Impact of Employee Motivation on Productivity in Oil and Gas Sector in UAE

Abstract

Purpose

The purpose of the present study was to examine the relationship between employee motivation and productivity in the Oil and Gas Sector in the United Arab Emirates (UAE). The central research question was “What is the impact of motivation on employee productivity in the Oil and Gas Sector in the UAE?”

Methodology

A qualitative approach was utilized to answer the research question. A survey was distributed among 30 employees of the Oil and Gas Sector in UAE. The participants were sent e-mails with a link to Google Forms with a survey consisting of 20 questions. A multiple regression model was created to assess the effect of motivation and demographic variables on perceived productivity. SPSS 26 was used to conduct all the calculations.

Findings

The results of the research revealed a significant correlation between employee motivation and self-reported productivity in the Oil and Gas Sector in the UAE (p < 0.001). The adjusted R² coefficient of the model was 0.598. The effect of motivation was similar for all the participants regardless of their age, gender, family income, and ethnicity.

Practical Implications

The results of the research suggested that managers in the Oil and Gas Sector in the UAE should use both monetary and non-monetary motivation to increase employee productivity. These methods include but are not limited to increased wages, special benefits, piece rate, commission, increased gratification, demonstrating interest in personal problems of employees, and giving challenging tasks. However, managers need to find a unique combination

Critical Literature Review

Overview

The present section aimed at providing a thematic literature review about the effect of employee motivation on productivity. Two major themes were revealed during the literature review, including the effect of monetary motivation on the productivity of employees and non-monetary motivation on the productivity of employees. Additionally, the review includes critical analysis of the themes, identification of research gaps, research aim, objectives, and hypotheses.

Monetary Motivation and Employee Productivity

Literature Overview

One of the primary ways to impact employee motivation is creating monetary incentives in the form of salaries, bonuses, and benefit programs (Ude and Coker, 2012). After studying manufacturing companies in Nnewi, Nigeria, Maduka and Okafor (2014) revealed that even though the majority of employees had low motivation, they retained their positions due to good salaries. While these employees stayed at work, the motivation was low, as salary was not tied to their performance (Maduka and Okafor, 2014). Ude and Coker (2012) stated that monetary reward needs to be tied to performance to have a positive effect on productivity.

In other words, the high portion of the monetary reward is tied to the performance, the higher motivation the employees have to increase their productivity. At the same time, Kang, Yu, and Lee (2016) revealed a positive correlation between employee incentives and productivity. The effect was stronger in the manufacturing industry in comparison with the non-manufacturing industry.

High monetary incentives do not always guarantee the high motivation of employees. Kamery (2004) stated that the monetary policy of the company needs to be fair and clear to all employees to ensure high productivity. This requires setting comprehensive output standards that can measure employee productivity (Ude and Coker, 2012). Employees should have a clear idea that they can achieve this standard and receive adequate remuneration (Ude and Coker, 2012). These standards should be equal for everyone to have a sense of fairness (Kamery, 2004). Ude and Coker (2012) outlined several types of monetary incentives that can affect employee productivity. They include cash incentives (money for meeting criteria), special benefits (such as additional paid leave), piece rate (payment per unit of production), commission, profit sharing, gain sharing, and shared ownership.

Several studies focused on the fact that motivation is closely connected to Maslow’s theory of needs. Maslow’s hierarchy of human needs has five levels, including physiological needs, safety needs, social needs, esteem needs, and self-actualization needs (Bawa, 2017). Employers’ failure to address one or several of these clusters of needs may lead to decreased employee satisfaction and motivation (Maduka and Okafor, 2014). Adequate remuneration helps to address the two layers of most basic needs, including physiological needs (such as food, comfort, and sleep) and safety (such as adequate housing), which is crucial for motivating the employees (Bawa, 2017).

Covering these two levels of needs adds to the motivation of employees; however, addressing the other three levels of needs is also crucial. Becchetti, Castriota, and Tortia (2013) examined the theory of donative labor, which supposed that the more intrinsic motivation employees have, the less monetary motivation they need. However, no proof of the hypothesis was found, as many employees in the non-profit organizations have both high intrinsic motivation and high payment (Becchetti, Castriota, and Tortia, 2013).

Critical Analysis

All the studies mentioned in this section demonstrate that there is high dependence between monetary motivation and productivity. All types of incentives, such as wages, special benefits, piece rates, commissions, profit sharing, gain sharing, and shared ownership, have a positive effect on motivation. Even though fixed wages have a significant positive impact on employee motivation, benefits tend to have a stronger influence on employee motivation when directly connected to employee performance. However, research demonstrates that the effect of the monetary incentives differs depending on the organization (Kamery, 2004).

