Abstract
This study aimed at evaluating whether motivation and locus of control are factors that contribute to occupational stress amongst oil company employees in Abu Dhabi, the United Arab Emirates. The study hypothesised that locus of control and motivation are two major factors that predict occupational stress among oil company employees. As a research methodology, the study employed correlational research design in determining if motivation and locus of control are statistically significant predictors of occupational stress. The study sampled 172 (Males = 99, Females = 73) participants with ages ranging from 18 to 66 years from the target population in the oil industry.
Specifically, the participants were oil company employees working in the premises of Shaikh Khalifa Energy Complex & ADCO in Abu Dhabi, the United Arab Emirates. In the collection of data, the study used a questionnaire, which contained demographic prompts. Moreover, the questionnaire had three scales, namely, motivation at work scale (MAWS), locus of control scale (LOCS), and job-related tension index (JRTI). The data collected were analysed using descriptive statistics and multiple regression analysis. The findings show that locus of control is statistically insignificant predictor of occupational stress, while motivation is statistically significant predictor occupational stress. In conclusion, the study suggests that motivation is a major factor that associates with occupation stress among oil company employees in Abu Dhabi, the United Arab Emirates.
Introduction
Stress is a predominant life problem that affects several people in the contemporary world where economic hardships, employment problems and poverty are constant problems (Ployhart, 2006; Rosenow, 2005). Stress occurs in diverse paradigms and when it occurs to people within the workplaces, industrial psychologists refer to it as occupational or work-related stress (Kumari, 2008; Maphalala, 2014). In 1976 industrial psychologists Greg Oldham and Richard Hackman unveiled that the degree of autonomy that workers have at their workplaces and their personal control over their work-related decisions influence their health, their workplace motivation, and their ability to manage their workload (Patwary, Uddin, Miah, & Sarker, 2013). Their industrial assessment about occupational stressors led to the growth in research about the occupational stress or the work-related stress. According to Patwary et al. (2013), occupational stress or work-related stress has for several years been a disturbing issue among the workers and managers who have interest in knowing how human psychological factors influence the performance of workers.
In a definition Shikieri and Musa (2012) define occupational stress or work-related stress as a “disruption of the emotional stability of the individual that induces a state of disorganisation in personality and behaviour, while a stressor is any demand made by the internal or external environment that upsets a person’s psychological status” (p. 134). Additionally, job stressors are normally a number of workplace characteristics or conditions that influence an individual’s state of mind (Shikieri & Musa, 2012). In an early investigation, industrial psychologist Robert Karasek discovered that employees whose occupations were high in terms of job demands whereas low in employee autonomy in decision-making recorded high workplace exhaustion, morning wake-up stress, high levels of nervousness, insomnia and depression (Ereno et al., 2014). Even though stress to several people sounds like a negative psychological disturbance, industrial psychologists discovered that occupational stress can possibility contribute to either negative or positive outcomes, depending on the form of stress.
When a work-related stress contributes to negative outcomes, researchers consider it as a destructive stress.
According to researchers Pienaar and Rothmann (2006), occupational stress that leads to uncomfortable behaviours such as exhaustion at workplace, morning tiredness, depression, frustration, insomnia, and nervousness can be examples of part of destructive stress. A destructive form of stress leads to a diminutive work performance, low motivation and poor concentration towards the work activities (Pienaar & Rothmann, 2006). From the psychological perspective, constructive stress is a form of work-related stress where individuals demonstrate increased creativity, constructive thinking, enhanced critical decision-making and a high sense of intellectuality. Whereas the knowledge about stress is diverse, people still lack the knowledge about job stressors that cause occupational stress (Gaus, 2014; Maphalala, 2014). Job stressors can normally associate with work overload, payment problems, role conflict, workplace conflict, role ambiguities or poor working conditions. Among others, locus of control and motivation are major stressors that contribute to work-related stress.
A 2014 study conducted in UAE by Sultan, Tariq, and Rile (2014) shows occupational stress is very dominant in the UAE companies. However, although research on occupational stress has intensified in the United Arab Emirates, a study on the association between the locus of control and motivation, as two significant stress factors that contribute to occupational stress still misses (Mohajan, 2012). Oil producing companies in the United Arab Emirates are the most productive and most relied upon industrial sectors given the fact that Abu Dhabi highly depends on the production and exportation of oil to boost its national economy. Given the fact that occupational stress is high in production demanding companies, this research paper will focus, investigate and analyse whether locus or degree of control and motivation are factors that contribute to work-related stress.
Stress is a universal problem among several human beings that are physically and psychologically normal (Mohajan, 2012). Being an unavoidable human aspect that happens in most living individuals, stress extends from the ordinary life circumstances to important life settings including workplaces. Even though stress can result in positive or negative outcomes, firms are increasingly encountering losses from stress-related problems that occur in workplaces. Recent studies have revealed that in America and within other developed nations, businesspersons pay over $150 billion annually to deal with various occupational stress problems that sometimes lead to employee absenteeism, lack of work commitment and lack of motivation, low productivity and several other mishaps (Jain & Singh, 2015; Sultan et al., 2014). Stressful work situations have also disturbed the peaceful survival of workers as occupational stress has often resulted in fatigue, depressions, unnecessary anxiety, cardiovascular diseases and several other psychological problems Hence occupational stress affects the individual wellbeing of the workers and the overall productivity of the organisations.
Even as companies seek means of enhancing their productivity through incorporating the best human skills and human resource techniques, workplace stress continues to influence several functionalities of the firms (Siddique & Farooqi, 2014). Being an inherent aspect seen in some individual persons, occupational stress or work-related stress continues to be a health and human resource problem among several individuals and organisations. Whereas occupational stress can manifest in individuals and contribute to either positive or negative outcomes in organisations, majority of the cases involving occupational stress have resulted in diminutive performances. Jesus, Rus, and Tobal (2013) state that since workplace stress is a dynamic problem caused by various circumstances, unravelling the real contributors of occupational stress in workplaces become a complex task. Among others, the locus of control and motivation seem to be some contributing factors that influence work-related stress (Sliskovic, Sersic, & Buric, 2011). Given such dilemmas, this paper sought to establish whether the locus of control and motivation contribute to occupational stress.
Given the rising demand for high productivity among the workers, who work to either fulfil certain personal obligations or meet organisational demands, experiencing workplace stress is becoming a norm (Uma & Manikandan, 2013). Occupational stress generally entails a situation whereby employees feel psychologically disturbed. Occupational stress continues to be a looming problem in several organisations across the world with little knowledge existing about the contributing factors that influence or predict it (Uma & Manikandan, 2013). Researchers on health psychology have always associated job characteristics such as work overload, payment problems, role conflict, workplace conflict, role ambiguities and poor working conditions, with occupational stress such as high levels of anxiety, insomnia and depression. In a study, Mark and Smith (2011) sought to examine the prevailing relationship connecting job characteristics as predictive factors in the levels of stress and depressions among the nurses. In their research, they involved 870 registered nurses who participated in an online survey conducted via the email.
