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Industry 4.0 Technologies Promote Micro-Level Circular Economy but Neglect Strong Sustainability in Textile Industry

Author

Listed:
  • Geraldo Cardoso de Oliveira Neto

    (Business Administration and Industrial Engineering Post-Graduation Program, FEI University, Tamandaré Street, 688—5 Floor, Liberdade, Sao Paulo 01525-000, Brazil)

  • Luiz Fernando Rodrigues Pinto

    (Industrial Engineering Post-Graduation Program, Universidade Nove de Julho (UNINOVE), Vergueiro Street, 235/249—12 Floor, Liberdade, Sao Paulo 01504-001, Brazil)

  • Dirceu de Silva

    (Department of Cultural Practices of Campinas University (UNICAMP), Street Bertrand Russell, 801, Cidade Universitária, Sao Paulo 13083-865, Brazil)

  • Flavio Luiz Rodrigues

    (Business Administration and Industrial Engineering Post-Graduation Program, FEI University, Tamandaré Street, 688—5 Floor, Liberdade, Sao Paulo 01525-000, Brazil)

  • Fabio Richard Flausino

    (Industrial Engineering Post-Graduation Program, Universidade Nove de Julho (UNINOVE), Vergueiro Street, 235/249—12 Floor, Liberdade, Sao Paulo 01504-001, Brazil)

  • Douglas Eldo Pereira de Oliveira

    (Industrial Engineering Post-Graduation Program, Universidade Nove de Julho (UNINOVE), Vergueiro Street, 235/249—12 Floor, Liberdade, Sao Paulo 01504-001, Brazil)

Abstract

Large textile industries are deploying Industry 4.0 Technologies (I4.0T) aiming to develop a micro-level circular economy (CECP), considering cleaner production practices as a strategic tool. However, due to the environmental impact generated by the textile industry, it has not yet achieved Strong Sustainability (SS), denoting an important path to be pursued by managers and shareholders in view of meeting the 2030 agenda. With this, the objective of this study is to evaluate whether the adoption of I4.0T promotes CECP-driving SS actions in large textile industries located in Brazil. A survey was the research method adopted, and for data analysis, structural equation modeling was used to test the hypotheses and Pearson correlation between variables. It was concluded that the adoption of I4.0T promotes CECP. However, they neglect SS actions. Facilitators for CECP practices were big data, augmented reality, and autonomous robots. In terms of SS, I4.0T has a low impact on increasing resource consumption efficiency, reusing waste as input in other processes, and increasing access to commodities. This research contributes to the linking I4.0T, CECP, and SS theory. Moreover, with the dissemination of knowledge to managers about the I4.0T that generates the CECP, it is possible to develop sustainable strategies in operations. However, to move in this direction, it is essential that there is a collective effort of the government, companies, and society, starting by raising awareness about the importance of SS in the textile sector.

Suggested Citation

  • Geraldo Cardoso de Oliveira Neto & Luiz Fernando Rodrigues Pinto & Dirceu de Silva & Flavio Luiz Rodrigues & Fabio Richard Flausino & Douglas Eldo Pereira de Oliveira, 2023. "Industry 4.0 Technologies Promote Micro-Level Circular Economy but Neglect Strong Sustainability in Textile Industry," Sustainability, MDPI, vol. 15(14), pages 1-23, July.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:14:p:11076-:d:1194827
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    References listed on IDEAS

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    1. Joseph F. Hair & G. Tomas M. Hult & Christian M. Ringle & Marko Sarstedt & Kai Oliver Thiele, 2017. "Mirror, mirror on the wall: a comparative evaluation of composite-based structural equation modeling methods," Journal of the Academy of Marketing Science, Springer, vol. 45(5), pages 616-632, September.
    2. Korhonen, Jouni & Honkasalo, Antero & Seppälä, Jyri, 2018. "Circular Economy: The Concept and its Limitations," Ecological Economics, Elsevier, vol. 143(C), pages 37-46.
    3. Sarstedt, Marko & Hair, Joseph F. & Ringle, Christian M. & Thiele, Kai O. & Gudergan, Siegfried P., 2016. "Estimation issues with PLS and CBSEM: Where the bias lies!," Journal of Business Research, Elsevier, vol. 69(10), pages 3998-4010.
    4. Behnam Fahimnia & Joseph Sarkis & Angappa Gunasekaran & Reza Farahani, 2017. "Decision models for sustainable supply chain design and management," Annals of Operations Research, Springer, vol. 250(2), pages 277-278, March.
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