The difference in the effect of monetary incentives can be explained in two ways. On the one hand, Maslow’s hierarchy of human needs explains the difference. Employee productivity depends on both intrinsic and monetary motivation (Ude and Coker, 2012). If intrinsic motivation that helps to address the three upper levels of needs is low, the effect of an increase in monetary incentives will be insignificant.

On the other hand, the difference in effects can be explained by the unique characteristics of organizational cultures. According to Hofstede’s model of cultural dimensions, national cultures differ considerably in six different aspects, including power distance, uncertainty avoidance, individualism vs. collectivism, masculinity vs. femininity, long-term vs. short-term orientation, and indulgence (Hofstede, 2011). For instance, UAE has a high score in terms of uncertainty avoidance, which may mean that employees prefer high fixed wages rather than high monetary incentives for increased productivity (Hofstede Insights, no date). Nevertheless, talented managers need to understand what works best for motivating employees in their companies.

Non-Monetary Motivation and Employee Productivity

Literature Overview

Non-monetary or intrinsic motivation has a significant effect on employee motivation (Bawa, 2017; Becchetti, Castriota, and Tortia, 2013; Kamery, 2004; Maduka and Okafor, 2014). Recent research by Sutrisno and Sunarsi (2019) confirmed that there was a positive link between employee motivation and productivity of employees and at PT. Anugerah Agung in Jakarta. The researchers measured both intrinsic and monetary motivation using a questionnaire. Moreover, employee motivation had a positive effect on discipline. Hanaysha and Majid (2018) demonstrated that both aspects of motivation had a significant impact on employee productivity in Malaysian workers.

The questionnaire utilized by Hanaysha and Majid (2018) had a greater emphasis on intrinsic motivation, such as job security, supervisor’s help, interest, and gratitude from peers and managers. After conducting a quantitative study, Ganta (2014) concluded that non-monetary motivation had a positive impact on employee productivity.

In particular, Ganta focused on six strategies for increasing motivation, including positive reinforcement, effective discipline and punishment, fairness, satisfying employees’ needs, setting adequate goals, and restructuring jobs. These strategies had a positive impact on human capital management, employees’ ability to meet personal goals, employee satisfaction, employee efficiency, and the ability to meet company goals. Nadeem (2010) also concluded that employee motivation, satisfaction, and commitment are crucial for improving productivity.

Critical Analysis

The literature review revealed that nine out of ten studies studying the impact of employee motivation on productivity had a greater emphasis on non-monetary incentives for motivating employees. All of the researchers were univocal in saying that non-monetary motivation techniques are as important as monetary motivation. However, as it was mentioned earlier, the effect of non-monetary motivation differs from organization to organization, and managers need to be able to understand the employee needs of their organization. Such a tendency can be explained by Maslow’s hierarchy of human needs. The needs addressed by non-monetary incentives are at higher levels in comparison with those addressed by monetary incentives. Therefore, they appear to be more important; however, their effect is significant only when the remuneration of employees is adequate.

Gaps in Literature

Even though the relationship between employee motivation and productivity is a widely discussed topic among scholars and managers, there is little information about how employee motivation affects the productivity of workers in the UAE (Bose, 2018; Ismail and Ahmed, 2015). Even less information is available about Oil and Gas Sector, as the majority of reviewed literature focused on other industries (Bawa, 2017; Ganta, 2014). The present research aimed at closing these two gaps in the literature.

Aim and Objectives

The aim of this research was to examine the relationship between employee motivation and productivity in the Oil and Gas Sector in the UAE. In order to achieve this aim, three objectives were considered, including:

1. Conduct a thematic literature review to identify appropriate methods for achieving the goal and formulate hypotheses;
2. Collect primary data from employees of the Oil and Gas Sector in the UAE;
3. Test the hypothesis using rigorous statistical methods and interpret the results.

Hypotheses

• H₀: There is no correlation between employee motivation and productivity in the Oil and Gas Sector in the UAE.
• H₁: There is a positive correlation between employee motivation and productivity in the Oil and Gas Sector in the UAE.

A positive correlation implies that the higher the motivation of employees, the higher is their productivity. The correlation is presumed to be linear, as the majority of reviewed studies examined linear or multiple regression models (Bawa, 2017; Kamery, 2004; Maduka and Okafor, 2014). This can be explained by the fact that employees with high motivation are more likely to be satisfied with their job, willing to give back more to the company (Becchetti, Castriota, and Tortia, 2013).

