الگوی پذیرش فناوری‌های نسل چهارم در صنعت قطعه‌‌سازی خودروی ایران

نوع مقاله : مقاله پژوهشی

نویسندگان

1 گروه مدیریت صنعتی، واحد کرج، دانشگاه آزاد اسلامی ، کرج، ایران

2 گروه مدیریت صنعتی، واحدکرج، دانشگاه آزاد اسلامی، کرج، ایران

3 گروه مدیریت صنعتی، واحد کرج، دانشگاه آزاد اسلامی، کرج، ایران.

چکیده

فناوری‌های صنعت چهارم می‌تواند باعث افزایش کارایی، تقویت استفاده از ظرفیت کامل تولید، کاهش هزینه‌ها و در نتیجه بهبود سودآوری شرکت‌ها شود. درک عوامل تاثیرگذار بر پذیرش این فناوری‌ها کمک فراوانی به شرکت‌های تولیدی جهت سرمایه‌گذاری در این حوزه می‌کند. این پژوهش با هدف ارائه الگوی پذیرش فناوری‌های صنعت چهارم در شرکت‌های قطعه‌سازی خودروی ایران انجام شده ‌است. جهت رسیدن به هدف در این پژوهش از روش تحقیق آمیخته اکتشافی در دو بخش کیفی و کمی استفاده شده است. بدین صورت که ابتدا 86 مقاله مرتبط با استفاده از روش فراترکیب بررسی و عوامل موثر بر پذیرش فناوری‌های صنعت چهارم در صنایع شناسایی شدند. سپس در مرحله دلفی با کمک 15 نفر ازخبرگان این حوزه، این عوامل بومی‌سازی و غربالگری شدند. در بخش کمی از طریق رویکرد مدل‌سازی معادلات ساختاری و روش کمترین مربعات جزئی، داده‌های حاصل از پرسشنامه تجزیه و تحلیل و الگوی نهایی ارائه شد. بر اساس نتایج این پژوهش 38 شاخص در قالب 11 بعد و 4 عامل اصلی "سازمانی"، "صنعتی"، "ملی" و "بین‌المللی" به عنوان عوامل موثر بر پذیرش فناوری‌های صنعت چهارم در شرکت‌های قطعه‌سازی خودروی ایران شناسایی شدند.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

The pattern of Industry 4.0 technologies adoption in Iran's auto parts manufacturing companies

نویسندگان [English]

  • Mohammad Hadi Rashmei 1
  • Mehrdad Hosseini Shakib 2
  • Abbas Khamseh 3
1 Department of Industrial management, karaj branch, Islamic Azad University, Karaj, Iran
2 Department of industrial management, Karaj Branch, Islamic Azad University, Karaj, Iran.
3 Department of Industrial Management, Karaj Branch, Islamic Azad University, Karaj, Iran.
چکیده [English]

Industry 4.0 technologies can increase efficiency, promote the use of full production capacity, reduce costs, and thus improve the profitability of companies. Knowing the factors affecting the adoption of these technologies will greatly help manufacturing companies to invest in this field. This research aims to provide a pattern of adoption of Industry 4.0 technologies in Iran's auto part companies. In order to achieve the goal in this research, a mixed exploratory research method has been used in two stages, qualitative and quantitative. In this way, first, 86 related articles were reviewed using the metasynthesis method and the factors affecting the adoption of Industry 4.0 technologies in industries were identified. Then, in the Delphi phase, with the help of 15 experts in this field, these factors were localized and screened. In the quantitative stage, the data obtained from the analysis questionnaire and the final model were presented using the structural equation modeling approach using the partial least squares method. Based on the results, 38 indicators in the form of 11 dimensions and 4 main factors "organizational", "industrial", "national" and "international" were identified as effective factors on the adoption of Industry 4.0 technologies in Iran's auto part companies.

