Artificial Intelligence and Efficiency Operations in Abu Dhabi National Oil Company in UAE
Waleed M. S. M. A. Hosani1*, Arsalan M. Ghouri1
1 Faculty of Management and Economics, Universiti Pendidikan Sultan Idris, 35900 Tanjong Malim Perak, Malaysia
*Corresponding Author: [email protected]
Accepted: 15 December 2022 | Published: 31 December 2022 DOI:https://doi.org/10.55057/ijbtm.2022.4.4.4
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Abstract: This study was conducted to investigate the effect of Artificial intelligence on the efficiency operations in Abu Dhabi oil and gas industry in UAE. This most especially in relation to quality of data, process efficiency, product-cost efficiency, task efficiency, process flexibility and quality of operations. The researcher used the survey descriptive research design, structured questionnaire and sampling strategies such as simple and stratified random sampling to garner data from participants. Primary data for the research scientific study was collected from 253 respondents as sample size out of 10563 people as target population in Abu Dhabi oil and gas industry in UAE. The tools for data analysis that were used include descriptive statistics, Pearson Linear Correlation Coefficient, regression analysis and Analysis of Variance. Statistical Package for the Social Sciences (SPSS) was used as a software to enter data into the computer for analysis. It was found out that the adoption of technological innovation of artificial intelligence has positive effects on quality of data, process efficiency, product-cost efficiency, task efficiency, process flexibility and quality of operations at UAE oil and gas companies. It was concluded that all governments in the world must put more emphasis on artificial intelligence (AI) implementation strategies because it has a positive impact on quality of data, process efficiency, product-cost efficiency, task efficiency, process flexibility and quality of operation which may act as an impetus to growth and development in any country. It was recommended that the top management of UAE should make more proactive policies that can help guide government and company officials in the best ways to execute artificial intelligence (AI) activities and programs so as to be more effective in government and organisational settings.
Keywords: Artificial Intelligence, Efficiency, Industry, UAE
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1. Introduction
Globally, business and other non-business sectors have gone a digital transformation. The oil and gas industry in has also not been left out. The oil and gas sector globally has responded to the changes in technology (Wong et al., 2018). The United Arab Emirates (UAE) oil and gas sector and the companies in the sector have also been on the lead in the adoption of innovative technologies. Different innovative technologies like advanced robotics, autonomous underwater vehicles, Artificial intelligence (AI), and 3-D scanning technology are available today in the oil and gas that have improved production, exploration, safety and monitoring of the systems in the gas and oil production process (Medal, 2018).
Abu Dhabi National Oil Company (ADNOC), the main producer of oil and gas products in Abu Dhabi, has a big capacity to produce nearly 4 million barrels of oil, 11 billion cubic feet of raw gas and more than 1 billion cubic feet of sour gas every day. This high capacity makes ADNOC one of the biggest oil and gas producers in the world. ADNOC is very interested in adopting and implementing the latest innovative technologies and approaches that can help in improving operations, increasing production, and in making ADNOC one of the lowest cost producers of oil and lowest carbon emitters in the world (ADNOC, 2019).
The need to support innovation and technology adoption in the oil sector is due to the importance of the sector to the UAE and the government’s agenda on innovation. The government agenda to innovation in all of the country’s economic and social sectors and the need to remain at a technological level with international oil producers and enjoy the benefits of technology in the production of oil and gas has emphasized the importance of adopting of innovative technologies in the gas and oil sector of the UAE (Hana, 2017). The UAE oil and gas sector has also provided a climate that is in support of innovation aimed at achieving production excellency and efficiency in the sector (Al Mazouqi, 2022), with efforts from an on-going clean energy awareness campaigns in the UAE (Aswad, Al-Saleh &Taleb, 2021).The dangerous nature of oil and gas production (Shukla & Karki, 2020), concern for the environment (Williams, 2004), has compelled the use technology intensively for reducing human involvement and enhancing operational efficiency. There is a direct relationship in the adoption of innovative technologies and reduced human involvement in the oil and gas production processes and the achievement of efficiency in the operations of the oil and gas sector of the UAE. Different innovative technologies like robotics, autonomous underwater vehicles, Artificial intelligence (AI), 3-D scanning technology, Internet of Things (IoT) and advanced robotics have been adopted in the various parts of the oil and gas sector for various operational reasons (Olajire, 2022; Medal, 2018).
The use of technological innovation in oil and gas exploration has participated in extracting fossil fuels that weren’t accessible before the adoption of technological machines. The use of innovative technological devices has helped in the varied activities of oil and gas exploration, drilling, extraction, processing and production (Hurley & Hunter, 2013).