Methodology

Method Selection

The method selected for the present research is quantitative correlational research. There are two general approaches to research in business: qualitative and quantitative. A qualitative approach is generally used to explore people’s perceptions of a subject area and provide ground for future research (Hair, 2015). Qualitative research utilizes focus groups, interviews, and observations as data sources (Saunders, Lewis, and Thornhill, 2019). Quantitative research is used to gain robust, specific knowledge by testing hypotheses created with the help of theory or previous quantitative research (Hair, 2015). The primary data sources for quantitative research are surveys (Saunders, Lewis, and Thornhill, 2019).

Since the purpose of the present study is to study relationships between two concepts, a correlational study design is most appropriate. According to Hair (2015), the correlational approach is a non-experimental research method that studies relationships between two or more variables using statistical methods. The proposed data collection and analysis process is provided in Figure 1 below.

Sampling and Data Collection

The present paper utilizes convenience sampling as the primary sampling technique. Convenience sampling presupposes that a researcher recruits participants ready-available to him (Saunders, Lewis, and Thornhill, 2019). This method is not usually used for quantitative studies, as it is associated with significant bias (Saunders, Lewis, and Thornhill, 2019). However, it was used for the pilot studies for time-related reasons.

Potential participants received an invitation to participate in the research through messages on social networks with a link to the survey. The survey included the purpose of the study and provided detailed direction. Google Forms was used to conduct the survey. All the information was stored in Google Drive and retrieved when the planned number of responses was received. A total of 30 participants (16 females and 14 males) were recruited with a response rate of 100%. Even though the sample size is considered small, it is still appropriate for a pilot study (Cochran, 1977).

Instrument

The present study utilized a self-created instrument to assess the effect of motivation on productivity on employees in the Oil and Gas Sector in the UAE. The instrument consisted of 20 questions, among which four questions measured demographical variables, ten questions measured employee motivation, and six questions measured self-reported employee productivity. All the content questions used a seven-point Likert scale to determine how much they agreed or disagreed with provided statements. The questionnaire was based on the survey utilized by Hanaysha and Majid (2018).

The reason for utilizing the instrument is its high validity and reliability, with Chronbach’s alpha above 0.74 (Hanaysha and Majid, 2018). The wording of the instrument was moderated, and demographical questions were added. The survey questions by section are provided below:

“The present survey is used for a pilot business research. The research aims to examine the relationship between employee motivation and productivity in the Oil and Gas Sector in the United Arab Emirates (UAE). This survey consists of two sections. The first section includes questions that collect demographical data of respondents. The second section contains questions that measure how motivated the participants are at their current job and their productivity. All the participants can withdraw from the study by simply closing the browser. Unfinished surveys will not be used for analysis. Please, remember that the research does not gather any personal data, which implies that the researcher will not be able to identify responses and exclude them from the analysis.

Please answer to all of the following questions using your best judgment.

Section 1: Demographic Questions

What is your gender?

• Female.
• Male.
• Other.

What is your age? (enter the number of full years)

What is your monthly household income?

• Less than 10,000 AED.
• 10,000 AED – 20,000 AED.
• 20,000 AED – 35,000 AED.
• 35,000 AED – 50,000 AED.
• More than 50,000 AED.

What is your ethnicity?

• GCC;
• Asian;
• European;
• African;
• Other.

Section 2. Content Questions

Ten statements below aim at measuring the motivation and productivity of participants at their current workplace. Please, indicate how much you agree with the following statements on the scale from 1 to 7, where:

• 1 = Strongly disagree;
• 2 = Disagree;
• 3 = Somewhat disagree;
• 4 = Neither agree nor disagree;
• 5 = Somewhat agree;
• 6 = Agree;
• 7 = Strongly agree.

1. I am satisfied with the level of my current job security.
2. In my workplace, employees receive enough supervisor’s help with their personal problems.
3. In my workplace, employees are satisfied with their wages.
4. The work is interesting in the organization where I work.
5. Managers show gratitude for a job well done in my workplace
6. I receive monetary incentives for a well-done job.
7. I accomplish tasks quickly and efficiently.
8. The quality of my work is high.
9. I have a high standard of task accomplishment.
10. My overall productivity is high.
11. My job role duties are my primary focus when I am working.
12. It’s exciting and challenging to do my job.
13. I am continually learning and developing new skills because of my role.
14. Goal-achieving motivates me at my workplace.
15. In my manager’s eyes, my personal achievement and development are very important.
16. I am trusted to handle high-level tasks by my manager.

Data Analysis Procedures

The purpose of the study was to study the relationship between employee motivation and productivity in the Oil and Gas Sector in the UAE. Employee motivation was measured as an average value of Questions 1-6 and 12-15. Employee self-reported productivity was measured using the average value of Questions 7-11 and 16. The analysis also used demographic variables, including gender, age, family income, and race, as controls.