کلیدواژه‌ها [English]

  • Industry 4.0 technologies
  • Technology adoption
  • Metasynthesis method
  • Delphi method
Adebanjo, D., Laosirihongthong, T., Samaranayake, P., & Teh, P. L. (2021). Key enablers of   industry 4.0 development at firm level: Findings from an emerging economy. IEEE Transactions on Engineering Management. https://doi.org/10.1109/TEM.2020.3046764
Ahadiani, M., Masoudi, O. A., Malaek, S. M. B., & Majidi Gahroudi, N. (2022). Identifying the Drivers and Propellants of IoT Application in the Management of Iran's Aviation Industry [In Persian]. Karafan Quarterly Scientific Journal, 19(Special Issue), 597-618. Doi: 10.48301/kssa.2022.316253.1870
Alsaadi, N. (2022). Modeling and Analysis of Industry 4.0 Adoption Challenges in the Manufacturing Industry. Processes, 10(10), 2150.‏ https://doi.org/10.3390/pr10102150
Attiany, M., Al-kharabsheh, S., Abed-Qader, M., Al-Hawary, S., Mohammad, A., & Rahamneh, A. (2023). Barriers to adopt industry 4.0 in supply chains using interpretive structural modeling. Uncertain Supply Chain Management, 11(1), 299-306. http://growingscience.com/beta/uscm/5849-barriers-to-adopt-industry-40-in-supply-chains-using-interpretive-structural-modeling.html
Bai, C., Dallasega, P., Orzes, G., & Sarkis, J. (2020). Industry 4.0 technologies assessment: A sustainability perspective. International journal of production economics, 229, 107776. https://doi.org/10.1016/j.ijpe.2020.107776
Bajic, B., Rikalovic, A., Suzic, N., & Piuri, V. (2020). Industry 4.0 implementation challenges and opportunities: A managerial perspective. IEEE Systems Journal, 15(1), 546-559. https://doi.org/10.1109/JSYST.2020.3023041
Barclay, D., Higgins, C., & Thompson, R. (1995). The partial least squares (PLS) approach to causal modeling: Personal computer adoption and use as an illustration. Technology studies.
Bholane, Kishor. (2023). Adoption, Status and Environmental Sustainability of Industry 4.0 in India.8.865-870. https://www.researchgate.net/publication/367053196_Adoption_Status_and_Environmental_Sustainability_of_Industry_40_in_India
Birkel, H. S., Veile, J. W., Müller, J. M., Hartmann, E., & Voigt, K. I. (2019). Development of a risk framework for Industry 4.0 in the context of sustainability for established manufacturers. Sustainability, 11(2), 384. https://doi.org/10.3390/su11020384
Cassia, F., & Ferrazzi, M. (2018). The economics of cars. Newcastle upon Tyne: Agenda publishing. https://doi.org/10.1017/9781911116738
Čater, T., Čater, B., Černe, M., Koman, M. and Redek, T. (2021).Industry 4.0 technologies usage: motives and enablers. Journal of Manufacturing Technology Management, Vol. 32 No. 9, pp. 323-345. https://doi.org/10.1108/JMTM-01-2021-0026
Chauhan, C., Singh, A., & Luthra, S. (2021). Barriers to industry 4.0 adoption and its performance implications: An empirical investigation of emerging economy. Journal of Cleaner Production, 285, 124809.‏‏ https://doi.org/10.1016/j.jclepro.2020.124809
Chin, W. W. (1998). The partial least squares approach to structural equation modeling. Modern methods for business research, 295(2), 295-336. https://books.google.com/
Cordeiro, R. F., Reis, L. P., & Fernandes, J. M. (2023). A study on the barriers that impact the adoption of Industry 4.0 in the context of Brazilian companies. The TQM Journal. https://doi.org/10.1108/TQM-07-2022-0239
Cronbach, L. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16(3), 297-334. https://doi.org/10.1007/BF02310555
Davari, A., & Rezazadeh, A. (2014). Structural equation modeling by PLS [In Persian]. University Jihad Publishing Organization. https://www.isba.ir/Default/BookDetail/18601
Drost, E. A. (2011). Validity and reliability in social science research. Education Research and Perspectives, 38(1), 105–123. https://search.informit.org/doi/10.3316/informit.491551710186460
