Abstract
The Industry 4.0 (I4.0) concept comprises advanced digital technologies that facilitate the digitally enabled sustainability approach leading to a Circular Economy (CE). I4.0 driven CE initiative leads to a paradigm shift in supply chain management (SCM), where quantitative methods provide practical solutions to issues that arise when adopting circular practices. Therefore, the intersection of I4.0, CE, SCM and quantitative methods has been identified as an upcoming area worthwhile investigation. Hence, we conduct a bibliometric analysis on extant literature to visualise and unravel the current scholarly discussion while providing insights to the scholars and practitioners who pursue the current dynamics, trends, prospects pertaining to the intersection mentioned above.
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1 Introduction
The role of digital technologies has been identified as crucial in the transition towards the Circular Economy (CE) [1]. This digitally enabled CE approach is facilitated by the Industry 4.0 (I4.0) technologies influencing its performance with a positive impact on the life cycle management of products. Hence, several elements of I4.0 were identified as digital enablers for CE [2]. Especially, I4.0 elements such as simulation along with quantitative methods have been recognised as practical techniques to address issues related to supply chain management (SCM) when adopting circular practices [2]. However, studies disseminating such methods are dispersed in the SCM discourse, focusing on the reverse and closed-loop supply chains in the CE context. Hence, this study accumulates such scholarly work and answers which facets, factors, and limitations are to be considered when applying quantitative methods and techniques for I4.0 enabled operations and supply chains in the CE context. Moreover, this review aims to pinpoint possible research directions while highlighting the boundaries of knowledge.
2 Background
CE aims to achieve sustainable development along with improved social equity and environmental and economic prosperity [3]. Integrated with I4.0, a technology-driven CE centric supply chain would be more sustainable, adaptable, secured, and interactive [4], ultimately paving the path to achieve the aims of CE.
Introduced in 2011, I4.0 exemplifies a set of automation technologies such as the Internet of Things (IoT), Cyber-Physical Systems (CPS), and cloud computing in the manufacturing industry [5]. It comprises nine pillars, namely, additive manufacturing (AM), simulation, augmented and virtual reality, big data and analytics (BDA), the Internet of Things (IoT), autonomous robots and vehicles, horizontal/vertical system integration, cloud, fog, and edge technologies, and blockchain and cyber-security [6, 7]. I4.0 represents a fundamental paradigm shift in SCM [8] which presents an immense possibilities to improve the SCM processes in areas such as responsiveness, efficiency, and sustainable performance [9]. Moreover, I4.0 technologies positively influence the lifecycle management of a product where technologies such as AM, BDA and IoT were identified as digital enablers of CE [2].
3 Methodology
Bibliometric analysis is adopted to analyse the relationships among articles efficiently and reliably and visualise the results to identify future research directions while providing comprehensive insights on the analysed research field [10]. Rowley and Slack [11] proposed a systematic methodology to scan resources, design the mind map to build the bibliography and structure a literature review. Literature review underlines the boundaries of the existing literature while identifying potential research gaps through a comprehensive evaluation of the body of literature [12]. In this study, we adopted the methodology followed by Fahimnia et al. [13] to conduct the bibliometric analysis.
To identify the relevant papers related to the focus of this study, keywords related to four areas, namely, I4.0, CE, SCM and quantitative methods, were selected. I4.0 related keywords covered all nine technological pillars and related areas proposed by Rosa et al. [2]. CE related keywords captured the different approaches for CE such as “circular economy”, “closed loop*”, “open loop*”, and 10 CE implementation strategies identified by Reike et al. [14]. SCM and quantitative method aspects were comprehended by including keywords such as “supply chain*”, “simulation”, “optimisation” and “quantitative methods”. The literature search only focused on papers published in English in peer-reviewed scientific journals, where the search was carried on title, abstracts and keywords in the Web of Science database. The initial search resulted in 526 papers. After removing duplicate papers among the search strings, the final dataset included 414 papers with a focus on technical and management perspectives. They were published from 2003 to December 2020.
