Implementation of Blockchain Technology in Construction Project Management: A Contemporary Approach
Article Sidebar
-
Blockchain Technology, Construction Projects, Contemporary Approach
Abstract
The construction industry is a sector known for its complexity in terms of project management. The involvement of various parties, the large flow of information, and the challenge of maintaining data validity are major challenges. In an effort to improve efficiency and transparency, blockchain technology is emerging as a potential solution. However, the applicability of this technology in the context of construction project management still requires further research. Research Objectives: This study aims to investigate the possibility and potential application of blockchain technology in construction project management. The main focus is to understand how this technology can improve efficiency, transparency, and data reliability in various aspects of construction project management. Research Methods: This research utilized a qualitative approach with descriptive analysis. Data was collected through a review of related literature as well as case studies of blockchain technology implementation in construction project management in several large-scale projects. An in-depth analysis was conducted to understand the challenges, benefits, and key factors affecting successful implementation. Research Results: The results show that blockchain technology has great potential in improving efficiency and transparency in construction project management. By utilizing features such as distributed ledgers, smart contracts, and secure transaction confirmation, the project management process can become more structured, efficient, and trustworthy. Research Conclusion: In the context of construction project management, the implementation of blockchain technology offers an attractive solution to address existing challenges. Although there are still some technical and policy hurdles that need to be overcome, the long-term potential of this technology in improving the productivity and quality of construction projects is promising. Therefore, strategic steps need to be taken to encourage wider adoption of this technology in the construction industry.
Full text article
References
Abd-alrazaq, A., AlSaad, R., Alhuwail, D., Ahmed, A., Healy, P. M., Latifi, S., Aziz, S., Damseh, R., Alabed Alrazak, S., & Sheikh, J. (2023). Large Language Models in Medical Education: Opportunities, Challenges, and Future Directions. JMIR Medical Education, 9, e48291. https://doi.org/10.2196/48291
Alma Çall?, B., & Ediz, Ç. (2023). Top concerns of user experiences in Metaverse games: A text-mining based approach. Entertainment Computing, 46, 100576. https://doi.org/10.1016/j.entcom.2023.100576
Andoni, M., Robu, V., Flynn, D., Abram, S., Geach, D., Jenkins, D., McCallum, P., & Peacock, A. (2019). Blockchain technology in the energy sector: A systematic review of challenges and opportunities. Renewable and Sustainable Energy Reviews, 100, 143–174. https://doi.org/10.1016/j.rser.2018.10.014
Besser, A., Flett, G. L., & Zeigler-Hill, V. (2022). Adaptability to a sudden transition to online learning during the COVID-19 pandemic: Understanding the challenges for students. Scholarship of Teaching and Learning in Psychology, 8(2), 85–105. https://doi.org/10.1037/stl0000198
Biswas, S. (2023). ChatGPT and the Future of Medical Writing. Radiology, 307(2), e223312. https://doi.org/10.1148/radiol.223312
Caselli, D., & Aricò, M. (2020). 2019-nCoV: Polite with Children! Pediatric Reports, 12(1), 8495. https://doi.org/10.4081/pr.2020.8495
Casino, F., Dasaklis, T. K., & Patsakis, C. (2019). A systematic literature review of blockchain-based applications: Current status, classification and open issues. Telematics and Informatics, 36, 55–81. https://doi.org/10.1016/j.tele.2018.11.006
Cunningham, F., Achuthan, P., Akanni, W., Allen, J., Amode, M. R., Armean, I. M., Bennett, R., Bhai, J., Billis, K., Boddu, S., Cummins, C., Davidson, C., Dodiya, K. J., Gall, A., Girón, C. G., Gil, L., Grego, T., Haggerty, L., Haskell, E., … Flicek, P. (2019). Ensembl 2019. Nucleic Acids Research, 47(D1), D745–D751. https://doi.org/10.1093/nar/gky1113
