Industry 4.0, Circular economy, Integration, Sustainability, Future research.


Purpose - To analyze whether the concepts of industry 4.0 and the circular economy are integrated or disjointed, recognizing which keywords are most used in the literature regarding this relationship and the occurrence.  

Design/methodology/approach – A bibliometric study and keyword study were used to recognize which were the most latent actions and strategies in the study of integration. The software VOSviewer was used to study the keywords.

Findings - The concepts of industry 4.0 and the circular economy can be considered interconnected, with some limitations explored in the article, along with proposed future research opportunities on the subject.

Originality/value - This study contributes to business managers in the sense that it facilitates an understanding that industry 4.0 and the circular economy can be used together. The result of the keywords identifies which skills, strategies, technologies and fundamentals the company should develop to make the circular economy effective, through industry 4.0. For academic research, another study has contributed to the integration of industry 4.0 and the circular economy, which is not found very often in the literature. Keywords were also mapped, which, until now, had not been developed in existing articles on integration, in addition to proposing a framework that can be transformed and suggesting research opportunities.

Keywords - Industry 4.0; Circular Economy; Integration; Sustainability; Future research.


Abdella, G.M., Kucukvar, M., Onat, N.C., Al-Yafay, H.M., Bulak, M.E., 2020. Sustainability assessment and modeling based on supervised machine learning techniques: the case for food consumption. J. Cl. Prod. 251, 119661. DOI:

Aberkane, I.J., 2017. From waste to kwaste: on the blue economy in terms of knowledge flow. Spring. Proceed. Compl., 283-290. DOI:

Adeogba, E., Barty, P., O’Dwyer, E., Guo, M., 2019. Waste-to-resource transformation: gradient boosting modeling for organic fraction municipal solid waste projection. ACS Sus. Chem. Eng. 7 (12), 10460-10466. DOI:

Ahmed, S., Huang, B., 2019. Control engineering practice in 25 years: a bibliometric overview. Cont. Eng. Prac. 88 (July),16-20. DOI:

Allenby, B., 2009. The industrial ecology of emerging technologies complexity and the reconstruction of the world. J. Ind. Ecol. 13 (2), 168-183. DOI:

Babiceanu, R.F.; Seker, R., 2016. Big data and virtualization for manufacturing cyber-physical systems: a survey of the current status and future outlook. Comp. Ind. 81, 128-137. DOI:

Bahrin, M.A.K., Othman, M.F., Azli, N.H.N., Talib, M.F, 2016. Industry 4.0: a review on industrial automation and robotic. Sc. Eng. 78 (6-13), 137-143. DOI:

Bendul, J.C., Blunck, H., 2019. The design space of production planning and control for industry 4.0. Comp. Ind. 105, 260-272. DOI:

Blomsma, F., 2018. Collective ‘action recipes’ in a circular economy – on waste and resource management frameworks and their role in collective change. J. Cl. Prod. 199, 969-982. DOI:

Blomsma, F., Brennan, G., 2017. The emergence of circular economy: a new framing around prolonging resource productivity. J. Ind. Ecol. 21 (3), 603-614. DOI:

Bressanelli, G., Adrodegari, F., Perona, M., Saccani, N., 2018. Exploring how usage-focused business models enable circular economy through digital technologies. Sustain. 10 (639), 1-21. (a) DOI:

Bressanelli, G., Adrodegari, F., Perona, M., Saccani, N., 2018. The role of digital technologies to overcome circular economy challenges im PSS business models: an exploratory case study. Procedia CIRP 73, 216-221. (b) DOI:

Castelo-Branco, I., Cruz-Jesus, F., Oliveira, T., 2019. Assessing industry 4.0 readiness in manufacturing: evidence for the European Union. Comp. Ind. 107, 22-32. DOI:

Chertow, M. R., 2000. Industrial symbiosis: literature and taxonomy. Annu. Rev. Energy Envir. 25, 313-337. DOI:

Chertow, M. R., 2007. “Uncovering” industrial symbiosis. J. Ind. Ecol. 11(1), 11-30. DOI:

Cole, R.J., 2012. Regenerative design and development: current theory and practice. Build. Res. Inf. 40 (1), 1-6. DOI:

Conti, M., Orcioni, S., 2019. Cloud-based sustainable management of electrical and electronic equipment from production to end-of-life. Int. J. Qual. Relia. Man., 36 (1), 98-119. DOI:

Díaz Lantada, A., Blas Romero, A., Sánchez Isasi, A., Garrido Bellido, D., 2017. Design and performance assessment of innovative eco-efficient support structures for additive manufacturing by photopolymerization. J. Ind. Eco., 21, S179-190. DOI:

Dinis, F.M., Sanhudo, L., Martins, J.P., Ramos, N.M.M., 2020. Improving project communication in the architecture, engineering and construction industry: coupling virtual reality and laser scanning. J. Build. Eng., 30, 101287. DOI:

Eglash, R., Robert, L., Bennett, A., Robinson, K.P., Lachney, M., Babbitt, W., 2019. Automation for the artisanal economy: enhancing the economic and environmental sustainability of crafting professions with human-machine collaboration. AI Soci., Article in press. DOI:

Ehrenfeld, J., Gertler, N., 1997. Industrial ecology in practice: the evolution of interdependence at Kalundborg. J. Ind. Ecol 1(1), 67-79. DOI:

Ellen MacArthur Foundation, 2015. Delivering the circular economy: a toolkit for policymakers. Available at: (accessed 21.05.19).

Ellen MacArthur Foundation, 2017. Infographic: Circular Economy Systems Diagram. Available at: (accessed 10.05.19).

Ellegaard, O., Wallin, J.A., 2015. The bibliometric analysis of scholarly production: how great is the impact?. Scientometrics 105, 1809-1831. DOI:

Ellis, L.A., Churruca, K., Clay-Williams, R., Pomare, C., Austin, E.E., Long, J.C., Grodahl, A., Braithwaite, J., 2019. Patterns of resilience: a scoping review and bibliometric analysis of resilient health care. Saf. Scie. 118 (October), 241-257. DOI:

Faroukhi, A.Z., El Alaoui, I., Gahi, Y., Amine, A., 2020. Big data monetization throughout big data value chain comprehensive. J. Big Data 7(1), 3. DOI:

Francis, J., Bian, L., 2019. Deep learning for distortion prediction in laser-based additive manufacturing using Big Data. Manuf. Let. 20, 10-14. DOI:

Frank, A.G., Dalenogare, L.S., Ayala, N.F., 2019. Industry 4.0 technologies: implementation patterns in manufacturing companies. Int. J. Prod. Econ. 210, 15-26. DOI:

Froemelt, A., Buffat, R., Hellweg, S., 2019. Machine learning based modeling of households: a regionalized bottom-up approach to investigate consumption-induced environmental impacts. J. Ind. Ecol., Article in press, 1-14. DOI:

Gabajová, G., Furmannová, B., Medvecká, I., Grznár, P., Krajcovic, M., Furmann, R., 2019. Virtual training application by use of augmented and virtual reality under university technology enhanced learning in Slovakia. Sust., 11 (23), 6677. DOI:

Garcia-Muinã, F.E., González-Sánchez, R., Ferrari, A.M., Settembre-Blundo, D., 2018. The paradigms of industry 4.0 and circular economy as enabling drivers for the competitiveness of businesses and territories: the case of an Italian ceramic tiles manufacturing company. Soc. Sci. 7 (255), 1-31. DOI:

Garcia-Muinã, F.E., González-Sanchez, R., Ferrari, A.M., Volpi, L., Pini, M., Siligardi, C., Settembre-Blundo., D. 2019. Identifying the equilibrium point between sustainability goals and circular economy practices in an industry 4.0 manufacturing context using eco-design. Soc. Sci. 8 (8), 241. DOI:

Gattullo, M., Scurati, G.W., Fiorentino, M., Uva, A.E., Ferrise, F., Bordegoni, M., 2019. Towards augmented reality manuals for industry 4.0: a methodology. Rob. Comp. Int. Manuf 56, 276-286. DOI:

Gazzola, P., Del Campo, A.G., Onyango, V., 2019. Going green vs going smart for sustainable development: quo vadis?. J. Cl. Produc. 214, 881-892. DOI:

Geisendorf, S., Pietrulla, F., 2018. The circular economy and circular economic concepts – a literature analysis and redefinition. Thunderbird Intern. Bus. Rev. 60(5), 771-782. DOI:

Geissdoerfer, M., Savaget, P., Bocken, N.M.P., Hultink, E.J., 2017. The circular economy – a new sustainability paradigm? J. Cl. Prod. 143, 757-768. DOI:

Ghadimi, P., Wang, C., Lim, M.K., Heavey, C, 2019. Intelligent sustainable supplier selection using multi-agent technology: theory and application for industry 4.0 supply chains. Comp. Ind. Eng, 127, 588-600. DOI:

Ghazal, M., Akmal, M., Yyanna, S., Ghoudi, K., 2016. Smart plugs: perceived usefulness and satisfactions: evidence from United Arab Emirates. Renew. Sust. Ener. Rev., 55, 1248-1259.Ghisellini, P., Cialani, C., Ulgiati, S., 2016. A review on circular economy: the expected transition to a balanced interplay of environmental and economic systems. J. Cl. Prod. (114), 11-32. DOI:

Ghobakhloo, M., 2018. The future of manufacturing industry: a strategic roadmap toward industry 4.0. J. Manuf. Tech. Manag. 29 (6), 910-936. DOI:

Gobbo Júnior, J.A., Busso, C.M., Gobbo, S.C.O., Carreão, H., 2018. Making the links among environmental protection, process safety, and industry 4.0. Process Saf. Environ. Prot. 117, 372-382. DOI:

González-Amarillo, C.A., Cárdenas-García, C.L., Mendoza-Moreno, M.A., 2018. M2M system for efficient water consumption in sanitary services, based on intelligent environment. DYNA, 85 (204), 311-318. DOI:

Grey, C.P., Tarascon, J.M., 2017. Sustainability and in situ monitoring in battery development. Nat. Mat. 16, 45-56. DOI:

Gu, F., Guo, J., Hall, P., Gu, X., 2019. An integrated architecture DOI:

for implementing extended producer responsibility in the context of Industry 4.0. Int.

J. Prod. Res., 57(5), 1458-1477.

Hafezalkotob, A., Hafezalkotob, A., Liao, H., Herrera, F., 2019. An overview of MULTIMOORA for multi-criteria decision-making: theory, developments, applications, and challenges. Inf. Fus. 51, 145–177. DOI:

Hermann, M., Pentek, T., Otto, B., 2016. Design principles for Industrie 4.0 scenarios. 2016 49th Hawaii International Conference on Systems Sciences, 3928-3937. DOI:

Hofmann, E., Rusch, M., 2017. Industry 4.0 and the current status as well as future DOI:

prospects on logistics. Comp. Ind. 89, 23–34.

Huang, K., Guo, J., Xu, Z., 2009. Recycling of waste printed circuit boards: a review of current technologies and treatment status in China. J. Hazard. Mat. 164, 399-408. DOI:

Issamar, F.H.M.K., Roberto, R.L., 2019. New and emerging occupational risks (NER) in industry 4.0: literature review. 2019 7th Int. Eng., Sc. Tech. Conf., 8943671, 394-399.

Ivanov, D., Dolgui, A., Sokolov. B., 2019. The impact of digital

technology and industry 4.0 on the ripple effect and supply chain risk analytics. Int. J. Prod. Res. 57 (3), 829-846. DOI:

Jabbour, C.J.C., Sousa Jabbour, A.B.L., Sarkis, J., Godinho Filho, M., 2017. Unlocking the circular economy through new business models based on large-scale data: an integrative framework and research agenda. Tech. For. Soc. Change (In Press), 1-7.

Jabbour, C.J.C., Sarkis, J., Sousa Jabbour, A.B.L, Renwick, D.W.S., Singh, S.K, Grebinevych, O., Kruglianskas, I., Godinho Filho, M., 2019. Who is in charge? A review and a research agenda on the ‘human side” of the circular economy. J. Cl. Prod. 222, 793 -801. DOI:

Jazdi, N., 2014. Cyber physical systems in the context of industry 4.0. 19th International Conference on Automation, Quality and Testing, Robotics, 3732-3735. DOI:

Jensen, J.P., Remmen, A., 2017. Enabling circular economy through product stewardship. Proc. Manuf. 8, 377-384. DOI:

Jiang, W., Wen, L., Zhan, J., Jiang, K., 2020. Design optimization of confidentiality-critical cyber physical systems with fault detection. J. Sys. Arch. 107, 101739. DOI:

Kagermann, H., Helbig, J., Hellinger, A., Wahlster, W., 2013. Recommendations for implementing the strategic initiative industrie 4.0: final report of the industrie 4.0 working group. ACATECH – National Academy of Science and Engineerring, 1-97. DOI:

Kamble, S.S., Gunasekaran, A., Sharma, R., 2018. Analysis of the driving and dependence power of barriers to adopt industry 4.0 in Indian manufacturing industry. Comp. in Ind. 101, 107-119. DOI:

Kamdem J.P., Duarte, A.E., Lima K.R.R., Rocha, J.B.T., Hassan, W., Barros, L.M., Roederd, T., Tsopmo, A., 2019. Research trends in food chemistry: a bibliometric review of its 40 years anniversary (1976–2016). Food Chem. 294, 448-457. DOI:

Kang, H.S., Lee, J.Y., Choi, S-S., Kim, H., Park, J.H., Son, J.Y., Kim, B.H., Do Noh, S. 2016. Smart manufacturing: past research, present findings, and future directions. International Journal of Precision Engineering and Manufacturing - Green Technology 3, 111-128. DOI:

Kang, L., Du, H.L., Zhang, H., Ma, W.L., 2018. Systematic research on the application of steel slag resources under the background of big data. Comp., 2018, 6703908, 1-12. DOI:

Kirkham, T., Armstrong, D., Djemame, K., Jiang, M., 2014. Risk driven smart home resources management using cloud services. Fut. Gen. Comp. Syst., 38, 13-22. DOI:

Kopnina, H., 2019. Green-washing or best case practices? Using circular economy and Cradle to Cradle case studies in business education. J. Cl. Prod 219, 613-621. DOI:

Kuznetsova, E., Zio, E., Farel, R., 2016. A methodological framework for eco-industrial park design and optimization. J. Cl. Prod., 126, 308-324. DOI:

Langmann, R., Rojas-Pena, L., 2016. PLCs as industry 4.0 components in laboratory applications. Int. J. Onl. Eng. 12 (7), 37-44. DOI:

Lasi, H., Fettke, P., Kemper, H.G, Feld, T., Hoffman, M., 2014. Industrie 4.0. Busin. Inform. Syst. Eng 4, 239-242. DOI:

Lawal, I.A., Klink, M., Ndungu, P., Moodley, B., 2019. Brief bibliometric analysis of “ionic liquid” applications and its review as a substitute for common adsorbent modifier for the adsorption of organic pollutants. Envir. Res. 175, 34–51. DOI:

Lee, J., Bagheri, B., Kao, H., 2015. A cyber-physical systems architecture for industry 4.0-based manufacturing sytems. Manufact. Letters 3, 18-23. DOI:

Lee, J., Kao, H.A, Yang, S., 2015. Service innovation and smart analytics for industry 4.0 and big data environment. Procedia CIRP 16, 3-8. DOI:

Lenzen, M., Geschke, A., Wiedmann, T., Lane, J., Anderson, N., Baynes, T., Boland, J., Daniels, P., Dey, C., Fry, J., Hadjikakou, M., Kenway, S., Malik, A., Moran, D., Murray, J., Nettleton, S., Poruschi, L., Reynolds, C., Rowley, H., Ugon, J., Webb, D., West, J., 2014. Compiling and using input-output frameworks through collaborative virtual laboratories. Sci. Total Envir. 485-486, 241-251. DOI:

Lieder, M., Asif, F.M.A., Rashid, A., Mihelic, A., Kotnik, S., 2017. Towards circular economy implementation in manufacturing systems using a multi-method simulation approach to link design and business strategy. Int. J. Adv. Manuf. Technol 93, 1953-1970. DOI:

Lieder, M., Rashid, A., 2016. Towards circular economy implementation: a comprehensive review in context of manufacturing industry. J. Cl. Prod. 115, 36-51. DOI:

Lin, K.Y., 2018. User experience-based product design for smart production to empower industry 4.0 in the glass recycling circular economy. Comp. Ind. Eng. 125, 729–738.López-Robles, J.R., Otegi-Olaso, J.R., Porto Gómez, I., Cobo, M.J., 2019. 30 years of intelligence models in management and business: a bibliometric review. Inter. J. Info. Mana. 48, 22–38. DOI:

Lu, Y., Xu, X., 2019. Cloud-based manufacturing equipment and big data analytics to enable on-demand manufacturing services. Rob. Comp. Int. Manuf. 57, 92-102.Luthra, S., Magla, S.K., 2018. Evaluating challenges to industry 4.0 initiatives for supply chain sustainability in emerging economies. Process Saf. Environ. Prot. 117, 168-179. DOI:

Lyle Center, 2019. History. Available at: (accessed 18.05.19).

