Interrelationships between circular economy and Industry 4.0: A research agenda for sustainable supply chains

The purpose of this article is to propose a novel classification of the interrelationships between Industry 4.0 (I4.0) technologies and circular economy (CE) principles that highlights the most conclusive findings and extant gaps in the relevant research. A systematic literature review has been developed to locate, select and evaluate relevant contributions made to CE interrelationships with I4.0 technologies. Studies have been analysed and classified according to the specific I4.0 technology and CE principle addressed (10Rs). The articles have been clustered into three main groups: (i) useful application of materials, (ii) extending the lifespan of products and their parts and (iii) smarter product use and manufacture. A mind map of the investigated articles has been used to establish the interrelationships between individual technologies and each CE principle at the supply chain level. Based on this classification, a focus group interview (FGI) was held with experts to dig deeper into the interrelationships between I4.0 technologies and CE principles. The FGI results have identified how each as yet unexplored I4.0 technology could be linked to each CE principle. A Fuzzy Delphi (FD) study

highlights the most conclusive findings and extant gaps in the relevant research.A systematic literature review has been developed to locate, select and evaluate relevant contributions made to CE interrelationships with I4.0 technologies.Studies have been analysed and classified according to the specific I4.0 technology and CE principle addressed (10Rs).The articles have been clustered into three main groups: (i) useful application of materials, (ii) extending the lifespan of products and their parts and (iii) smarter product use and manufacture.A mind map of the investigated articles has been used to establish the interrelationships between individual technologies and each CE principle at the supply chain level.Based on this classification, a focus group interview (FGI) was held with experts to dig deeper into the interrelationships between I4.0 technologies and CE principles.The FGI results have identified how each as yet unexplored I4.0 technology could be linked to each CE principle.A Fuzzy Delphi (FD) study was also applied to identify the most relevant I4.0 technologies for improving CE principles and closing gaps in the literature regarding the 10R CE principles.In addition, guidelines have been established to assist with practical applications and generate a research agenda on the interrelationships between I4.0 technologies and CE principles at the supply chain level.Implications for theory include the extension of view from the research gaps between I4.0 technologies and the 10Rs identified in the literature; also, an FGI and FD were performed based on the detected research gaps to identify future lines of research for academics and offer useful guidance to directors and managers on I4.0 technology interrelationships for improving at least one of the 10R CE principles.The contribution to practice aims to enable managers to easily identify which technology from the Abbreviations: AI, artificial intelligence; AM, additive manufacturing; BDA, big data analytics; CE, circular economy; CPS, cyber-physical systems; FD, fuzzy Delphi; FGI, focus group interview; I4.0, Industry 4.0; IoT, Internet of Things; SDGs, Sustainable Development Goals; SLR, systematic literature review; SM, smart manufacturing; UN, United Nations; VR, virtual reality; WoS, Web of Science.
I4.0 domain should be used to advance any given CE principle.Lastly, we provide useful guidance on the application of as-yet-unused technologies to improve CE principles.

