Unlocking Supply Chain Visibility and Operational Efficiency: A Systematic Review of Industry 4.0 Technologies

1. Introduction

Industry 4.0 has brought about a significant change in manufacturing and supply chain methods, introducing a new age defined by linked, intelligent, and automated systems (Xu et al., 2018). Industry 4.0, often known as the fourth industrial revolution, signifies the integration of technology progress that has fundamentally changed conventional business structures and operating procedures (A. C. Pereira & Romero, 2017; Xu et al., 2018). This revolution expands upon the groundwork established by previous movements, integrating cyber-physical systems, the Internet of Things (IoT), Artificial Intelligence (AI), big data analytics, and automation into a unified and revolutionary structure (X. Zhang et al., 2018). The term "Industry 4.0" was coined in Germany as a component of a government endeavour to promote the digitization of industry (Mariani & Borghi, 2019; Reischauer, 2018). The concept draws upon the chronological development of industrial revolutions - the initial one distinguished by the utilization of water and steam power for mechanization, the second one characterized by the widespread production facilitated by electric power, and the third one propelled by automation and computerization (Allen, 2011; Kurt, 2019; Thomes, 2022). Industry 4.0 signifies the merging of physical and digital technologies, resulting in the development of intelligent systems that can make decisions in a decentralized manner and communicate in real-time (Alcacer & Cruz-Machado, 2019; Salkin et al., 2018).

Although there is an increasing amount of literature on Industry 4.0 and its influence on supply chain management, there is a requirement for a methodical examination that combines and assesses the current understanding. While individual studies may give insights into certain issues, a holistic knowledge of how Industry 4.0 technologies together contribute to supply chain visibility and operational efficiency is absent (Emon et al., 2024). This systematic review seeks to address this deficiency by thoroughly examining and consolidating the existing literature, so enhancing our comprehension of the present research landscape. It will uncover patterns, discern trends, and provide valuable perspectives for future studies and industry implementations.

Industry 4.0 is fundamentally based on a set of essential components that work together to provide its revolutionary capacity (Kagermann, 2014; A. C. Pereira & Romero, 2017). Cyber-physical systems serve as the foundation, merging physical operations with digital connection to provide independent decision-making (Yao et al., 2019; Zhou et al., 2019). The Internet of Things (IoT) enables the linking of devices, enabling smooth data interchange and live monitoring throughout the whole production and supply chain (Broo & Schooling, 2021). AI facilitates the use of sophisticated machine learning algorithms, empowering systems to scrutinize data, provide well-informed judgements, and adjust to ever-changing surroundings (Allioui et al., 2023; Li et al., 2022; Ren et al., 2019). Big data analytics utilizes extensive databases to derive significant insights, which guide strategic decision-making. Automation, which integrates robots and autonomous systems, improves efficiency and adaptability in manufacturing and supply chain processes (Woo et al., 2018).

The ramifications of Industry 4.0 extend well beyond the physical production area, exerting a substantial influence on the management of supply chains (Bonilla et al., 2018; Nagy et al., 2018). The conventional linear supply chain model, which is defined by distinct and sequential phases, has transformed into a dynamic, networked, and data-centric supply network (Aboutorab et al., 2021; Aggarwal et al., 2013; Engelhardt-Nowitzki & Markl, 2019). The incorporation of Industry 4.0 technology offers unparalleled insight into the complete supply chain ecosystem, encompassing the procurement of raw materials to the delivery of the final product to the end-user (T. C. Ng et al., 2022).

Industry 4.0 significantly improves supply chain visibility, which is a crucial aspect of supply chain management. Historically, supply chain visibility denoted the capacity to monitor the progression of merchandise across many phases (Fatorachian & Kazemi, 2021; Ghadge et al., 2020; Mubarik et al., 2021). Nevertheless, in the era of Industry 4.0, it assumes a more expansive connotation. Organization’s may obtain valuable information about inventory levels, manufacturing progress, and logistical operations through real-time monitoring, which is made possible by IoT devices and sensors (Ammar et al., 2021; Qu et al., 2016). The utilization of real-time data enables organizations to forecast and take proactive measures to mitigate future interruptions, optimize the management of inventories, and improve overall operational resilience (Aljohani, 2023; Ivanov & Dolgui, 2021).