The distribution of papers over the considered time horizon, as depicted in Fig. 1, shows a compound annual growth rate (CAGR) of 35%. Within the last five years, the CAGR accounted for 58%. This highlights the interest of scholars and practitioners in the intersection of I4.0, CE, SCM and quantitative methods.
4 Bibliometric Analysis
We performed the bibliometric analysis using Biblioshiny software, which uses bibliometrix package of R to generate results. Moreover, data cleaning and data visualisation were completed using MS Excel. The key findings of the bibliometric analysis are discussed in this section.
Figure 2 presents the top 10 journals. These journals accounted for approximately 45% of the total number of articles selected for the study. Journal of Cleaner Production tops the list with 58 articles, closely followed by Sustainability with 53 papers. International Journal of Production Research and International Journal of Production Economics published 17 and 16 studies, respectively. This journal distribution depicts that journals from operations management and sustainability dominate the investigated research domain while journals representing the technology domain are emerging.
Figure 3 depicts the most local cited documents, which illustrates the number of citations an article received from the articles included in the analysed collection (414 papers). The top four local cited documents are research agendas and road maps discussing the intersection of I4.0 technologies and CE/sustainability. This shows the sources where the literature has started evolving in our analysed collection, and these articles provide insights on future research directions.
A thorough scan of the content of these articles listed in Fig. 3 revealed that I4.0 technologies facilitate and enable CE implementation. For instance, Jabbour et al. [15] highlighted that I4.0 technologies may amplify the profit and efficiency by improved productivity whilst facilitating the CE. Despeisse et al. [16] also underlined that 3D printing stimulates more improved sustainable production and consumption while paving the path to enable CE. Moreover, Nascimento et al. [1] emphasised that 3D printing and I4.0 promote the CE and its related practices such as reuse, which extend the lifecycle of a product and recycle, which optimises the consumption of natural resources. It is interesting to see that blockchain also facilitates CE by improving the recycling process through enhanced data tracking and introducing various incentives such as cryptographic tokens in exchange for recyclable bottles and cans [17].
Analysis of the top 10 keywords shown in Fig. 4 reveals that sustainability and supply chains top the table, followed by the CE. AM and BDA were the most frequently discussed I4.0 related technologies. This finding is further aligned with the results of Fig. 3 where articles published by Despeisse et al. [16] and Hazen et al. [18] discuss research agendas related to AM and BDA intersecting CE and sustainable supply chains. I4.0 becoming the fourth in the most used keyword list along with AM and BDA also supports the findings depicted in Fig. 3 as the most local cited article by Jabbour et al. [15] provides a roadmap and research agenda for sustainable operations incorporating I4.0 and CE. Further, after a close investigation of all keywords listed in 414 papers, it is noteworthy that I4.0 technologies such as CPS, cloud computing, autonomous robots, augmented reality, and horizontal and vertical integration are the least explored areas intersecting CE, SCM and quantitative methods related research fields.
Examining the author collaboration network highlighted five main thematic clusters. These clusters include three or more papers per cluster, as shown in Table 1.
Cluster 1 investigates the impacts of BDPA on sustainability performance measures. The effects of I4.0 technologies (specially BDA) on logistics, SSCM, CE performance and CE implementation strategies such as remanufacturing has been studied using SEM in cluster 2. Articles in cluster 3 and 4 employ multiple quantitative methods/techniques such as system dynamics, MCDM methods (e.g., DEMATEL) and mixed integer nonlinear programming. Cluster 3 investigates the barriers, challenges and benefits of I4.0 technologies on sustainability performance, where cluster 4 explores how different quantitative methods can be operationalised to achieve highly efficient logistics services under the I4.0 enabled CE and SSCM environment. Cluster 5 underlines the impacts of digital technologies on sustainability performance while understanding the implications of I4.0 technologies. The comparably low number of studies per cluster suggests that the research potential of these topics is not yet fully exploited.
