Industry 4.0 Innovation: A Systematic Literature Review on the Role of Blockchain Technology in Creating Smart and Sustainable Manufacturing Facilities

Abstract

Industry 4.0 has revolutionized manufacturing processes and facilities through the creation of smart and sustainable production facilities. Blockchain technology (BCT) has emerged as an invaluable asset within Industrial Revolution 4.0 (IR4.0), offering increased transparency, security, and traceability across supply chains. This systematic literature review explores the role of BCT in creating smart and sustainable manufacturing facilities, while exploring its implications for supply chain management (SCM). Through a detailed examination of 82 research articles, this review highlights three areas where BCT can have a dramatic effect on smart and sustainable manufacturing: firstly, BCT can promote green production methods by supporting efficient resource use, waste reduction strategies and eco-friendly production methods; and secondly, it allows companies to implement smart and eco-friendly manufacturing practices through BCT solutions. BCT promotes intelligent manufacturing systems by facilitating real-time data sharing, predictive maintenance, and automated decision-making. Furthermore, BCT strengthens SCM by increasing visibility, traceability, and collaboration between partners of SC operations. The review also highlights the potential limitations of BCT, such as scalability challenges and the need for standardized protocols. Future research should focus on addressing these limitations and further exploring the potential of BCT in IR4.0.

1. Introduction

Industry 4.0 (IR4.0) refers to the incorporation of innovative cutting-edge cyber technologies into companies’ business operations, such as “blockchain technology” (BCT), “big data”, “cloud computing”, “Artificial Intelligence (AI)”, “3D printing”, “smart manufacturing”, “autonomous robots”, “Internet of Things (IoTs)”, “RFID Tags”, and so on. These innovative cutting-edge digital technologies are gaining much traction in management practices as digitalization (conversion to digital format), and this is regarded as a positive trend that can lead to a competitive edge, economic expansion, gaining innovative capability, and operational development [1,2,3,4]. While the practical use of such technologies (particularly BCT) in the context of firms’ operational activities, logistics, and supply chain (SC) members is relatively new and unestablished, it is clear that this technology will undoubtedly reshape the relationship between businesses, logistics, and SCs members [5,6,7,8].

Furthermore, by implementing such cutting-edge digital technologies, businesses can gain a competitive edge over their rivals by differentiating themselves, cutting costs or improving efficiency, and supporting innovation [9]. They also assist companies in rethinking their economic paradigm (value propositions), optimally organizing their processes, streamlining the way they are structured [4], transforming their mechanism of value creation [10], and sharing widespread knowledge, data, and information across the entire company [11]. As such, implementing industrial 4.0 applications will result in an improved firm act. Nevertheless, the applications of IR4.0 technologies in the development of smart and sustainable manufacturing facilities have long been a source of contention in the world of management, with critics arguing that such investments might take a long time to pay off [3]. This is can be explained by the substantial costs and high level of knowledge and skills required for their deployment [12]. Alternative viewpoints posit that certain developed technologies may not yield statistically significant improvements in business performance within the realm of short-term investments [11,13].

More specifically, academics from different fields have extensively investigated the multifaceted outcomes of Industry 4.0 (IR4.0). The initial research primarily centered on its expediency and value-related benefits [14,15]. In contrast, newer studies have expanded their focus to encompass strategic and operational consequences, including innovation performance [3,16], supply chain management (SCM) effectiveness [13,17], and financial results [18,19]. However, due to the diverse fields and disciplines involved in studying the IR4.0—business performance relationship, our comprehension of how IR4.0 influences firm performance, the mediating and moderating factors affecting its effectiveness, and the mechanisms and barriers shaping its outcomes remains limited. While recent investigations have explored mediating variables such as competitive advantage [20], SC visibility [7,21,22], and technological functionality [23], contributing to our knowledge, inconsistent findings in earlier research and the complex nature of IR4.0 call for a deeper exploration of the underlying mechanisms and organizational determinants linking IR4.0 to business innovation [24] and the advancement of intelligent and sustainable manufacturing facilities [3]. This research is particularly relevant as it responds to the scholarly call for further investigation. It is also important to note that a momentous portion of prior research in this domain suffers from limitations, as is discussed in the following sections, such as being in early stages of development, relying on descriptive or anecdotal methods, lacking comprehensive coverage of the entire SC, or exhibiting regional and sectoral biases.

In light of the above, this study explores the role of BCT in developing smart and sustainable manufacturing facilities. It also analyzes the implications of BCT for the future of SCM. To achieve these objectives, the following research questions (RQs) have been posed: RQ1: What role does BCT play in the development of smart and sustainable manufacturing facilities? By unlocking the answer to this crucial question, we focus on how BCT enhances resource efficiency, optimizes production processes, and enables real-time data analysis for informed decisions, driving intelligent and smart operations. RQ2: What specific SC performance metrics can be improved using BCT? By unlocking the answer to this crucial question, we can explore key BCT features critical for practical use in SCs and smart manufacturing. We also critically review the literature on the role of BCT in supporting the key objectives of SCs. Consequently, we zero in on areas such as visibility, flexibility, traceability, and streamlined logistics and collaboration within the SC network, aiming to quantify BCT’s impact. RQ3: How can BCT be used to develop new sustainable practices for manufacturers? This question pushes boundaries, exploring how BCT can birth novel approaches to circular economy models, closed-loop production systems, and responsible waste management strategies, propelling sustainable practices into the future.

2. Literature Review

2.1. Industry 4.0

IR4.0, as described by [25], is a framework that hinges on integrating vertical and horizontal value chains, digitizing services and products, and introducing innovative business models. It can be viewed as a “policy-driven product”, as indicated by [26]. Ghobakhloo [27] outlines IR4.0 as a holistic system that creates value by integrating advanced technologies and processes that are guided by twelve “design principles” and influenced by fourteen contemporary technological developments. This concept comprises six aspects and principles, as well as four components, which encompass “vertical networking”, “horizontal integration”, “business solutions”, and “expanding technologies” [25].

Prior works, such as [9,28], have identified more than ten essential elements/factors of success for implementing Industry 4.0. Nonetheless, existing studies have predominantly concentrated on three aspects: “drivers and barriers”, “implementation patterns”, and “maturity assessment”. These drivers and barriers can be categorized into “technology, society, and environment”, with technology-related factors being central. For instance, the acceptance of IR4.0 is influenced by variables such as “information technology maturity”; “technology incentives” [29]; “investments in advanced manufacturing technologies”; “novel technologies” such as “BCT, big data, cloud computing, AI, 3D-printing, smart manufacturing, robotics, augmented reality, IoTs, RFID Tags” [13,30]; and so on. Technological advances that help in the integration of SC information [13,30] and enhance SC “collaboration” and “transparency” [31] are also pivotal drivers. Regarding to the “social factors”, these encompass “sustaining government policies” [29], “legislation, and public advisory systems” [32]. Ecological elements/factors encompass socioeconomic and business sustainability dimensions, with market environments in emerging or developed economies being examples of socioeconomic factors [9]. Various business environmental factors play crucial roles, including top management support [9,28,30,33], worker participation [32], human resource development [34], and change facilitation [28].

In addition, most of the research on how to implement Industry 4.0 focuses on using new information technologies, especially front-end technologies such as block chain technology and Digital Twin solutions encompassing “intelligent manufacturing”, “intelligent SCs”, and “smart manufacturing” serving as the core [9,35,36]. With regard to assessing the maturity of IR4.0 implementation, it is considered as another vital research area, aiding companies in understanding their current implementation level and guiding further improvement.