The incorporation of Industry 4.0 technology profoundly transforms the methods by which operational efficiency is attained within the supply chain. Utilizing data-driven solutions improves operational processes, resulting in shorter lead times, decreased bottlenecks, and improved resource utilization (Moeuf et al., 2018; Tseng et al., 2021). AI systems utilize past and current data to predict patterns in demand, allowing organizations to optimize their production schedules and inventory levels. AI and robotics-driven automation optimizes repetitive tasks, allowing human resources to dedicate their efforts to intricate decision-making processes (Dash et al., 2019; Pournader et al., 2021; Tseng et al., 2022). This cohesive strategy establishes a versatile and efficient network of suppliers, resulting in a supply chain structure that can easily adjust to dynamic market requirements (Golgeci & Gligor, 2017; Yan et al., 2015).

Industry 4.0 offers unique prospects for improving supply chain operations, but it also brings about obstacles that organizations need to overcome. Factors such as worries about cybersecurity, protection of data privacy, and the necessity of a competent staff to handle these sophisticated technology necessitate thoughtful deliberation (Ghobakhloo, 2018; Hofmann & Rusch, 2017; Ncubukezi, 2022). Furthermore, the adoption of Industry 4.0 technologies requires a change in the culture of organizations, ensuring that all stakeholders are in sync with the revolutionary nature of these innovations (Ghadge et al., 2020; Shin & Lowry, 2020).

In addition to its growing significance in business, I4T is also becoming more widely discussed in academic circles. This has influenced a variety of fields, including business research, which has taken an interest in the topic and is now researching I4T from a more comprehensive standpoint (Hmamed et al., 2023). In this connection, Supply Chain Management (SCM) has been identified as one of the domains that stands to gain the most from I4T applications (E. Ali & Gossaye, 2023). It is necessary to investigate how AI might benefit the dynamic aspects of SCM such as SCV and OE, as evident from the emerging interest from practitioners and researchers in this area (Imtiaz et al., 2023; Kalaiarasan et al., 2022). This need has come up in a number of investigations. The current study fills this gap by examining the research aims and conducting a systematic review. This, we hope, will encourage more study on this fascinating and significant subject.

Aim of the Paper

The main aim of this work is to provide a thorough and analytical systematic evaluation of the current literature that examines the effects of Industry 4.0 technologies on supply chain visibility and operational efficiency. In this regard, the article focuses on a thorough analysis of a wide range of studies that focus on the relationship between Industry 4.0 and supply chain management. Keeping this in mind, the primary objective of the research is to comprehensively analyze relevant research studies on Industry 4.0 technologies, such as the Internet of Things (IoT), Artificial Intelligence (AI), big data analytics, and automation, specifically in the context of supply chain operations. In addition, the article aims to thoroughly assess the methodological quality of the chosen studies by examining their research designs, data collection techniques, and analytical procedures to assure the credibility and accuracy of the information provided. An essential task is to identify and analyze recurring patterns, emerging trends, and common themes in the chosen literature. This will provide valuable insights into the impact of various Industry 4.0 technologies on supply chain visibility and operational efficiency. The article seeks to draw comprehensive conclusions on the impact of Industry 4.0 on supply chain dynamics by conducting analytical research and interpretation. It examines how these technologies affect visibility, simplify processes, and improve overall efficiency. Furthermore, it is essential to identify gaps and limits in the current body of literature in order to direct future research and provide valuable insights to academics, practitioners, and policymakers on unanswered problems and challenges in the field. Thereby, the research aims to examine the practical implications of the findings for industry practitioners and decision-makers. It provides actionable advice on how to successfully use Industry 4.0 technologies to improve supply chain visibility and operational efficiency. Having said that, the present study aims to enhance scholarly knowledge by summarizing important insights, theoretical frameworks, and methodological advancements from the literature review. It provides a comprehensive and current understanding of the research on Industry 4.0 in the context of supply chain management. Altogether, the article intends to serve as a helpful resource for academics, industry experts, and policymakers who are interested in the convergence of Industry 4.0 technologies and supply chain operations. It aspires to stimulate additional study in this dynamic and expanding sector.