Data Analysis Procedures

The collected data was cleaned and formatted for further analysis using SPSS. A multiple regression model was created to assess the relationships between employee motivation and productivity in the Oil and Gas Sector in the UAE. The model was assessed using SPSS 26. After that, the coefficients and the adjusted R² coefficient was interpreted. The assessed model is provided below.

Productivity=β₀ + β₁Motivation + β₂ Age + β₃ Gender+ β₄ Monthly Family Income + β₅ Ethnicity+Employe Motivation

The model is visualized in Figure 2 below.

Results and Discussion

Results

The age of the participants varied between 19 and 38 with the mean of 23.5 years. The gender distribution was almost even (16 females and 14 males), and half of the participants identified their ethnicity as “GCC.” The majority of the participants (56.7%) had family income below 10,000 AED.

The research results revealed that the model had a high predictive ability with adjusted R² = 0.598. The estimations of the coefficients are provided in Table 1 below.

Table 1. Coefficients.

Model		Unstandardized Coefficients		Standardized Coefficients	t	Sig.
		B	Std. Error	Beta
1	(Constant)	-.163	1.171		-.139	.890
	Gender	.254	.290	.110	.878	.389
	Age	.042	.042	.124	1.002	.326
	Family Income	-.011	.126	-.011	-.086	.932
	Race	-.013	.101	-.016	-.126	.900
	Motivation	.844	.162	.728	5.212	.000

The estimation of coefficients revealed that motivation had a significant impact on employee productivity, as the p-value (p = 0.000) was below the alpha level of 0.05. At the same time, no control variables reached statistical significance. In summary, the research results demonstrated that there was significant evidence to reject the null hypothesis.

Discussion

The results of the analysis supported the hypothesis that there is a positive correlation between employee motivation and productivity in the Oil and Gas Sector in the UAE. The effect was similar for all the participants regardless of their age, gender, race, and family income. The results of the present research stand in line with the current body of knowledge (Bawa, 2017; Becchetti, Castriota, and Tortia, 2013; Ganta, 2014; Hanaysha and Majid, 2018; Kamery, 2004; Kang, Yu, and Lee, 2016; Maduka and Okafor, 2014; Nadeem, 2010; Ude and Coker, 2012). This demonstrates that motivation is as important for employee productivity in the Oil and Gas Sector in the UAE as for other countries and industries. The present study adds to the generalizability of the findings of previous research.

Even though the results of this research were statistically significant and had a large effect size, it is crucial to acknowledge the limitation of findings. The primary drawback of the present research is sample characteristics. The sample size for the present research was small, which may have decreased the reliability of findings (Hair, 2015). Moreover, the sampling technique was inadequate for the selected approach. Probability sampling methods, such as simple random sampling, would be a more appropriate method for the quantitative study, as it would let all the members of the population have a similar chance to participate in the study (Saunders, Lewis, and Thornhill, 2019).

This resulted in the sample being non-representative of the population. The problem is that 93% of the sample were aged between 20 and 30 (see Figure 2 for the sample’s age distribution). This implies that the results of the pilot study can be applied only to the employees of the Oil and Gas Sector in the UAE aged between 20 and 30. Further research is required to address the biases associated with the methods of the present paper.

Practical Implications and Conclusion

Even though the results of the present research are limited they can still be used by managers in the Oil and Gas Sector in the UAE with caution. The results have the following implication for managerial practice:

1. Managers in the Oil and Gas Sector in the UAE can increase workplace productivity by using monetary incentives to increase employee motivation. The methods may include increased wages, special benefits, piece rate, commission, profit sharing, gain sharing, and shared ownership.
2. Managers in the Oil and Gas Sector in the UAE can increase workplace productivity by using non-monetary incentives to increase employee motivation. These may include increased gratification, demonstrating interest in the personal problems of employees, giving challenging tasks, and improving workplace culture.
3. The managers need to find the most appropriate combination of monetary and non-monetary incentives to improve employee motivation. Hofstede’s model of cultural dimensions and empirical evidence demonstrates that all organizations have different cultures, which affect the effectiveness of the instruments used to increase motivation (Bawa, 2017; Hofstede, 2011).

In conclusion, the results of the present research demonstrated that there is a positive correlation between employee motivation and productivity in the Oil and Gas Sector in the UAE aged between 20 and 30. Even though the sampling methods for the present research are associated with an increased possibility of bias, the results can still be used in practice and for future studies. The pilot studies demonstrate that there is a full potential to find positive results in the case of full-scale research. Future research should utilize probability sampling and increase the number of participants to address the weaknesses of the present study.

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