the supply chain can introduce uncertainty, and these uncertainties can be challenging to predict or manage effectively.
In the case of the agricultural industry, although it is categorized as an essential sector, yet, uncertainty in the system, such as the border closures during the pandemic, has forced immigrant workers to return to their home country, resulting in a labor shortage, particularly during harvesting operations in palm oil [19]. Despite the likelihood that the COVID-19 epidemic is accountable for these losses, a different economic evaluation strategy to consider dynamic circumstances is needed [20]. According to Kusrini and Maswadi [21], sustainable supply chain management is a vital strategy for controlling the operations and activities of the entire supply chain for the palm oil industry during this pandemic.
As the literature heralded, the pandemic crisis has caused substantial disruptions and exposed the weakness of the current supply chain system, which critically forces the need for a revised framework to cope with such disruption in the future. Thus, the main purpose of this study is to investigate the trends of supply chain uncertainty, to highlight the future direction. In detail, the aims are divided into the following specific questions:
RQ1: 
What are the most representative articles, authors, and journals in supply chain uncertainty?
RQ2: 
What organizations, countries, and institutions generate more contributions related to supply chain uncertainty?
RQ3: 
What is the understanding of supply chain uncertainty in the literature, particularly within the main research cluster?
RQ4: 
What are the top strategies and future research lines in supply chain uncertainty?
To realize these research objectives, the PRISMA 2020 (Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020) protocol is employed to narrow down the selected articles [22]. Precisely, 884 peer-reviewed journal articles are included for bibliometric analysis using VOSviewer. In comparison to a conventional literature review, a bibliometric review takes a more comprehensive approach and offers more insightful data. Researchers from a variety of fields have adopted this approach, and it helps academics quickly catch up with the direction of the intensive and original research project [23,24,25]. This approach makes it easy to quantify the breadth and depth of research on a subject, which reduces subjectivity when justifications for the research’s course are needed afterwards. The researcher’s focus and targeting can be made more effective in the future with the help of this knowledge.
The remainder of this study is organized as follows. Section 2 discusses the methodology through the PRISMA 2020 protocol. Next, Section 3 summarizes the findings which include performance analysis and science mapping analysis. Section 4 discusses the literature through four clusters, namely, overall impact of uncertainty, demand uncertainty, challenges uncertainty, and uncertain strategy. In this section, we also provide recommendations for future research. Finally, Section 5 presents the conclusion of the present study.

2. Methodology

This study follows a 27-checklist item and three phases of a flow diagram from PRISMA 2020 (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) protocol to ensure the transparency, robustness, and reliability of the search method (Figure 1) [22,26]. The bibliometric methodology was used in this study to quantify and synthesize bibliographic data extracted from research documents on uncertainty in supply chain management. In summary, a bibliometric approach offers a technique to bring coherence to the huge body of research on uncertainty and its effects on the supply chain that has developed since three decades ago.

2.1. Search Strategies

To retrieve relevant articles that can answer the research question, the Web of Science (WoS) database, which is among the most comprehensive and pertinent databases, is explored [19]. Herein, two sets of related keywords, namely, supply chain [27] AND uncertain*, are employed together with the search protocol processes, which have been narrowed down to (1) peer-reviewed articles—to ensure the credibility of selected articles is high; (2) language: English language as a medium for knowledge transfer—to concentrate on knowledge understanding and consistency; (3) search field—title/abstract/keywords to encompass all the publications containing the selected keywords in any of these fields; and (4) the Clarivate Analytics limited to Social Science Citation Index®®®® [23,28]. To note, the searches were conducted on 10 January 2023. Based on these keywords and criteria, the first step has identified 10,341 articles. To move towards the second screening step, 9415 articles are removed based on title and abstract. Next, 35 articles were excluded from duplicated articles, inaccessible articles, and articles that were not relevant based on WoS categories. A final set of 884 articles has been considered for the analysis.