2. Method

2.1. Search Strategy

The search strategy aimed to systematically identify and retrieve relevant studies published between 2015 and 2023 that explored the intersection of Industry 4.0 technologies with supply chain visibility and operational efficiency. This search was conducted in major academic databases, including PubMed, IEEE Xplore, ScienceDirect, and SpringerLink. The search utilized a combination of keywords and Boolean operators to refine and target the query effectively (I. Ali & Phan, 2022; Ghobakhloo et al., 2023; Iftikhar et al., 2022; Nottbrock et al., 2023). The primary search terms included "Industry 4.0," "supply chain visibility," "operational efficiency," "Internet of Things (IoT)," "Artificial Intelligence (AI)," "big data analytics," and "automation." The search was restricted to English-language publications, and the publication date range was set from 2015, to the knowledge cutoff date in 2023. The search strategy was an iterative process, allowing for adjustments based on initial search results and additional keywords identified during the process (Bramer et al., 2018; Livoreil et al., 2017).

2.2. Inclusion and Exclusion Criteria

To maintain the relevance and rigor of the systematic review in Table 1, explicit inclusion and exclusion criteria were established. Inclusion criteria encompassed studies published in peer-reviewed journals or conference proceedings, focusing on the integration of Industry 4.0 technologies (specifically IoT, AI, big data analytics, and automation) in supply chain management. Studies were required to examine the impact of Industry 4.0 on both supply chain visibility and operational efficiency. Exclusion criteria included studies not published in English, those not directly related to Industry 4.0 technologies or supply chain management, and studies lacking a clear focus on supply chain visibility or operational efficiency.

2.3. Methodological Quality Assessment

To ensure the reliability and validity of the synthesized findings, a methodological quality assessment was conducted for each selected study. The Critical Appraisal Skills Programme (CASP) framework for systematic reviews was adapted for this purpose (Purssell, 2020; Quigley et al., 2019). The assessment criteria included study design, data collection methods, data analysis, and the overall contribution to the research area. Two independent reviewers assessed each study, and any discrepancies were resolved through discussion and consensus. The methodological quality assessment aimed to identify biases and limitations within each study, allowing for the weighting of evidence during data synthesis (Borges Migliavaca et al., 2020; Carroll & Booth, 2015). Studies with robust methodologies and transparent reporting were given greater weight in the analysis.

2.4. Selection of Studies

The systematic review commenced with an exhaustive database search, spanning prominent academic repositories such as PubMed, IEEE Xplore, ScienceDirect, and SpringerLink. This initial search identified a total of 152 records related to Industry 4.0 technologies and their implications for supply chain visibility and operational efficiency. Subsequently, the removal of duplicates was undertaken to streamline the dataset, resulting in the elimination of 74 redundant records. Following this de-duplication process (Kaur et al., 2018; Praveena & Bharathi, 2021; Xia et al., 2016), the remaining records underwent a meticulous title and abstract screening to assess their alignment with the systematic review's research objectives.

Figure 1. Search strategy, outlining the subsequent identification and screening of appropriate sources. Source: Developed by Author

Figure 1. Search strategy, outlining the subsequent identification and screening of appropriate sources. Source: Developed by Author

The next step involved a comprehensive evaluation of the full texts of these retained studies, applying predefined inclusion and exclusion criteria. This critical assessment led to the exclusion of certain studies based on quality issues identified during the checklist evaluation. After this thorough evaluation, 67 studies remained eligible for inclusion in the qualitative and, where applicable, quantitative synthesis. The systematic review process adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines (Hasan et al., 2023; Moher et al., 2015; Nawijn et al., 2019; Pussegoda et al., 2017), and a PRISMA flowchart was employed to document the transparent selection process, illustrating the progression from the identification of relevant records to the final inclusion of studies in the synthesis.