Ferreira, J. J., Lopes, J. M., Gomes, S., & Rammal, H. G. (2023). Industry 4.0 implementation: Environmental and social sustainability in manufacturing multinational enterprises. Journal of Cleaner Production, 404, 136841. https://doi.org/10.1016/j.jclepro.2023.136841
Fettermann, D. C., Cavalcante, C. G. S., Almeida, T. D. D., & Tortorella, G. L. (2018). How does Industry 4.0 contribute to operations management? Journal of industrial and Production Engineering, 35(4), 255-268. https://doi.org/10.1080/21681015.2018.1462863
Gadekar, R., Sarkar, B., & Gadekar, A. (2022). Investigating the relationship among Industry 4.0 drivers, adoption, risks reduction, and sustainable organizational performance in manufacturing industries: An empirical study. Sustainable Production and Consumption, 31, 670-692. https://doi.org/10.1016/j.spc.2022.03.010
Gallab, M., Bouloiz, H., Kebe, S. A., & Tkiouat, M. (2021). Opportunities and challenges of the Industry 4.0 in industrial companies: A survey on Moroccan firms. Journal of Industrial and Business Economics, 48(3), 413-439. https://doi.org/10.1007/s40812-021-00190-1
Geisser, S. (1974). A Predictive Approach to the Random Effects Model, Biometrika, 61(1): 101-107. https://doi.org/10.1093/biomet/61.1.101
Ghadimi, P., Donnelly, O., SAR, K., Wang, C., & Azadnia, A. H. (2022). The successful implementation of industry 4.0 in manufacturing: An analysis and prioritization of risks in Irish industry.Technological Forecasting and Social Change, 175, 121394. https://doi.org/10.1016/j.techfore.2021.121394
Ghobakhloo, M., Iranmanesh, M., Vilkas, M., Grybauskas, A., & Amran, A. (2022). Drivers and barriers of Industry 4.0 technology adoption among manufacturing SMEs: a systematic review and transformation roadmap. Journal of Manufacturing Technology Management, (ahead-of-print).‏ https://doi.org/10.1108/JMTM-12-2021-0505
Ghosh, R. K., Banerjee, A., Aich, P., Basu, D., & Ghosh, U. (2022). Intelligent IoT for Automotive Industry 4.0: Challenges, Opportunities, and Future Trends. Intelligent Internet of Things for Healthcare and Industry, 327-352. https://doi.org/10.1007/978-3-030-81473-1_16
Govindan, K., & Arampatzis, G. (2023). A framework to measure readiness and barriers for the implementation of Industry 4.0: A case approach. Electronic Commerce Research and Applications, 59, 101249. https://doi.org/10.1016/j.elerap.2023.101249
Habraken, M., & Bondarouk, T. (2020). Embracing variety in decision-making regarding adoption of industry 4.0. Administrative Sciences, 10(2), 30. https://doi.org/10.3390/admsci10020030
Hair Jr, J. F., Hult, G. T. M., Ringle, C. M., Sarstedt, M., Danks, N. P., & Ray, S. (2021). Partial least squares structural equation modeling (PLS-SEM) using R: A workbook (p. 197). Springer Nature.https://doi.org/10.1007/978-3-030-80519-7
Havle, C. A., & Üçler, Ç. (2018). Enablers for industry 4.0. In 2018 2nd International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT).‏‏ Ankara, Turkey, 2018, pp. 1-6, doi: 10.1109/ISMSIT.2018.8567293.
Hayat, A., Shahare, V., Sharma, A. K., & Arora, N. (2023). Introduction to Industry 4.0. In Blockchain and its Applications in Industry 4.0 (pp. 29-59). Singapore: Springer Nature Singapore. https://doi.org/10.1007/978-981-19-8730-4_2
Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the academy of marketing science, 43, 115-135. https://doi.org/10.1007/s11747-014-0403-8
Himang, C., Ocampo, L., Obiso, J. J., Bongo, M., Caballes, S. A., Abellana, D. P. ... & Ancheta, R. (2020). Defining stages of the Industry 4.0 adoption via indicator sets. Engineering Management in Production and Services, 12(2), 32-55. https://doi.org/10.2478/emj-2020-0010
Hulland, J. (1999). Use of partial least squares (PLS) in strategic management research: a review of four recent studies. Strategic management journal, 20(2), 195-204. https://doi.org/10.1002/ (SICI) 1097