In their analysis, Mark and Smith (2011) based their research on the factors of occupational stress and predictors such as social support, job demands, skill discretion, control, over-commitment, rewards and the authority to make decisions. In their main responses, Mark and Smith (2011) discovered that extrinsic efforts, job demands, and over-commitment were stressors that highly associated with high levels of anxiousness and depression. On the other hand the participants described rewards, social support, and skill discretion control as job characteristics or job stressors that are negatively related with mental health complications. In their study, Mark and Smith (2011) also discovered that workers tend to feel stressed at workplaces when they are either under strenuous conditions or leadership, or when they are sometimes trying to control certain workplace situations independently. When struggling to handle certain situations or cope with certain workplace conditions, whether in self-governed or in controlled circumstances, workers develop coping behaviours that predispose them to anxiety and depression.
The word motivation represents a theoretical term that explains the human behaviour and it normally represents the nature of the actions of the people, the people desire, and the needs of the people (Ryan & Deci, 2000). Psychologists define motivation as an urge, a desire, or a force that enables people to act or react. In the field of psychology, researchers have identified two forms of motivation, which include the intrinsic type of motivation and the extrinsic type of motivation. According to Ryan and Deci (2000), intrinsic motivation refers to an innate feeling that develops within a person, with a motive of achieving some established goals or targets through autonomous plans. Touré-Tillery and Fishbach (2011) extrinsic motivation refers to an external force such as rewards, extraneous incentives, supervisory techniques or other external benefits that propel individuals towards achieving certain targets in organisations. These two major forms of motivation have highly associated with job satisfaction, organisational performance and sometimes workplace stress.
Motivation is the tendency of having morale towards achieving something. Motivation in workplaces can originate from an individual’s innate effort to achieve something or from an external pressure created by the management, the organisational policies, or the work demands (Bianchi, 2004). In workplaces, individuals may feel intrinsically or extrinsically motivated because they want to achieve certain personal targets, they want to fulfil their professional obligations, want to receive recognition or want to obtain rewards from their employers (Michael, 2009). Employee motivation brings about an unintended pressure to push towards achieving better workplace results, better personal goals or better life standards. Occupational stress is a complex subject where the aspects of job demands and the amount of discretion that a person has on a job determine the level of stress that an employee can experience (Galletta, 2011; Nakasis & Ouzouni, 2008). Combined together these aspects may depict that the more an individual experiences high job demands, the more that individual works harder, and the more he or she becomes stressed.
In a study, Kakkos, Trivellas, and Fillipou (2010) wanted to examine the existing relationship between job motivation and work-related stress through an analysis of the perceptions of employees concerning the link between job motivation and stress. Using a sample of 143 employees from the banking industry in Greece, Kakkos et al. (2010) used the 1967 motivation theory of Alderfer, which contains the concept of multiple needs’ satisfaction. The multiple needs’ satisfaction model argues that, “existence needs a good pay, existence needs-fringe benefits, relatedness needs-supervisors, relatedness needs-peers, and growth needs” (Kakkos et al., 2010, p. 211). Moreover, the researchers wanted to examine the influence of work stress on work experience, work position and gender issues. Kakkos et al. (2011) explained that employees expect numerous benefits in terms of resources, salaries and wages, moral satisfaction, self-esteem and social support. Lack of these important benefits often results in mental disturbances and restlessness among the working individuals.
According to their findings, since unemployment in the world of today highly associates with high levels of depression, anxiety and even deadly psychological traumas, people prefer working hard than being idle. Kakkos et al. (2011) discovered that this inner urge to work and to work even harder, makes people have a motive towards achieving even higher work performances. However, Kakkos et al. (2011) discovered that motivation that results from external forces such as one that comes from the management due to high job demands often causes stress and depression among the workers. In another study Fernet, Austin, and Vallerand (2013) designed a research that investigated the impact of work motivation on the exhaustion trends and commitment behaviours of the employees. Using 596 French-Canadian school principals subjected to quantitative questionnaires, the researchers concentrated on analysing the impact of the extrinsic forms of motivation, which are the autonomous motivation and controlled motivation on the worker’s exhaustion and commitment.
In their study, Fernet et al. (2013) discovered that work motivation automatically influences employee functioning and performance as rewards, recognition, social support and resource support motivates employees to work extra hard. Therefore, as employees work to maintain their positions and secure their jobs to survive in the highly competitive labour markets, their increased commitments to meet the increasing job demands make them predisposed to psychological problems such as stress. In general, Fernet et al. (2013) revealed that job resources routinely influence work motivation both in the form of autonomous and controlled motivation and motivation subsequently affects occupational commitment and emotional exhaustion. In a similar recent study, Beheshtifar and Modaber (2013) sought to examine the manner in which the concept of career plateau relates with the aspect of occupational stress. Using descriptive statistics methods to analyse the two aspects, the study focused on using the Cochrane formula to select 154 employees as the study sample from the Azad University.
Career plateau is the arrangement of jobs in accordance with the hierarchical order of managing organisations. According to the results of the research undertaken by Beheshtifar and Modaber (2013), respondents agreed that there is a great correlation between occupational stress and the job content plateau where the aspect of hierarchy forms part of the struggle for more remuneration and greater motivation. When individuals possess the personality of having a feeling that their professional capacities and their hierarchies make them better than others, they tend to remain predisposed to frustrations and stress to meet the present job demands expected of them.
The more responsibilities and power a person has, the more likelihood to be part of a continuous pressure that constantly brings about stress and frustrations at work. According to Beheshtifar and Nazarian (2013), when people have higher hierarchies that probably resulted from on-job promotions, they tend to experience pressure to maintain their job positions and meet the expectations of their organisations without fail.
The concept of locus of control first appeared in the professional research in 1954, when Julian B. Rotter first introduced the idea of the locus of control from the perspective of workforce reinforcement. According to Karimi and Alipour (2011), “locus of control is defined as the general belief that individual’s successes, failures, and outcomes remain controlled by the individual’s actions and behaviours (internal); or perhaps, people’s achievements and failures remain controlled by other forces like chances, luck, and fate (external)” (p. 234). The definition depicts that the concept of locus of control exists in two distinct forms namely the internal locus of control and the external locus of control. Internal locus of control is a people’s belief that successes, failures, and outcomes of individuals are achievements or outcomes of the individual’s actions and efforts (Cosio, Olson, & Francis, 2011). External locus of control is a belief that a certain fate, chance, the presence of managers, organisational policies or supervisors are determinant factors that drive person’s outcomes.
As a personality aspect, locus of control in the world of professionalism symbolises the beliefs of individuals concerning their perceived control over their work environments (Bernardi, 2012). Researchers dealing with the concept of occupational stress have always sought to uncover the existing relationship between the degree of control on one’s job and the existence of occupation stress or the work-related stress. Bernardi (2012) carried out a qualitative research study of two Big-Six American accounting firms to establish the existing relationship among locus of control, workforce performance and the perceptions created on the issue of workplace stress. Using about 206 newly employed junior workers to establish the above relationship, the responses of the participants revealed that the higher the internal locus of control of individuals, the more those individuals perceive stress as a contributing factor to higher achievements.