2.2. Finding Analysis

To discuss the related articles appropriately, bibliometric analysis, which is useful for summarizing findings from a large volume of data, including a bibliography in a statistical pattern, is used. According to Hashemi et al. [25], such a method uses information sourced from published articles in a specific domain and provides insight into the performance of the research constituent. Interestingly, Mukherjee et al. [29] justified that bibliometric analysis also contributes to the theoretical and practical implications in two aspects: (i) performance analysis for the practical value—that emerges in objectively assessing research productivity and impact and (ii) science mapping’s utility and novelty—emerges in the objective discovery of knowledge clusters. Prior literature [24,30] explored the bibliometric analysis to structure the knowledge in the domain using several indicators, such as the leading publications, authors, journals, affiliations, and geographies. Donthu et al. [31] suggested VOSviewer, Gephi, and Leximancer software tools to analyze the indicators pragmatically. For this reason, the current study adopted MS Excel and VOSviewer software (version 1.6.18) to comprehensively scrutinize the performance and sciences mapping for the supply chain and uncertainty crisis domain. To note, current finding analysis in VOSviewer also undergoes the data cleaning process with the aim of creating a thesaurus file, where different variants of keywords are merged. This process is also important for reducing multiple nodes that have the same variant of keywords and strengthening the rigor of analysis [30].

3. Results

The current study conducted a bibliometric analysis of 884 articles, following Donthu et al.’s (2021) [31] methodology including performance and science mapping analyses.

3.1. Performance Analysis

Table 1 summarizes the main findings of the data collection from the WoS library on the theme of uncertainty in the supply chain. The related articles consist of 884 articles, published from 1993 to 2022, written by 2335 authors, and published in 176 journals, with an average citation level per article equal to 32.2. In particular, most of the authors contributed to only one paper, with 10.4% of the 2335 authors contributing to more than one paper, leaving 2091 authors contributing to only one. Likewise, the number of articles has increased at an 82.5% annual rate on average.
Figure 2 depicts the 30-year distribution of the selected articles. Surprisingly, the number of published articles can be categorized into three phases. The articles have never exceeded 10 per year in the first 15 years since the first study was published in 1993 until 2007. In the second phase, between 2008 and 2013, the articles fluctuated in the range of ±30 articles per year. But, the third phase shows a steady increase from 2014 until 2022, where the number of articles increases yearly. The peak year for published articles was 2022, with a 48.6% increase over the previous years. The trend is increasing yearly, with 41.4% of articles published in the last three years, particularly since the COVID-19 pandemic struck the world.
Table 2 lists the top 10 leading journals regarding related articles published. Along with the number of publications, the number of citations obtained from journals on the analyzed topic is displayed. Supply Chain Management—An International Journal (SCM-IJ) published the most articles on the theme of uncertainty in the supply chain (75 articles), followed by the International Journal of Operations and Production Management (IJOPM) and International Journal of Logistics Management (IJLM), both with 57 and 56 articles, respectively. Interestingly, these top three journals were all from Emerald. According to this, SCM-IJ has received the most citations, totaling 3793. Also, IJOPM and IJLM, on the other hand, received 2649 and 2401 citations, respectively. According to Journal Citation Reports, only 60% of the top 10 leading journals are ranked in the management category’s first quartile (Q1) by Journal Impact Factor, with the lowest impact factor of 3 and the highest of 11 impact factors for the reference year 2021.
Table 3 displays the top 10 most productive authors in terms of published articles in the field of uncertainty in the supply chain and the productivity of their H-index and i-10 index. Particularly, the results also show Yu, Kangkang from Renmin University of China (China) as the top author with seven publications, followed by Craighead, Christopher W. from the University of Tennessee (USA) with six publications. Also, 70% of the top 10 authors (7 out of 10 authors) appeared as the first authors in their publications, with Shi, Yangyan and Yan, Ruiliang each having 80% of articles (4 out of 5 articles), followed by Srinivasan, Mahesh 75% articles (3 out of 4 articles), Yu, Kangkang 71% articles (5 out of 7 articles) Tseng, Ming Lang 40% articles (2 out of 4 articles) Naim, Mohamaed M. 20% articles (1 out of 5 articles), and Craighead, Christopher W. 17% articles (1 out of 6 articles). The remaining top 10 authors, including Ketchen, David J. Jr., Potter, Andrew, and Kim, Daekwan, do not appear as the first authors in the articles selected in this study.
On the right hand, the H-index is a metric that assesses publication productivity and citation impact for authors. It is determined using an ordered list of the researcher’s most cited works and the total number of citations in other publications [25]. Instead, the i-10 index shows the number of works published by writers who have received at least 10 citations. The most well-known and extensively used scientific indexes for assessing research and giving a more accurate picture of intellectual activity are those listed above [31]. By assessing these two metrics, the authors with the greatest H-index and i-10 index values are Ketchen, David J. Jr. and Tseng, Ming Lang.
As shown in Table 4, most of the studies were published by authors affiliated with United States (USA) universities. Other countries that register a relevant number of published articles within the analyzed research field are England and China. Authors affiliated with universities in the USA have been cited more frequently. Table 4 also reports the number of published articles whose authors are all from the same country (single-country publications) or different countries (multiple-country publications). As expected, the USA, the country with the highest number of published articles within the analyzed research field, shows the highest percentage of inter-country collaboration. On the contrary, almost 95% of articles published by authors affiliated with Taiwanese universities derive from international collaborations. Although the USA has the most articles and total citations (12,541), it has the lowest MCP ratio of 36%, indicating that authors affiliated with the United States collaborate with authors from other countries less frequently.
In summary, 50% of the top 10 organizations were from the USA, namely, Michigan State University, University of Tennessee, Arizona State University, Auburn University, and Ohio State University (see Table 5). This is followed by 20% of organizations from England, namely, Cardiff University and Cranfield University. With 10% each, the University of Tehran (Iran), Hong Kong Polytechnic University (China), and National Chengchi University (Taiwan) divided the remaining 30% of the organizations. The organizations that include universities and have the most publications published in this study are Michigan State University and the University of Tennessee, both from the USA, with 21 and 17 articles, respectively. Despite having 14 published articles in this analysis, Cranfield University in England had the most overall citations (1550) and average article citations (111), respectively.