Manufacturing companies have tackled challenges arising from IR4.0 by innovating business models [37], fostering innovative ecosystems [38], achieving value-based innovation [39], formulating global strategies [1,40], adopting data-driven and sustainable manufacturing practices [41,42,43], and establishing smart factories [23]. Previous works has identified two noteworthy sets of IR4.0-related business practice relationships. First, studies have found a complementary impact on “IR4.0-lean management relationship” [44], enhancing existing practices like Lean Manufacturing principles [45], Lean Six Sigma [46], and “total quality management” [46]. These complementary relationships help to promote the circular economic system and sustainable growth [37,43]. However, some studies have suggested no significant improvements in environmental sustainability from all IR4.0 technologies [46].

Second, earlier works indicated that IR4.0 can benefit various aspects of SC management, including “innovation” [47], “technology transformation” [33], “sustainability dissemination” [31], resilience, ripple effects, and risk mitigation [48], and synergy with Lean Manufacturing principles [49].

Several categorizations of IR4.0 applications have emerged in the literature [50]. The most common classification distinguishes between “physical process-driven technologies” and “digital technologies”. The first is physical technologies, which encompass “hardware components” are primarily used to enhance tangible production processes. Examples include “additive manufacturing, collaborative robots, and transportation systems” [51]. The second is a broad range of “digital technologies”, categorized into three distinct subgroups. (i) “Digital Interface Technologies”: these encompass network-connectable hardware components, such as “BC”, “cyber-physical systems”, “IoT”, and “visualization technologies” [52,53]. (ii) “Network Technologies”: these are predominantly software components like “cloud computing” and “cybersecurity solutions” [54,55]. (iii) “Data Processing Technologies”: these are also information-driven software components, e.g., “artificial intelligence”, “simulation”, and “big data analytics” [56,57].

A common reference [50] is the “ten pillars of IR4.0 technologies”, which include “BCT”, “big data analytics”, “autonomous robots”, “simulation”, “horizontal and vertical systems integration”, “IoT”, “cybersecurity”, “cloud computing”, “additive manufacturing”, and “augmented reality” [13,50]. The interpretations of these pillars may vary, with some focusing on specific components. For instance, Frank et al. [36] emphasize “the connectivity and intelligence capabilities of IoT, cloud computing, and big data analytics”. Rojko [58] underscores the application of “cyber-physical systems” and “IoT”. Moeuf et al. [34] replace “additive manufacturing” with “cyber-physical systems”, change systems integration to “machine-to-machine” (M2M) communication, and revise “autonomous robots” to “collaborative robots”. Certain works, such as the work of Roblek et al. [59] have limited the focus to four major technological components: “cyber-physical systems”, “IoT”, “IoS”, and “smart factories”.

In this review, we identify 18 widely utilized technologies in the literature [50], grouped into five categories. (i) “Infrastructure Technologies”: this category includes “cloud computing” and “big data collection”. (ii) “Tracking and Monitoring Technologies” [13]: this category encompasses “BC”, “digitalized control systems”, “real-time tracking technologies”, “sensors”, “RFID tags”, and “M2M communication”. (iii) “Production Technologies”: this category comprises “3D printing” and “additive manufacturing”. (iv) “Transport Technologies”: this category covers “autonomous robots” and “drones”. (v) “Digital Technologies”: this category focuses on “IoT”, “big data analytics”, “cybersecurity”, “simulation”, “augmented reality”, and “artificial intelligence”. These technologies collectively form the foundation of contemporary research in IR4.0 [50].

In the realm of “BCT”, its potential to facilitate the effective implementation of IR4.0 innovations has been highlighted [60]. The various applications of BCT, particularly in manufacturing and SC domains, are emphasized by [61]. Numerous enablers, drivers, and capabilities of BCT for IR4.0 innovation are discussed in the next sections and subsections.

More importantly, the utilization of BCT in the domain of decision-making shows promise. It forms an essential foundation for the future of manufacturing and SCM. An efficient decision-making process serves as the primary defense against uncertainties for any organization. A particularly promising potential application may involve using BCT to streamline and enhance decision-making. For any organization, ensuring a decision-making process is the most efficient way to deal with all uncertainties. SCM specialists are required by most businesses in order to develop and implement procedures used for making decisions to ensure competitiveness. An individual’s decision-making is improved when a BCT protocol is used, facilitating outcome predictions. Studies such as [60,61,62] have shown how vital effective decision-making is to success through the tracking and monitoring tools of BCT.

Recent studies on IR4.0 innovation mostly adhere to the antecedents–practice–response–performance logic, with a focus on technical aspects [9]. The current focus of antecedents is primarily at the technical level. Similarly, the effects of “social and environmental factors”, which are the focus of our research in the context of a sustainable manufacturing system, have received little attention. The practice of “IR4.0 innovation” primarily focuses on the implementation of relevant sophisticated technological innovations, whereas IR4.0′s “strategic response” discuss the digital and intelligent changes in businesses and their SCs enabled by these sophisticated technological innovations. Given the significant investment required in the early stages of IR4.0 adoption, it is not yet known how IR4.0 can be used to improve organizational financial performance. Figure 1 outlines the existing research on IR4.0 innovation against this backdrop.

Figure 1. Theoretical framework of IR4.0 innovation.

2.2. BCT

“BCT” is a P2P process that does not require an intermediary. To this end, each of the different parties elaborated in any transaction functions as “nodes”, and this process is verified through “cryptography” (i.e., “hash”). Records of these transactions are maintained in a single, transparent database across all participating organizations. Once a record is transmitted to the “distributed ledger network”, it is nearly impossible to change, as it is in an unalterable record of past activity [63].

The cryptography, or hashing process, converts “tangible assets” (such as raw materials), or “intangible assets” (such as file ownership), into a digitally encoded “token”. This token can be logged, monitored, and transmitted using a “private key” on the BCT [64]. The invention of BCT can be traced back to 2008 to Satoshi Nakamoto, an anonymous author of the “Bitcoin white paper”, which describes a data structure that incorporates data records referred to as “blocks in a chain”.

Following the studies of [21,65], BCT is characterized as follows:

(i)

BCT is intended to be “distributed and synchronised via networks”, allowing companies to connect and exchange data, and, therefore, is suitable for multi-actor enterprise networks that consist of SCs or financial partnerships.

(ii)

BCTs provide “smart contracts”, which are agreements that parties form beforehand and hold within the network. “A smart contract” is a code protocol designed to promote, validate, or execute the agreed clauses and conditions of the contract on a digital basis. This allows for the execution of legitimate contracts without the need for third-party interference because it is entirely performed digitally. This also affords various parties on the network the mutual trust that everyone will comply with the rules.

(iii)

BCT relies on using “P2P networks”, where an agreement on the validity of a transaction is reached among all relevant parties, and these networks serve to keep incorrect or possibly deceitful transactions away from the database.

(iv)

Lastly, BCT is considered “data immutable”, which means that the agreed-upon transactions are logged and not altered. It offers a history of assets; thus, it is easy to know where it is, where it has been, and what has occurred in every object in its lifetime.

BCT stands apart from conventional information system architectures due to the incorporation of its four fundamental features, as shown in Figure 2:

Figure 2. An overview of the steps and features of BCT information and transactions.

(i)

Non-localization (decentralized database): Centralized databases are more vulnerable to hacking, manipulation, or crashing. By contrast, decentralized databases are more reliable and trusted due to the reliability of the intermediary or other network members [65];

(ii)

Security: This is an essential requirement for reliable and long-term information exchange. It is necessary for managing the demands among members of the network [66]. Transaction history is only available to authorized network users, while no one else can remove or change data without the consent of others;

(iii)

Auditability: BCT is a more open system, enabling auditors and third parties, such as compliance officers, to easily access the data. Due to its transparency and immutability, BCs force companies to operate within the framework of consumer protection legislation and regulations [65,67].