Researchers have discovered that locus of control, being a widespread belief that personal behaviours contribute to certain outcomes, whether in the form of success or failure. In their research, Karimi and Alipour (2011) discussed the manner in which locus of control affects occupational stress or the manner in which locus of control associate with work-related stress. If locus of control represents those contributing factors that individuals attribute to their failure or successes in certain workplace obligations, then the idea of the locus of control comes with varied positive and negative outcomes. Karimi and Alipour (2011) discovered that locus of control is a personality and individuals possess these attributes even in their workplaces. Psychologists believe that when people tend to rely on their personal judgments or external influences to have certain outcomes, their behaviours predispose them to certain workplace stress (Ashby, Kottman, & Draper, 2002). Both the internal locus of control and the external locus of control contribute to certain forms of stress and depressions at workplaces.
An intrinsic feeling that makes people feel that they can control their own behaviours and attributes is another cause of work-related stress (Ashby, Kottman, & Draper, 2002). People who possess an internal locus of control tend to perform well in areas marred by stressful situations and are likely to have better capabilities to handle and adapt to the problems affecting their workplaces. In a study, Basim, Erkenekli, and Sesen (2011) wanted to examine the existing relationship between locus of control found in individual’s behaviour with the workplace aspects of role conflict and role ambiguity. Based on a qualitative data of about 153 purposefully selected employees from a giant public sector organisation; the study sought to investigate whether or not role conflict and the idea of role ambiguity differ among people with external form of locus of control and those with internal locus of control. Using t-test and the correlation analysis, Basim et al. (2011) discovered a unique relationship.
The empirical analysis of the research of Basim et al. (2011) revealed that there exists a significant difference between role ambiguity of individuals with internal locus of control and those individuals regarded to be with external locus of control. In organisations, role conflict and role ambiguities are factors that often lead to emotional challenges or simply psychological problems. According to Rehman (2008), psychological problems that associate with role conflict and role ambiguity issues include job dissatisfaction, indecisiveness, overexcitement, anxiety, nervousness, tension and sometimes these problems lead to organisational underachievement such as loss of work confidence, low personal turnover, waste of resources, workplace insufficiency and low organisational commitment. In the survey results, Basim et al. (2011) discovered that 65% of the respondents possessed an internal locus of control while the remaining 35% had an external locus of control. The research survey also revealed that the respondents with an internal locus of control in role conflict and role ambiguity considerably high scores on the t-test scale.
As a result of this study, Basim et al. (2011) concluded that the relationship between internal locus of control and role conflict comes in the sense that locus of control is a personal trait. Basim et al. (2011) also concluded that majority of the respondents had possessed traits associated with internal locus of control and consequently recorded high tendencies in experiencing role conflict and role ambiguity. Just as Islam, Mohajan and Datta (2012) discovered in their research, these results literary mean that certain levels of employee control over job sometimes lead to increased conflicts and role ambiguities which are major variables of occupational stress.
However, these attributes make them positively focused on their work, as people with internal locus of control remain more vigil and careful in their workplaces; thus, causing little errors and losses that rarely predispose these people to stressful situations at their workplaces (Fazio & Olson, 2003). However, in worse situations, people with internal locus of control tend to be introvert, hence suffer more stress.
Internal locus of control associates with the behaviour of introversion. Introversion is the behaviour or a character in people, whereby victims of certain situations tend to keep secrets to themselves (De-Nobile & McCormick, 2005). When people tend to believe that they can control events or situations that affect them try to cope with the problems by preferring to remain silent and suffer depressions, stress, and several other psychological problems. In a mental health study that reflected issues of stress in organisations, Darshani (2014) wanted to examine the reality behind the idea that locus of control positively correlates with a mental strain. In his study Darshani (2014) investigated the manner in which people with a belief in the internal locus of control and those with a belief in the external locus of control tend to behave in different stressful situations. Using characteristics described as type A personalities, and type B personalities Darshani (2014) discovered that people who believe in internal locus of control can hardly control stress.
People who believe in fate, luck or those who believe in the presence of certain managers and supervisors to control events that affect them tend to experience occupational stress in certain circumstances (Vaezi & Fallah, 2014). Studies have revealed that people with a belief in external locus of control tend to have high expectations on the fate and lack and whenever the outcomes appear different from the expected, they suffer more stress and depression. According to the research of Basim et al. (2011) individuals or employees who excessively rely on natural circumstances such as fate and luck tend to record high failures that predispose them to mental strain and other psychological problems. In a workplace scenario, these kinds of people often possess a low amount of control on several job aspects such as decision authority and skill discretion (Vaezi & Fallah, 2014). The on-demand control model is a famous model that can best explain the relationship between job control and stress factors.
According to the on-demand control model, control in a workplace has a great association with workplace stress (De-Nobile & McCormick, 2005). The on-demand control model explains the association that exists between the psychological demands of human beings and the issues of decision latitude or decision control. According to the on-demand control model, job demands can be workplace factors such as employee conflicts, work overload, efficiency demands, production pressures and role ambiguities. The on-demand model predominantly believes that when employees are under a high control and under high job demand and have little sovereignty in their job obligations, they tend to suffer from psychological problems and other stress issues. Such stressful circumstances make workers suffer occupational stress as job control highly contributes to the reduction of occupational stress through allowing individuals to make autonomous job decisions.
In a recent study, Cascio, Magnano, Costantino, and Battiato (2014) sought to examine the existing relationship among the beliefs of self-efficacy, the concept of external locus of control and occupational stress in schoolteachers of public setting. The researchers used an Occupational Stress Indicator (OSI) of the Italian version and a self-administered questionnaire based on the qualitative research approach. Cascio et al. (2014) also integrated a Cronbach test of four major factors that were relevant to the investigation of the relationship among the concepts of occupational stress, external locus of control and beliefs of self-efficacy. The four factors included the job stressors, personal features, stress symptoms and coping strategies. Using about 222 qualified teachers in the investigation, the research acquired some unique findings. In their findings, Cascio et al. (2014) discovered that higher levels of external locus of control automatically lead to lower levels of individual self-effectiveness and this situation further aggravates physical and mental illnesses.
As part of their investigation, Cascio et al. (2014) also discovered that self-efficiency rarely predicts psychological stress although it highly associates with the external locus of control. Since individuals with the external locus of control tend to believe in some external conditions that influence their outcomes, they rarely manage to cope with the demands that arise within their workplaces. According to Agolla (2008) workers who believe in the external locus of control find them-selves subjected to pressure, stress and psychological disturbances because their managers and supervisors are prone to controlling the factors that matter most in their workplaces. Due to their belief in the power of other people to control workplace situations, workers who believe in external locus of control have limited abilities to control work overload, work pressure and workplace conflict which are the factors that contribute largely to occupational stress. According to Parija and Shukla (2012) work overload, work pressure and workplace conflict are major predictors of physical strain and psychological discomforts.
