A Bibliometric Article Regarding Twin Technology In Technology Management For The Year 2019-2025: Industry In Malaysia

Authors

  • Mazzlida Mat Deli Graduate School of Business, Universiti Kebangsaan Malaysia
  • Ummu Ajirah Abdul Rauf Universiti Kebangsaan Malaysia, Graduate School of Business
  • Maryam Jamilah Asha’ari Graduate School of Business, Universiti Kebangsaan Malaysia
  • Ainul Huda Jamil Graduate School of Business, Universiti Kebangsaan Malaysia
  • Astri Ayu Purwati Faculty of Business, Institut Bisnis dan Teknologi Pelita Indonesia, Indonesia
  • Siti Intan Nurdiana Wong Abdullah Nottingham Business School, Nottingham Trent University
  • Fauziah Ismail Institut Aminuddin Baki, Malaysia

DOI:

https://doi.org/10.37385/jaets.v5i2.3244

Keywords:

Bibliometric, twin technology, technology management, Malaysia

Abstract

The purpose of this research is to analyze the application of digital twin technology in the efficient management of new innovative technology. The research is directed to perform a bibliometric analysis of the subject topic. The relevancy of the research can be underlined by the fact that digital twin technologies are a popular concept of Industry 4.0. In addition, this research is advantageous to identify the application of digital twin technology in efficient technology management, especially in Malaysia. As a scope, it would highlight possible use cases of digital twin technology.  The review of existing literature highlighted that digital twin technology has serious use case potential in supply chain operations. Whereas other scholars argue that digital twin technology can bring out major disruptive innovations to improve the internal competencies of major manufacturing firms. The methodology for the research involves the use of secondary data with bibliometric analysis. It has been identified in the findings that there is a rise in research associated with digital twin technology between the timelines from 2019 to 2022. Furthermore, Chinese Academies are most active in propagating research on variables like digital twins.

Downloads

Download data is not yet available.

References

Aghaei Chadegani, A., Salehi, H., Yunus, M., Farhadi, H., Fooladi, M., Farhadi, M. and Ale Ebrahim, N. (2013), “A comparison between two main academic literature collections: web of science and Scopus databases”, Asian Social Science, 9(5), 18-26.

Agnusdei, G. P., Elia, V., & Gnoni, M. G. (2021). Is digital twin technology supporting safety management? A bibliometric and systematic review. Applied Sciences, 11(6), 2767. https://doi.org/10.3390/app11062767

Agostinelli, S., Cumo, F., Guidi, G., & Tomazzoli, C. (2021). Cyber-physical systems improving building energy management: Digital twin and artificial intelligence. Energies, 14(8), 2338. https://doi.org/10.3390/en14082338

Agouzoul, A., Tabaa, M., Chegari, B., Simeu, E., Dandache, A., & Alami, K. (2021). Towards a digital twin model for building energy management: Case of Morocco. Procedia Computer Science, 184, 404-410. https://doi.org/10.1016/j.procs.2021.03.051

Alharahsheh, H. H., & Pius, A. (2020). A review of key paradigms: Positivism VS interpretivism. Global Academic Journal of Humanities and Social Sciences, 2(3), 39-43. DOI: 10.36348/gajhss.2020.v02i03.001

Ali, J., Jusoh, A. and Abbas, A. F. (2021). “Thirty- Eight Years of ‘Wellbeing’ Research: Bibliometric Analysis of Open Access Documents,” Stud. Appl. Econ., 10, 1–11, doi: 10.25115/eea.v39i10.5412.

Bag, S., Sahu, A. K., Kilbourn, P., Pisa, N., Dhamija, P., & Sahu, A. K. (2022). Modeling barriers of digital manufacturing in a circular economy for enhancing sustainability. International Journal of Productivity and Performance Management, 71(3), 833-869.

Bag, S., Sahu, A.K., Kilbourn, P., Pisa, N., Dhamija, P., Sahu, A.K., 2022. Modeling barriers of digital manufacturing in a circular economy for enhancing sustainability.