The use of innovative technologies in oil and gas industry doesn’t only participated in increasing production but in improving operation as well as ensuring high level of safety for all people working in oil and gas exploration, drilling, extraction, processing and production.
The use of modern technologies has participated in providing oil and gas industry with new ways of exploring, extracting, drilling, processing, and producing oil and gas besides providing new ways of monitoring and inspecting all activities during the production of oil and gas products. Innovative technologies have also participated in increasing the levels of safety so that oil and gas companies can enter more challenging environment. For example, the development of fiber optic sensing systems has participated in making the off-shore drilling platforms safer than before. Overall, the gas and oil industry has benefited highly from the adoption and the use of technology innovations in improving the quality of operation, increasing productivity, and ensuring high level of safety in the varied activities of exploration, drilling, extraction, processing and production (Hurley & Hunter, 2021).
2. Methods and Materials 2.1 Data Capturing
The information used for the organized correlation study was gathered while applying both primary and secondary sources of data. Primary data was collected by means of structured
questionnaires in connection to the investigative research study. Additional information was put together with the use of documentary records. The systematic study applied a survey descriptive design with a positivism paradigm.
Amin (2005) mentioned that descriptive research design is usually employed to echo a phenomenon and its data characteristics. The academic got a total of 382 participants (sample size) while uutilizing a table developed by Morgan & Krejcie (1970) to fit in the investigation study.
2.2 Sampling methods
The scholar used simple and stratified random sampling strategies in the inquiry rational study.
The target population included the categories like Senior managers, Chief Executive officers, citizens, political leaders, civil servants, cultural leaders and departmental heads.
2.3 Questionnaires
The intellectual researcher utilized an adapted questionnaire to garner facts from the ground because it covers a varied geographical world in data coverage; it gathers much proof within a short epoch, and offers great assurance in connection to anonymity (Karoro, 2017).
2.4 Validity and reliability of logical research instruments
Validity of the adapted questionnaire was reached at by uutilizing content validity Index. After testing of the validity of the examination study instruments, the researcher obtained content validity index (CVI) of 0.78 which was by and large above 0.75 meaning that the research tool wasreal to elicit data important for the reasonable scientific study (Amin ,2005).
Reliability of the researcher generated questionnaire was measured using Cronbach’s alpha coefficient formula looking at the examination study variables that acquired an alpha coefficient of digit more than 0.70. Since the reliability figure got by the intellectual talked of 0.79 alpha value, it signified that the research actualities collecting method was reliable to produce data reliable for the investigation (Gibbs, 2007).
2.5 Data analysis
Research statistical methods which were involved to analyse data for this careful survey study included; descriptive statistics, Pearson Linear Correlation Coefficient, Regression Analysis and Analysis of Variance (ANOVA) to test the hypothesis involving quantitative data or information.
3. Origin of Constructs
In this research study, structured and self-administered survey questionnaires prepared to be distributed among the population of the study. The online survey has five main sections.
Section one asked questions about the demographics and details of the participants. Section two asked questions about the impacts of Advanced Robotics (AR) on quality of data, process efficiency, product cost efficiency, task efficiency, process flexibility, and quality of operations. Section three asked questions about the impacts of Autonomous Underwater Vehicles (AUV) on quality of data, process efficiency, product cost efficiency, task efficiency, process flexibility, and quality of operations. Section four asked questions about the impacts of Artificial Intelligence (AI) on quality of data, process efficiency, product cost efficiency, task efficiency, process flexibility, and quality of operations. Section five asked questions about the impacts of 3-D scanning technology on quality of data, process efficiency, product cost efficiency, task efficiency, process flexibility, and quality of operations. The survey
questionnaire was developed basing on some structured questions that are adopted from constructs of previous research studies that are related to the variables of the study. However, some adjustments have been done in order to fit the current study. The development of the survey based on previous constructs added more reliability and validity to the questionnaire and it ensured that the study was going to be more reliable.
There are six main constructs in this study. Each construct had some certain items that sustain in measuring the construct. The six main constructs are quality of data, process efficiency, product cost efficiency, task efficiency, process flexibility, and quality of operations. Each construct had some items and these items were measured on five-point Likert scale. The first construct of quality of data had four items and it was adopted from Wixom (2001). The second construct of process efficiency had three items and it was adopted from Karimi, Somers and Bhattacherjee (2007). The third construct of product cost efficiency had four items and it was adopted from Nidumolu and Subramani (2003). The fourth construct of task efficiency had four items and it was adopted from Gattiker and Goodhue (2005). The fifth construct about process flexibility had four items and it was adopted from Karimi, Somers and Bhattacherjee (2007). The sixth construct of quality of operations had six items and it was adopted from Karimi, Somers and Bhattacherjee (2007). All this is explained in table 1 below:
Table 1:Origin of constructs
Construct Item Coding No. Author
Demographics 6
Quality of data
-Users have more accurate data now from adoption of technological innovations than they had before
- Adoption of technological innovations provide more comprehensive data to users.