2.5. Data Extraction and Analysis

Once the final set of studies was selected, a systematic data extraction process was implemented (Petersen et al., 2015). A standardized data extraction form was developed, including key elements such as study characteristics (see Table 2), research objectives, Industry 4.0 technologies investigated, supply chain visibility outcomes, operational efficiency outcomes, and key findings. Data extraction was performed independently by two reviewers to enhance reliability. The extracted data were then synthesized to identify common themes, trends, and patterns related to the impact of Industry 4.0 technologies on supply chain visibility and operational efficiency. This synthesis involved both qualitative and, where appropriate, quantitative analysis. The findings were organized and presented in a structured manner, facilitating the exploration of relationships and variations across the selected studies. This systematic approach aims to provide a robust foundation for the subsequent presentation and discussion of the systematic review results (Durach et al., 2017; Merli et al., 2018; Siddaway et al., 2019).

3. Results

The synthesis of findings from the reviewed studies provides comprehensive insights into various aspects of supply chain management, with a particular focus on factors influencing agility, resilience, and performance. The studies encompass diverse methodologies, geographic locations, and industrial contexts, contributing to a nuanced understanding of the complex interplay between different variables. The key results can be categorized into several themes, each shedding light on crucial elements within the realm of supply chain dynamics.

Influence of Information Visibility and Sharing

A recurring theme across multiple studies is the pivotal role of information visibility and sharing in shaping supply chain outcomes. Enhanced visibility is consistently associated with improved performance metrics, including agility, adaptability, and responsiveness. For instance, Dubey et al. (2018) highlight the positive impact of effective information sharing and connectivity resources on supply chain visibility, further amplified by top management commitment. Similarly, Williams et al. (2013) stress the importance of organizational information processing capability in translating higher supply chain visibility into improved responsiveness. This emphasizes the need for a refined understanding of supply chain integration beyond mere visibility, considering internal integration as a critical factor.

Technology Adoption and Industry 4.0

A significant portion of the reviewed studies delves into the transformative effects of technology adoption, particularly within the context of Industry 4.0. The integration of technologies such as big data analytics, artificial intelligence (AI), and the Internet of Things (IoT) emerges as a common thread. Notably, Wan et al. (2020) and Pereira and Frazzon (2021) showcase how AI-driven automation and IoT integration contribute to increased production speed, reduced errors, and real-time monitoring, ultimately enhancing supply chain efficiency. Furthermore, the studies conducted in various countries, including China, India, and South Korea, provide a global perspective on the widespread adoption of Industry 4.0 technologies and their positive implications for supply chain visibility and performance.

Supply Chain Resilience and Adaptability

The resilience of supply chains is a critical factor, especially in the face of uncertainties and disruptions. Dubey et al. (2021) and Eckstein et al. (2015) contribute valuable insights into the relationship between supply chain resilience and different organizational capabilities. Dubey et al. (2021) emphasize the synergy between tangible and intangible resources, highlighting the role of artificial intelligence-driven big data analytics and intergroup leadership in shaping humanitarian supply chain dynamics. In contrast, Eckstein et al. (2015) explore the positive impact of supply chain agility and adaptability on cost and operational performance. This underscores the interconnected nature of resilience, adaptability, and agility in ensuring supply chain robustness.

Global Variances and Cross-National Comparisons

The geographical diversity of the studies enables a nuanced understanding of how supply chain dynamics vary across regions. Jajja et al. (2018) present findings from Europe, Asia, and the Americas, indicating that the relationship between supply chain risk and agility performance is influenced by factors like supplier and customer integration. Yildirim et al. (2023) conduct a cross-national analysis comparing Industry 4.0 adoption in South Korean and German automotive industries, revealing differences in approaches and commonalities in efficiency gains. This global perspective emphasizes the need for context-specific strategies in addressing supply chain challenges and leveraging opportunities.