(iv)

Smart execution: Another feature of BCT is the self-execution of digital transactions using decentralized cryptographic mechanisms that astutely bridge protocols and user interfaces to foster regulated and secure communications across computer networks [24].

2.3. Key Classification of BCT

A key advantage of this technology in a work-related setting where no one party retains control is that it addresses issues of transparency and responsibility between individuals and organizations where priorities are not inherently mutually aligned [66]. It allows for updating data relevant to all of the participants in real time, eliminating the need for time-consuming and inaccurate reconciliation procedures that require the confidential information of each party/participant.

BCT reaches the economy using a variety of techniques, which can be categorized as shown in Table 1:

Table 1. BCT techniques and example applications.

Type of BC	Description	Access	Examples
Permissionless or public BCT	Public BCTs are decentralized, institution-free, completely public, and peer networks which any member can join (perform transactions and join in the consensus process) without the need for permissions from other members.	Open to anyone	Bitcoin, Ethereum, Solana
Private BCT	Private BCTs are those that hold centralized write and/or read permissions for a single organization. There are some disputes about whether these can be classified as BCTs, i.e., multi-chain, where a number of banks approve the network.	Controlled by a specific group of people or organizations	Hyperledger Fabric, Corda, Quorum
Permissioned or permitted BCT	Permissioned or Permitted BCTs are an integration of both “public and private BCTs”. These are similar to a federation model, like Ripple, where a group allows new members to join with the permission of existing members, similar to accessing an exclusive club. These BCTs may also grant selected authorizations to carry out certain activities in the network [68].	Limited number of users, but users are not necessarily known to each other	Ripple, R3 Corda, Hedera Hashgraph

3. Methodology

This study utilized a “systematic literature review” (SLR) approach to collect “data” based on well-known scientific principles, minimizing subjective influences (bias) in research endeavors. The SLR is a “replicable, scientific, and transparent method based on comprehensive literature searches that enhances methodological rigor and reliability throughout the review process” [69,70,71]. The approach followed (SLR) aligns with the research goal of knowledge development by synthesizing prior research, identifying “knowledge gaps”, and “establishing the foundation for new research” [72]. The study process began with developing the “research protocol”, which was then complemented by carrying out and analyzing the query string with “inclusion and exclusion criteria” adapted from [73].

A key step in SLR research is to select “search phrases” that will access a broad spectrum of sources. To this end, we first developed the three research questions by consulting with industry experts and identifying key concerns, which would serve as the basis for our research. Next, we explored potential synonyms and alternative phrases for all relevant topics. Finally, we used Boolean operators (AND, OR) to combine these phrases and generate a search string.

In this study, we structured our search terms according to the established “population” and “intervention” framework [72]. For the population, we focused on the scope of application, which, in our case, is “IR4.0”, while the “intervention” included BCT innovation and sustainable manufacturing. An initial pilot search with a few selected phrases revealed that some yielded irrelevant results. Notably, the acronym “IR4.0” proved far more prevalent than “Fourth Industrial Revolution” in the literature. Building on these preliminary findings and consultations with information retrieval bibliographers, we opted for the broader term “sustainable manufacturing facilities” to encompass a wide range of sustainability concepts, including “triple bottom line” (TBL), “circular economy”, and “sustainable development”. Similarly, we used terms like “smart manufacturing” and “smart factories” to capture the development of smart and sustainable manufacturing facilities. The final search string (as shown in Figure 3) was, thus, developed to address the key questions of this investigation within its defined scope.

Figure 3. The search string tailored to the research scope.

This literature review employed four electronic databases—“IEEEXplore, ScienceDirect, Web of Science, and SCOPUS”—to gather scholarly papers. These databases represent the most extensive and appropriate collections for our research endeavor, as demonstrated by different scholars (e.g., [72,74]). Our keyword searches targeted “article titles and abstracts” to gather as much pertinent literature as possible on IR4.0 innovation, sustainability, and smart manufacturing. We identified a total of (1039) items in the four databases. Each of the outcomes of the search was then entered into a “Microsoft Excel spreadsheet”. In phase 1, the collected documents were classified by the “date of publication” (2018–2023). Following the guidelines of the PRISMA declaration [75]. Figure 4 illustrates “the literature selection approach” used in this study. Moreover, Table 2 and Figure 5 show that the items identified in the four databases were found relevant for further exploration.

Figure 4. Literature selection process based on PRISMA flowchart on three levels.

Table 2. The items identified in the four databases prioritized for in-depth analysis.

Year of Publication	Web of Science	Scopus	Science Direct	IEEEXplore	Total
2018	2	14	1	0	17
2019	9	23	14	3	49
2020	19	41	33	9	102
2021	32	139	67	19	257
2022	48	180	125	13	366
2023 (up to August 4)	39	52	150	7	248
Grand Total	149	449	390	51	1039

Figure 5. Publication distribution in the four chosen databases.

In the first phase, we implemented a preliminary screening filter to eliminate papers outside the focus and approach of our research endeavor, e.g., those on the fields of physics, and/or mathematical information, and/or physical science of materials, and/or chemical research. This phase yielded 922 items from the initial count of (1039). In the second phase, we further eliminated articles based on irrelevant titles, replication, other languages, and those lacking in scientific rigor. This resulted in 117 distinct items. In the final phase, the authors themselves screened these 117 papers against the specific research aims and objectives defined in Table 3, applying the inclusion and exclusion criteria outlined therein.

Table 3. Inclusion and exclusion criteria.

Inclusion/Exclusion	Criteria	Clarification
Exclusion	Language disparity	An article’s title and abstract may be in English, but the content may be in another language.
	Unrelated content	A research paper is not the same as an academic journal article; e.g., “editorial materials”, “letters, or forewords are not articles”. Unrelated papers that do not emphasize IR4.0-technologies, leading to “innovativeness”, or the associated sustainability outcomes. 1: IR4.0 innovation is only used as a case in point. 2: Smart Manufacturing is regarded as an immanent feature of IR4.0 rather than a consequence of BCT implementation. 3: The IR 4.0 innovations have no additional implications for sustainability/TBL.
Inclusion	Time frame	Papers published in “peer-reviewed journals” between 2018 and August 2023 are the only ones involved.
	Related content	The link between the research constructs should be examined from the perspective of IR4.0-led innovations and sustainability, rather than the reverse.
	Review articles	The related content criteria do not apply to review articles. This means that regardless of the causal relationship flow stated above, review articles will be incorporated if they tackle all of the research constructs.

We carefully selected and rigorously examined all primary studies to eliminate researcher bias. Triangulation among researchers and detailed data extraction protocols ensured consistent evaluation. Following recommendations in [74], we assessed all major articles for quality and study characteristics, considering factors such as research rigor, relevance, study type, methodology, domain, industry type, publisher, sustainability aspects, and innovation type. Our key quality criteria included the following: (1) whether the research articles appropriately outlined the study terms, (2) whether the data recuperation and investigation methods were abundantly apparent, (3) whether results were drawn, and (4) whether the article was useful for theory and practice. The authors read each “original article” independently prior to incorporating its findings into the study. This approach facilitated the discussion and resolution of any discrepancies. To end with, one author took a comprehensive view of the entire systematic literature review (SLR) and each step involved, ensuring a consistent analysis and interpretation of findings, grouping results, and disseminating them effectively. We sought to identify and elucidate the link between the various constructs of our study. These links can bridge the gap between a diversity of knowledge on different types of “IR4.0 innovations”, ultimately advancing various aspects of smart and sustainable manufacturing facilities.

Following the application of a series of filters based on the aforementioned criteria, each article was meticulously assessed by the authors, leading to a unanimous decision regarding its “inclusion or exclusion”. A stringent selection process was employed to identify pertinent articles. Filters were employed to remove items (articles) that fell outside the scope of the research. Of the initial 117 primary papers, 35 articles were excluded due to their insufficient coverage of IR4.0 innovation outcomes in terms of processes, products, and other relevant aspects. The final selection for data extraction and analysis consisted of 82 articles.