| INTRODUCTION
The circular economy (CE) is a robust approach to promoting a change to sustainable practices in processes, technologies and people in society (Nascimento et al., 2019).CE proposes a transition from linear systems to circular production systems that reduce the need for mineral extraction, emissions, waste and contamination through a sustainable economy (Lopes de Sousa Jabbour et al., 2018).According to Caiado et al. (2022), the Sustainable Development Goals (SDGs) established by the United Nations (UN) are directly benefitted by CE, especially Goals 9 (build resilient infrastructure, promote inclusive and sustainable industrialisation and foster innovation), 12 (ensure sustainable consumption and production patterns) and 13 (take urgent action to combat climate change and its impacts).
Several studies highlight the relevance and contribution of the interrelationships (i.e. a mutual relationship between the two concepts) between CE principles and Industry 4.0 (I4.0) technologies to accelerate the transition process towards circular production systems (Bag, Gupta, & Kumar, 2021; Lopes de Sousa Jabbour et al., 2018;Nascimento et al., 2019), for example, big data analytics (BDA) and CE in the flexible supply chain to improve sustainable manufacturing (Edwin Cheng et al., 2022).Kerin and Pham (2019) identified these interrelationships in a systematic review of I4.0 technologies such as the Internet of Things (IoT), virtual reality (VR) and augmented reality (AR) to support re-manufacturing.Also, circular business models that connect additive manufacturing (AM) and recycling practices in a digital sustainable supply chain have been found to achieve circularity (Nascimento et al., 2019).It is also important to mention blockchain technology, which revolutionises and securely digitises financial transactions and data exchange between companies in circular supply chains (Choi et al., 2020;Kouhizadeh et al., 2020).
The recent literature on CE has identified and improved strategies, principles and capabilities to transit from a linear to a CE (Bag, Gupta, & Kumar, 2021;Kirchherr et al., 2017;Potting et al., 2017).
According to Kirchherr et al. (2017), there are 16 possible combinations of CE core principles in the 4Rs (Reduction, Reuse, Recycling and Recovery).However, the CE core principle that is most frequently used and most frequently cited as the most holistic is the 3R framework (Reduce, Reuse and Recycle) in the production, circulation and consumption process.It must be mentioned that some new principles and strategies have been derived from this definition, for example, the 9R framework proposed by Potting et al. (2017), which separates groupings of characteristics from linear to circular production systems into 10Rs: (i) useful application of materials (R9 Recover; R8 Recycle); (ii) extending the lifespan of products and their parts (R7 Repurpose; R6 Re-manufacture; R5 Re-furbish; R4 Repair; R3 Reuse); and (iii) smarter product use and manufacture (R2 Reduce; R1 Re-think; R0 Refuse).
In a literature review of the 10R principles and I4.0 in general, Bag, Gupta, and Kumar (2021) verified the degree to which I4.0 implementation enhances CE principles in mainly manufacturing companies and the causal relationships.However, the influence of specific I4.0 technologies on each of the 10R principles was not evaluated in either the literature or empirically.So, although specific I4.0 technologies can positively influence each of the CE principles, neither the relationships that are still unexplored in the literature nor how they can be extended to increase circularity in sustainable supply chains have been verified.This supports the problem statement to evaluate the interrelationships between these specific I4.0 technologies and 10R principles to create a research agenda for sustainable supply chains.This work will undertake a systematic literature review (SLR) to identify the interrelationships between I4.0 technologies and 10R principles.A proposed classification of the interrelationships between individual I4.0 technologies and 10R principles will be used to create a CE-I4.0 mind map to evaluate these interrelationships with the literature.This is then used to categorise the 10R principles into three groups (useful application of materials, extending the lifespan of products and their parts and smarter product use and manufacture) and observe which I4.0 technologies influence each of these groups to deduce the most consistent interrelationships.The identification of the research gaps in the literature enables a focus group interview (FGI) and Fuzzy Delphi (FD) to evaluate, analyse and discuss some new interrelationships in which I4.0 technologies can influence CE principles to drive sustainable development.Based on the SLR, FGI and FD results, the objective is to create metacognitive mind maps and carry out qualitative analyses to establish some guidelines for implementing CE-I4.0 practices in sustainable supply chains.FGI and FD will enable researchers to determine the best directions in which to take their future research and managers to identify how they can For managers, this work will help to identify which I4.0 technologies they should use depending on the CE principle (R) that they want to advance.It also gives guidance on how newer technologies as yet unstudied in the literature could support each CE principle.The remainder of this paper is structured as follows: First, we provide a summary of the methodology used (Section 2).This is followed by the results (Section 3) and the discussion (Section 4).Finally, some conclusions (Section 5) are presented.

| MATERIAL AND METHODS
The research method is exploratory, with an SLR based on a central question that aims to investigate the main contributions that I4.0 technologies make to improving at least one of the 10R principles (Denyer & Tranfield, 2009).This research is mixed (Caiado et al., 2022) as it combines qualitative practices with the use of a rigorous process of evaluation, selection and reading to classify the relevant literature findings (Denyer & Tranfield, 2009), while new interrelationships are evaluated empirically through focus groups that address the identified research gaps (Nascimento et al., 2019).A quantitative approach is also used (Thomé et al., 2016) in the form of a descriptive analysis of the selected sample to determine the characteristics, frequency and distribution of the authors' institutions and the number of works that use the CE-I4.0approach to support sustainable management systems (Garza-Reyes, 2015).
Note that this approach starts with an SLR with a rigorous literature selection and evaluation process (Denyer & Tranfield, 2009).This enables an innovative knowledge classification between CE and I4.0 that enables a mind map to be established that systematises these relationships (Saieg et al., 2018).In addition, an empirical approach is applied with an SLR PRISMA graph (Thomé et al., 2016), a FGI to discuss the implementation of CE-I4.0 interrelationships and FD to select from the FGI the most urgently required I4.0 technologies for improving CE principles, as shown in Figure 1.
An SLR has been developed to locate, select and evaluate the relevant contributions on I4.0 technologies and CE fields.The Denyer and Tranfield (2009) recommendations were followed to select and analyse the works and said authors' five-step methodology was applied.The validation and data coding step was included to guarantee the reliability of the systematic review process (Danese et al., 2018).Two further complementary steps were added based on the relationship gaps identified by the SLR: the focus group step for expert empirical verification (Nascimento et al., 2020).Thus, the seven research stages are (i) formulation of the research question; (ii) identification of the studies; (iii) selection and evaluation of studies; (iv) analysis and synthesis (Denyer & Tranfield, 2009); (v) validation and data code (Danese et al., 2018); (vi) focus group (Nascimento et al., 2020); (vii) FD (Garcia-Buendia et al., 2021); and (viii) presentation of results (Denyer & Tranfield, 2009).

| Question formulation
The initial step of an SLR is the formulation of the research question (Denyer & Tranfield, 2009).RQ4.What are the guidelines for increasing the maturity of the integration between I4.0 and CE in sustainable supply chains?