Bell, R., & Martin, J. (2012). The relevance of scientific management and equity theory in everyday managerial communication situations. Journal of Management Policy and Practice, 13(3). https://doi.org/10.3390/en14082338

Bhandal, R., Meriton, R., Kavanagh, R. E., & Brown, A. (2022). The application of digital twin technology in operations and supply chain management: a bibliometric review. Supply Chain Management: An International Journal. https://doi.org/10.1108/SCM-01-2021-0053

Bhatti, G., Mohan, H., & Singh, R. R. (2021). Towards the future of smart electric vehicles: Digital twin technology. Renewable and Sustainable Energy Reviews, 141, 110801. https://doi.org/10.1016/j.rser.2021.110801

Bojovi?, S. M. R. P. Z. E. A. (2014). “An overview of forestry journals in the period 2006–2010 as basis for ascertaining research trends,” Scientometrics, 8, 1331–1346.

Dubey, R., Gunasekaran, A., Childe, S. J., Blome, C., & Papadopoulos, T. (2019). Big data and predictive analytics and manufacturing performance: integrating institutional theory, resource?based view and big data culture. British Journal of Management, 30(2), 341-361. https://doi.org/10.1111/1467-8551.12355

Eck, V. and Rousseau, R. (2014). Visualizing bibliometric networks.

Emergen research. (2023). Digital Twin Market, Retrieved from: https://www.emergenresearch.com/industry-report/digital-twin-market [Retrieved on: 8th June 2023]

Fahimnia, B., Sarkis, J. and Davarzani, H. (2015), “Green supply chain management: a review and bibliometric analysis”, International Journal of Production Economics, 162, 101-114.

Fernandez-Prados, J. S., Lozano-Diaz, A., Bernal-Bravo, C. and Muyor-Rodriguez, J. (2021). “Influencers and Social Media: State of the Art and Bibliometric Analysis,” 456–460, doi: 10.1109/iciet51873.2021.9419581.

Gargalo, C. L., Udugama, I., Pontius, K., Lopez, P. C., Nielsen, R. F., Hasanzadeh, A., & Gernaey, K. V. (2020). Towards smart biomanufacturing: a perspective on recent developments in industrial measurement and monitoring technologies for bio-based production processes. Journal of Industrial Microbiology & Biotechnology: Official Journal of the Society for Industrial Microbiology and Biotechnology, 47(11), 947-964. https://doi.org/10.1007/s10295-020-02308-1

GreenTech Malaysia. (2016). Green Technology Financing Scheme: Empowering Green Businesses. https://www.gtfs.my/

Hanim, K., Rasyikah, M. K., Dina, I. S., Syahirah, A. S., & Normawati, H. (2016). Deforestation and haze in Malaysia: Status of corporate responsibility and law governance. European Proceedings of Social and Behavioural Sciences (EpSBS), 374 383. http://dx.doi.org/10.15405/epsbs.2016.11.02.34

Jyeniskhan, N., Keutayeva, A., Kazbek, G., Ali, M. H., & Shehab, E. (2023). Integrating Machine Learning Model and Digital Twin System for Additive Manufacturing. IEEE Access, 11, 71113-71126.

Khalyasmaa, A. I., Stepanova, A. I., Eroshenko, S. A., & Matrenin, P. V. (2023). Review of the Digital Twin Technology Applications for Electrical Equipment Lifecycle Management. Mathematics, 11(6), 1315. https://doi.org/10.3390/math11061315

Kshetri, N. (2021). The Economics of Digital Twins. Computer, 54(4), 86-90. https://doi.org/10.1108/SCM-01-2021-0053

Kwok, P. K., Yan, M., Qu, T., & Lau, H. Y. (2021). User acceptance of virtual reality technology for practicing digital twin-based crisis management. International Journal of Computer Integrated Manufacturing, 34(7-8), 874-887. https://doi.org/10.1080/0951192X.2020.1803502

Liu, W. G. M. H. G. E. A. (2014). “Profile of developments in biomass-based bioenergy research: a 20-year perspective,” Scientometrics, 99, 507–521.

Lu, Y., Liu, C., Kevin, I., Wang, K., Huang, H., & Xu, X. (2020). Digital Twin-driven smart manufacturing: Connotation, reference model, applications and research issues. Robotics and computer-integrated manufacturing, 61, 101837.

Mastos, T. D., Nizamis, A., Terzi, S., Gkortzis, D., Papadopoulos, A., Tsagkalidis, N., ... & Tzovaras, D. (2021). Introducing an application of an industry 4.0 solution for circular supply chain management. Journal of Cleaner Production, 300, 126886.