Humanitarian Supply Chains

Several studies focus specifically on humanitarian supply chains, recognizing their unique challenges and the need for specialized approaches. Dubey (2023) highlights the role of crisis leadership in enhancing the impact of digital technologies in emergency supply chain relief efforts. Dubey et al. (2018) delve into the significance of big data predictive analytics (BDPA) in humanitarian supply chains, challenging the notion that swift trust is essential for enhancing actor coordination. The findings underscore the complexity of humanitarian supply chain management and the multi-faceted factors that contribute to its effectiveness.

Environmental Influences and Sustainable Practices

Cadden et al. (2022) contribute to the understanding of how environmental dynamism influences key business dimensions, with volume and velocity showing significance in relation to competitive pressures. The study emphasizes the need for supply chain organizational learning and a data-driven culture to moderate the impact of environmental dynamism on supply chain agility. This aligns with the growing emphasis on sustainable practices and the recognition that supply chain strategies must be responsive to environmental considerations.

Role of External and Internal Factors

Brusset (2016) highlights the contributions of both external and internal managerial processes to enhanced agility. The study suggests that while supply chain visibility processes, such as those utilizing Enterprise Resource Planning and tracking tools, have a limited impact, unexplored higher-level processes and routines play a crucial role in explaining agility. This distinction between external and internal factors underscores the complexity of achieving agility and the need for a holistic approach that considers both dimensions.

The synthesis of results from the reviewed studies offers a rich tapestry of insights into contemporary supply chain management. The findings contribute to advancing theoretical frameworks, refining practical strategies, and guiding future research directions in this dynamic field. The multifaceted nature of supply chain dynamics, influenced by factors ranging from information visibility to technology adoption and global variances, underscores the need for a holistic and adaptable approach to supply chain management.

4. Discussion

A state-of-the-art summary of empirical research on I4T and SCV is provided by this comprehensive literature review and the conceptual structure that goes with it.

To present an all-encompassing overview of SCV, this paper compiles previously published research. Thereby, the study specifically helps in the following ways. First, a large number of variables connected to SCV and I4T were found. Next, in order to enable a thorough understanding of the essential components of supply chain visibility, the authors also combined the main traits and findings from past research to present a synopsis of how these parameters are connected to I4T, SCV and OE. Therefore, by combining various viewpoints and SCV-related elements, this study advances the prevailing knowledge on SCV.

The discussion part presents important insights obtained from the thorough synthesis of data, revealing the complex relationships among the identified themes and their significant implications for using Industry 4.0 technology in supply chain management. The studies consistently highlight the crucial importance of making information visible and sharing it to improve supply chain outcomes. This emphasizes the need for a comprehensive approach that goes beyond just integrating technology and includes organizational processes and managerial dedication. The findings support the idea of investing in both modern technical solutions and building a collaborative culture that promotes knowledge exchange. Furthermore, the widespread impact of Industry 4.0 technologies on the way supply chains operate is becoming a powerful driver for change. This requires organizations to strategically align their aims and consider the specific details of their context in order to achieve the best possible results. Nevertheless, the subtle differences in the impacts of particular technologies in various situations emphasize the insufficiency of a one-size-fits-all strategy, prompting organizations to customize their implementation tactics according to their own circumstances. The discussion on supply chain resilience and adaptation reveals the interconnectedness of these concepts, emphasizing the significance of a holistic strategy that considers both tangible and intangible resources. In addition to strengthening real infrastructure, organizations must allocate resources to intangible assets such as leadership and teamwork in order to successfully traverse risks. The combination of agility, flexibility, and improved cost and operational performance strengthens the strategic benefit of flexible supply chain structures, impacting decision-making, resource allocation, and risk mitigation measures. International comparisons demonstrate the wide range of techniques in supply chain management, highlighting the importance of tailored solutions influenced by legislative frameworks, cultural subtleties, and market forces. It is crucial to use geographically sensitive techniques in order to match plans with the unique problems and possibilities present in various locations. By including research that specifically examine humanitarian supply chains, we get insight into the distinct difficulties that arise in these situations. Understanding the significance of crisis leadership, the use of big data predictive analytics, and the utilization of adaptive technology offer significant insights for improving disaster relief operations. These findings enhance our understanding of supply chain management in humanitarian settings and highlight the flexibility and versatility of particular solutions in different situations. Furthermore, the analysis of environmental factors highlights the increasing significance of using sustainable methods in supply chain management. The results emphasize the need of organizational learning and a culture that relies on data to mitigate the influence of environmental changes on the ability of the supply chain to adapt quickly. This places sustainability as a top priority in strategic decision-making. Brusset's analysis of the impacts of external and internal elements leads to a reassessment of conventional methods to supply chain management. Although visibility procedures are important, the study indicates that unknown higher-level processes and routines are essential for attaining agility. Organizations face the task of exploring their own capabilities more thoroughly, promoting a culture of ongoing development and innovation. The consequences go beyond just investing in technology, highlighting the importance of organizational procedures and routines in attaining agility. To summarize, the comprehensive discussion combines various research findings to provide a detailed understanding of the intricate relationship between information visibility, technology adoption, resilience, global differences, humanitarian concerns, environmental impacts, and the influence of external and internal factors. These deep discoveries have a significant influence on the strategic decision-making process, organizational practices, and the future direction of supply chain management in the era of Industry 4.0. The complex nature of supply chain dynamics necessitates a comprehensive and flexible strategy that takes into account the interdependence of different components, enabling the implementation of agile, resilient, and sustainable supply chain practices.