5 Conclusion and Future Directions
This paper presented a structured review on the intersection of I4.0, CE, SCM and quantitative methods. A comprehensive bibliometric analysis was conducted on this upcoming research arena that paves the path for new research avenues. The results identified the most influential authors, articles and pointed out the evolving research clusters in this intersection of four research fields. The study also identified research agendas and road maps discussing the juncture of I4.0 and CE/SSCM, which were identified as the most cited articles of the investigated scope of our study. Further investigation of these studies highlighted that I4.0 is becoming a digital enabler of CE. I4.0 driven sustainable supply chains and manufacturing supply chains are emerging for future research directions where AM, IoT and BDA are the most prominent technologies discussed in those research fields. Careful investigation of the author collaboration network provided several suggestions for future research opportunities connecting I4.0 with sustainable business models, sustainable operations and sustainability performance focusing CE. Moreover, it is noteworthy to mention that quantitative methods gained a new approach with the introduction of BDA.
References
Nascimento, D.L.M., et al.: Exploring Industry 4.0 technologies to enable circular economy practices in a manufacturing context: a business model proposal. J. Manuf. Technol. Manag. 30, 607–627 (2019)
Rosa, P., Sassanelli, C., Urbinati, A., Chiaroni, D., Terzi, S.: Assessing relations between circular economy and industry 4.0: a systematic literature review. Int. J. Prod. Res. 7543, 0–26 (2019)
Kirchherr, J., Reike, D., Hekkert, M.: Conceptualizing the circular economy: an analysis of 114 definitions. Resour. Conserv. Recycl. 127, 221–232 (2017)
Rajput, S., Singh, S.P.: Connecting circular economy and industry 4.0. Int. J. Inf. Manage. 49, 98–113 (2019)
Xu, L.D., Xu, E.L., Li, L.: Industry 4.0: state of the art and future trends. Int. J. Prod. Res. 56, 2941–2962 (2018)
Rüßmann, M., et al.: Industry 4.0: the future of productivity and growth in manufacturing industries. The Boston Consulting Group (2015)
Machado, C.G., Winroth, M.P., Ribeiro da Silva, E.H.D.: Sustainable manufacturing in Industry 4.0: an emerging research agenda. Int. J. Prod. Res. 58, 1462–1484 (2020).
Fatorachian, H., Kazemi, H.: Impact of Industry 4.0 on supply chain performance. Prod. Plan. Control. 32, 63–81 (2020)
Chauhan, C., Singh, A.: A review of Industry 4.0 in supply chain management studies. J. Manuf. Technol. Manag. 31, 863–886 (2019)
Feng, Y., Zhu, Q., Lai, K.H.: Corporate social responsibility for supply chain management: a literature review and bibliometric analysis. J. Clean. Prod. 158, 296–307 (2017)
Rowley, J., Slack, F.: Conducting a literature review. Manag. Res. News. 27, 31–39 (2004)
Tranfield, D., Denyer, D., Smart, P.: Towards a methodology for developing evidence-informed management knowledge by means of systematic review. Br. J. Manag. 14, 207–222 (2003)
Fahimnia, B., Sarkis, J., Davarzani, H.: Green supply chain management: a review and bibliometric analysis. Int. J. Prod. Econ. 162, 101–114 (2015)
Reike, D., Vermeulen, W.J.V., Witjes, S.: The circular economy : new or refurbished as CE 3.0 ?—exploring controversies in the conceptualization of the circular economy through a focus on history and resource value retention options. Resour. Conserv. Recycl. 135, 246–264 (2018)
Lopes de Sousa Jabbour, A.B., Jabbour, C.J.C., Godinho Filho, M., Roubaud, D.: Industry 4.0 and the circular economy: a proposed research agenda and original roadmap for sustainable operations. Ann. Oper. Res. 270, 273–286 (2018)
Despeisse, M., et al.: Unlocking value for a circular economy through 3D printing: a research agenda. Technol. Forecast. Soc. Change. 115, 75–84 (2017)