| Locating studies
The second step is to locate the relevant studies.Two decisions are essential at this stage: choice of search engine and formulation of search strings.Web of Science (WoS) was selected as the search engine as it offers exhaustive coverage of the field with high-quality international academic publications from influential publishers (Garcia-Buendia et al., 2021;Marín et al., 2021;Olawumi & Chan, 2018;Wamba & Queiroz, 2020).Authors agreed on a selection of search keywords based on the previous literature (Pagliosa et al., 2021).The search string was designed using Boolean operators as a combination of two-word groups, one group representing I4.0 technologies and the other representing CE principles.Table 1 presents the search string intended to ensure that the located articles contained at least one of the search keywords from each of the two groups in the document's title, abstract or keywords.This step retrieved a total of 551 documents.

| Study selection and evaluation
Inclusion and exclusion criteria are applied in this step.Only articles in English and published in journals with an impact index in Journal Citation Reports (JCR) and/or Scimago Journal Rank (SJR) were selected.
Next, the article abstracts were meticulously read focusing on three main criteria: Are I4.0 technologies and CE addressed together in the article?Does the article have a management focus?Are CE or I4.0 technologies the main topic of the article?Each item had to meet all three criteria to be considered.The articles were then read in full to ensure that they complied with the study's objective.One hundred and seventy-two articles remained after this final assessment with one further article added after cross-referencing the selected literature (snowballing), giving a final sample of 173 articles.

| Analysis and synthesis
The method and definitions required to carry out the analysis and synthesis of the research had to be selected.Several methods that included thematic analysis/synthesis with metacognitive mind maps, qualitative comparative, meta-summary and content analysis were considered for the research synthesis (Barnett-Page & Thomas, 2009;Garza-Reyes, 2015;Thomas & Harden, 2008).
Descriptive analysis was adopted for this research as it does not infer the human being and enables a variety of research data and statistics to be elaborated and demonstrated, thus providing a more quantitative view of the entire study (Marín et al., 2021).Content analysis, in which human inference occurs, was also used to provide a metacognitive analysis of the researched articles and a thematic synthesis that allows a comprehensive analysis of all the articles used in the research, such as benefits, barriers, category and research approach.
The results were entered into an Excel database to analyse the following data for each article: authors, title, journal/conference, year of publication, document source, findings, research category and approach, technologies addressed and used, description of how technologies were used, impact on and approach to CE and classification of benefits and barriers.At this stage, structures had to be pre-defined to collect the required information needed to explore each article's essential and relevant details (Denyer & Tranfield, 2009;Núñez-Merino et al., 2020;Thomé et al., 2016).Complementary research using the snowballing technique identified one further work that would add value to the study, and this was included in the bibliographic portfolio, yielding a final total of 173 articles (see appendices).
Complementary research is essential and should extend beyond the keywords used (Greenhalgh et al., 2005).

| Validation and data code
The data validation and coding stage proposes that the review of articles be shared by the authors.This enables a comparison of the collected information and discussions to solve any possible differences, thus ensuring inter-evaluator reliability (Caiado et al., 2022;Danese et al., 2018).Each author analysed and read the articles and filled out the information sheet.After this step, the results were compared, and the differences were discussed in virtual meetings to generate greater consistency, validation and reliability of the processed data.This additional step allows for transparency in the analysis, minimises errors and evaluator bias and improves the quality and validation of the entire research process (Caiado et al., 2022).

| Focus group
In the analysis and synthesis stage, the documents are analysed and synthesised.Each study was analysed and classified according to the specific I4.0 technology and CE principle addressed.Based on this classification, which determined the interrelationships between I4.0 and CE principles, an assessment was made of the identified research gaps in an FGI with academic participants with research published in the three most cited JCR-indexed journals in WoS.New interrelationships were empirically established for theory-building (Voss et al., 2002).FGI data were collected via a recorded videoconference with FGI participants in line with the planned schedule.An agreement, disagreement and consensus-based qualitative approach produced a matrix table from the consensual interrelationships for guidelines for the CE-I4.0interrelationship research agenda.
The general objective of this FGI protocol is to assess the interrelationships between I4.0 technologies and CE principles of research gaps identified in an SLR and, in addition, to extract new guidelines and best practices to support the interrelationships between I4.0 technologies and CE principles.Considering the need to analyse the interest group's perception of I4.0 technologies and 10R principles, theory-building explores the interaction between subject and object.
Therefore, the purposes of the investigation are defined during this process (Voss et al., 2002).Below is an overview of the focus group discussion moderation guide:

Search string
Group 1 TS = ("Circular Economy" OR "Industrial Ecology" OR "industrial symbiosis" OR "Closed loop supply chain" OR "reverse logistics") Group 2 AND TS = ("Big data" OR "Cloud Computing" OR "I4.0 Technolog*" OR "Artificial Intelligence" OR "Robotic" OR "Additive Manufacturing" OR "Augmented Reality" OR "Advanced manufacturing" OR "Blockchain" OR "Cyber?security"OR "Internet of Things" OR "Industrial simulation" OR "3d print*" OR "Industry 4.0" OR "Smart manufacturing" OR "Autonomous Robots" OR "Advanced robots")  The FGI participant selection criteria were: Participants had to have authored at least one of the three most cited works that integrate CE and I4.0 in the WoS database.The experts also had to be able to participate in the FGI via a videoconference.The authors selected the most cited researchers in CE-I4.0 interrelationships in WoS who met these requirements and agreed to participate in the FGI event on 27 September 2021 to discuss and define guidelines for a research agenda in the short term (Nascimento et al., 2020).FGI participants analysed the interrelationships between specific I4.0 technologies that aim to improve CE principles in sustainable supply chains (de Mattos Nascimento et al., 2018).

| Fuzzy Delphi
The FD method seeks to integrate the theory of the fuzzy set with the traditional Delphi method, with the objective of reducing uncertainties related to the specialists' preferences, thereby improving the quality of the results obtained in the research (Bouslama & Ichikawa, 1993).It was developed by Helmer and his associates as a long-term forecasting method that required repeated surveys of experts for the forecast values to converge (Bouslama & Ichikawa, 1993).
Based on the FGI results, a questionnaire was designed to collect the experts' opinions on the relevance of the CE principles for improv- The corresponding triangular fuzzy numbers are given in Table 3.
Table 3 shows the triangular fuzzy numbers that correspond to the indicated linguistic terms.Tsai et al. (2020) and Lee et al. (2018) demonstrate an assumption that the significance value of an attribute b is rated by a respondent a as j ¼ x ab , y ab ,z ab ð Þ , a ¼ 1,2, 3,…,n and b ¼ 1, 2,3, …, m.Thus, the j b weight of the b attribute is computed as According to Wu et al. (2016), the value of the convex combination D b is generated using α cut, as in Equation ( 1).
The α value adopted to represent a common situation is normally 0.5, but this value can be adjusted based on the experts' level of optimism or pessimism defined as 0 or 1 (Lee et al., 2018).The calculation of the value of the convex combination can be expressed as Equation (2).
where λ is used to express a decision maker's level of optimism and stabilise the expert group's radical judgments.Therefore, is the filter threshold of the required attributes.If D b ≥ δ, attribute b is accepted; otherwise, it must be rejected (Garcia-Buendia et al., 2022;Lee et al., 2018;Tsai et al., 2020).

| Reporting and using results
The last step is to report the results, with all the information extracted from the systematic review literature to a discussion of the results to identify any research gaps that can be used to determine guidelines for future research via the FGI and FD approaches (Denyer & Tranfield, 2009;Durach et al., 2017;Núñez-Merino et al., 2020;Okoli & Schabram, 2010).At this stage, the results are displayed quantitatively through descriptive and qualitative analysis using content analysis and thematic synthesis.

| RESULTS
The obtained results are presented in a descriptive analysis with graphs and tables to illustrate the contextual characteristics of the selected sample of 173 articles (see appendices