3.2. Science Mapping Analysis

The connections between the study elements are examined through science mapping analysis. Furthermore, the analysis focuses on the structural relationships and conceptual exchanges between the different elements of the investigation. Several well-known techniques include citation analysis, co-citation analysis, bibliographic coupling, co-word analysis, and co-authorship analysis. When these techniques are integrated with network analysis, the research field’s bibliometric structure and intellectual structure can be presented [31].
The first technique is citation analysis, commonly called the fundamental scientific mapping method. It is based on the premise that citations represent the intellectual connections between publications created when one journal references another [25]. In other words, the number of citations a publication receives in this analysis determines its influence. The results in Table 6 indicate that the article titled “The agile supply chain—competing in volatile markets” (by Christopher) [32] has the most citations with 923, followed by Ponomarov and Holcomb [33] with articles titled “Understanding the concept of supply chain resilience” with 788 citations and third highest citation is articles titled “Aligning supply chain strategies with product uncertainties” from Lee [34] with 724 articles. Articles from Min [35] titled “Blockchain technology for enhancing supply chain resilience” and Sarkis [1] “Supply chain sustainability: learning from the COVID-19 pandemic” garnered the most citations in terms of most recent publications within five years, each with 257 and 194 citations, respectively. There is a total of 362 articles that have no citations (Figure 3).
The second study is called a “co-citation analysis”, which assumes that works frequently mentioned together have overlapping themes; thus, this can be utilized to shed light on the conceptual framework of a research area [29]. In this case, management researchers can find the most influential publications and theme clusters by employing co-citation analysis, which has the added benefit of helping them find the most influential publications. The papers cited are used to create the topic cluster [31]. The results in Table 7 and Figure 4 show that with at least 20 citations of a cited reference, the 119-threshold item is met. Overall, articles from Fornell and Larcker [36] with 118 citations are the top cited references, followed by articles from Podsakoff et al. [37] and Armstrong and Overton [38], each with 108 and 86 citations, respectively.
Following this, reference that included in this are Cui et al. [39]; Qazi et al. [40]; Schøyen et al. [41]; Radivojević et al. [42]; Münch et al. [43]; Furlan Alves et al. [44]; Sydow et al. [45]; Manuj et al. [46]; Pederneiras et al. [47]; Yassine et al. [48]; Cho et al. [49]; Xu et al. [50]; Chen et al. [51]; Ray et al. [52]; Prior et al. [53], Ugarte et al. [54], Anupindi et al. [55]; Alyami et al. [56] and Poppo et al. [57].
The third analysis is the bibliographic coupling analysis, where two articles are bibliographically linked if at least one cited source appears in both reference lists [29]. It is necessary to analyze the relationships between citing articles to comprehend the ongoing or current evolution of themes in a study field. In this case, articles with at least 100 citations are shown in Figure 5, and summarized details are presented in Table 8. From the figure, the article titled “The agile supply chain—competing in volatile markets” by Christopher [32] has the most citations totaling 923 but among the lowest total link strength with a score of 2. In contrast, articles from Stevenson and Spring [58] titled “Flexibility from a supply chain perspective: definition and review” have the greatest link strength value of 64, although the number of citations is only 340.
The co-word analysis unit is “words”, as opposed to the three science mapping techniques that preceded it, which analyze publications. To put it another way, unlike citation analysis, co-citation analysis, and bibliographic coupling, which use cited or citing publications as a focus point or a proxy, co-word analysis analyzes the actual text of the publication. This co-word analysis also attempts to uncover the conceptual structure by using a word co-occurrence network to map and cluster the terms collected from all keywords in a bibliographic collection, as depicted in Figure 6. The current study considers keywords that appeared in at least five articles. A thick line denotes a close relationship between two items, and a node’s size denotes frequency. In this network visualization figure, the term “supply chain” has the most occurrences and link strength (498 and 2260, respectively), followed by “management” (436 occurrences and 2117 link strength, respectively), “performance” (349 occurrences and 1873 link strength, respectively), and “model” (327 occurrences and 1615 link strength, respectively). Table 9 presents a summary of the findings.
The final technique is the co-authorship analysis, in which two articles are cited in the same article, thus the antithesis of bibliographic coupling. Considering authors with at least 24 citations, the 249-threshold item is met, as shown in Figure 7. A node, in particular, represents an author, its size represents an author’s citations, and a connection represents a co-authorship. According to the figure, Christopher, M. (275 citations), Lee, H.L. (240 citations), and Podsakoff, P.M. (162 citations) were the top three authors with the highest total link strength of 5739, 4322, and 3488, respectively. On the other hand, the Journal of Operation Management was identified as the leader among the journal sources, with a maximum co-citation of 2594 and a total link strength of 159,911 (refer to Figure 8 and Table 10).