Park, K. T., Son, Y. H., & Noh, S. D. (2021). The architectural framework of a cyber-physical logistics system for digital-twin-based supply chain control. International Journal of Production Research, 59(19), 5721-5742. https://doi.org/10.1080/00207543.2020.1788738

Phanden, R. K., Aditya, S. V., Sheokand, A., Goyal, K. K., Gahlot, P., & Jacso, A. (2022). A state-of-the-art review on implementation of digital twin in additive manufacturing to monitor and control parts quality. Materials Today: Proceedings, 56, 88-93.

Polyanin, A. V., & Tat'iana, A. G. (2021). The concept of innovation management of industrial systems based on digital twin technology. St. Petersburg State Polytechnical University Journal. Economics, 14(5), 7. DOI:10.18721/JE.14501

Popescu, D., Dragomir, M., Popescu, S., & Dragomir, D. (2022). Building Better Digital Twins for Production Systems by Incorporating Environmental Related Functions—Literature Analysis and Determining Alternatives. Applied Sciences, 12(17), 8657.

Santos, H., Lannelongue, G., & Gonzalez-Benito, J. (2019). Integrating green practices into operational performance: Evidence from Brazilian manufacturers. Sustainability, 11(10), 2956.

Schmidt, A., Helgers, H., Lohmann, L. J., Vetter, F., Juckers, A., Mouellef, M., & Strube, J. (2022). Process analytical technology as a key enabler for digital twins in continuous biomanufacturing. Journal of Chemical Technology & Biotechnology, 97(9), 2336-2346. DOI 10.1002/jctb.7008

Taylor, F. W. (2004). Scientific management. Routledge.

Udugama, A., Öner, M., Lopez, P. C., Beenfeldt, C., Bayer, C., Huusom, J. K., & Sin, G. (2021). Towards Digitalization in Bio-Manufacturing Operations: A Survey on Application of Big Data and Digital Twin Concepts in Denmark. Front. Chem. Eng, 3, 727152. https://doi.org/10.3389/fceng.2021.727152

van der Valk, H., Strobel, G., Winkelmann, S., Hunker, J., & Tomczyk, M. (2022). Supply Chains in the Era of Digital Twins–A Review. Procedia Computer Science, 204, 156-163. https://doi.org/10.1016/j.procs.2022.08.019

Vanalle, R. M., Ganga, G. M. D., Filho, M. G., & Lucato, W. C. (2017). Green supply chain management: An investigation of pressures, practices, and performance within the Brazilian automotive supply chain. Journal of Cleaner Production, 151, 250-259. https://doi.org/10.1016/j.jclepro.2017.03.066

Verbeek, A., Debackere, K., Luwel, M. and Zimmermann, E. (2002), “Measuring progress and evolution in science and technology – I: the multiple uses of bibliometric indicators”, International Journal of Management Reviews, 4(2), 179-211.

V?lchez-Roman, C., Sanguinetti, S. and Mauricio-Salas, M. (2021), “Applied bibliometrics and information visualization for decision-making processes in higher education institutions”, Library Hi Tech, 39(1), 263-283, doi: 10.1108/LHT-10-2019-0209.

Wu, Y.C.J. and Wu, T. (2017), “A decade of entrepreneurship education in the Asia Pacific for future directions in theory and practice”, Management Decision, 55(7), 1333-1350.

Yu, W., Patros, P., Young, B., Klinac, E., & Walmsley, T. G. (2022). Energy digital twin technology for industrial energy management: Classification, challenges, and future. Renewable and Sustainable Energy Reviews, 161, 112407. https://doi.org/10.1016/j.rser.2022.112407

Zhang, Y., Moe, W. W., Schweidel, D. A., Real, E. C., Clara, S. and Moe, W. W. (2016). “Modeling the Role of Message Content and Influencers in Social Media Rebroadcasting,” Int. J. Res. Mark., 1–52, doi: 10.1016/j.ijresmar.2016.07.003.

Zhao, Y., Cao, C., & Liu, Z. (2022). A framework for prefabricated component hoisting management systems based on digital twin technology. Buildings, 12(3), 276. https://doi.org/10.3390/buildings12030276

Downloads

Published

2024-06-06

How to Cite

Deli, M. M., Rauf, U. A. A., Asha’ari, M. J., Jamil, A. H., Purwati, A. A., Abdullah, S. I. N. W., & Ismail, F. (2024). A Bibliometric Article Regarding Twin Technology In Technology Management For The Year 2019-2025: Industry In Malaysia. Journal of Applied Engineering and Technological Science (JAETS), 5(2), 925–940. https://doi.org/10.37385/jaets.v5i2.3244