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Abstract : Perpustakaan Tuanku Bainun |
This study aimed to examine the technological innovation and its effect on operation
efficiency of the Oil and Gas Sector of the United Arab Emirates. The causal research
design was employed through quantitative research methodology, using selfadministered
online surveys for data collection. The purposive sampling technique
selected 253 respondents of 5 ADNOC group and its subsidiaries from ADNOC
Onshore, ADNOC Offshore, ADNOC Drilling, ADNOC Sour Gas and ADNOC LNG..
The study used regression, correlational, and descriptive statistics to analyse the
proposed conceptual framework where after regression, Advanced Robotics
significantly predicted OPE, F(1, 251) = 590.627, p < 0.001, which indicates that AR
can plays a significant role in shaping OPE (b = 0.821, p < 0.001) hence HI supported.
Autonomous under Water Vehicles significantly predicted OPE, F(1, 251) = 761.505,
p < 0.001, which indicates that AU can play a significant role in shaping OPE (b =
0.867, p < 0.001). Artificial intelligence in the same way significantly predicted OPE,
F(1, 251) = 1564.411, p < 0.001, which indicates that AI can play a significant role in
shaping OPE (b = 0.955, p < 0.001) yet 3-D Scanning Technology significantly
predicted OPE, F(1, 251) = 761.505, p < 0.001, which indicates that 3D-Scanning can
play a significant role in shaping OPE (b = 1.005, p < 0.001). Adopting advanced
robotics, autonomous under water vehicles, artificial intelligence and 3-D scanning
technology higly influence the operation efficiency of an organization. This study thus
checks policy implementation on technological adoption, introduces cost-efficient
ways for production and prepares the oil and gas companies to be more flexible and
adaptable to changes in the environment. Future scholars have also found this study as
baseline for their research. |
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