4. Discussion: Literature Clustering

This study tried to examine the supply chain uncertainty on different facets of business and management through bibliometric review analysis and identified four major clusters, including overall impact of uncertainty, demand uncertainty, challenges uncertainty, and uncertain strategy (see Table 11). As mentioned earlier, this study aims to investigate the trends of supply chain uncertainty.

4.1. Cluster 1: Overall Impact of Uncertainty

Uncertainty in the supply chain can have a significant impact on businesses and their operations. This uncertainty arises from various factors, including supply disruptions, demand fluctuations, and external events. The impact of uncertainty in the supply chain can exist across multiple dimensions of a business, including financial, operational, customer satisfaction, and strategic aspects. As suggested by Hofer et al. [59], businesses may struggle to balance their reliance on internal and external resources to meet these needs. So, for the benefit of the future, firms should think about coopetition as a useful external integration strategy and unique form of partnership. However, to achieve collaboration between firms within a supply chain, past literature has also emphasized the role of top management teams in developing firms’ dynamic capabilities and formulating contingency plans to deal with the turbulent business environment, which is a crucial competitive advantage [60]. However, dependence on a few key suppliers or single-source suppliers can lead to vulnerabilities if those suppliers encounter problems or fail to meet their commitments.
Furthermore, stakeholders should concentrate on finding a competitive edge like distance in locations, logistic requirements, and information sharing while addressing pricing fluctuation issues [61]. The new product development team was said to be able to reduce this type of uncertainty and improve operational performance and the development of new products by engaging in information technology and knowledge-sharing activities [62]. Particularly, this can impact internal information processing within firms and improve absorptive capabilities, which leads to innovation in capability [63]. Likewise, five overarching themes—governance and organization, knowledge and skills, information systems, regulation, and supply chain base issues—can be used to summarize developments in 23 countries, including China, as well as practitioners’ learning about supply and procurement [64]. Therefore, by strengthening the relational governance in an organization, firms can improve coordination despite complex organizational structure [64]. Poor communication between the business and its drivers is cited by Wang et al. [65] as an internal uncertainty and risk, while the labor/driver shortage is cited as an environmental uncertainty and risk management.
The notion of environmental uncertainty includes the incapacity, at various levels, to determine the likelihood of future events and to accurately predict the implications of decisions, including responsibility towards market demands and climate change [6]. Srinivasan et al. [66] observed that when environmental uncertainty is increased, the positive association between partnership quality and supply chain performance is diminished. They reached this conclusion by applying the transaction cost economic theory. According to Zacharia et al. [67], the resource-based view theory suggests that firms are becoming increasingly reliant on external organizations’ knowledge and experience to innovate, solve issues, and boost organizational performance. Additionally, to offset the disruption in market orientation, firms severely impacted by natural disasters are eager to use their knowledge creation to speed up the deployment of supply chain digital technology [60]. Also, firms can use contractual manufacturing strategies to scale production in response to answers in market orientation through interfirm partnerships regulated by flexible contractual responsibilities and information sharing [68].
To offset the disruption in market orientation, firms use their knowledge creation to speed up the deployment of supply chain digital technology [60]. Also, the findings from Kumar et al. [69] show how managers can improve their manufacturing flexibility operations by using resilience practices that can be implemented quickly and accurately. Literature [70] represents that the drivers affecting transportation operations are delays, delivery restrictions, a lack of coordination, and changing demand/poor information, while unplanned traffic congestion is the main individual determinant contributing to uncertainty. In future research, it is important to investigate the following questions: (1) What are the impacts of uncertainty in the supply chain at the strategic, tactical, and operational levels from a buyer–supplier perspective? (2) How to mitigate the impact of uncertainty in the buyer–supplier chain at different managerial levels (strategic, tactical, and operational)? (3) How cultures and social sustainability concerns are impacted by uncertainty in the buyer–supplier relationship chain?