4. Analysis and Results

4.1. Descriptive Analysis

Our final set of data for the current study included 82 research articles published between 2018 and August 2023. We limited our search to studies published after 2018, as this topic has gained significant traction within the academic and professional communities [1]. Nonetheless, our findings suggest that academic discussions and debates about the influence of IR4.0 innovation on the development of smart and sustainable manufacturing facilities likely began earlier, possibly around 2017. Since then, the amount of new research on this subject has skyrocketed, highlighting the growing interest among scholars in the critical and pertinent domain of digitalization, IR4.0 and IR5.0 innovations, and their connections to sustainability. Figure 6 below illustrates this trend of increasing publications over time.

Figure 6. The spread of research contributions across a timeline.

Given the importance of research methods, we observed a variety of techniques used to explore the link between IR4.0 innovation (specifically BCT) and the sustainability of smart manufacturing facilities. As shown in Figure 7, mixed-method studies (combined qualitative and quantitative approaches) are the most prevalent (n = 26), followed by surveys (n = 11), case studies (n = 5), literature reviews/conceptual studies (n = 23), modeling studies (n = 11), and a smaller number of studies employing experimentation (n = 2) and computer simulation (n = 4). These results indicate that the present study’s theme has received academic focus from both qualitative and quantitative standpoints. Theoretical and review articles have explained how IR4.0 technologies, with particular emphasis on BCT, influence various forms of innovations for sustainable development, while case studies have largely endorsed hypothetical concepts with empirical applications. Conversely, experimentation, prototyping, and simulation methods need to be utilized to help assess design problems and recommend effective solutions.

Figure 7. Overview of research methods used in the reviewed studies.

Our bibliographic analysis revealed that the sample studies were published in 38 different sources. The largest proportion of primary articles (n = 14) appeared in the “International Journal of Production Research”, followed by “Sustainability” (n = 9). The “Journal of Cleaner Production” published (n = 6) primary articles, and the journal of “Production Planning & Control” published (n = 5) articles; similarly, “Technological Forecasting and Social Change” published (n = 5) articles. The remaining 44 articles were published across a variety of journals.

While our results suggest a wide range of journals publishing research on this topic, identifying recurring themes, author groups, or journal-specific features could be valuable for future research. Table 4 provides a complete list of primary study venues, and Table 5 highlights the most prolific authors contributing to this domain.

Table 4. Primary articles relating to the journal’s publisher.

Journal Name	Count of Articles	Citation
International Journal of Production Research	14	[31,34,40,41,44,47,48,49,63,67,73,76,77,78]
Sustainability	9	[17,24,79,80,81,82,83,84,85]
Journal of Cleaner Production	5	[1,4,10,16,86]
Production Planning & Control	4	[28,32,33,46]
Technological Forecasting and Social Change	5	[9,23,26,37,42]
International Journal of Production Economics	4	[11,36,38,43]
Benchmarking: An International Journal	2	[25,87]
Communications of the ACM	2	[54,88]
Computers & Industrial Engineering	2	[20,89]
European Journal of Innovation Management	2	[3,30]
Industrial Management & Data Systems	2	[29,90]
Information and Software Technology	2	[72,74]
International Journal of Information Management	2	[7,8]
Procedia Computer Science	2	[91,92]
Robotics and Computer-Integrated Manufacturing	2	[35,93]
British Journal of Management	1	[70]
Cluster Computing	1	[13]
European Management Journal	1	[19]
Future Generation Computer Systems	1	[94]
Global Journal of Enterprise Information System	1	[95]
IEEE Access	1	[96]
IEEE Communications Surveys & Tutorials	1	[56]
IEEE Transactions on Industrial Informatics	1	[97]
Industry and Innovation	1	[2]
Information & Management	1	[12]
Information Systems Research	1	[15]
International Journal of Computer Information Systems and Industrial Management Applications	1	[98]
International Journal of Distributed Sensor Networks	1	[99]
International Journal of Information Technology and Computer Science	1	[62]
International Journal of Interactive Mobile Technologies	1	[58]
International Journal of Operations & Production Management	1	[45]
Journal of Business & Industrial Marketing	1	[39]
Journal of Human Behavior in the Social Environment	1	[100]
Journal of Manufacturing Technology Management	1	[27]
Journal of Systems Science and Information	1	[18]
Logistics	1	[64]
Supply Chain Management: An International Journal	1	[21]
The International Journal of Logistics Management	1	[6]

Table 5. The ten most influential scholars in the field of study.

Key Research Areas	Year	Author(s)	Publication Channel	Citations Count *
IR4.0 adoption; Sustainable innovation and circular economy	2021	[10]	Journal of Cleaner Production	13,767
BCT solutions; Sustainability implications	2018	[94]	Future Generation Computer Systems	5347
BCT in supporting the key objectives of SCs; Manufacturing and SC sustainability	2019	[76]	International Journal of Production Research	2640
IR4.0 acceptance; Sustainability implications	2018	[29]	Industrial Management & Data Systems	2196
IR4.0 technologies; Firm performance; BCT solutions; Sustainability implications	2021	[16]	Journal of Cleaner Production	1940
IR4.0 revolutionize the environmental sustainability; Smart manufacturing	2018	[42]	Technological Forecasting and Social Change	1426
BCT roles in achieving SC objectives; Sustainability implications	2018	[7]	International Journal of Information Management	1077
IR4.0 technologies; BCT solutions; SC sustainability and traceability	2020	[31]	International Journal of Production Research	998
IR4.0 innovations; BCT benefits; Smart manufacturing	2018	[27]	Journal of Manufacturing Technology Management	920
BCT adoption; SC performance; Sustainability and smart manufacturing	2019	[8]	International Journal of Information Management	844

* Google Scholar citations count as of November 2023.

According to Table 5, the top ten studies reveal a collective exploration of the transformative potential of IR4.0 and BCT in shaping smart and sustainable manufacturing practices. A prominent theme across all ten studies is the use of advanced technologies to optimize resource utilization, reduce environmental impact, and support circular economy principles.

These studies highlight the significance of IR4.0 technologies such as AI, IoT, and big data analytics in increasing production efficiency, minimizing waste, and creating closed-loop manufacturing processes. Notably, BCT plays a crucial role in enhancing supply chain transparency, traceability, collaboration, and facilitating sustainable manufacturing practices across networks of peers.

These studies convincingly demonstrate the transformative potential of IR4.0 and BCT technologies in shaping sustainable manufacturing’s future. By adopting them, manufacturing facilities can maximize resource usage while simultaneously decreasing environmental impact and contributing to a more circular economy, ultimately paving the way for a sustainable future in manufacturing.

More recently, we focused on six studies [23,24,43,57,96,101] particularly relevant to this literature review’s exploration of IR4.0 innovations and smart manufacturing. These studies shed light on the potential of these technologies to revolutionize manufacturing processes while enhancing sustainability. They emphasize the pivotal role of BCT in optimizing production efficiency, minimizing waste, and enabling closed-loop processes, thereby laying the foundation for smart and sustainable manufacturing practices.

While acknowledging the challenges and limitations inherent in implementing technological advancements, the aforementioned studies recognize their transformative potential for manufacturing. For instance, [23] highlights the need for an objective performance measurement system to effectively assess IR4.0 initiatives. Similarly, ref. [96] emphasizes the importance of security and privacy when utilizing BCT.

Despite these challenges, a general consensus emerges from these studies: IR4.0 and smart manufacturing hold immense promise for the future of the industry. By embracing these advancements, manufacturing facilities can unlock significant improvements in resource utilization, environmental impact reduction, and contributions to a broader circular economy, paving the way for a more sustainable and prosperous future.