| Descriptive analysis
The distribution of publications by year is given in Figure 2. The first paper in the sample was published in 2005 and is a study of the use of artificial intelligence (AI) to simulate and evaluate the reverse logistics of containers in the automobile industry (Cheng & Yang, 2005).
The I4.0 concept was coined at a later date, in 2011 (Kagermann, 2017), although some of the technologies included in the concept had begun to be developed previously.As can be observed, only three articles were found to have been published during the  Table 4 gives further details on the journals in which papers dealing simultaneously with CE and I4.0 technologies were located.
Regarding I4.0 technologies, most papers have adopted a general perspective (see Figure 3).More than one technology was discussed in some papers, which resulted in 213 technology references from 173 papers.The most singly addressed I4.0 technologies in papers were IoT, BDA, blockchain, AM and AI.Some of the technologies are at more advanced stages of maturity (e.g.cloud computing, BDA and IoT) in research and industry applications, while others such as quantum computing (Sarkis, 2021) are still in the early stages of development.
Remarkably, although blockchain applications are only starting to be implemented in industry (Kouhizadeh et al., 2020), blockchain itself has already attracted considerable academic attention.
As can be observed in Figure 4, the literature has not devoted the same level of attention to all the principles.The most covered principles were Reduce, Recycle and Reuse, which is not surprising since these are the principles that make up the 3R framework (Khan Re-think and Refuse principles.The use of IoT has been also extensively addressed to extend the lifespan of products and their parts (through the Reuse, Re-manufacture, Repair, Re-furbish and Repurpose principles) and to achieve the application of materials (via the Recycle and Recover principles).The literature on the use of BDA and CE mainly focuses on the principles of reduction and recycling.However, the use of BDA to enhance circularity ranges from supporting the conception of new business models (Xiang & Xu, 2019) to the extension of the life cycle of materials and products by using product use patterns and customer requirement data to carry out predictive maintenance (Edwin Cheng et al., 2022) and the useful application of end-of-life materials, which supports the management of urban recycling systems (Nobre & Tavares, 2017).Therefore, all 10 principles have been considered, although less attention has been paid to Repurpose and Refuse.
Regarding the use of blockchain, its ability to render information unalterable makes it an ideal technology to address the problem of data reliability.Therefore, together with other technologies such as IoT or big data, it supports product life cycle analysis to improve supply chains' performance in CE issues (Ajwani-Ramchandani et al., 2021;Chidepatil et al., 2020).In this sense, a variety of applica- for example, by minimising the types of materials present in a product (Colorado et al., 2020;Despeisse et al., 2017) and by enabling the manufacture of products and/or components in local locations, which reduces the CO 2 emissions associated with transport (Sauerwein et al., 2019).The literature also deals with issues related to the useful application of materials for both recycling and recovery.Regarding the extension of the lifespan of products/parts, AM enables the design of products that can be repaired or used to manufacture other products (Colorado et al., 2020;Despeisse et al., 2017).
Evidence was found for all groups and principles in the literature on AI and CE.In line with the previous technologies, the principles that were recurrently addressed were reducing and recycling.AI is often presented in conjunction with other technologies such as smart manufacturing/advanced manufacturing, advanced robotics, IoT and blockchain.AI's role is often associated with optimal decision-making and providing autonomy to systems pursuing CE objectives (Tozanlı et al., 2020;Wilts et al., 2021).In CE contexts, cloud computing is being used for the development of powerful platforms that enable collaboration and support the implementation of numerous sustainability-related projects (Wiedmann, 2017).Cloud computing is mainly associated with smarter product use and manufacture through the Re-think and Reduce principles.Solutions for extending the lifespan of products/parts (Reuse, Re-manufacture, Repair, Re-furbish) and the useful application of materials (Recycle and Recover) have also been addressed in the literature.Furthermore, this technology is often cited in conjunction with IoT devices for the analysis of the life cycle of products achieving, in conjunction with some specific cloud platforms, the efficient management of repair, reuse and recycling of products and/or their components, as is currently the case of electronic products and household appliances, for example (Conti & Orcioni, 2019).
Traditional manufacturing technologies are being transformed in the context of I4.0, giving rise to smart factories (Cioffi et al., 2020;Kerin & Pham, 2020).Applications of smart manufacturing/cyberphysical systems (SM/CPS) are being used to enhance product use and manufacturing, as well as to extend and manage the product life cycle.In this sense, by using CPS in conjunction with a variety of I4.0 enabling technologies, smart manufacturing is primarily enabling materials reduction and product repair, reuse, re-manufacturing, recycling and recovery (Kerin & Pham, 2019;Nascimento et al., 2019).
Therefore, the literature on SM/CPS and CE is not as extensive as on the previously mentioned technologies, although it has covered almost all principles (with the sole exception of repurposing).
Furthermore, technologies such as VR, AR and advanced robotics have been addressed, albeit in a small number of papers.Even so, VR is being used in the simulation of systems for CE objectives, for example, by simulating the automated sequence of product disassembly in robotics systems (Kerin & Pham, 2019;Rocca et al., 2020).Despite the small number of papers that have addressed this technology, the use of VR was also related to the three groups of principles.Similarly, advanced robotics applications were associated with all three groups.Among other objectives, this technology aims to automatically separate recyclable and reusable components and classify all components and waste for subsequent management (Sarc et al., 2019).Conversely, AR was associated with only one group of principles-extending the lifespan of products/parts-specifically with Re-manufacturing.Its main application in CE contexts is to facilitate work by tagging information to physical products and providing precise information on tasks and the sequence in which they should be performed (Kerin & Pham, 2020).
Finally, drones, AV and quantum computing technologies were addressed in one article each.According to the literature, drones can be linked to principles from each of the three groups: Reduce, Refurbish and Recovery activities (Mahroof et al., 2021).AV was associated with smarter product use and manufacture (Re-think and Reduce) (Prideaux & Yin, 2019), and future applications of quantum computing could be used to improve product use and manufacture (Re-think and Reduce) to extend the lifespan of products/parts (Reuse) and to improve the application of materials (Recovery) by dynamic route optimisation and simulation to maximise product usability, reusability and life cycle (Sarkis, 2021).The results are summarised in Figure 5 and detailed in the appendices.