Jain, V., & Ajmera, P. (2020). Modelling the enablers of industry 4.0 in the Indian manufacturing industry. International Journal of Productivity and Performance Management.‏‏ https://doi.org/10.1108/IJPPM-07-2019-0317
Javaid, M., Khan, S., Haleem, A., & Rab, S. (2022). Adoption of modern technologies for implementing industry 4.0: an integrated MCDM approach. Benchmarking: An International Journal, (ahead-of-print). https://doi.org/10.1108/BIJ-01-2021-0017
Karabegović, I., Karabegović, E., Mahmić, M., & Husak, E. (2021). The application of Industry 4.0 in production processes of the automotive industry. J. Mobil. Vehicle, University of Kragujevac, Faculty of Engineering, Kragujevac, Serbia, 47(2), 35-44. DOI: 10.24874/mvm.2021.47.02.02
Karbasi, S., Hashemzadeh Khoorasgani, G., Khamseh, A., & Fathi Hafshejani, K. (2022). Identifying and Prioritizing the Key Effective Factors on the Industry 4.0 Technology Roadmap with an Approach to Economic Productivity Development in Power Planet Equipment and Energy Supply Industries [In Persian]. Quarterly Journal of Applied Theories of Economics, 9(3), 203-230. Doi: 10.22034/ecoj.2022.46363.2896
Kendall, M. G., & Smith, B. B. (1939). The Problem of m Rankings. The Annals of Mathematical Statistics, 10(3), 275–287. http://www.jstor.org/stable/2235668
Khanahmadloo, R., zoghi S. (2022). Identifying Barriers and Drivers of Virtual Reality Technology Adoption in order to create a Virtual Command and Control System: A Case Study of a Military Organization [In Persian]. C4I Journal, 5(4), 23-42. http://ic4i-journal.ir/article-1-301-fa.html
Khin, S. and Kee, D.M.H. (2022). Factors influencing Industry 4.0 adoption. Journal of Manufacturing Technology Management, Vol. 33 No. 3, pp. 448-467. https://doi.org/10.1108/JMTM-03-2021-0111
Khin, S., & Hung Kee, D. M. (2022). Identifying the driving and moderating factors of Malaysian SMEs’ readiness for Industry 4.0. International Journal of Computer Integrated Manufacturing, 35(7), 761-779. https://doi.org/10.1080/0951192X.2022.2025619
Krishnan, S., Gupta, S., Kaliyan, M., Kumar, V., & Garza-Reyes, J. A. (2021). Assessing the key enablers for Industry 4.0 adoption using MICMAC analysis: a case study. International Journal of Productivity and Performance Management, 70(5), 1049-1071. https://doi.org/10.1108/IJPPM-02-2020-0053
Kumar, R., Singh, R. K., & Dwivedi, Y. K. (2020). Application of industry 4.0 technologies in SMEs for ethical and sustainable operations: Analysis of challenges. Journal of cleaner production, 275, 124063. https://doi.org/10.1016/j.jclepro.2020.124063
Kumar, S., Raut, R. D., Aktas, E., Narkhede, B. E., & Gedam, V. V. (2022). Barriers to adoption of industry 4.0 and sustainability: a case study with SMEs. International Journal of Computer Integrated Manufacturing, 1-21. https://doi.org/10.1080/0951192X.2022.2128217
Le, V. L. T., Nguyen, T. H., & Pham, K. D. (2023). What Drives Industry 4.0 Technologies Adoption? Evidence from a SEM-Neural Network Approach in the Context of Vietnamese Firms. Sustainability, 15(7), 5969. https://doi.org/10.3390/su15075969
Liu, C., Li, W., Lian, J., & Yin, Y. (2012). Reconfiguration of assembly systems: From conveyor assembly line to serus. Journal of Manufacturing Systems, 31(3), 312-325. https://doi.org/10.1016/j.jmsy.2012.02.003
Maisiri, W., van Dyk, L., & Coeztee, R. (2021). Factors that inhibit sustainable adoption of Industry 4.0 in the South African manufacturing industry. Sustainability, 13(3), 1013.‏ https://doi.org/10.3390/su13031013
Mohajan, H. (2019). The first industrial revolution: Creation of a new global human era. https://mpra.ub.uni-muenchen.de/id/eprint/96644
Mohajan, H. (2021). Third industrial revolution brings global development. https://mpra.ub.uni-muenchen.de/id/eprint/110972
Moktadir, M. A., Ali, S. M., Kusi-Sarpong, S., & Shaikh, M. A. A. (2018). Assessing challenges for implementing Industry 4.0: Implications for process safety and environmental protection. Process safety and environmental protection, 117, 730-741.‏ https://doi.org/10.1016/j.psep.2018.04.020