4.2. BC-Based SC

An SC is described as a series of interconnected actors (including suppliers/vendors, distributors, manufacturers/producers, transporters/carriers, retailers/buyers, warehouses, and customers) engaged in the manufacturing and delivery chain of products/and services, from the stage of procurement to the final customer or the point of consumption [1]. In the conventional model, an SC entails various stages and locations. Thus, it is challenging to track events across the entire chain. Furthermore, as a result of the lack of visibility in the SC, “buyers and customers” cannot be entirely confident about the actual value of goods or services [20]. Additionally, several non-traceable elements, including environmental incidents, are also embedded within the SC, potentially fostering issues (e.g., counterfeiting, forced labor, and poor manufacturing conditions). BCT can serve as an effective solution to enhance transparency within SCs, thereby acting as a security guarantor.

4.3. Key Features for Implementing BCT in SCs

BCT can address the challenges of manufacturers and other SC participants and support key SC management purposes such as “cost reduction”, “quality improvement”, “speed”, “reliability”, “risk mitigation”, “sustainability”, and “flexibility” [7,20]. The study of [102] emphasized that efficiency through BC-based SC technology can result in increased market reach, as well as balanced and equitable trade relationships and pricing structures for SC participants. This would then improve transparency and traceability in SC processes and play a role in mitigating and resolving current sustainability challenges that intersect social justice, economic sustainability, and environmental protection. Therefore, among the various operations that are anticipated to undergo significant advancements with the advent of BCT, the SC demands particular attention. The key features of BCT that are critical for application and practical use in SCs and a smart manufacturing system are as follows:

• Traceability, accountability, and visibility: The most common use of BCT for SC purposes is the verification of the source of the goods (mainly the location, time, and producer) and details of the route of the flow of goods from the starting point “its origin” (the back-end SC) to the place of consumption (the front-end SC). “Traceability, accountability, and visibility” issues are critical in providing quality logistics services to customers. To increase the accuracy of tracking the goods from their source to their final destination, BCT is commonly employed in conjunction with RFID tags for items that have different product details and are scanned in a non-contact transfer manner through radio waves imitating different “scanners” [66]. Once the data are gathered and digitized, BCT enables its verification, insertion into a shared distributed ledger, enhancement, and real-time validation. Therefore, BCT serves as a tool for mapping the SC and as a protected platform for exchanging “information”. The benefits of using BCT to record and share information are that all participants in the SC have equal access to real-time updates on product movements and operations [66].
• Boosting demand forecast: The difficulty of forecasting demand is becoming more acute as product life cycles shorten and manufacturing lead times extend. In these scenarios, SCs are increasingly confronting the possibility of either an overabundance of production capacity (stemming from decreased consumer demand) or inadequate product availability [20]. Nevertheless, traditional methods of information sharing, such as the use of an electronic data exchange network to incorporate various coding standards (standards), or the introduction of an “integrated ERP system” to gain “visibility”, are costly and impractical. This is due to BCTs relying on an alternative technology, namely, “peer-to-peer networking”. In this peer-to-peer network, each node serves as a repository for the entire transaction history, encompassing both client and server activities. This distributed approach ensures that all nodes agree on the current state of the ledger, safeguarding data consistency [20]. Consequently, BCTs find an efficient and long-term exchange of information that is central to the management of demand in the supply network [66]. In practice, this means that on the basis of available orders, every entity within the SC develops its demand estimate based on the orders placed by the downstream link (from the distributed ledger). These demands are referred to as derived demands.
• Improved partnership, contract management, and governance of SC partners: The “creation and management” of SCs or network partnerships as per the traditional (“conventional”) method necessitates collaborative efforts, including information dissemination and resource sharing, decision-making coordination, alignment of interests, and a process of trusted exchange [13,79,87,98,100,103,104,105,106,107,108,109,110]. As SCs consist of a series or “network” of interconnected partnerships, the competitive edge of SCs can only be sustained by a positive inter-organizational cooperation among SC participants. Information transparency is a feature of BCT resulting in fast and reliable information shared with the entire community of BCT users. If the BCT features apply to the entire SC of the final product, these BCT features forward information immediately and whenever necessary to all approved actors of the distributed network within the SC, including suppliers of product components [79]. Consequently, this improves SC partnerships and overall performance. In addition, a smart contract execution also improves contract management and the governance of SC partners. A “smart contract” is a self-executing computer program that mimics a traditional contract to oversee digital assets and clearly define the rights and responsibilities of the involved SC members [20]. Upon meeting a set of criteria, the “smart contract” will execute automatically without any human intervention. It can streamline the negotiation process, standardize the terms, automate the execution, and facilitate the real-time monitoring of the contract’s performance. Consequently, specific tasks (e.g., payments) can be carried out through an open disclosure (“transparency”) and effectively [20].
• Improved manufacturing cycle: A substantial volume of information is produced during the manufacturing cycle, ranging from tracking the origins of conflict-free raw materials to implementing process improvement methodologies as in the case of Lean and Six Sigma methodologies. BCT validates manufacturing parameters that are perceived as bulk operations. Smart contracts, equipped with executive powers, can enforce and validate terms and conditions to facilitate the large scale automation of units [111]. By leveraging BC, high-quality data can be centralized, standardized, and shared with all participants in a network to enable better decision-making. BCT can also assist in the additive manufacturing process through constructing a more documentable and design-related process [63].

The essential characteristics (“features”) of BCTs create a great interest in the context of industry and SCs, with the potential to become Industry 5.0 [63]. Considering how BCTs disrupt different segments, it is inevitable that SCs and manufacturers will reap the benefits of it.

4.4. Role of BCT in the Development of Smart and Sustainable Manufacturing Facilities

Earlier sections describe how BCT can be used to create a more secure, traceable, authentic, and collaborative environment while boosting demand forecasts and improving the manufacturing cycle. In this part, we explain the role of “BCT” in the development of smart and sustainable manufacturing facilities, as found in both the literature and practical applications. According to [101], “BCT” has been widely adopted across diverse industries in industrialized and developed economies, leading to innovative applications in smart manufacturing within four key areas: ensuring data security; increasing data sharing, traceability and trust mechanisms; increasing system development; and performance improvement. These areas are summarized in Table 6 below.

Table 6. Key application areas of BCT in smart manufacturing.

Application Area	Explanation	Practical Example
Ensuring data security	BCT uses its chain storage structure with timestamps to ensure data security in smart manufacturing systems [63,101]. Every block of data in the BCT is immutable because it possesses a timestamp and a link to the former block. Furthermore, the encryption algorithm safeguards data security. BCT’s traceability facilitates the optimization of manufacturing systems by tracking the journey of materials and products from source to destination within the SC [13,66]. This helps manufacturers to identify and address inefficiencies.	In an actual situation, BCT-enabled industrial IoT is able to mitigate the risks of information loss and malicious interference as a result of malicious activity on any single network node.
Increasing data sharing	BCT enhances data sharing through its distributed ledger technology, which allows all participants to simultaneously record and share information [97]. This enables both up-and-down-stream actors to share data in real time. Moreover, BC’s privacy protection mechanisms encrypt sensitive data, addressing the inconsistencies between data privacy and sharing [35]. As a result, BCT can break down information silos and enable effective data sharing among various parties.	In a practical example, a BC-based logistics data-sharing platform can accelerate document transfer and reconciliation, improving overall logistics performance.
Traceability and trust mechanism	BCT can serve as a “trust machine and/or mechanism” for all parties in smart manufacturing [99]. Critical data throughout the design, production, and sales processes are cooperatively managed through trusted mechanisms [99,101]. Producers, vendors/contractors, distributors, and other smart manufacturing actors communicate transparent and trustworthy data, establishing trust relations between them [99].	In practice, BCT can eliminate the need for supplier background checks and product quality inspections, further reducing the cost of smart manufacturing.
System development and performance improvement	BCT significantly improves system coordination. Paperless, digital transactions and reliable electronic memory based on BCT critically enhance a firm’s transaction efficiency [35,101]. Additionally, BC’s smart contracts support partnership between up-and-down stream actors in the smart manufacturing and the entire SC. Consequently, BCT becomes a capable driver for the synchronized development of the entire “smart manufacturing system” [20,79,111].	In practice, a BCT-based smart procurement platform can advance procurement coordination and support the transparency of industry trade relationships.