The research area of occupational stress or work-related stress has grown immensely since industrial psychologists Greg Oldham and Richard Hackman discovered that the degree of autonomy and motivation that workers have at their workplaces are among the important job stressors (Lee, Cadogan, & Durden, 2006). Several researchers have tried to distinguish and elaborate on the manner in which several job stressors such as work overload, payment problems, role conflict, workplace conflict, role ambiguities or poor working conditions influence workers. However, according to Lee et al. (2006), the knowledge as to whether locus of control and motivation are stress factors contributing to work-related stress; in research, continues to be minimal even as several issues of occupational stress continue to arise. In the perspective of the Abu Dhabi workplaces, Sultan et al. (2014) reveal that cases of occupational stress have dominated numerous oil-producing companies even though researchers have neglected to investigate how locus of control and motivation act as factors that contribute to work-related stress.
Several dynamics exist pertaining to the factors that contribute to work-related stress or occupational stress (Gray-Stanley, Muramatsu, Heller, Hughes, Johnson, & Ramirez-Valles, 2010). However, the association existing between the locus of control and motivation as factors that predict occupational stress continues to be unclear and miniature in research. With a special focus on the oil-producing companies of Abu Dhabi, where pressure on productivity is relentless (Gray-Stanley et al., 2010), this research aimed to evaluate whether locus of control (internal and external) and motivation (intrinsic and extrinsic), are factors contributing to work-related stress amongst the oil company employees. The target population of the study was oil company employees in Abu Dhabi, the United Arab Emirates. In the United Arab Emirates, the oil industry is the primary driver of the economy because it employs many people and generates a considerable gross domestic product.
Davidson (2009) reports that Abu Dhabi is among the wealthiest cities in the United Arab Emirates and across the world owing to its oil economy. The report implies that the oil industry in Abu Dhabi has racially diverse employees who are from different nations across the globe. According to Harhara, Singh, and Hussain (2015), the oil industry in Abu Dhabi has been experiencing increased turnover of employees. The increased turnover is partly due to occupational stress which compels employees to resign. Chen and Wong (2005) state that the oil industry is stressful because of demanding tasks, long working hours, vibration, noise, poor ventilation, job insecurity, high risk and perceived control. In this view, employees in the oil industry were appropriate target population because of the occupational stress and racial diversity. Specifically, the target population of the study was employees working in the premises of Shaikh Khalifa Energy Complex & ADCO.
The premises hosted nine different oil companies namely ADNOC (Abu Dhabi National Oil Company), ADCO (Abu Dhabi Company for Petroleum Operations Limited), ADMA-OPCO (Abu Dhabi Marine Operating Company), ZADCO (Zakum Development Company), GASCO (Abu Dhabi Gas Industries Limited), ADGAS (Abu Dhabi Gas Liquefaction Company Limited), TAKREER (Abu Dhabi Oil Refining Company), FERTIL (Ruwais Fertilizer Industries) and Borouge (Abu Dhabi Polymers Company Limited), which provided a sufficient number of employees that the study required. The target population in this premise was appropriate because they reflect global diversity in terms of race, nationality, and gender and education level. According to Reis and Judd (2014), the diversity enhances external validity of findings and allows generalisation of findings. In essence, the target population enhance external validity of the findings because they included individuals from all over the world. Hence, the study hypothesised that locus of control and workplace motivation predicts occupational stress.
Methodology
Research Design
The study employed the correlational research design in determining if motivation and locus of control are statistically significant predictors of occupational stress among oil company employees in Abu Dhabi. The correlational study is relevant to establishing the relationship between quantitative variables (Goodwin, 2010). The degree of relationship can be a weak correlation, moderate correlation, or high correlation. A correlational study aims to establish the existence of covariance between two or more variables (Kumar, 2010; Siddique & Farooqi, 2014). In this case, since the study seeks to establish whether motivation and locus of control are predictors of occupational stress, the appropriate research design is correlational study.
Sample
The study sampled participants of the study from the target population who were the employees working in the premises of Shaikh Khalifa Energy Complex & ADCO. Specifically, the study employed purposive sampling in selecting 200 participants to take part in research. The purposive sampling is advantageous because it is not only cheap and simple, but also enhances the external validity of the research (Gorard, 2013; Leedy & Osmond, 2010). The purposive sampling ensured that the participants of the study comprise adult employees aged between 18 and 66 years and of both genders (M = 33.77, SD = 7.55). The standard deviation shows that the mean varies from 26.22 to 41.32 at 95% confidence interval. Most participants (70.3%) have the ages between 18 and 36 years. Moreover, the study ensured that the participants are from diverse nationalities and with different educational backgrounds. As the study administered questionnaires to 200 employees, 172 managed to respond their questionnaires appropriately.
Instruments
In the collection of required data, the study employed three questionnaires, namely, motivation, stress, and locus of control. The study combined three questionnaires into one questionnaire, which collected demographic data, motivation data and locus of control data. In the collection of motivation data, the study used motivation at work scale (MAWS) by Gagne, Forest, Gilbert, Aube, Morin, Malorni (2010), which is a Likert scale. MAWS comprise of 12 questions that measure motivation level of employees using a seven-point Likert scale. The scale rate responses of employees from 1 meaning ‘not at all’ to 7 meaning ‘exactly’.
The total scores for MAWS range from 12 to 84 scores, which are the smallest to the highest scores. Gagne et al. (2010) state that MAWS is an established scale that measures motivation level among employees for it uses self-determination theory and assesses both extrinsic and intrinsic motivation. Extrinsic motivation is a form of motivation that one achieves from prestige, social status, financial status, and other materialistic achievements. In contrast, intrinsic motivation is a form of motivation that individuals gain from aspects such as personal development, tasks, and workplace relationships (Agle, Hart, & Thompson, 2014). Thus, the study used MAWS in assessing motivation level of employees in the oil industry.
Locus of control scale (LOCS) is another scale that the study used in measuring locus of control among employees. Locus of control is the ability of individuals to control activities or events that surround and influence them in diverse ways. According to Rotter (1966), LOCS measures external locus of control and internal locus of control using two contrasting statements. LOCS comprise 29 pairs of contrasting questions, which adequately assess locus of control among employees. The scores range from 0 to 29, which indicate low scores and high scores respectively. Low scores suggest internal locus of control and high scores indicates external locus of control.
Trevino and Nelson (2011) explain that individuals with the external locus of control and internal locus of control have different abilities to control activities and events that surround them. Individuals with the external locus of control believe that activities and events that surround them are beyond their control. In contrast, individuals with the internal locus of control believe that they have the capacity to control activities and events that surround them. Thus, LOCS is a valid scale that the study used in measuring locus of control among oil company employees.
Job-related tension index (JRTI) by Wooten, Fakunmoiu, Kim, LeFevre (2010) is a scale that the study used in measuring the level of occupational stress among employees. JRTI is a scale that contains 12 Likert items, which rate the responses from employees on a five-point Likert scale. The scale rated responses using the five-point scale, which range from 1 signifying ‘never’ to 5 signifying ‘nearly all the time’. The high scores imply a high level of stress while low scores imply a low level of stress. Wooten, Fakunmoju, Kim, and LeFevre (2010) state that JRTI has a reliability of 0.87 which means that it has high internal validity. Calculation of a composite variable from the 12 Likert items gives the JRTI scores ranging from 12 to 60 scores, which accurately determine the stress level. Thus, JRTI is a very reliable instrument for measuring occupational stress amongst employees in the oil industry.