Mokyr, J. (1992). The lever of riches: Technological creativity and economic progress. Oxford University Press. https://academic.oup.com/book/10218
Obermayer, N., Csizmadia, T., & Hargitai, D. M. (2022). Influence of Industry 4.0 technologies on corporate operation and performance management from human aspects. Meditari accountancy research, 30(4), 1027-1049. DOI: 10.1108/MEDAR-02-2021-1214
Obiso, J. J. A., Himang, C. M., Ocampo, L. A., Bongo, M. F., Caballes, S. A. A., Abellana, D. P. M., ... & Jr, R. A. (2019). Management of Industry 4.0–reviewing intrinsic and extrinsic adoption drivers and barriers. International Journal of Technology Management, 81(3-4), 210-257.‏ https://doi.org/10.1504/IJTM.2019.105310
ÖZCAN, N. A., SEVİNÇ, A., Şeyda, G. Ü. R., ÖZCAN, E., & Tamer, E. R. E. N. (2020). Evaluation of the Transition Process of Industry 4.0 in Automotive Supplier Industry. Başkent Üniversitesi Ticari Bilimler Fakültesi Dergisi, 4(2), 1-18. https://dergipark.org.tr/en/pub/jcsci/issue/57092/710652
Öztürk, Ö. (2023). Analysis of industry 4.0 technologies’ adoption using interpretive structural modelling: empirical findings from manufacturing sector in Turkey (Master's thesis, Middle East Technical University). https://hdl.handle.net/11511/102145
Pasi, B. N., Mahajan, S. K., & Rane, S. B. (2022). Development of innovation ecosystem framework for successful adoption of industry 4.0 enabling technologies in Indian manufacturing industries. Journal of Science and Technology Policy Management, 13(1), 154-185. https://doi.org/10.1108/JSTPM-10-2020-0148
Petrillo, A., De Felice, F., Cioffi, R., & Zomparelli, F. (2018). Fourth industrial revolution: Current practices, challenges, and opportunities. Digital transformation in smart manufacturing, 1, 1-20. DOI: 10.5772/intechopen.72304
Rad, F. F., Oghazi, P., Palmié, M., Chirumalla, K., Pashkevich, N., Patel, P. C., & Sattari, S. (2022). Industry 4.0 and supply chain performance: A systematic literature review of the benefits, challenges, and critical success factors of 11 core technologies. Industrial Marketing Management, 105, 268-293. https://doi.org/10.1016/j.indmarman.2022.06.009
Raj, A., Dwivedi, G., Sharma, A., de Sousa Jabbour, A. B. L., & Rajak, S. (2020). Barriers to the adoption of industry 4.0 technologies in the manufacturing sector: An inter-country comparative perspective. International Journal of Production Economics, 224, 107546. https://doi.org/10.1016/j.ijpe.2019.107546
Rezqianita, B. L., & Ardi, R. (2020, June). Drivers and barriers of industry 4.0 adoption in Indonesian manufacturing industry. In Proceedings of the 3rd Asia Pacific Conference on Research in Industrial and Systems Engineering 2020 pp. 123-128.‏ https://doi.org/10.1145/3400934.3400958.
Rojas-Berrio, S., Rincon-Novoa, J., Sánchez-Monrroy, M., Ascúa, R., & Montoya-Restrepo, L. A. (2022). Factors influencing 4.0 technology adoption in manufacturing SMEs in an emerging country. Journal of Small Business Strategy, 32(3), 67-83. http://dx.doi.org/10.53703/001c.34608
Sandelowski, M., & Barroso, J. (2006). Handbook for synthesizing qualitative research. Springer publishing company.
Sayem, A., Biswas, P. K., Khan, M. M. A., Romoli, L., & Dalle Mura, M. (2022). Critical Barriers to Industry 4.0 Adoption in Manufacturing Organizations and Their Mitigation Strategies. Journal of Manufacturing and Materials Processing, 6(6), 136.‏ https://doi.org/10.3390/jmmp6060136
Schmidt, R. C. (1997). Managing Delphi surveys using nonparametric statistical techniques. Decision Sciences, 28(3), 763-774. https://doi.org/10.1111/j.1540-5915.1997.tb01330.x