Mami, F., Revéret, J-P., Fallaha, S., Margni, M., 2017. Evaluating eco-efficiency of 3D printing in the aeronautic industry. J. Ind. Eco., 21, S37-S48. DOI:

Manavalan, E., Jayakrishna, K., 2019. A review of internet of things (IoT) embedded sustainable supply chain for industry 4.0 requirements. Comp. Ind. Eng. 127, 925–953. DOI:

Marques, G., Pitarma, R., 2019. An internet of things approach for environmental quality management and laboratory activity support. CISTI, 8760876. DOI:

Martín-Gómez, A., Aguayo-González, F., Luque, A., 2019. A holonic framework for managing the sustainable supply chain in emerging economies with smart connected metabolism. Res., Cons. Recy. 141, 219-232. DOI:

Massod, T., Egger, J., 2019. Augmented reality in support of industry 4.0 – implementation challenges and success factors. Rob. Comp. Int. Manuf. 58, 181-195. DOI:

Mavi, R., Saen, R.F., Goh, M., 2019. Joint analysis of eco-efficiency and eco-innovation with common weights in two-stage network DEA: a big data approach. Tech. For. Soc. Ch., 144, 553-562. DOI:

Mirabella, N., Castellani, V., Sala, S., 2014. Current options for the valorization of food manufacturing waste: a review. J. Cl. Prod 65, 28-41. DOI:

Moeuf, A., Pellerin, R., Lamouri, S., Giraldo, Tamayo, S., Barbaray, R., (2018). The industrial management of SMEs in the era of industry 4.0. Int. J. Prod. Res., 56 (3), 1118-1136. DOI:

Munodawafa, R.T., Johl, S.K., 2019. Big data analytics capabilities and eco-innovation: a study of energy companies. Sust., 11 (15), 4254. DOI:

Naderi, M., Ares, E., Peláez, G., Prieto, D., Araújo, M., 2019. Sustainable operations management for industry 4.0 and its social return. IFAC-Papers on line, 52 (13), 457-462. DOI:

Nascimento, D.L.M., Alencastro, V., Quelhas, O.L.G., Caiado, R.G.G., Garza-Reyes, J.A., Lona, L.R., Tortorella, G., (2019). Exploring industry 4.0 technologies to enable circular economy practices in a manufacturing context: a business model proposal. J. Manuf. Tech. Manag. 30 (3), 607-627. DOI:

Nasir, M.H.A., Genovese, A., Acquaje, A.A., Koh, S.C.L., Yamoah, F., 2017. Comparing linear and circular supply chains: a case study from the construction industry. Int. J. Prod. Econ. 183 (B), 443-457. DOI:

Okorie, O., Salonitis, K., Charnley, F., Moreno, M., Turner, C., Tiwari, A., 2018. Digitisation and the circular economy: a review of current research and future trends. Energies 11 (3009), 1-31. DOI:

Pistol, L., Tonis (Bucea-Manea), R., 2017. The “7Ps” & “1G” that rule in the digital world the marketing mix. 11th Int. Conf. Bus. Exc., 11 (1), 759-769. DOI:

Potting, J., Hekkert, M., Worrell, E., Hanemaaijer, A., 2017. Circular economy: measuring innovation in the product chain. PBL Netherlands Envir. Assess. Agency (2544), 1-46.