Procedure
In the collection of data, the study sought permission from the Middlesex University Ethics Committee (see appendix) that assessed ethical compliance of the study and approved it. Woodside (2010) asserts that informed consent is a requirement in research that deals with humans as participants. In compliance with research ethics, the study also sought the consent of the employees by explaining to them the essence of the study and requesting them to participate after obtaining their written consent (see appendix). Moreover, the researcher assured employees that the information collected would be confidential and applicable for research purposes only. Consequently, the study administered questionnaires to the selected participants and directed them on how they would complete the questionnaires. The researcher gave the participants ample time to answer questionnaires and debriefed them once they completed. The researcher collected questionnaires and spent around five minutes to debrief each participant or on occasions, a group of participants.
Data Analysis
The study used multiple regression analysis in determining the influence of motivation and locus of control on occupational stress among employees in the oil industry. Since the study sought to determine if motivation and locus of control are statistically significant predictors of occupational stress, the multiple regression analysis offered an appropriate test. Multiple regression analysis is a powerful statistical method for predicting the influence of two or more independent variables on a dependent variable (Cohen, West, and Aiken, 2014; Neuman, 2011). Motivation and locus of control are two independent variables while occupational stress is the dependent variable. In multiple regression analysis, independent variables are predictors of the dependent variables. Thus, motivation and locus of control are predictors of occupational stress among employees in the oil industry.
In this case, the locus of control and motivation are two variables that the study used in predicting occupational stress amongst oil company employees in Abu Dhabi. Therefore, multiple regression analysis was conducted to study the correlation of the independent variables and the dependent variable. The study used descriptive statistics in the analysis of data that relate to demographics, motivation, locus of control, and occupational stress. According to Babbie (2010), descriptive statistics offers primary analysis of data because they provide patterns and trends of a certain phenomenon. In this case, since the study has demographic data, which indicate gender, education level, marital status, and age group, descriptive statistics offers an appropriate method of analysing them. Locus of control has both internal and external parameters, and motivation has both extrinsic and intrinsic parameters. As occupational stress has both high and low levels of stress, descriptive statistics described their trends and patterns among employees.
Results
The descriptive statistics and multiple regression analysis present results, which are important in determining the influence motivation and locus of control on occupational stress. Frequency tables indicate the distribution of demographic data among employees. Table 1 below shows most employees (47.7%) fall within the age bracket of 27-36 years followed by those (22.7%), who fall within the age bracket of 18-26 years. Therefore, the frequency table indicates that most employees (70.3%), who participated in the study, are young adults with ages between 18 and 36 years.
Table 1.
Table 2 below shows the crosstab between the gender and marital status of the participated employees. The gender distribution of employees who participated in the study reveals that male employees comprise 56.4% while female employees comprise 40.7% of the total participants. In addition, the results show that most of the female employees are single (70.8%) while most of the male employees are married (69.3%). The distribution of employees means that most of the male employees have considerable burden because have they have families.
Table 2.
The table below (Table 3) shows the crosstab of the age and the education level of the employees. Most of the participants (47.7%) fall within the age bracket of 27-36 years followed by those (22.7%) who fall within the age bracket of 18-26 years. Therefore, the cross-tabulation indicates that most employees (70.3%) who participated in the study are young adults of the ages between 18 and 36 years. In addition, notably 85.5% of employees who participated in the study are learned and have reached bachelors, masters, and doctorate educational levels. That is (57%) have attained bachelor’s level followed by (27.3%) of the participants who have attained masters’ level.
Table 3.
Table 4 is crosstab showing the distribution of age and education level of employees. From the table, it is apparent that 42.9% and 42.9% of employees with high school level of education are in the age brackets of 18-26 and 17-36 respectively. Moreover, 50% of employees with diploma level of education are in the age bracket of 27-36. Most employees (45.9% and 53.2%) with bachelor and masters’ levels of education respectively are in the age bracket of 27-36. These findings show that most employees with the ages between 18 and 36 years have high school, diploma, bachelor, and masters’ levels of education. However, all employees with doctorate are within the ages of 47-56 (50%) and 57-66 (50%).
Table 4.
Descriptive Statistics
The descriptive statistics in terms of mean and standard deviation indicate a measure of central tendency and dispersion respectively. JRTI measures occupational stress on a scale that ranges from 12 to 60. Occupational stress has a mean of 32.43 and a standard deviation of 10.21, which indicate that most employees have average occupational stress. Motivation scale measures motivation on a scale that ranges from 12 to 84. Motivation has a mean of 57.91 and standard deviation of 10.15, which shows that most employees have above average motivation level. LOCS has a scale that ranges from zero to 29. The mean and standard deviation of LOCS is 15.5 and 3.02 respectively. The descriptive statistics indicate that almost equal number of employees have internal and external locus of control.
Table 5.
Multiple Linear Regression Analysis
The multiple regression model has a weak multiple correlation coefficient (R = 0.245) which is positive. The weak multiple correlation coefficient implies that the locus of control and motivation are weak positive predictors of occupational stress among employees. The coefficient of determination (R2) is 0.06, which means that locus of control and motivation explains 6% of the variation in occupational stress. With consideration of irrelevant independent variable, the adjusted R-square shows that motivation and locus of control explain 4.7% of occupational stress. The multiple regression table (Table 6) shows locus of control and motivation as significant predictors of occupational stress amongst oil company employees, F(2, 144) = 4.607, p<0.05.
Table 6. Multiple Regression Analyses of Motivation and Locus of Control on Occupational Stress.
Note: R2 is adjusted for two predictors; β is a standardized coefficient; *p<.05; **p<.01.
The coefficients of motivation and locus of control in Table 5 give a regression equation, which predict occupational stress. The equation: occupational stress = 19.345 + 0.240 × Motivation – 0.031 × locus of control. The standardised coefficient of motivation means that for a unit increase in motivation, there is an increase in occupational stress by 0.240 when locus of control is constant. Comparatively, the standardised coefficient of locus of control implies that for a unit increase in locus of control, there is a decrease in occupational stress by 0.031 when motivation is constant. Analysis of the contribution of each independent variable to the model indicates motivation as a significant contributor to the model (p<0.01) and locus of control as an insignificant contributor to the model (p>0.05).
Discussion
Demographic variables such as age, gender, education level, and marital status provide valuable information about the nature of oil company employees selected to participate in the study. Although the study did target employees with ages between 18 and 66 years, most employees (70.3%), who took part in the study, had the ages between 18 and 36 years. According to Bresic, Knezevic, Milosevic, Tomljanovic, Golubovic, and Mustajbegovic (2007), the demanding nature of work in the oil industry requires young employees because they have a high work ability index. In this view, the demographic attribute reflects the trend in the oil industry. Moreover, Ekundayo (2014) states that young employees have the capacity to manage occupational stress. Therefore, analysis of findings considers that most employees in the oil industry are young with the ages ranging between 18 and 36 years.