- Adoption of technological innovations provide more correct data to users.
- Adoption of technological innovations have improved the consistency of data to users.
QD01
QD02
QD03 QD04
4
(Wixom, 2001)
Process Efficiency
-The adoption and the implementation of technological innovations has improved efficiency of operations.
-The adoption and the implementation of technological innovations has lowered our cost of operations.
-The adoption and the implementation of technological innovations has reduced the amount of rework needed for data entry errors.
PE01
PE02 PE03
3
(Karimi, Somers
& Bhattacherjee, 2007)
Product-cost efficiency
Compared to your competitors, how does your organization rate on each of the following?
(Nidumolu &
Subramani, 2003) -Ability of adopted technological innovations to
produce products at low cost for current product lines
PCE01
-Ability of adopted technological innovations to help in charging competitive prices for current product lines.
-The role of adopted technological innovations in increasing the efficiency of production for current product lines.
-The role of adopted technological innovations in increasing the productivity of current product lines.
PCE02
PCE03
PCE04 4
Task Efficiency
-Since we implemented technological innovations, plant employees such planners and production supervisors need less time to do their jobs.
-Adoption of technological innovations saves time in jobs like production, material planning and production management.
- Technological innovations are more time- saving to do work like purchasing, planning and production management.
TE01
TE02
TE03
4
(Gattiker &
Goodhue, 2005)
- Technological innovations help plant employees like planners, and production supervisors to be more productive.
TE04
Process Flexibility
-The implementation of technological innovations has given us more ways to customize our processes.
-The implementation of technological innovations has made our company more agile.
-The implementation of technological innovations has made us more adaptive to changing business environment.
-The implementation of technological innovations has improved the flexibility of our operations.
PF01
PF02
PF03 PF04
4
(Karimi, Somers
& Bhattacherjee, 2007)
Quality of Operations
-Data provided by adopted technological innovations add value to our operations.
-The implementation of adopted technological innovations has improved timely access to corporate data.
- Adopted technological innovations provide a high level of enterprise wide data integration.
-The implementation of technological innovations helps us make better sales forecasts than before.
-The functionalities of technological innovations adequately meet the requirements of our jobs.
-The implementation of technological innovations has improved our quality of operations.
QO01 QO02 QO03
QO04
QO05 QO06
6
(Karimi, Somers
& Bhattacherjee, 2007)
Source: Primary data
4. Findings
4.1 Profile of respondents
Table 2: Demographic characteristics of the participants of the study
Sample (n=253)
Gender Male 206
Female 47
Nationality UAE national 201
Non-UAE national 52
Age Group ˂25 (in Years) 27
25-35 (in Years) 83
36-46 (in Years) 115
˃46 (in years) 28
Length of work ˂ 3 years 44
3-5 years 35
6 -10 years 68
˃10 years 106
Management Level Executive leadership Team 36
Top management 62
Middle management 155
Company ADNOC Onshore 52
ADNOC Offshore 87
ADNOC Drilling 40
ADNOC Sour Gas 30
ADNOC LNG 44
Source: Primary data
Table 2 above showed the demographic characteristics details of the population sample. It is shown that the majority of the participants are males from UAE nationals. The majority of the participants are in the age group between 25 and 46 years old. The majority of the participants are working for ADNOC for more than 10 years and the majority are also from the middle management. The majority of the participants are from ADNOC Offshore followed by ADNOC Onshore.
4.2 Tests of Normality
Table 3: It shows the Tests of Normality of the dependent variable
Tests of Normality
Kolmogorov-Smirnova Shapiro-Wilk Statistic Df Sig. Statistic df Sig.
efficiency operations .111 253 .000 .923 253 .000 a. Lilliefors Significance Correction
It is clear that the degrees of the dependent variable are not moderate, because the values of the Lelivozer and Shapiro-Wilk tests are statistically significant. Hence, we find that the results of the two tests are in complete agreement with the results of the skewness and kurtosis coefficients shown in Table 3 above.
4.3 Descriptive statistics
Table 4: shows the descriptive statistics of the efficiency operations Variable.
