BIG DATA ADOPTION IN KUNMING CONSTRUCTION INDUSTRY, THE PEOPLE’S REPUBLIC OF CHINA: AN EMPIRICAL STUDY
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Date:
28/6/2024
Publisher:
Silpakorn University
Abstract:
This study investigates the current situation, benefits and drawbacks, and primary factors of adopting big data technology in Kunming’s construction industry. Three instruments for investigating were innovated. The first questionnaire asked respondents about the current situation and opinions on adopting big data technology. The second one was a questionnaire asking experts in the construction industry and academic sections their opinions about the gains and losses of adopting technology. The last instrument was a semi-structured interview question about primary factors that need to promote big data technology in the construction industry.
There were three hundred twenty-seven respondents in the first section, ten respondents in the second section, and five interviewees in the last section. The result, analysis, and discussion revealed that adopting big data technology is not proliferating. The main barriers are lack of knowledge, skilled staff, and investment. It also needs to be improved to bridge the gap between construction and building management companies, chiefly by utilizing big data technology. The principal benefit of big data technology is that it facilitates procurement operations of construction projects. The data and analysis help management monitor, control, and award the parties. Please note that internet-of-thing technology is needed to boost big data technology. However, it needs a significant investment.
Lastly, building information modeling (BIM) technology is a primary factor influencing a construction project to implement big data technology. Augmented big data-building information modeling (BD-BIM) is an excellent strategy. BIM helps the adoption of big data technology successfully. Please note that this study not only helps report the situation of technology adoption but also guides the academic section to do more research on the practical framework of big data technology adoption. -
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การจัดการงานวิศวกรรม แผน ก แบบ ก 2
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