Schmidt, R., Möhring, M., Härting, R. C., Reichstein, C., Neumaier, P., & Jozinović, P. (2015). Industry 4.0-potentials for creating smart products: empirical research results. In Business Information Systems: 18th International Conference, BIS 2015, Poznań, Poland, June 24-26, 2015, Proceedings 18 (pp. 16-27). Springer International Publishing. https://link.springer.com/chapter/10.1007/978-3-319-19027-3_2
Senna, P. P., Ferreira, L. M. D., Barros, A. C., Roca, J. B., & Magalhães, V. (2022). Prioritizing barriers for the adoption of Industry 4.0 technologies. Computers & Industrial Engineering, 171, 108428.‏‏ https://doi.org/10.1016/j.cie.2022.108428
Singh, A., Kumar, V., Verma, P., & Kandasamy, J. (2022). Identification and severity assessment of challenges in the adoption of industry 4.0 in Indian construction industry. Asia Pacific Management Review. https://doi.org/10.1016/j.apmrv.2022.10.007
Stone, M. (1974). Cross-Validatory Choice and Assessment of Statistical Predictions. Journal of the Royal Statistical Society, 36(2): pp 111-147. https://doi.org/10.1111/j.2517-6161.1974.tb00994.x
Stornelli, A., Ozcan, S., & Simms, C. (2021). Advanced manufacturing technology adoption and innovation: A systematic literature review on barriers, enablers, and innovation types. Research Policy, 50(6), 104229.‏ https://doi.org/10.1016/j.respol.2021.104229
Straub, E. T. (2009). Understanding technology adoption: Theory and future directions for informal learning. Review of educational research, 79(2), 625-649. https://doi.org/10.3102/0034654308325896
Subramanian, G., Patil, B. T., & Gardas, B. B. (2021). Evaluation of enablers of cloud technology to boost industry 4.0 adoption in the manufacturing micro, small and medium enterprises. Journal of Modelling in Management, 16(3), 944-962. https://doi.org/10.1108/JM2-08-2020-0207
Tamvada, J. P., Narula, S., Audretsch, D., Puppala, H., & Kumar, A. (2022). Adopting new technology is a distant dream? The risks of implementing Industry 4.0 in emerging economy SMEs. Technological Forecasting and Social Change, 185, 122088.‏ https://doi.org/10.1016/j.techfore.2022.122088
Ullah, F., Sepasgozar, S. M., Thaheem, M. J., & Al-Turjman, F. (2021). Barriers to the digitalisation and innovation of Australian Smart Real Estate: A managerial perspective on the technology non-adoption. Environmental Technology & Innovation, 22, 101527.‏ https://doi.org/10.1016/j.eti.2021.101527
Vinzi, V., Trinchera, L., & Amato, S. (2010). PLS path modeling: from foundations to recent developments and open issues for model assessment and improvement, in Handbook of partial least squares. Springer, 47-82. https://doi.org/10.1007/978-3-540-32827-8_3
Virmani, N., Salve, U. R., Kumar, A., & Luthra, S. (2021). Analyzing roadblocks of Industry 4.0 adoption using graph theory and matrix approach. IEEE Transactions on Engineering Management. https://doi.org/10.1109/TEM.2020.3048554
Vuksanović Herceg, I., Kuč, V., Mijušković, V. M., & Herceg, T. (2020). Challenges and driving forces for industry 4.0 implementation. Sustainability, 12(10), 4208.‏‏ https://doi.org/10.3390/su12104208
Wankhede, V. A., & Vinodh, S. (2021). Analysis of industry 4.0 challenges using best worst method: A case study. Computers & Industrial Engineering, 159, 107487. https://doi.org/10.1016/j.cie.2021.107487
Wong, A. P. H., & Kee, D. M. H. (2022). Driving Factors of Industry 4.0 Readiness among Manufacturing SMEs in Malaysia. Information, 13(12), 552. https://doi.org/10.3390/info13120552
Yang, M., Fu, M., & Zhang, Z. (2021). The adoption of digital technologies in supply chains: Drivers, process and impact. Technological Forecasting and Social Change, 169, 120795. https://doi.org/10.1016/j.techfore.2021.120795
Zheng, T., Ardolino, M., Bacchetti, A., & Perona, M. (2021). The applications of Industry 4.0 technologies in manufacturing context: a systematic literature review. International Journal of Production Research, 59(6), 1922-1954. https://doi.org/10.1080/00207543.2020.1824085