Póvoa, P., Oehmen, A., Inocêncio, P., Matos, J.S., Frazão, A., 2017. Modelling energy costs for different operational strategies of a large water resource recovery facility. Wat. Sci. Tech., 75 (9), 2139-2148. DOI:

Rajput, S., Singh, S.P, 2019. Connecting circular economy and industry 4.0. Int. J. Inf. Manag. 49, 98–113. DOI:

Redeker, G.A., Kessler, G.Z., Kipper, L.M., 2019. Lean information for lean communication: Analysis of concepts, tools, references, and terms. Inter. J. Info. Mana. 47, 31–43. DOI:

Rojas Luiz, J.V., Jugend, D., Jabbour, C.J.C., Rojas Luiz, O., Bernardi De Souza, F. (2016). Ecodesign field of research throughout the world: mapping the territory by using an evolutionary lens. Scientometrics 109, 241-259 DOI:

Rose, D.C., Chilvers, J., 2018. Agriculture 4.0: broadening responsible innovation in an era of smart farming. Front. Sust. Food Syst., 2, 87. DOI:

Ross, S.A., Cheah, L., 2019. Uncertainty quantification in life cycle assessments: exploring distribution choice and greater data granularity to characterize product use. J. Ind. Ecol., 23 (2), 335-346. DOI:

Salah, B., Abidi, M.H., Mian, S.H., Krid, M., Alkhalefah, H., Abdo, A., 2019. Virtual reality-based engineering education to enhance manufacturing sustainability in industry 4.0. Sust. 11 (1477), 2-19. DOI:

Sahimaa, O. et al (2017). Towards zero climate emissions, zero waste, and one planet living – testing the applicability of three indicators in Finnish cities. Sust. Prod. Consu., 10, 121-132. DOI:

Shahrokni, H., Ârman, L., Lazarevic, D., Nilsson, A., Brandt, N., 2015. Implementing smart urban metabolism in the Stockholm Royal Seaport: smart city SRS. J. Ind. Ecol., 19 (5), 917-929. DOI:

Shrouf, F., Ordieres, J., Miragliotta, G., 2014. Smart factories in industry 4.0: a review of the concept and of energy management approached in production based on the internet of things paradigm. IEEE International Conference on Industrial Engineering and Engineering Management, 697-701. DOI:

Singh, S.P., Singh, R.K., Gunasekaran. A., Ghadimi, P., 2019. Supply chain management, industry 4.0, and the circular economy. Res., Cons. Recy. 142, 281–282. DOI:

Song, B., Yeo, Z., Kohls, P., Herrmann, C., 2017. Industrial symbiosis: exploring big-data approach for waste stream discovery. Proc. CIRP 61, 353-358. DOI:

Sony, M., 2018. Industry 4.0 and lean management: a proposed DOI:

integration model and research propositions. Prod. Manuf. Res. 6(1), 416-432.

Sousa Jabbour, A.B.L., Jabbour, C.J.C., Foropona, C., Godinho Filho, M., 2018. When titans meet – can industry 4.0 revolutionise the environmentally sustainable manufacturing wave? The role of critical success factors. Tech. For. Soc. Change 132 (July), 18-25. (a) DOI:

Sousa Jabbour, A.B.L., Jabbour, C.J.C., Godinho Filho, M., Roubaud, D., 2018. Industry 4.0 and the circular economy: a proposed research agenda and original roadmap for sustainable operations. Ann. Oper. Res. 270, 273-286. (b) DOI:

Stabel, W.R., 2010. The performance economy. Palgrave Macmilan, Basingstoke, UK.

Stock, T., Seliger, G., 2016. Opportunities of sustainable manufacturing in industry 4.0. Procedia CIRP 40, 536-541. DOI:

Strandhagen, J.W., Alfnes, E., Strandhagen, J.O., Vallandingham, L.R., 2017. The fit of industry 4.0 applications in manufacturing logistics: a multiple case study. Adv. Manuf. 5, 344-358. DOI:

Su, B., Heshmati, A., Geng, Y., Yu, X., 2013. A review of the circular economy in China: moving from rhetoric to implementation. J. Cl. Prod. 42, 215-227. DOI:

Swain, B., 2017. Recovery and recycling of lithium: a review. Sep. Pur. Tech. 172, 388-403. DOI:

Thurer, M. Pan, Y.H., Qu, T., Luo, H., Li, C.D., Huang, G.Q., 2019. Internet of things (IoT) driven kanban system for reverse logistics: solid waste collection. J. Intel. Manuf., 30 (7), 2621-2630. DOI:

Timma, L., Blumberga, A., Blumberga, D., 2015. Combined and mixed methods research in environmental engineering: when two is better than one. Ener. Proc., 72, 300-306. DOI:

Tseng, M.L., Tan, R.R., Chiu, A.S.F., Chien, C.F., Kuo, T.C, 2018. Circular economy meets industry 4.0: can big data drive industrial symbiosis? Res., Cons. Recy. 131, 146-147. DOI:

Tseng, M.L., Chiu, A.S.F., Chien, C.F., Tan, R.R., 2019. Pathways and barriers to circularity in food systems. Res., Cons. Recy. 143, 236-237. DOI:

Tukker, A., 2015. Product services for a resource-efficient and circular economy – a review. J. Cl. Prod. 97, 76-91. DOI:

United Nations Environment Programme (UNEP), 2014. Towards a circular economy: program to end waste in Europe.