Statistic Std. Error
efficiency operations Mean 574.4190 6.45501
95% Confidence Interval for Mean Lower Bound 561.7063 Upper Bound 587.1316
5% Trimmed Mean 581.1375
Median 591.0000
Variance 10541.776
Std. Deviation 102.67315
Minimum 102.00
Maximum 700.00
Range 598.00
Interquartile Range 142.50
Skewness -.969- .153
Kurtosis 1.255 .305
Source: Primary data
It is clear from the table 4 above, that the cut-off average amounting to 581.13 is the cut-off average after deleting the highest 5% and the lowest 5% of the data in order to cancel the effect of the outliers values, as it becomes clear the quadratic range of 142.50 which is equal to the length of the box in the box plot. This showed that the data was not normal for the variable.
4.4 Hypothesis Testing
Table 5: Pearson linear Correlation Coefficient calculation
Artificial intelligence
Quality of operations
Quality of operations
Pearson
Correlation .956** 1 Sig. (2-
tailed) .000
N 253 253
It is clear from the results of Table (5) above that:
There is a statistically significant correlation at the level of significance 0.01 between the Quality of operations variable and the variable of Artificial intelligence, where the correlation coefficient between them is (0.956), which is a very strong correlation coefficient and is close to the correct one, as well as the presence of a statistically significant correlation at the level of significance of 0.01 between the Quality of operations variable and artificial intelligence Variable..
Table 6: Summary of results
Category: The adoption of technological innovation of Artificial intelligence (AI) and its impacts on efficiency operations
quality of data Hypothesis 1: the adoption of technological innovation of Artificial
intelligence (AI) has positive impacts on quality of data. Supported process efficiency Hypothesis 2: the adoption of technological innovation of Artificial
intelligence (AI) has positive impacts on process efficiency. Supported product cost
efficiency
Hypothesis 3: the adoption of technological innovation of Artificial
intelligence (AI) has positive impacts on product cost efficiency. Supported task efficiency Hypothesis 4: the adoption of technological innovation of Artificial
intelligence (AI) has positive impacts on task efficiency. Supported process flexibility Hypothesis 5: the adoption of technological innovation of Artificial
intelligence (AI) has positive impacts on process flexibility. Supported Quality of
operations.
Hypothesis 6: the adoption of technological innovation of Artificial
intelligence (AI) has positive impacts on quality of operations. Supported Source: Primary Data
From the above table 6, it was revealed that the adoption of technological innovation of artificial intelligence has positive impacts on quality of data, process efficiency, product cost efficiency, task efficiency, process flexibility, quality of operations. Overall, it can be concluded that the adoption of technological innovation of artificial intelligence has positive impacts on efficiency operations at oil and gas companies in the UAE.
5. Discussion
The results indicated that the correlation between artificial intelligence and efficiency operations in Abu Dhabi was statistically significant. This signified that the artificial intelligence really affects efficiency operations in oil and gas industry in the UAE.
This finding was in agreement with the study conducted by Wai, Seebaluck &
Teeroovengadum (2020) on Flexibility of operations in China, who found out that artificial intelligence can improve the quality of operations in some ways, improve the design process , skills and can help in measuring and reducing the cost of production. However, these results did not concur with a popular investigation study conducted by Gatticker & Goodhue (2005) on Work and Productivity in Singapore who found out that even if people are motivated to embrace artificial intelligence principles, their personality can betray the to the detriment for the development of the government at a certain epoch in communities.
6. Conclusion
The ways of doing business globally are changing through the adoption digital platforms and approaches in the management of resources and processes. The adoption of innovative technologies affects positively the efficiency of the operations of oil and gas industry in UAE.
Therefore, all governments in the world must put more emphasis on artificial intelligence (AI) implementation strategies because it has a positive impact on quality of data, process efficiency, product-cost efficiency, task efficiency, process flexibility and quality of operation.
which may act as an impetus to growth and development in any country.
7. Implications for the study
The investigator recommended that the UAE government should spend a lot of time in proper planning in order to put things right in relation to artificial intelligence and avoid losses in public expenditure. The UAE political leadership should divulge pertinent information to the bureaucrats in oil and gas industry on the best techniques to deal with artificial intelligence (AI) implementation processes in order to allow development to blossom. The UAE government should also augment the budget for artificial intelligence (AI) implementation programs so that efficiency can be realized. The top management of UAE should make more proactive policies that can help guide government and company officials in the best ways to execute artificial intelligence (AI) activities and programs so as to be more effective in government and organisational settings.
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