| Focus group outcomes
Based on the gaps identified in the systematic review, focus groups were held to analyse and discuss the potential contributions of CE

| FD results
An FD study was applied with Equations ( 1) and ( 2) to identify the most relevant CE principles for improving I4.0 technologies.The values adopted for α and λ were 0.5 and 1, respectively (Chang et al., 2000).The FD was carried out in two rounds, the first exploratory and the second confirmatory (Garcia-Buendia et al., 2022), with the answers of experts who responded to the two stages of the questionnaire accepted as valid (Tsai et al., 2020).This also allowed to reflect on their responses and confirm their assessment in this process of evaluating the I4.0 technologies that can most contribute to CE principles for which no CE-I4.0interrelationship exists in the literature.The experts who participated in the research are listed in and Italy (7.14%).The experts responded on a 5-point Likert scale from 1 = irrelevant to 5 = extremely relevant, as described in Table 3.
FD responses are presented in Table 5.
The experts' responses on the relevance of the I4.0 technologies for improving CE principles are given in Table 5, where T1 is blockchain technology, T2 is additive manufacturing, T3 is autonomous vehicles, T4 is augmented reality, T5 is virtual reality, T6 is cloud computing, T7 is advanced robotics, T8 is smart manufacturing/advanced manufacturing/cyber-physical systems (CPS), T9 is quantum computing, and T10 is drone technology.
The calculated threshold (δ) value was 0.796, and all the criteria whose convex combination values were lower than δ were rejected, as can be observed in

| DISCUSSION
SLR, FGI and FD triangulation culminated in the guidelines for the research agenda and discussions that aimed to contrast the results obtained with state-of-the-art literature to generate innovative knowledge (de Mattos Nascimento et al., 2022;Tortorella et al., 2020).Triangulation showed that the most analysed technologies in the literature were IoT (Rajput & Singh, 2020), BDA (Xiang & Xu, 2019), blockchain (Choi et al., 2020), AM (Colorado et al., 2020) and AI (Wilts et al., 2021).The least cited were quantum computing (Sarkis, 2021), drones (Mahroof et al., 2021), AV (Prideaux & Yin, 2019), AR (Kerin & Pham, 2020) and advanced robotics (Tozanlı et al., 2020).The intermediaries with a respective frequency of 9 and 8 were cloud computing and smart manufacturing.Regarding the CE principles, the most analysed were Reduce, Recycle and Reuse.The I4.0 technologies that most contribute to each of the 10Rs were also identified, with Refuse, Re-furbish, and Repurpose most associated with BDA; Re-think, Reduce, Reuse, Re-manufacture, Recycle and Recover with IoT; and Repair with AM.
From the two rounds of the FD, four I4.0 technologies and their consequent interrelations with CE principles were rejected.This generated an order of priority, with the I4.0 technologies from the FGI that were prioritised and evaluated as most relevant included in the research agenda.An SLR with a matrix of interrelationships and mind maps, FGIs with discussions and conclusions on CE-I4.0 interrelationships and FD were also performed to prioritise the research agenda.
The guidelines for the research agenda were established based on the results of the FGI and FD; these iterations analysed how I4.0 technologies could be used to close the existing research gaps in the literature and propose best practices, points of attention and/or guidelines for each I4.0 technology and the respective 10R principles (Nascimento et al., 2020).A research agenda (see Figure 6) was then generated based on these priorities to achieve the guidelines categorised as very urgent, urgent and not very urgent.
Figure 6 shows that, based on the guidelines generated through the FGI results, the categorisation is made with the most frequent I4.0 technologies and the corresponding highest value of the convex combination in the FD, which generates a sense of urgency for the guidelines by using a weighted sum calculation to order the research agenda.Note that the guidelines were created from the FGI discussions that evaluated how each I4.0 technology could improve the implementation of each respective R when no interrelationships were identified in the literature.So, the guidelines for the research agenda are separated into a short-term view of the efforts made for future CE-I4.0 theory-building (Voss et al., 2002).
Based on the research agenda presented in Figure 6, which summarises and classifies the guidelines established through FGI discussions and FD rounds, Repurposing is considered the CE principle with the highest frequency of non-interrelation and, therefore, identified as a research gap.The research gaps identified were repurposing with drones, quantum computing, smart/advanced manufacturing/CPS, advanced robotics, AV, AM/3D printing, blockchain, virtual reality, AR and cloud computing.