Regarding the aspect of gender, male employees constitute 57.6% while female employees constitute 42.4%. Given that the total number of respondents is 172, it implies that there is no significant difference between the number of male and female employees. Education level is an important demographic variable that defines and differentiate employees. From Table 3, it is apparent that 57% of employees have bachelor’s level of education, and 27.3% of employees have masters’ level of education. Overall, 85.5% of employees have attained bachelor, masters, and doctorate educational levels of education. Shallal (2011) argues that the oil industry attracts employees with higher education level than other industries because they offer competitive remuneration to employees. Hence, the employees who participated in the study have required knowledge and skills as per their education levels. The analysis of marital status shows that about two-third of employees are married (66.9%), while a third of employees are single. These findings indicate that most employees have dependents in their families, and thus, depict the extent of their responsibilities in addition to their industrial duties.
Motivation is an important independent variable, which determines occupational stress among employees in the oil industry. Statistical analysis of the responses obtained from 172 employees indicates that 12%, 45.1%, and 33.3% moderately, strongly, and very strongly agree with the Likert items of MAWS respectively. These data show that most employees (92%) have high motivation scores. Gagne et al. (2010) states that MAWS measures the degree of motivation as low scores suggest low motivation and high scores suggest high motivation. The degree of motivation can also be extrinsic and intrinsic, depending on the source of motivation. Extrinsic motivation originates from prestige, social status, financial status, and other materialistic achievements whereas intrinsic motivation originates from personal development, tasks, and workplace relationships (Agle et al. 2014).
MAWS has subscales, which assess extrinsic motivation and intrinsic motivation. Ayub and Rafif (2011) state that Likert items 4, 8, and 12 assess intrinsic motivation, while Likert items 1, 5, and 9 assess extrinsic motivation. Distribution of both extrinsic motivation and intrinsic motivation scores depict negative kurtosis with an approximate mean of 14. These data indicate that employees have above average level of extrinsic motivation and intrinsic motivation.
To perform multiple regression analysis, the data collected using MAWS should follow the normal distribution. According to Davis (2013), the assumption of normality is paramount in regression analysis because it enhances the reliability of multiple regression models. In this view, the test of normality done on motivation variable indicates that it follows the normal distribution. Field (2013) states that the descriptive statistics offer important information regarding the distribution of data relative to the normal curve. The descriptive statistics of motivation shows that the data follow the normal distribution (57.9, SD = 10.15). In this perspective, the distribution of motivation data meets the assumption of normality, which in central in multiple regression analysis. Therefore, the distribution of motivation data clearly indicates that there are no apparent outliers, which could reduce the reliability of the multiple regression model.
Description of the locus of control shows that 57.6% of employees have an internal locus of control, while the remaining 42.4% have an external locus of control. Bernardi (2012) argues that internal locus of control means that individuals have the capacity to control activities and events in their environment while external locus of control means that activities and events in an environment control individuals. Whereas the majority of employees (57.6%) have the capacity to control activities and events in their workplace, the minority of employees (42.4%) is subject to activities and events in their place of work. Analysis of the distribution of data collected using locus of control scale signifies that it follows the normal distribution and has no significant outliers. The descriptive statistics indicate that locus of control has a mean and a standard deviation of 15.5 and 3.02 respectively.
As the dependent variable in multiple regression analysis, the level of occupational stress varies among employees. Frequency analysis shows the distribution of occupation stress among employees in terms of different levels. It is apparent that 44.8%, 23.3%, and 21.5% of employees sometimes, rarely, and often agree with Likert items. Descriptive statistics gives an enhanced view of the distribution of data. Table 5 clearly indicates that occupational stress among employees ranges from 12 to 57 with the mean of 32.43 and the standard deviation of 10.21(M = 32.43±10.21). The standard deviation indicates that occupational stress has a marked variation from the mean. Regarding the test of normality, kurtosis and skewness are within the range of ±0.5, which means that there are no biased distributions of data. According to Khine (2013), kurtosis and skewness within the range of ±0.5 indicate that a distribution of data follows the normal distribution. Furthermore, descriptive statistics shows that the occupation stress data meet the assumption of normality, and thus, fit multiple regression analysis.
Multiple regression analysis is applicable in developing a statistical model that predicts an independent variable based on two or more independent variables. Gaurav (2011) argues that multiple regression analysis is a robust statistical method that assesses the nature and degree of association between a dependent variable and numerous independent variables. In this view, the multiple regression analysis determined the nature and degree of relationships that exist between occupational stress, which is the dependent variable, and locus of control and motivation, which are independent variables. Essentially, multiple regression analysis has numerous coefficients, which are applicable in interpreting relationships between independent variables and dependent variable (Allen, 2007). Hence, the study used relevant factors in interpreting multiple regression analysis.
The coefficient of multiple correlation (R) is a central parameter, which indicates the nature and strength of association between occupational stress and two independent variables, namely, motivation and locus of control. Acton, Miller, Maltby, and Fullerton (2009) explain that the nature of association can be either negative or positive, and the strength of association can be weak, moderate, or strong. Multiple regression analysis shows that R is 0.245, which means that there is a weak association. Moreover, the coefficient means that the association between the independent variables and the dependent variable is positive. In this view, the model indicates that motivation and locus of control positively predict occupational stress among employees.
The coefficient of determination (R-square) is a significant variable in multiple regression analysis. According to Weinberg and Abramowitz (2008), R-square defines the predictive ability of a multiple regression model. In this case, R-square of 0.06 suggests that motivation and locus of control explain 6% of the variation in occupational stress among employees. Franck (2013) argues that when independent variables explain less than 50% of a dependent variable, they have weak explanatory power. Thus, motivation and locus of control only explains 6% of the variation in occupational stress and leaves 94% unexplained.
Given that unexplained proportion is less than explained proportion, apparently the model does not fit the data analysed. Adjusted R-square is 0.047, a figure that is significantly lower than R-square. According to Sa (2007), R and R-square are inaccurate coefficients as they increase as the number of independent variables increase, in spite of their insignificant contribution to the model. Fundamentally, adjusted R-square takes into account the number of independent variables and factor in their contribution to the model (Woodhouse, 2003). In this case, adjusted R-square holds that locus of control and motivation explains 4.7% of the variation in occupational stress, which is considerably lower than the explanatory power of R-square.
Given that the model has positive values of R, R-square, and adjusted R-square, there is a need to determine the significance of the multiple regression model. Longnecker (2015) states that F-ratio is a statistic that determine if the model predictive capacity that is statistically significant. In essence, F-statistic indicates if motivation and locus of control are collective predictors of occupational stress. From Table 6, it is evident that locus of control and motivation are significant predictors of occupational stress among employees, F(2, 144) = 4.607, p<0.01. Numerous studies demonstrate that locus of control determines the level of occupational stress among individuals (Basim et al. 2010; Bernardi, 2012; Karimi & Alipour, 2011). Two types of locus of control, namely, external locus of control and internal locus of control have marked influence on occupational stress.