4.2. Cluster 2: Demand Uncertainty

Demand uncertainty is closely related to the unpredictability and variability in market demand for a product or service. As supported by Yazdani et al. [11], untrustworthy coordination of supplier lead times and supplier exchange contributed to supply chain uncertainty and complexity. From this, one could say that vertical integration will help to channel coordination. Herein, firms can access contractual manufacturing capacity, including the agricultural sector, to satisfy market spikes in product demand, and distribution capacity (warehousing and transportation) can be accessed to maintain supply chains [68]. Alongside this, Baghalian et al. [71] presented a strong supply chain network design with service level against interruptions and demand uncertainty. Particularly, this can impact internal information processing within firms and improve absorptive capacity, which leads to innovation in capability [63]. Herein, absorption capacity is considered as a mediating role at the link between performance and information sharing [72].
Building reliable simulation models to analyze the efficiency of global supply networks under various scenarios is a genuine demand, notwithstanding the limited availability, complexity, and dependability of data regarding the effects of the risks and dynamics situations like COVID-19 [73]. According to Fattahi et al. [3], the pandemic’s supply chain disruptions were unprecedented and forced firms to develop several strategies to mitigate the negative effects. The COVID-19 pandemic also has disrupted and impacted the global supply chain, increasing risk management and causing uncertainty towards the demand [1,2]. Although organizational uncertainty hinders a company’s potential to grow profitably because of the high degree of business instability, uncertainty plays an intriguing role in determining the worth of a firm’s qualities, particularly managerial capability [62]. According to the literature, the primary objective in ethical issues is to lower costs throughout the supply chain [74]. Thus, managers must use efficient financial tools, such as exchange rate derivatives, foreign currency debt, and the operational structure of the exporting firm, to decrease periodic change/uncertain interest/exchange rate policies to an acceptable level [75].
Four types of flexibility strategies are laggard, cautious, agile, and aggressive, which are recognized in the case analysis as responses to the numerous environmental uncertainties and hazards in supply chain management [76]. On the other hand, Ning and You [77] proposed a novel data-driven robust optimization framework that leverages the power of machine learning and big data analytics for uncertainty-free decision-making. Thereby, management may encounter some different experiences as each sort of uncertainty causes a certain bias in decision-making management [78]. Still, it can also be impacted by the choices managers make in the face of significant disruptions like trade conflicts or worldwide pandemics [79]. Üstündağ and Ungan [80] developed a conceptual model where supplier flexibility is related to environmental uncertainty, relationships with the customer as the moderating role, and the quality of the information provided between the buyer and the supplier [81], but not to the quantity of information shared between the two parties. The findings from Kumar et al. [69] show how managers can improve their manufacturing flexibility operations by using resilience practices that can be implemented quickly and accurately. However, such an investment may seem like a poor use of resources if the firm is not protecting the environment [82].
Likewise, to increase their resilience, firms often make changes or adjustments to their internal information technology infrastructure, which may temporarily disrupt their smooth operation [83]. As supply chains become more global, they are exposed to additional risks related to geopolitical factors, trade policies, and currency fluctuations. Thus, the supply chain uncertainty has created a situation, where global operations management, service, and quality have declined [9]. Therefore, future research might want to investigate the following questions: (1) How coordination can help to improve the demand uncertainty in the supply chain? (2) How to implement an analytical roadmap in an organization that faces supply disruption? (3) What are the possible long-term success factors in an organization during a supply disruption crisis?