Demuyakor, J. (2020). Coronavirus (COVID-19) and Online Learning in Higher Institutions of Education: A Survey of the Perceptions of Ghanaian International Students in China. Online Journal of Communication and Media Technologies, 10(3), e202018. https://doi.org/10.29333/ojcmt/8286
Dong, H., & Liu, Y. (2023). Metaverse Meets Consumer Electronics. IEEE Consumer Electronics Magazine, 12(3), 17–19. https://doi.org/10.1109/MCE.2022.3229180
Dube, B. (2020). Rural online learning in the context of COVID 19 in South Africa: Evoking an inclusive education approach. Multidisciplinary Journal of Educational Research, 10(2), 135. https://doi.org/10.17583/remie.2020.5607
Dubey, J. P. (2021). Toxoplasmosis of Animals and Humans (3rd ed.). CRC Press. https://doi.org/10.1201/9781003199373
Dwivedi, Y. K., Kshetri, N., Hughes, L., Slade, E. L., Jeyaraj, A., Kar, A. K., Baabdullah, A. M., Koohang, A., Raghavan, V., Ahuja, M., Albanna, H., Albashrawi, M. A., Al-Busaidi, A. S., Balakrishnan, J., Barlette, Y., Basu, S., Bose, I., Brooks, L., Buhalis, D., … Wright, R. (2023). Opinion Paper: “So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy. International Journal of Information Management, 71, 102642. https://doi.org/10.1016/j.ijinfomgt.2023.102642
Falke, C. (2021). Hopes for Reading in the Era of Globalization. Pedagogy, 21(3), 505–520. https://doi.org/10.1215/15314200-9131896
Favale, T., Soro, F., Trevisan, M., Drago, I., & Mellia, M. (2020). Campus traffic and e-Learning during COVID-19 pandemic. Computer Networks, 176, 107290. https://doi.org/10.1016/j.comnet.2020.107290
Gosal, A. S., Geijzendorffer, I. R., Václavík, T., Poulin, B., & Ziv, G. (2019). Using social media, machine learning and natural language processing to map multiple recreational beneficiaries. Ecosystem Services, 38, 100958. https://doi.org/10.1016/j.ecoser.2019.100958
Hao, J., & Ho, T. K. (2019). Machine Learning Made Easy: A Review of Scikit-learn Package in Python Programming Language. Journal of Educational and Behavioral Statistics, 44(3), 348–361. https://doi.org/10.3102/1076998619832248
Howe, K. L., Achuthan, P., Allen, J., Allen, J., Alvarez-Jarreta, J., Amode, M. R., Armean, I. M., Azov, A. G., Bennett, R., Bhai, J., Billis, K., Boddu, S., Charkhchi, M., Cummins, C., Da Rin Fioretto, L., Davidson, C., Dodiya, K., El Houdaigui, B., Fatima, R., … Flicek, P. (2021). Ensembl 2021. Nucleic Acids Research, 49(D1), D884–D891. https://doi.org/10.1093/nar/gkaa942
Jan, B., Farman, H., Khan, M., Imran, M., Islam, I. U., Ahmad, A., Ali, S., & Jeon, G. (2019). Deep learning in big data Analytics: A comparative study. Computers & Electrical Engineering, 75, 275–287. https://doi.org/10.1016/j.compeleceng.2017.12.009
Kapasia, N., Paul, P., Roy, A., Saha, J., Zaveri, A., Mallick, R., Barman, B., Das, P., & Chouhan, P. (2020). Impact of lockdown on learning status of undergraduate and postgraduate students during COVID-19 pandemic in West Bengal, India. Children and Youth Services Review, 116, 105194. https://doi.org/10.1016/j.childyouth.2020.105194
Kim, J., & Bae, J. (2023). Influences of persona self on luxury brand attachment in the Metaverse context. Asia Pacific Journal of Marketing and Logistics. https://doi.org/10.1108/APJML-05-2022-0390
Kraus, M., Feuerriegel, S., & Oztekin, A. (2020). Deep learning in business analytics and operations research: Models, applications and managerial implications. European Journal of Operational Research, 281(3), 628–641. https://doi.org/10.1016/j.ejor.2019.09.018
Lapitan, L. Ds., Tiangco, C. E., Sumalinog, D. A. G., Sabarillo, N. S., & Diaz, J. M. (2021). An effective blended online teaching and learning strategy during the COVID-19 pandemic. Education for Chemical Engineers, 35, 116–131. https://doi.org/10.1016/j.ece.2021.01.012
Lauriola, I., Lavelli, A., & Aiolli, F. (2022). An introduction to Deep Learning in Natural Language Processing: Models, techniques, and tools. Neurocomputing, 470, 443–456. https://doi.org/10.1016/j.neucom.2021.05.103