4.5. Potential Use of BCT to Facilitate SCM

A wide range of benefits can be realized by implementing BCTs that are important to the management of the SC, as presented in Figure 8 and Table 7 below. These benefits reflect the role of BCT implementation in achieving the objectives of the SC and offer a summary of how they are linked to the key features of BCT.

Figure 8. The role of BCT in supporting the key objectives of SCs.

Table 7. A review of the scholarly literature on the role of BCT in supporting the key objectives of SCs.

Key Performance Area	SC Objectives	BCT Enabling Features	BC’s Roles	Supporting References
SC transparency and real-time information sharing	data availability	Non-localization	One key empowering feature of BCT is its ability to democratize data access by distributing it across a network of peers, as BCT is based on a decentralized structure. This is because the system user must “record” the transaction with the BCT P2P network in order to preserve the backup of the ledger. The digital ledger is available to all users, regardless of their physical location, to track and manage data	[79,80,91,95,112,113,114]
	data immutability	Security	“Information immutability” forbids unauthorized changes or deletions of information or data without the permission of the network participants. More specifically, the moment the transaction is accepted by a consensus algorithm, the block embedded in the BCT will prevail.	[79,80,95,113]
	data consistency	Auditability	Considering the above discussion and the availability and immutability characteristics of the SC transparency, the BCT with a decentralized ledger, similar to the “stock ledger”, serves as “a single unified data source”, providing a unified and verifiable record of all SC activity, ensuring that all participants are operating on the same term [21]. For example, manufacturing companies that use BCT may be able to improve the efficiency and transparency of their production, assembly, supply, and repair processes by ensuring that all participants follow the same rules [115].	[21,76,102,112,115]
SC speed and reliability	SC visibility	Non-localization and Auditability	BCT may encourage companies to broaden the visibility of their SCs beyond level (tier) one and to react, such as those proposed in modern legislation on SC dependency. However, in cases of short, local SCs, the cost–benefit of using BCT might be questionable [21].	[7,21,22,88,94,102,116]
	SC traceability	Non-localization and Security	The features of BCs (decentralized ledger and security) make them particularly suitable for applications involving traceability. Each time goods and their accompanying paperwork (such as shipping manifests or notifications) are transferred between different participants in the SC, there is a risk of fraud or theft. But with BCT, we can track the item’s journey from its source to its current location. This gives end-users more confidence in the information they receive because no single entity can change the data on the BCT without the consent of all participants [64].	[7,64,76,88,91,102,114,116,117,118]
Cost and risk reduction	reduction of errors	Non-localization, Security, and Auditability	BCT can automatically update shared data whenever it is changed, speed up the process of getting new products to customers and other SC actors, and also decrease the number of mistakes made by humans and the amount of time it takes to process things. BCT can ensure that data are safe and accurate, which makes it less expensive to prevent malicious or arbitrary changes to data, growing risks to the SC, and making a business less trustworthy and reliable [48].	[48,76,90,112,113]
	reduction of attacks	Non-localization and Auditability	BCT can uniquely help to improve the security of both cyber and physical systems, while also ensuring that the chain of custody for evidence is maintained. Digital ownership of an asset could be transferred instantly and without friction once a set of pre-defined criteria have been satisfied. “BCT” can “trace and control” the transactions throughout their journey as well as in a highly secure manner as follows [67]: (i) each authorized user on the network has a “unique identifier”, and only the intended recipient can process a transaction, which helps to prevent misuse; (ii) the cryptographic security, which is also known as a “Block encryption”, of BCT and its decentralized structure make it difficult for hackers and criminal organizations to attack the network.	[67,68,90,119]
	reduction in structural complexity	Non-localization, Security, and Auditability	As mentioned above for the reduction of attacks and errors using BCT, one of the primary motivations behind the BCT framework is to improve productivity while simultaneously reducing the costs and complexity of the SC by eliminating duplication and human error through digitization, where all documented information is shared in a transparent public ledger rather than in the binders of individual companies participating in the SC.	[88,116,119]
SC flexibility	SC coordination	Non-localization and Auditability	BCT can be seen as a better solution for coordinating the SC network. By increasing “visibility”, any entity in the SC network will be able to keep tabs on the status of the products as they pass through the SC. This will allow all parties to follow the whereabouts of specific commodities or containers in transit. Entities can monitor the status of “customs records”, “report invoices”, and “track” other forms of data in an instantaneous fashion [120]. This claim is confirmed by [119] as the ability of each node in the BCT to see everything (i.e., product and document flow). Another advantage of full SC flexibility is preventing repeating similar or identical duties and facilitating communication between different locations in the SC.	[7,22,67,79,92,94,116,119,120]
SC flexibility	SC restructuring and innovations	Non-localization, Security, and Auditability	Drawing upon the findings of the “Market Watch report (2019)”, the role of BCT in the SC market is expected to be seen as disruptive and sustaining innovation as well as advanced transformation, enabling participants (SC actors) to access everything they want on a single platform. In addition, the BCT can potentially be viewed as an incentive to reconsider critical decisions concerning, for example, “sustainability and product sourcing” [117]. This is likely to be seen as a BCT arrangement for gaining revolutionary new insights into the product’s sources. These insights, in turn, can motivate organizations and other SC members to adjust their procurement strategies away from unsuitable suppliers and toward new, much more sustainable, and innovative ones. This can give rise to opportunities for new product ideas and new markets, as data get resilient and adhere to the various components that pass through the SC.	[76,88,117]
SC sustainability	SC sustainability (“environmental, social, and economic performance”)	Non-localization, Security, and Auditability	In terms of environmental sustainability, BCT can be used to monitor low-standard goods effectively to detect more product transactions that can help reduce preprocessing and reprocessing and help mitigate excessive resource consumption and pollution from “greenhouse gases”. This is due to the centralized nature of conventional power mechanisms, whereas a “peer-to-peer network” based on BCT “energy system technology” would minimize the demand for long-distance electricity transmission, saving a significant amount of energy lost during transmission over long distances [76]. In terms of economical sustainability, BCTs can result in a disintermediation of the SC, where fewer third parties participate in transaction costs and time reductions that minimize the duplication and redundancy of the SC. It may also immediately transfer any changes to the data, enabling likely faster product and procedure delivery while reducing errors caused by humans and processing times. Regarding social sustainability, the traceability of BCT facilitates social sustainability through enhanced “human rights”, “protections and fairness”, and “safe working conditions”, i.e., a detailed record of a product’s provenance instills in consumers a sense of assurance that the items they acquire originate from responsible sources.	[76,102,117]
Strategic SC Partnership Management	SC partnerships	Non-localization, Security, and Auditability	BCT is viewed as a tool for strengthening trust in transactions as well as a potential enabler of cross-border mutual exchange of ownership. Increased transparency and visibility would also encourage SC participants to learn more about the BC’s embedded partner companies. This enables partners to interact instantaneously across a vast area encompassing various nations and worldwide [119]. In practice, integrating BCT and IoT technologies offers durable, authentically collaborative distributed networks and the ability to communicate with partners in a secure, accountable manner, which is completely unlike conventional IT or database solutions [96]. Since it has the potential to not only build credibility between system players (such as customers, manufacturers, and distributors), it may additionally provide a trustworthy platform that ensures the confidentiality needed by network actors.	[7,22,79,88,96,119]
	contract management and SC governance	Non-localization and Smart execution	It can be noted that the decentralized structure of BCTs and the smart contract minimize the transaction costs of entering into and enforcing SC agreements [112]. This facilitates the formalization and compliance of agreements throughout the SC. In other words, it regulates the partnership arrangements between companies as well as all other types of actors in the SC and the properties they own. [91].	[7,79,88,91,94,96,112,117];
SC capability	SC competencies	Non-localization, Security, Auditability, Smart execution	In the light of the above-mentioned discussion on non-location, security, auditability, and smart execution features of BC-based SC technology, BCT can be considered a technique that leads to enhanced management capabilities by leveraging existing SC assets and competencies [119]. These capabilities include logistical, relational, and informational capabilities.	[118,119];