4.3. Cluster 3: Challenges Uncertainty

Events such as natural disasters, political unrest, labor strikes, or transportation issues can disrupt the flow of raw materials or finished products, causing delays and potential stockouts, which are among the main challenges in the supply chain that indirectly impact sustainable development. Prior studies have shown that such an uncertain situation causes several barriers and challenges to the firms’ performance [69,80]. Accordingly, a fundamental challenge to efficient performance measurement and management is the inability to achieve alignment, or “fit”, between the internal performance measurement and management systems and the external environment, according to the performance alignment matrix [82]. While emerging technologies like blockchain, the Internet of Things, and cloud-based solutions may make handling changes easier by offering safe, affordable, and scalable solutions, Kopanaki [83] claims that more established systems may impede such changes. Nandi et al. [84] show that efforts to improve operational-level capabilities rather than strategic-level capabilities are prioritized more in the current blockchain-enabled supply chain systems. Sislian and Jaegler [85] proposed that enterprise resource planning and blockchain should be utilized in tandem for an uncertain future.
To address challenges in the supply chain during uncertain periods and achieve sustainable development, firms need to invest in technology. However, rapid changes in technology can lead to the obsolescence of products, making it challenging to accurately predict the market’s future demands. For this reason, recent technological innovations such as big data analytics and blockchain applications are among the developing technologies that can aid businesses in reducing supply chain uncertainty [77,84] and improving sustainable development. Past literature [86] employed contingency theory and concluded that firms with blockchain-enabled supply chains had a less adverse impact when the pandemic hit compared to firms without such technology. Therefore, future research might want to examine the following questions: (1) What causes challenges uncertainty to occur? (2) How has technology uncertainty concern impacted supply chain management? (3) How does innovation technology impact multi-tier networks’ transparency, and should businesses consider cooperating with them as they implement the technology?

4.4. Cluster 4: Uncertain Strategy

As supply chains become more global and uncertain situations may be encountered negatively, firms need to have multiple strategies to maintain their significance in the industry. Primarily, a supply chain strategy is employed to boost productivity, save money, or lessen unpredictability and disruption. A supply chain strategy was perceived as a strategic tool that had to satisfy internal and external needs that helped explain a firm’s performance [8]. Most importantly, such a strategy needs to meet many requirements, such as flexibility, resilience, and agility [69,76,87]. Interestingly, firms with more agile supply chains may benefit from their efforts to increase firm performance which positively affects the firm’s sales, profitability, market share, client satisfaction, and speed to market [69]. In addition, Ramos et al. [88] demonstrate that organizational culture motivates better agility in agri-food supply chains. Therefore, future research might want to examine the following questions: (1) What is the most suitable strategy to overcome uncertainty in the global supply chain? (2) What effects do particular uncertainty have on the variables that make up dynamic capabilities? (3) How might the SCOR model be included in the global supply chain uncertainty?

5. Conclusions

The current study undertook a bibliometric review of supply chain uncertainty across a three-decade span. Using PRISMA 2020, related articles were chosen for review and presented in two ways, namely, the performance and scientific mapping analyses. In total, 884 publications with 2335 authors and 176 journals were published between 1993 and 2022, with an average citation level of 32.2. The primary finding of the current study is twofold and addresses both research topics related to the trend in supply chain uncertainty. First, compared to 1993, the supply-chain-related subject of uncertainty is becoming more prevalent in 2022. Even though there are many more papers that exist between 1993 and 2022, the fundamental supply chain management strategy is still lacking. This was demonstrated when the COVID-19 outbreak shocked the world, and the global supply chain was hampered. Because of this, it is necessary to reinforce the supply chain operations reference (SCOR) model in the present supply chain management plan. Especially in small-scale firms, smallholders should strengthen collaboration and consider adopting innovative technologies such as big data analytics and blockchain in the operation and production system.
Second, through the analysis of keyword occurrences, four clusters—namely, overall impact of uncertainty, demand uncertainty, challenges uncertainty, and uncertain strategy—emerged. Twelve possible research questions were recommended for future research directions to lessen the harmful effects of uncertain crises in the supply chain, as discussed in Section 4. A conceptual framework for managing the uncertainty supply chain should be established to assist practitioners and policymakers. This conceptual framework, particularly concerning the palm oil sector, might serve as a road map for smallholder farmers to manage and maintain their resources in times of crisis. Finally, further research may be able to address some of the shortcomings of this study. First, this study looks into one particular database, Web of Science, which restricted the choice of articles. Second, the study only looked at peer-reviewed articles, leaving working papers, reports, or books out of the picture. Third, future research may employ alternative software programs for more complete cluster analysis, such as R-based biblioshiny and Bib Excel.