Van Eck, N.J., Waltman, L., 2010. Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics 84 (2), 523-538. DOI:

Wahrmann, D., Hildebrandt, A.C., Schuetz, C., Wittmann, R., Rixen, D., 2019. An autonomous and flexible robotic framework for logistics applications. J. Int. Rob. Sys. 93, 419-431. DOI:

Wakiyama, T., Lenzen, M., Geschke, A., Bamba, R., Nansai, K., 2020. A flexible multiregional input-output database for city-level sustainability footprint analysis in Japan. Res., Cons. Recy., 154, 104588. DOI:

Wang, H., Yang, Y., 2019. Neighbourhood walkability: a review and bibliometric analysis. Cities 93 (October), 43-61. DOI:

Wan, J., Tang, S., Shu, Z., Li, D., Wang, S., Imran, M., Vasilakos, A.V., 2016. Software-defined industrial internet of things in the context of industry 4.0. IEE Sens. J. 16 (20), 7373-7380. DOI:

Wang, S., Wan, J., Zhang, D., Li, D., Zhang, C., 2016. Towards smart factory for industry 4.0: a self-organized multi-agent system with big data based feedback and coordination. Comp. Net. 101, 158-168. DOI:

Wollschlaeger, M., Sauter, T., Jasperneite, J., 2017. The future of industrial communication: automation networks in the era of the internet of things and industry 4.0. IEE Ind. Elect. Mag., 17-27. DOI:

Xu, M., Cai, H., Liang, S., 2015. Big data and industrial ecology. J. Ind. Ecol., 19 (2), 205-210. DOI:

Yang, S., Raghavendra, A.M. R., Kaminski, J., Pepin, H., 2018. Opportunities for industry 4.0 to support remanufacturing. Appl. Sci. 8 (1177), 2-11. DOI:

Yazdi, P.G., Azizi, A., Hashemipour, M., 2018. An empirical investigation of the relationship between overall equipment efficiency (OEE) and manufacturing sustainability in industry 4.0 with time study approach. Sust. 10 (3031), 1-28. DOI:

Yi, L., Glatt, M., Sridhar, P., Payrebrune, K., Linke, B.S., Ravani, B., Aurich, J.C., 2020. An eco-design for additive manufacturing framework based on energy performance assessment. Addit. Manuf., 33, 101120. DOI:

Yuan, Z., Bi, J., Moriguichi, Y., 2006. The circular economy: a new development strategy in China. J. Ind. Ecol. 10 (1-2), 4-8.Zezulka, F., Marcon, P., 2016. Industry 4.0 – an introduction in the phenomenon. IFAC-Papers on Line 49 (25), 8-12. DOI:

Zhan, Z.H., Liu, X.F., Gong, Y.J., Zhang, J., Ching, H.S.H, Li, Y., 2015. Cloud Computing resource schediling and survey of its evolutionary approaches. ACM Comp. Sur. 47 (4), 63-63:33. DOI:

Zhang, C., Romagnoli, A., Zhou, L., Kraft, M., 2017. Knowledge management of eco-industrial park for efficient energy utilization through ontology-based approach. App. Ener., 204, 1412-1421. DOI:

Zhang, Z., Huisingh, D., 2017. Carbon dioxide storage schemes: technology, assessment and deployment. J. Cl. Prod., 142, 1055-1064. DOI:




Como Citar

Agudo, F. L., Gobbo Júnior, J. A., & Oliveira Gobbo, S. C. de. (2020). INDUSTRY 4.0 AND THE CIRCULAR ECONOMY: ARE THESE INTEGRATED OR DISJOINTED CONCEPTS? A RESEARCH AGENDA. Revista Gestão Da Produção Operações E Sistemas, 15(4), 48.