5. Conclusion

In conclusion, this systematic review has meticulously explored the intersection of Industry 4.0 technologies with supply chain visibility and operational efficiency, offering a comprehensive synthesis of findings from a diverse range of studies. The extensive analysis has revealed a nuanced landscape where information visibility, collaborative culture, and the strategic adoption of technological solutions converge to reshape contemporary supply chain management. The synthesized evidence underscores the transformative potential of Industry 4.0 technologies but equally emphasizes the need for organizations to navigate this landscape with a context-specific, adaptive approach. The centrality of information visibility emerges as a key takeaway, with studies consistently highlighting its pivotal role in bolstering supply chain outcomes. From increased collaboration and adaptability to enhanced agility and cost performance, the visibility of information acts as a linchpin for achieving optimal results. However, the discussion has also illuminated the multifaceted nature of this influence, urging organizations to go beyond technological investments and cultivate a collaborative culture that encourages information sharing. The strategic integration of Industry 4.0 technologies in supply chain management extends beyond mere technological adoption. The findings advocate for a dual investment strategy, encompassing both advanced technological solutions and the cultivation of organizational processes conducive to innovation and collaboration. The recognition of intangible assets, such as leadership and organizational culture, as critical elements in fortifying supply chain resilience and adaptability underscores the need for a holistic organizational approach. Global variances in supply chain practices have been a focal point, emphasizing the diversity in approaches across different regions. The findings urge organizations to tailor their strategies based on local contexts, considering regulatory environments, cultural nuances, and market dynamics. Such a geographically sensitive approach becomes imperative for organizations to navigate the specific challenges and opportunities inherent in diverse regions. Furthermore, the inclusion of studies focusing on humanitarian supply chains provides valuable insights into the adaptability and versatility of certain strategies across various contexts. The lessons learned from crisis leadership, big data analytics, and adaptive technologies in humanitarian settings contribute not only to disaster relief efforts but also broaden the applicability of these strategies in other domains. The exploration of environmental influences on supply chain agility underlines the growing importance of sustainable practices. Organizations are encouraged to foster a data-driven culture and prioritize environmental sustainability in their strategic considerations. The nuanced findings from studies, such as those by Brusset, challenge traditional paradigms by highlighting the crucial role of unexplored higher-level processes and routines in achieving agility. In essence, this systematic review propels the discourse on Industry 4.0 and supply chain management into a new dimension. The multifaceted discussion and synthesized findings provide a robust foundation for strategic decision-making, guiding organizations toward agile, resilient, and sustainable supply chain practices. As we navigate the evolving landscape of Industry 4.0, this synthesis serves as a compass, guiding practitioners, researchers, and policymakers toward an informed and adaptive future in supply chain management.