The cited literature shows both the excitement surrounding BCT in the industrial and SC sectors and its potential to emerge as a defining technology for Industry 5.0 [63]. The transformative power of BCT, already evident in its disruption of various industries, suggests that SCs will soon be next in line for its transformative impact. A comprehensive study conducted by “Chain-Business Insights” surveyed supply chain practitioners to assess the adoption and utilization of BCT in SCM. The study’s key findings, as outlined in [63], revealed the following. (i) Limited understanding: over 40% of the participants indicated a lack of in-depth understanding of BCT, demonstrating their early stage comprehension of its potential applications. (ii) Focus on traceability: the majority of the participants (80%) envisioned utilizing BCT primarily for product tracking throughout the SC, highlighting its potential to enhance transparency and traceability. (iii) Improved visibility: nearly half of the participants recognized improved SC-visibility as a key benefit of BCT implementation, emphasizing its ability to provide real-time insights into product movement and status. (iv) Growing adoption: nearly half of the participants expressed their companies’ plans to implement BCT in the near future, indicating a growing recognition of its potential transformative impact on SCM. (v) Understanding is key: a lack of understanding remained the most significant barrier to adoption, with 27.5% of the participants citing it as the biggest problem.

4.6. How BCT Can Be Used to Make Manufacturing More Sustainable

Sustainable manufacturing requires considering and balancing “economic”, “social”, and “environmental” aspects. As mentioned earlier, centralized information management in traditional SCs carries risks of data loss and system failures due to security vulnerabilities, mismanagement, and attacks [76,81]. This can ultimately erode trust among SC participants. More specifically, centralized manufacturing SCs lack the appropriate degree of “dependability and transparency” in SC practices, productions, and operations [81]. As a result, enhancing the visibility, data security, trustworthiness, and traceability of current SC processes is crucial for developing trust relationships and achieving sustainability, as highlighted above in this paper. BCT facilitates sustainable manufacturing practices by enabling a reliable, transparent, traceable, and secure SC [121]. The positive impacts of BCT on the three pillars of “sustainability”, commonly known as the triple bottom line (TBL), namely, “economic, environmental, and social”, are presented in Table 8 and Figure 9.

Table 8. BCT solutions and their sustainability implications.

Sustainability Factor	Main Measures	Main Challenges	BCT Solutions	Supporting References
Economic Factor	- Reliability - Responsiveness - Flexibility - Financial metrics - Quality	- High labor cost - Customer service - Dynamic and unpredictable market - Complex regulatory environment - Volatile customer demand - Changing customer preferences - High purchase cost - Limited SC options - Inefficient manufacturing processes - High inventory cost	Reliability: BCT enables distributed and synchronized dissemination of data among SC participants, which can improve the accuracy and efficiency of information sharing. BCT’s “immutability” ensures that data cannot be altered, which, in turn, leads to more reliable customer service, supplier service, forecasts, and stock levels. Responsiveness: Direct Connections and Distributed Operations—BCT provides direct connections among SC stakeholders as well as distributed ledgers that streamline transaction processes to decrease associated costs, time, and waste, making the SC more responsive to changes in demand or disruption. Smart contract solutions can automate the execution of SC agreements, streamlining processes and reducing manual interventions. Flexibility: Consensus Agreements and Resource Sharing—BCT provides its SC partners with the means to develop consensus agreements and share resources, which enables agile decision-making and partnership optimization. Smart contracts provide an effective and flexible means to draft flexible SC agreements that can adapt to changing conditions. Financial Performance: BCT’s P2P network can assist in lowering costs associated with product development, resource use, and waste while increasing transparency among SC participants resulting in lower transaction expenses and improved financial performance. BC’s immutability helps prevent fraud or errors which further contributes to reduced expenses and enhanced financial results. Quality: BCT can help to enhance data availability and sharing among SC stakeholders, which can improve quality management and assurance practices. BC’s immutability can help to ensure that product quality records are accurate and cannot be tampered with.	[63,76,77,81,82,83,86,89,94]
Environmental Factor	- Environmental management - Exploitation of resources - Pollution - Ecosystem	- Implementing environmental management systems and control mechanisms compliant with standards, e.g., ISO 14001 [81] - Optimizing the use of resources, energy, water, etc. - Assigning budgets for environmental protection - Measuring environmental impacts - Education and training on how to respond to environmental accidents - Wastes and emissions reductions	Environmental management: BCT, through the distributed and synchronized feature, as well as its data immutability feature, can be used to track the sourcing, production, and transportation of raw materials and finished products. This can help manufacturers to identify and reduce environmental impacts. Exploitation of resources: BCT can be used to create a decentralized marketplace for recycled materials throughout its smart contracts and P2P network features. This may help manufacturers to reduce their reliance on virgin materials and minimize waste; e.g., manufacturers can create a platform where buyers and sellers of recycled materials can connect directly. It can help reduce transaction expenses and enhance the effectiveness of recycling processes. Pollution: BCT can help manufacturers track emissions from transportation vehicles, which, in turn, helps them reduce their carbon footprint. Manufacturers could create a system that tracks the fuel consumption and emissions of their fleet vehicles; using this information, they could identify strategies to lower emissions further. Ecosystem: BCT, through a smart contracts feature, can automate the execution of environmental management practices, such as product recalls and recycling programs. This can help to save resource cost and reduce emissions. In practice, manufacturers can create a smart contract that automatically triggers a product recall if a product is found to be defective. This can help to minimize the environmental impact of product recalls.	[1,10,16,42,76,77,78,81]
Social Factor	- The work conditions and well-being of workers - Human rights - Corporate social responsibility - Customer satisfaction - Fair trading, accountability, and transparency	- Developing and nurturing mutually beneficial partnerships - Building a favorable image and goodwill among stakeholders - Human resource development - Monitoring violations of human rights - Creating new opportunities and new business models - Facilitating product personalization and extending innovative practices - Promoting fair trading activities	Worker Well-being and Work Conditions: BCT with its smart contracts can automate safety audits and training sessions based on predefined criteria. These data are accessible through a distributed network, ensuring transparency and trust in safety protocols. Human Rights: in a complex global SC, a manufacturer employs BCT to trace the origin of raw materials. The BCT feature of peer-to-peer networks involving suppliers and relevant stakeholders ensures that no materials are sourced from regions with a history of child labor or human rights violations. This guarantees adherence to ethical standards and prevents any engagement with unethical practices. Corporate Social Responsibility: A manufacturing firm is committed to supporting local communities. Utilizing BCT, the company maintains a transparent record of investments in local healthcare, education, and job creation initiatives. The immutability of these data ensures that the community can easily verify the company’s contributions, fostering trust and accountability. Customer Satisfaction: utilizing the synchronized and distributed network offered by BCT, customers engage directly with the manufacturing process, selecting features and configurations. This real-time collaboration guarantees that the final product aligns precisely with the customer’s specifications, resulting in high levels of satisfaction. Fair Trading, Accountability, and Transparency: smart contracts integrated into the BCT automatically verify that suppliers adhere to fair trade principles. The immutability of data ensures that historical records of fair trading practices remain unaltered, enhancing the company’s reputation for transparency and accountability.	[78,81,84,86,89,93,122]

Figure 9. BCT solutions for the challenges of sustainability factors.