Karimi and Lipour (2011) argue that individuals with an internal locus of control can easily cope with occupational stress while individuals with an external locus of control have trouble in coping with occupational stress. Other studies also indicate that motivation is a significant predictor of occupational stress in workplaces (Alamdari & Mehrabi, 2014; Siddique & Farooqi, 2014; Jamadar, 2012). According to Alamdari and Mehrabi (2014), a study done to establish the relationship between occupational stress and managerial motivation indicate that they have a positive association. In this case, the regression model supports early findings by indicating that both occupational stress and locus of control have a positive relationship with occupational stress. In determining the contribution of individual independent variables to the model, the study undertook an analysis of motivation and locus of control. Table 6 indicates that locus of control gives statistically insignificant contribution to the model (p>0.05) while motivation gives a statistically significant contribution to the model (p<0.01).
Using the coefficients, the regression equation is that: Occupational stress = 19.345 + 0.240 × Motivation – 0.031 × locus of control. The regression equation implies an increase in motivation by a unit results in an increase in occupational stress by 0.240 when locus of control remains constant. These findings are consistent with earlier findings of a study done among 54 university employees to determine the relationship between occupational stress and career growth (Beheshtifar & Modaber, 2013).
The career plateau, job content, and hierarchical plateaus are three aspects of career growth that mediate occupational stress. The findings of the study show that job content and hierarchical promotions associate with occupational stress because employees constantly struggle to perform and meet the required demands of their respective jobs. In this perspective, job content and hierarchical promotion are factors that motivating employees to perform, but they eventually predispose them to occupational stress. The findings of another study by Kakkos et al. (2011) also support these findings because they assert that the motivation to perform compels employees to work hard and ensure significant strain, which stresses them. Hence, the motivation to perform in the workplace is a significant factor that increases occupational stress among employees.
Comparatively, the regression equation also implies that for a unit increase in locus of control, there is a decrease in occupational stress by 0.031 when motivation remains constant. Locus of control determines predisposition to occupational stress in the workplace. Basim et al. (2010) hold that role ambiguities create psychological problems, and thus, increase occupational stress among employees, particularly those with external locus of control. Employees with external locus of control are susceptible to occupational stress because they experience great challenges in their workplaces (Serratore, 2015).
In contrast, employees with internal locus of control have the capacity to handle challenges that they encounter in the course of their duties, and hence, they are able to alleviate occupational stress. A study done by Ashby et al. (2002) shows employees with internal locus of control perform better than the employees with external locus of control because they have the ability to overcome challenges in their workplace. Descriptive statistics indicate that locus of control was average among oil company employees because the mean and standard deviation was 15.50 and 3.02 respectively. These statistics mean the oil company employees were distributed approximately equally to groups with external locus of control and internal locus of control. Basim et al. (2011) found out that discovered that 65% of the respondents had an internal locus of control while the remaining 35% had an external locus of control. Kumasey, Delle, and Ofei (2014) found out that occupational stress varies according to sex and roles of employees. These findings show that locus of control varies across populations of employees in various professions.
Overall, the study findings support earlier findings that motivation and locus of control individually and collectively predict occupational stress in the workplace. Multivariate analysis shows that occupational stress emanates from diverse factors in the workplace, which vary according to the nature of the work and the workplace (Ereno et al., 2014). Vegchel, Jonge, and Landsbergis (2005) established that occupational stress emerges from the interplay of workplace resources and job demands. In the oil industry, it is apparent that motivation and locus of control determine the level of occupational stress. In this view, the study concludes that motivation is a statistically significant predictor of occupational stress, but locus of control is statistically insignificant predictor of occupational stress.
Conclusion
Occupational stress is one of the factors that determine the productivity of employees in the workplaces. Fundamentally, occupational stress affects mental health and consequently reduces the productivity of employees. As mental health is a significant aspect of human health, occupational stress deteriorates it. Occupational stress reduces productivity of employees by causing psychological and emotional disturbances leading to behavioural changes. Psychologists have established that occupational stress poses a serious challenge to the health of employees. Occupational stress is common in modern workplaces, mainly industries because they have demanding tasks, which overwhelm capabilities of employees. Employers experience great challenges in the management of employees in industries with demanding tasks such as oil industry.
Usually, some factors mediate the occurrence of occupational stress in various industries. As an industry with demanding tasks, oil industry predisposes employees to occupational stress. This study hypothesised that the independent variables, namely, locus of control and motivation, predict the occurrence of occupational stress among employees who work in the oil industry in Abu Dhabi. The findings support the hypothesis partly because they indicate that motivation is a statistically significant predictor of occupation stress, whereas locus of control is a statistically insignificant predictor of occupation stress. Therefore, the findings highlight motivation as a significant factor that associates with occupational stress among employees who work in the oil industry in Abu Dhabi. These findings imply that companies in the oil industry should leverage motivation and locus of control in reducing occupational stress and promoting productivity. Overall, the study holds that motivation and locus of control are determinants of occupational stress among employees in the oil industry.
References
Acton, C., Miller, R., Maltby, J., & Fullerton, D. (2009). SPSS for Social Scientists. London: Palgrave Macmillan.
Agle, R., Hart, W., & Thompson, A. (2014). Research companion to ethical behavior in organisations: Constructs and measures. London: Edward Elgar Publishing.
Agolla, H. (2008). Occupational stress in organisations and its effects on organisational performance. Journal of Management Research, 3(1), 123-135.
Alamdari, S., & Mehrabi, J. (2014). The relationship of tress and occupational motivation in managers of social welfare organisation of Tehran city. Indian Journal of Fundamental and Applied Life Sciences, 4(4), 2276-2287.
Allen, M. (2007). Understanding Regression Analysis. Rotterdam: Springer Science & Business Media.
Ashby, J., Kottman, T., & Draper, K. (2002). Social interest and Locus of Control: Relationship and implications. The Journal of Individual Psychology, 58(1), 52-61.
Ayub, N., & Rafif, S. (2011). The Relationship between Work Motivation and Job Satisfaction. Pakistan Business Review, 1(2), 322-347.
Babbie, R. (2010). The practice of social research. Belmont, Calif: Wadsworth Cengage.
Basim, H., Erkenekli, M., & Sesen, H. (2010). The Relationship of Locus of Control in Individual Behavior with the Perception of Role Conflict and Role Ambiguity: an Investigation in the Public Sector. Review of Public Administration, 4(1), 169-189.
Beheshtifar, M., & Modaber, H. (2013). The investigation of Relation between Occupational Stress and Career Plateau. Interdisciplinary Journal of Contemporary Research in Business, 4(11), 650-660.
Beheshtifar, M., & Nazarian, R. (2013). Role of Occupational Stress in organisations. Interdisciplinary Journal of Contemporary Research in Business, 4(9), 648-657.
Bernardi, R. (2012). The relationship among locus of control, perceptions of stress, and performance. Journal of Applied Business Research, 13(4), 1-8.
Bianchi, E. (2004). Stress and coping among cardiovascular nurses: a survey in Brazil. Issues in mental health nursing, 25(7), 737-745.
Bresic, J., Knezevic, B., Milosevic, Tomljanovic, T., Golubovic, R., & Mustajbegovic, M. (2007). Stress and work ability in oil industry workers. Archives of Industrial Hygiene and Toxicology, 58(1), 399-405.