Saberi, S., Kouhizadeh, M., Sarkis, J., Shen, L.: Blockchain technology and its relationships to sustainable supply chain management. Int. J. Prod. Res. 57, 2117–2135 (2019)
Hazen, B.T., Skipper, J.B., Ezell, J.D., Boone, C.A.: Big data and predictive analytics for supply chain sustainability: a theory-driven research agenda. Comput. Ind. Eng. 101, 592–598 (2016)
Dubey, R., et al.: Can big data and predictive analytics improve social and environmental sustainability? Technol. Forecast. Soc. Change. 144, 534–545 (2019)
Dubey, R., et al.: Examining the role of big data and predictive analytics on collaborative performance in context to sustainable consumption and production behaviour. J. Clean. Prod. 196, 1508–1521 (2018)
Jeble, S., Dubey, R., Childe, S.J., Papadopoulos, T., Roubaud, D., Prakash, A.: Impact of big data and predictive analytics capability on supply chain sustainability. Int. J. Logist. Manag. 29, 513–538 (2018)
Bag, S., Yadav, G., Wood, L.C., Dhamija, P., Joshi, S.: Industry 4.0 and the circular economy: resource melioration in logistics. Resour. Policy 68, 101776 (2020)
Bag, S., Dhamija, P., Gupta, S., Sivarajah, U.: Examining the role of procurement 4.0 towards remanufacturing operations and circular economy. Prod. Plan. Control. 0, 1–16 (2020).
Bag, S., Gupta, S., Luo, Z.: Examining the role of logistics 4.0 enabled dynamic capabilities on firm performance. Int. J. Logist. Manag. 31, 607–628 (2020)
Ozkan-Ozen, Y.D., Kazancoglu, Y., Mangla, S.K.: Synchronized barriers for circular supply chains in industry 3.5/industry 4.0 transition for sustainable resource management. Resour. Conserv. Recycl. 161 (2020).
Janssen, M., Luthra, S., Mangla, S., Rana, N.P., Dwivedi, Y.K.: Challenges for adopting and implementing IoT in smart cities: an integrated MICMAC-ISM approach. Internet Res. 29, 1589–1616 (2019)
Luthra, S., Kumar, A., Zavadskas, E.K., Mangla, S.K., Garza-Reyes, J.A.: Industry 4.0 as an enabler of sustainability diffusion in supply chain: an analysis of influential strength of drivers in an emerging economy. Int. J. Prod. Res. 58, 1505–1521 (2020)
Liu, S., Zhang, Y., Liu, Y., Wang, L., Wang, X.V.: An ‘Internet of Things’ enabled dynamic optimization method for smart vehicles and logistics tasks. J. Clean. Prod. 215, 806–820 (2019)
Cao, C., Li, C., Yang, Q., Liu, Y., Qu, T.: A novel multi-objective programming model of relief distribution for sustainable disaster supply chain in large-scale natural disasters. J. Clean. Prod. 174, 1422–1435 (2018)
Zhang, Y., Ren, S., Liu, Y., Sakao, T., Huisingh, D.: A framework for big data driven product lifecycle management. J. Clean. Prod. 159, 229–240 (2017)
Li, Y., Dai, J., Cui, L.: The impact of digital technologies on economic and environmental performance in the context of industry 4.0: a moderated mediation model. Int. J. Prod. Econ. 229, 1077 (2020)
Cui, L., Zhai, M., Dai, J., Liu, Y., Zhang, P.: Assessing sustainability performance of high-tech firms through a hybrid approach. Ind. Manag. Data Syst. 119, 1581–1607 (2019)
Acknowledgements
This research has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Innovative Training Networks (H2020-MSCA-ITN-2018) scheme, grant agreement number 814247 (ReTraCE project).
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Hettiarachchi, B.D., Seuring, S., Brandenburg, M. (2021). Industry 4.0 Driven Quantitative Methods for Circular Supply Chains: A Bibliometric Analysis. In: Dolgui, A., Bernard, A., Lemoine, D., von Cieminski, G., Romero, D. (eds) Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems. APMS 2021. IFIP Advances in Information and Communication Technology, vol 632. Springer, Cham. https://doi.org/10.1007/978-3-030-85906-0_44
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