5. Discussion

This study identified multiple fields where further investigation is needed to address gaps in the existing body of knowledge. One such area is BCT’s potential to enable both innovative business solutions and the widespread use of smart and sustainable manufacturing systems. Forthcoming research efforts should concentrate on delving into the effects of various IR4.0 technologies on the generation of groundbreaking innovations such as:

• Developing new business models: a dynamic network of interconnected businesses, facilitated by BCT, seamlessly collaborating to create and deliver value to customers in entirely new ways.
• Fostering innovative ecosystems: BCT can empower the creation of collaborative environments where startups, established companies, and research institutions can co-innovate and bring revolutionary ideas to life.
• Achieving value innovation: by leveraging BCT’s transparency and traceability features, businesses can optimize their operations, develop data-driven insights, and create new revenue streams through improved products and services.

With a specific emphasis on developing countries, it would be particularly insightful to explore the viability of IR4.0 innovation in emerging economies and how BCT can leverage smart manufacturing to reduce costs and accelerate the time to market for new technologies:

• Reduce costs: streamlined, automated processes enabled by BCT can lead to significant cost savings in areas like production, logistics, and inventory management.
• Accelerate time to market: improved transparency and shorter production cycles facilitated by BCT can bring new technologies to market faster, giving businesses a competitive edge.

Furthermore, BCT applications to boost long-term profitability vary between industries. Future research should explore the potential advantages of BCT for different sectors, focusing on how it can contribute to: (i) enhanced circular economy strategies: BCT can enable closed-loop production systems by tracking materials and resources throughout their lifecycle, promoting waste reduction and resource conservation; (ii) cost-effectiveness: streamlined supply chains, optimized resource utilization, and reduced waste generation, all facilitated by BCT, can lead to significant cost savings and improved financial performance.

Notable in this literature review is that BCT remains in its early development and exploratory stages, with applications in industrial settings still emerging [1,5,6,7,8,60,101]. As a result, numerous formidable challenges must be overcome before the full range of BCT gains can be actualized. One of the major challenges is the decentralized consensus algorithm, a core component of BCT, which demands a heavy load on computing infrastructure, requires vast data storage, and entails intensive energy utilization. As a result, implementing consensus mechanisms with high-power consumption and low-power IoT devices is impractical. Similarly, the effectiveness of smart manufacturing and digital logistics systems is reliant on a wide variety of IoT devices, which makes integrating these devices with BCT components a difficult task. To overcome these obstacles, future research efforts must focus on developing solutions for system integration and conservation mechanisms.

Lastly, the current generation of BCT systems may struggle to handle the demands of high-throughput applications, limiting their potential use in large-scale smart manufacturing. The exponential growth in the user base and the corresponding expansion of the ledger mandate an equivalent increase in the BCT’s data processing and storage infrastructure. This limitation could hinder the adoption of BCT in high-volume smart manufacturing environments, leading to increased system latency, higher storage costs, and decreased performance. Future research should concentrate on addressing scalability limitations and developing high-performance BC-enabled smart manufacturing systems.

6. Conclusions, Implications, and Limitations

The main focus of this systematic review is to explore the impact of BCT applications in developing smart and sustainable manufacturing facilities. It addresses three research questions:

RQ1: What role does BCT play in developing smart and sustainable facilities?

RQ2: What specific SC performance metrics can be improved using BCT?

RQ3: How can BCT be used to develop new sustainable practices for manufacturers?

To address these questions, 82 research studies are critically examined and analyzed. The discussion explores, in detail, the implications of using BCT for achieving “sustainable manufacturing” and meeting SC objectives. Drawing from referenced articles and Table 6, this review categorizes the benefits of BCT for “sustainable performance”, “smart manufacturing systems”, and “SC management objectives”.

More specifically, with respect to the RQ1, Table 6 summarize the use of BCT in smart and sustainable manufacturing facilities. Its findings reveal how BCT enhances resource efficiency, optimizes production processes, and enables real-time data analysis for informed decisions, driving intelligent and smart operations. To address the second research question RQ2, Section 4.3, Section 4.4 and Section 4.5 discuss the ways in which BCT can enhance essential SC metrics, providing a foundation for explaining how BCT can help organizations achieve their SC goals. Consequently, we zero in on areas such as visibility, flexibility, traceability, and streamlined logistics and collaboration within the SC network, aiming to quantify BCT’s impact. Lastly, regarding RQ3, Section 4.6 discusses how BCT can help manufacturers improve their sustainability performance by utilizing BCT features and characteristics such as smart contracts, peer-to-peer networks, traceability, transparency, security, and distributed and synchronized data sharing.

Considering real-world implications, this study may raise the perception of the benefits of BCT for smart manufacturing, encouraging managers to use digital technologies. This could involve converting paper documents and manual processes to digital formats and transitioning to digital communication and storage. This research also assists manufacturing executives in understanding how BCT can address challenges associated with implementing sustainable strategies, which have long been a source of contention for manufacturers. Additionally, this work serves as a valuable resource for researchers by offering current insights into BCT’s potential contributions to sustainable and smart manufacturing systems.

In terms of theoretical implications, this study reveals that current BCT implementations may lack the necessary scalability to support high-volume usage scenarios. This impedes the adoption of BCT in large-scale manufacturing and makes the transition to digital processes difficult for manufacturers. The growth in BCT participants and the corresponding ledger expansion lead to increased resource demands and decreased performance. Therefore, future research should focus on addressing the scalability issue and developing high-performance BC-enabled smart manufacturing systems.

Although this study successfully addresses the three research questions, it also identifies some limitations that future research can address. Firstly, recognizing the comprehensiveness of WoS, ScienceDirect, Scopus, and IEEE Xplore, future research could consider expanding the scope to include SpringerLink, Wiley Online Library, EBSCO, and ProQuest databases for a more exhaustive search. Additionally, while this review focused on journal articles, incorporating conference papers and book chapters in future reviews could offer a more comprehensive examination of the field. To mitigate potential biases arising from subjectivity in article selection, two authors independently reviewed each piece of literature, with any discrepancies reconciled through collaborative discussions. As discussed above, a significant portion of prior research in this domain exhibits certain limitations: early stage of development, reliance on descriptive/anecdotal methodologies, incomplete coverage of the entire SC, and regional/sectoral biases. Future research should address these limitations and fill these gaps in the literature by: (i) conducting longitudinal studies to track changes and assess long-term impacts within the SC; (ii) employing robust quantitative methodologies for more objective and generalizable findings; (iii) encompassing a wider range of regions and sectors to ensure inclusivity and avoid regional/sectoral biases; (iv) developing novel theoretical frameworks that effectively capture the intricate dynamics of the SC.

Lastly, new research (e.g., [85]) indicates that Web 3.0, fueled by BCT, cryptocurrencies, and NFTs, grants users greater control over their digital assets. This decentralized structure, through mechanisms such as “transparency and energy efficiency”, promotes trust, data privacy, and sustainability. However, hurdles remain in building secure and effective smart contracts, and legal uncertainties persist. To fully unlock Web 3.0′s potential for a future that is secure, empowered, and sustainable, further research is essential. Exploring areas related to building sustainable supply chains with Web 3.0 and integrating AI with responsible governance will be key to unlocking this potential. While some may dismiss it as mere hype, Web 3.0 has the power to reshape the digital landscape, demanding our careful and responsible engagement.