| Implications for theory
Research gaps between 10R principles and I4.0 technologies identified in the literature (Nascimento et al., 2018;Voss et al., 2002)  Blockchain is a protocol that promotes security and end-to-end integration of information and is widely used in cryptocurrencies (Expert 4).It can also be used to repurpose if the technology is applied in a supply chain.This has to involve several actors: One designer in one country and the other designer in another country and marketing and product people in a third country.Thus, secure communication protocols are possible between different countries and different actors, and, for example, payments can be made to these people in cryptocurrencies, thus promoting digital culture and communication through these blocks (Expert 4).So, digital blockchains can facilitate transactions, not only of a digital product (Expert 3) but also to re-propose a service or a business model, for example, servitisation (Expert 2).I believe that there will be a need to create a safety chain between these companies in the production chain, such as rules of trust to increase cooperation between actors at the digital supply chain level (Expert 1) (i) Digital workflow for better communication and transactions to repurpose products and/or services (ii) Technological framework to implement a management system with blockchain for repurposing products and/or services at sustainable supply chain level (iii) Case study to repurpose products or services using blockchain, IoT, cloud computing and big data analytics How can additive manufacturing/3D printing technology improve Repurpose capabilities/principles? AM is a real possibility for manufacturing and perfectly replicating a variety of machines that can be sold with a service.So, 3D printing is a very viable option: You print whatever you want, you make a 3D project and print it.This generates tremendous freedom (Expert 4).The primary way to implement circularity is by recycling steel and plastic, to transform waste into inputs for 3D printers (Expert 4).
Regarding the potential interrelationship between repurposing and 3D printing, the challenge is to take a product that already has a purpose and find a new function or adapt it to a new function (Expert 2).Nowadays, if I think about taking a product apart and making a new product if this is the re-proposal that we are talking about, then yes, I agree with you (Expert 2).I agree with what (Expert 2) said; it would be like taking a product apart and using it to make a powder for a 3D printer to make another product that could be used in the same way as this product or for something else (Expert 3).Most importantly, you must make it simple, simple because complex is questionable (Expert 1).
exploit I4.0 technologies to advance the 10R principles.The innovation for theory is provided by the results of an SLR that investigates works related to I4.0 technologies and CE principles to analyse, verify and identify conclusive relationships and research gaps in the literature.Based on the FGI and FD results, a research agenda is created of the interrelationships between some specific I4.0 technologies and 10R principles with an innovative classification of the literature that also allows to analyse the research gaps.Thus, a contribution is made to theory by indicating directions to guide future research on how underexplored I4.0 technologies could enhance CE principles in the short term.
The central research question formulated to guide this study is: What interrelationships exist in the literature between I4.0 technologies and CE principles?Considering the central question, the secondary questions to segment the expected results of the present investigation are: RQ1.What relationships exist in the literature between CE principles and I4.0 technologies?RQ2.What research gaps between CE principles and I4.0 technologies can be identified in the literature?RQ3.How can the research gaps between CE principles and I4.0 technologies identified in the literature be exploited to improve sustainable supply chains?
Introductory question: From your perspective, describe how you perceive I4.0 technologies and circular economy integration can improve sustainable supply chains?Main questions: How can blockchain technology improve the Repurpose and Refuse principles?How can additive manufacturing/3D printing technology improve the Repurpose principle?T A B L E 1 Research protocol for WoS database.
Final questions:What are the future directions, points of attention and goals for the implementation of integrated CE-I4.0 practices in sustainable supply chains?
ing I4.0 technologies, which identified some gaps in the literature regarding the 10R CE principles and taking in account the CE-I4.0interrelationships relevance discussed in the FGI.The questionnaire was separated into two stages.The first stage dealt with demographic information, and the second stage elicited responses from the participants.Fourteen specialists were selected using established criteria: a minimum of 6 years of experience in either sustainable operations, supply chain management, lean operations, operations management or I4.0 technologies, as shown in Table 2.This table lists the experts that participated in the research, including the FGI and FD stages.The first two experts participated in the FGI stage only.Interviews focused on explicit information in RQs and holding FGI sessions to discuss a topic raised by a skilled moderator and reporter are critical success factors for data collection.As reported in the study by Mishra et al. (2016), FGIs are carried out by two researchers, with one researcher facilitating the FGI content and process by assisting the participants while the other records the discussion with the prior authorisation of the participants and later prepares the transcripts.The expected duration of FGIs is approx.60-90 min.
figure that then more than tripled in 2021, when 71 publications were recorded.Two main points can help explain this enormous increase: Firstly, while the CE concept is not entirely new, the topic has undeniably found its way onto the agenda of policymakers in recent years.Some important examples are the EU's Circular Economy Action Plan(European Commission, 2015)  and the Chinese Circular Economy Promotion Law(Geissdoerfer et al., 2017).Secondly, a steady increase in the maturity and applicability of I4.0 technologies is being seen(Jabbour et al., 2020), and they offer potential solutions that facilitate the transition to CE practices.As mentioned in Section 2, we focused on high-quality peerreviewed journals to ensure the quality of the data.The articles were spread over 71 different journals.The Journal of Cleaner Production (28 publications), Sustainability (17), Resources, Conservation and Recycling (9), Technological Forecasting and Social Change (8), Applied Sciences (7) and Business Strategy and Development (7) have the highest number of publications and together represent 43% of the total.

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literature review of CE principles and I4.0 technologies resulted in a metacognitive mind map with 140 possible interrelationships.Evidence of 100 of these was found.In addition, the works have been grouped into the three groups of Rs (useful application of materials; extending the lifespan of products and their parts; and smarter product use and manufacture).The most addressed interrelationships identified in the literature were between IoT and BDA use and the principles of reducing and recycling and a general perspective of Industry 4.0 associated with the principles of reducing, reusing, remanufacturing and recycling.In contrast, less use has been noted of I4.0 technologies in relation to the Refuse and Repurpose principles.More specifically, in the literature on the use of IoT, smarter product use and manufacture are mainly addressed from the point of view of a reduction in waste generation, and the use of raw materials is one of the main topics covered (Garrido-Hidalgo et al., 2020).The use of IoT systems plays an important role by enabling efficient management of the use of resources, for example, energy management and water consumption (Ingemarsdotter et al., 2019; Rajput & Singh, 2020).Furthermore, some articles have associated IoT with the F I G U R E 3 Specific I4.0 technologies by frequency.F I G U R E 4 CE principles by frequency.
tions have been addressed to link the use of this technology and the development of solutions to extend the lifespan of products and their parts through the Reuse, Re-manufacture, Repair and Re-furbish principles.The useful application of materials was discussed regarding the Recycle and Recovery principles.Smarter product use and manufacture were mostly approached from the point of view of the principle of reduction.AM is another technology that has received considerable research attention.According to the reviewed literature, this technology can lead to the achievement of CE goals through smarter product use and manufacture by enabling designs that support the value cycle,