Funding

The authors acknowledge the GSB-2023-09 and GSB-2023-026 research grants funded by UKM-Graduate School of Business, Universiti Kebangsaan Malaysia.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Research methodology using PRISMA 2020.
Figure 1. Research methodology using PRISMA 2020.
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Figure 2. Year-wise distribution of the selected articles.
Figure 2. Year-wise distribution of the selected articles.
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Figure 3. Science mapping citation analysis.
Figure 3. Science mapping citation analysis.
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Figure 4. Science mapping co-citation analysis.
Figure 4. Science mapping co-citation analysis.
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Figure 5. Science mapping bibliographic coupling analysis.
Figure 5. Science mapping bibliographic coupling analysis.
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Figure 6. Science mapping co-word analysis.
Figure 6. Science mapping co-word analysis.
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Figure 7. Science mapping of co-authorship analysis of authors.
Figure 7. Science mapping of co-authorship analysis of authors.
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Figure 8. Science mapping of co-authorship analysis of sources.
Figure 8. Science mapping of co-authorship analysis of sources.
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Table 1. Main information of data collection from WoS library (n = 884).
Table 1. Main information of data collection from WoS library (n = 884).
Timespan (1993–2022)884Authors2335
Sources (Journals)176Authors of single-authored documents2091
Countries76Authors of multi-authored documents244
Keywords Plus (ID)1805Articles per author0.38
Author’s keywords (DE)2626Authors per article2.64
Average publication per year29.7Collaboration index (single: multi)8.60
Average citations per article32.2Growth rate percentage82.5
Table 2. Top 10 leading journals.
Table 2. Top 10 leading journals.
JournalsPublisherNo of ArticlesCitationsBest RankImpact Factor (2021)
Supply Chain Management—An International JournalEmerald753793Q111.263
International Journal of Operations and Production ManagementEmerald572649Q19.360
International Journal of Logistic ManagementEmerald562401Q25.446
Decision SciencesWiley481436Q34.551
International Journal of Logistics-Research and ApplicationsTaylor & Francis38563Q25.992
International Journal of Physical Distribution and Logistics ManagementEmerald28878Q17.290
Industrial Marketing ManagementElsevier241966Q18.890
Journal of Business and Industrial MarketingEmerald24211Q33.319
Journal of Business LogisticsWiley211148Q17.875
Operations Management ResearchSpringer21172Q17.032
Table 3. Top 10 most productive authors.
Table 3. Top 10 most productive authors.
AuthorsAffiliationPublications (First Authors)H-Indexi-10 Index
Yu, KangkangRenmin University of China (China)7 (5)1729
Craighead, Christopher W.University of Tennessee (USA)6 (1)3758
Shi, YangyanMacquarie University (AUS)5 (4)1524
Ketchen, David J. Jr.Auburn University (USA)5 (0)95176
Yan, RuiliangTexas A&M University (USA)5 (4)3046
Naim, Mohamed M.Cardiff University (England)5 (1)61151
Tseng, MLAsia University (Taiwan)5 (2)76257
Potter, AndrewCardiff University (England)4 (0)3556
Kim, DaekwanFlorida State University (USA)4 (0)3141
Srinivasan, MaheshUniversity of Akron (USA)4 (3)1112
Table 4. Top 10 most productive countries.
Table 4. Top 10 most productive countries.
CountryNo ArticlesTotal CitationsAverage Article CitationSingle-Country PublicationMultiple-Country PublicationsMCP Ratio (%)
USA26912,54146.61729736
China179276115.46311665
England125521641.7646149
India75164321.9373851
Australia55133224.2213462
Germany50134726.9163468
Taiwan44137631.324295
Canada3688824.7201644
Iran3549514.153085
France2992231.832689
Table 5. Top 10 most productive organizations.
Table 5. Top 10 most productive organizations.
OrganizationsNo ArticlesTotal CitationsAverage Article Citation
Michigan State University (USA)2188342
University of Tennessee (USA)171782105
Cardiff University (England)1640125
Arizona State University (USA)1532922
Auburn University (USA)1441330
Cranfield University (England)141550111
Ohio State University (USA)1160555
University of Tehran (Iran)1119117
Hong Kong Polytechnic University (China)1027427
National Chengchi University (Taiwan)938543
Table 6. Citation analysis.
Table 6. Citation analysis.
Citation AnalysisTotal ItemsCriteriaLargest Set ConnectedMeet Threshold ItemNo of ClusterLinks
Document884Citations of documents ≥ 1484797361140
Table 7. Co-citation analysis.
Table 7. Co-citation analysis.
Co-Citation AnalysisTotal ItemsCriteriaMeet Threshold ItemNo of ClusterLinksTotal Link Strength
Reference42,627Citations of cited reference ≥ 201184519918,104
Table 8. Bibliographic coupling analysis.
Table 8. Bibliographic coupling analysis.
Bibliographic CouplingTotal ItemsCriteriaMeet Threshold ItemNo of ClusterLinksTotal Link Strength
Document884Citations of documents ≥ 120338419542
Table 9. Co-word analysis.
Table 9. Co-word analysis.
Total KeywordsCriteriaMeet Threshold ItemNo of ClustersLinksTotal Link Strength
3895Occurrences of keywords ≥ 1042473410,936
Table 10. Co-authorship analysis.
Table 10. Co-authorship analysis.
Co-AuthorshipTotal ItemsCriteriaMeet Threshold ItemNo of ClusterLinksTotal Link Strength
Author26,718Citations of authors ≥ 30170511,97695,758
Source11,846Citations of sources ≥ 40169412,7811,143,575
Table 11. Major clusters and keywords related to supply chain uncertainty.
Table 11. Major clusters and keywords related to supply chain uncertainty.
Major ClusterKeywords
Overall impact of uncertainty
(Red color)		China, collaboration, competitive advantage, drivers, dynamic capabilities, environment, firms, information, knowledge, manufacturing strategy, market orientation, performance, procurement, product development, relational governance, supply chain, theory, trust
Demand uncertainty
(Green color)		Absorptive-capacity, complexity, coordination, cost, COVID-19, decision-making, demand uncertainty, disruption, flexibility, investment, management, methodology, model, network design, policies, resilience, risks
Challenges uncertainty
(Blue color)		Challenges, sustainable development, systems, technology
Uncertainty strategy
(Yellow color)		Agility, organizational culture, strategies
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MDPI and ACS Style