Li, X., Jiang, P., Chen, T., Luo, X., & Wen, Q. (2020). A survey on the security of blockchain systems. Future Generation Computer Systems, 107, 841–853. https://doi.org/10.1016/j.future.2017.08.020
Martin, F., Sun, T., & Westine, C. D. (2020). A systematic review of research on online teaching and learning from 2009 to 2018. Computers & Education, 159, 104009. https://doi.org/10.1016/j.compedu.2020.104009
Meng, L., Hua, F., & Bian, Z. (2020). Coronavirus Disease 2019 (COVID-19): Emerging and Future Challenges for Dental and Oral Medicine. Journal of Dental Research, 99(5), 481–487. https://doi.org/10.1177/0022034520914246
Pardo, A., Jovanovic, J., Dawson, S., Gaševi?, D., & Mirriahi, N. (2019). Using learning analytics to scale the provision of personalised feedback. British Journal of Educational Technology, 50(1), 128–138. https://doi.org/10.1111/bjet.12592
Payal, R., Sharma, N., & Dwivedi, Y. K. (2024). Unlocking the impact of brand engagement in the metaverse on Real-World purchase intentions: Analyzing Pre-Adoption behavior in a futuristic technology platform. Electronic Commerce Research and Applications, 65, 101381. https://doi.org/10.1016/j.elerap.2024.101381
Saberi, S., Kouhizadeh, M., Sarkis, J., & Shen, L. (2019). Blockchain technology and its relationships to sustainable supply chain management. International Journal of Production Research, 57(7), 2117–2135. https://doi.org/10.1080/00207543.2018.1533261
Sallam, M. (2023). ChatGPT Utility in Healthcare Education, Research, and Practice: Systematic Review on the Promising Perspectives and Valid Concerns. Healthcare, 11(6), 887. https://doi.org/10.3390/healthcare11060887
Selwyn, N. (2019). What’s the Problem with Learning Analytics? Journal of Learning Analytics, 6(3). https://doi.org/10.18608/jla.2019.63.3
Shadiev, R., & Yang, M. (2020). Review of Studies on Technology-Enhanced Language Learning and Teaching. Sustainability, 12(2), 524. https://doi.org/10.3390/su12020524
Spernjak, A. (2021). Using ICT to Teach Effectively at COVID-19. 2021 44th International Convention on Information, Communication and Electronic Technology (MIPRO), 617–620. https://doi.org/10.23919/MIPRO52101.2021.9596878
Van Den Berghe, R., Verhagen, J., Oudgenoeg-Paz, O., Van Der Ven, S., & Leseman, P. (2019). Social Robots for Language Learning: A Review. Review of Educational Research, 89(2), 259–295. https://doi.org/10.3102/0034654318821286
Wang, C., Pan, R., Wan, X., Tan, Y., Xu, L., Ho, C. S., & Ho, R. C. (2020). Immediate Psychological Responses and Associated Factors during the Initial Stage of the 2019 Coronavirus Disease (COVID-19) Epidemic among the General Population in China. International Journal of Environmental Research and Public Health, 17(5), 1729. https://doi.org/10.3390/ijerph17051729
Wei, H.-C., & Chou, C. (2020). Online learning performance and satisfaction: Do perceptions and readiness matter? Distance Education, 41(1), 48–69. https://doi.org/10.1080/01587919.2020.1724768
Yates, A. D., Achuthan, P., Akanni, W., Allen, J., Allen, J., Alvarez-Jarreta, J., Amode, M. R., Armean, I. M., Azov, A. G., Bennett, R., Bhai, J., Billis, K., Boddu, S., Marugán, J. C., Cummins, C., Davidson, C., Dodiya, K., Fatima, R., Gall, A., … Flicek, P. (2019). Ensembl 2020. Nucleic Acids Research, gkz966. https://doi.org/10.1093/nar/gkz966
Yudiawan, A., Sunarso, B., Suharmoko, S., Sari, F., & Ahmadi, A. (2021). Successful online learning factors in COVID-19 era: Study of Islamic higher education in West Papua, Indonesia. International Journal of Evaluation and Research in Education (IJERE), 10(1), 193. https://doi.org/10.11591/ijere.v10i1.21036
Zhang, Z., Xiao, Y., Ma, Z., Xiao, M., Ding, Z., Lei, X., Karagiannidis, G. K., & Fan, P. (2019). 6G Wireless Networks: Vision, Requirements, Architecture, and Key Technologies. IEEE Vehicular Technology Magazine, 14(3), 28–41. https://doi.org/10.1109/MVT.2019.2921208
Authors
Copyright (c) 2024 Xie Guilin, Kailie Maharjan, Elladdadi Mark
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.