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I G U R E 5 Mind map of CE-I4.0 interrelationships.principles to improving I4.0 technologies not identified in the literature.The appendices present the core questions that the focus group addresses regarding research gaps, focus group discussions and research lines in the agenda on CE-I4.0 interrelationships.The results presented in the appendices describe how, according to the iterations in the focus group, CE principles can improve I4.0 technologies through interrelationships not identified in the literature.It should be noted that AM was identified as one of the technologies most cited as relevant for enabling redesign, repurposing, remanufacturing and re-thinking in sustainable supply chains.In contrast, quantum computing and advanced robotics technologies were perceived to have few short-term benefits and/or applicability for improving at least one of the CE principles with no interrelationships identified in the literature.According to the FGI results, 16 guidelines were established with research lines to extend the literature with new theory and practical works to better explore CE-I4.0 interrelationships.The points of attention and future goals are related to best CE-I4.0 implementation and what is still missing for this integration to happen.According to Expert A4 and Expert A1, the lack of governance, communication and reliability among actors in the value chain stands out.What is required above all is the support of top management and organisational culture (Expert A3) to generate confidence in the supply chain for innovation and continuous improvement (Expert A4).It is worth noting that one challenge is the replacement of the workforce, which today depends on high-quality industrial jobs (Expert A1).To verify the most critical and urgent I4.0 technologies to improve CE capabilities, and given that the FGI discussed no CE-I4.0interrelationships identified in the literature, FD study rounds were performed both to determine priority CE-I4.0 interrelationships and also identify CE-I4.0 interrelationship guidelines for a research agenda generated by multiple theoretical and empirical methodological procedures (SLR, FGI and FD) to support continuous and incremental improvements in SDGs 9, 12 and 13.
were used in the FGI and FD to analyse, discuss and propose interrelationships with I4.0 technologies for improving at least one of the 10R principles.Thus, a novel literature classification is provided that enables to identify the interrelationships between each I4.0 technology and each CE principle grouped by purpose (see metacognitive mind map in Figure 5) used to create mind maps with the state-ofthe-art CE-I4.0 literature.Furthermore, guidelines are provided based on the FGI and FD to guide future research on the as-yet-unstudied I4.0 technologies that must be investigated to analyse their impact on CE principles.The present work differs from earlier research studies in the adaptation and rigour of the proposed methodology, which combines an SLR, FGI and FD to generate guidelines for the CE-I4.0interrelationship research agenda for improving sustainable supply chains.The methodology used combines theoretical and empirical approaches and qualitative and quantitative categories (Caiado et al., 2022).It is worth noting that the results identified and presented in metacognitive mind maps are innovative for the literature as they find relationships in the approach or applications of CE-I4.0 to assist researchers or companies in their planning and empirical validations.A further novelty of the present work that distinguishes it from previous studies is that it identifies research gaps in the form of relationships that do not exist in the prior literature, which can be used to extend theory and propose recommendations and guidelines for the development of new works focused on unexploited opportunities for theory-building (Voss et al., 2002).F I G U R E 6 CE-I4.0 guidelines for a research agenda for sustainable supply chains.APP E NDIX B : GUIDELINES FOR RESEARCH AGENDA Core questions in the focus group Focus group discussions Guidelines for research agenda How can blockchain technology improve repurpose and Refuse capabilities/ principles?

Table 6 .
The ability of four of the 10 I4.0 technologies to improve CE principles was rejected, namely, blockchain, autonomous vehicles, quantum computing and drone technologies.Fuzzy Delphi responses.Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/bse.3502by Readcube (Labtiva Inc.), Wiley Online Library on [18/06/2024].See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions)on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License If it is not viable on a large scale, it is practically just for show (Expert 1).I do not know if I would say for show, but low volume and high customisation are the best practices for AM implementation(Expert 4) How can autonomous vehicle technology improve Reuse, Re-manufacture, Repair, Re-furbish, Repurpose, Recycle, Recover and Refuse capabilities/principles? I do not see much maturity in this; I even believe that it will be more applied in internal logistics (Expert 4).Another problem is that when they leave university, professionals do not receive (vii) Autonomous vehicle technology can improve the capabilities/principles of Reuse, Re-manufacture, Repair, Re-furbish, Repurpose, Recycle, Recover and Refuse