Abdul-Hamid, A.-Q.; Osman, L.H.; Omar, A.R.C.; Rahman, M.R.C.A.; Ali, M.H. What Have We Learned? A Bibliometric Review of a Three-Decade Investigation into the Supply Chain Uncertainty and a Revised Framework to Cope with the Challenges. Sustainability 2023, 15, 15911. https://doi.org/10.3390/su152215911

AMA Style

Abdul-Hamid A-Q, Osman LH, Omar ARC, Rahman MRCA, Ali MH. What Have We Learned? A Bibliometric Review of a Three-Decade Investigation into the Supply Chain Uncertainty and a Revised Framework to Cope with the Challenges. Sustainability. 2023; 15(22):15911. https://doi.org/10.3390/su152215911

Chicago/Turabian Style

Abdul-Hamid, Asma-Qamaliah, Lokhman Hakim Osman, Ahmad Raflis Che Omar, Mara Ridhuan Che Abdul Rahman, and Mohd Helmi Ali. 2023. "What Have We Learned? A Bibliometric Review of a Three-Decade Investigation into the Supply Chain Uncertainty and a Revised Framework to Cope with the Challenges" Sustainability 15, no. 22: 15911. https://doi.org/10.3390/su152215911

APA Style

Abdul-Hamid, A. -Q., Osman, L. H., Omar, A. R. C., Rahman, M. R. C. A., & Ali, M. H. (2023). What Have We Learned? A Bibliometric Review of a Three-Decade Investigation into the Supply Chain Uncertainty and a Revised Framework to Cope with the Challenges. Sustainability, 15(22), 15911. https://doi.org/10.3390/su152215911

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