Cascio, M., Magnano, P., Elastico, S., Costantino, V., & Battiato, A. (2014). The Relationship among Self-Efficacy Beliefs, External Locus of Control and Work Stress in Public Setting Schoolteachers. Open Journal of Social Sciences, 2(1), 149-156.
Chen, W., & Wong, T. (2005). Impact of occupational stress and other psychosocial factors on musculoskeletal pain among Chinese offshore oil installation workers. Occupation & Environmental Medicine, 62(4), 251-256.
Cohen, P., West, S., & Aiken, L. (2014). Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences. New York: Psychology Press.
Cosio, S., Olson, L., & Francis, J. (2011). Social Support and Occupational Stress among University Employees. Graduate Student Journal of Psychology, 13(3), 30.
Darshani, R. (2014). A Review of Personality Types and Locus of Control as Moderators of Stress and Conflict Management. International Journal of Scientific and Research Publications, 4(2), 1-8.
Davidson, C. (2009). Abu Dhabi’s new economy: Oil, investment, and domestic development. Middle East Policy, 16(2), 59-79.
Davis, C. (2013). SPSS Step by Step: Essentials for Social and Political Science. New York: Policy Press.
De-Nobile, J., & McCormick, J. (2005). Job Satisfaction and Occupational Stress in Catholic Primary Schools. Leading & Managing, 13(2), 31-48.
Ekundayo, J. (2014). Occupational stress and employees productivity in the workplace. International Journal of Scientific Research in Education, 7(2), 157-165.
Ereno, J., Andrade, K., Miyauchi, S., Salinda, R., Arevalo, R., & Reyes, J. (2014). Encountering and Countering Work Stress: A Multivariate Analysis of the Occupational Stress and Coping Mechanisms of Fast Food Restaurant Personnel in the Philippines. European Scientific Journal, 10(8), 148-158.
Fazio, R., & Olson, M. (2003). Implicit measures in social cognition research: Their meaning and use. Annual Review of Psychology, 5(2), 297-327.
Fernet, C., Austin, S., & Vallerand, R. (2013). The effects of work motivation on employee exhaustion and commitment: An extension of the JD-R model. An International Journal of Work, Health & Organisations, 26(3), 213-229.
Field, A. (2013). Discovering statistics using SPSS (4th ed.). London: SAGE Publisher.
Franck, R. (2013). The Explanatory Power of Models: Bridging the Gap between Empirical and Theoretical Research in the Social Sciences. Dordrecht: Springer Netherlands.
Gagne, M., Forest, J., Gilbert, M.-H., Aube, C., Morin, E., & Malorni, A. (2010). Motivation at work scale: English version. Web.
Galletta, M. (2011). Intrinsic motivation, job autonomy, and turnover intention in the Italian healthcare: The mediating role of affective commitment. Journal of Management Research, 3(2), 1-19.
Gaurav, K. (2011). Multiple Regression Analysis: Key to Social Science Research. Munchen: GRIN Verlag GmbH.
Gaus, N. (2014). Locus of Control Job Satisfaction Job Stress among Female Head teachers at Primary Schools in Makassar, Indonesia. Advancing Women in Leadership, 34(1), 19-27.
Goodwin, C. J. (2010). Research in psychology: Methods and design. Hoboken: John Wiley.
Gorard, S. (2013). Research design: Creating robust approaches for the social sciences. New York: SAGE Publisher.
Gray-Stanley, J., Muramatsu, N., Heller, T., Hughes, S., Johnson, T., & Ramirez-Valles, J. (2010). Work stress and depression among direct support professionals: the role of work support and locus of control. Journal of Intellectual Disability Research, 54(8), 749–761.
Harhara, A., Singh, S., & Hussain, M. (2015). Correlates of employee turnover intentions in oil and gas industry in the UAE. International Journal of Organisational Analysis, 23(3), 12-23.
Islam, J., Mohajan, H., & Datta, R. (2012), Stress Management Policy Analysis: A Preventative Approach, International Journal of Economics and Research, 3(4), 3-10.
Jain, M., & Singh, I. (2015). A Study on Factors Affecting Motivation and Job Satisfaction Level of Faculty Members In Colleges of Ludhiana. International Journal in Management and Social Science, 3(4), 220-231.
Jamadar, C. (2012). Occupational Stress and Work Motivation among Telecom Employees. Golden Research Thoughts, 1(1), 1-14.
Jesus, S., Rus, C., & Tobal, J. (2013). Effectiveness of a stress management training on Motivation and Well-being. Journal of Spatial and Organisational Dynamics, 1(3), 143-152.
Kakkos, N., Trivellas, P., & Fillipou, K. (2010). Exploring the link between job motivation, work stress and job satisfaction. Evidence from the banking industry. Accounting and Logistics, 2(1), 211-230.
Khine, M. (2013). Application of structural equation modeling in educational research and practice. Rotterdam: Springer Science & Business Media.
Karimi, R., & Alipour, F. (2011). Reduce Job stress in Organisations: Role of Locus of Control. International Journal of Business and Social Science, 2(18), 232-236.
Kumar, R. (2010). Research Methodology: A Step-by-Step Guide for Beginners. New York: SAGE Publisher.
Kumari, M. (2008). Personality and Occupational Stress Differentials of Female School Teachers in Haryana. Journal of the Indian Academy of Applied Psychology, 34(2), 251-257.
Kumasey, A., Delle, E., & Ofei, S. (2014). Occupational Stress and Organisational Commitment: Does Sex and Managerial Status Matter?. International Journal of Business and Social Research, 4(5), 173-182.
Lee, N., Cadogan, J., & Durden, G. (2006). Work-Related Stressors and Psychological Strain in the Sales Force: The Role of Intrinsic and Extrinsic Motivation. Organisational Psychology, 8(3), 371-400.
Leedy, P., & Osmond, J. (2010). Practical Research: Planning and Design. Upper Saddle River: Prentice Hall.
Longnecker, M. (2015). An Introduction to Statistical Methods and Data Analysis. New York: Cengage Learning.
Maphalala, M. (2014). The Manifestation of Occupational Stress in the Teaching Profession: The Unheeded Voices of Teachers. Mediterranean Journal of Social Sciences, 5(1), 77-88.
Mark, G., & Smith, A. (2012). Occupational stress, job characteristics, coping, and the mental health of nurses. British Journal of Health Psychology, 17(3):505-521.
Michael, O. (2009). Job stress and organisational commitment among mentoring coordinators. International Journal of Educational Management, 23(3), 266-288.
Mitchell, M., & Jolly, J. (2012). Research Design Explained. New York: Cengage Learning.
Mohajan, H. (2012). The occupational stress and risk of it among the employees. International Journal of Mainstream Social Science, 2(2), 17-34.
Nakasis, K., & Ouzouni, C. (2008). Factors influencing stress and job satisfaction of nurses working in psychiatric units. Health science, 2(4), 183-195.
Neuman, W. (2011). Social Research Methods: Qualitative and Quantitative Approaches. Boston: Allyn & Bacon.
Parija, S., & Shukla, A. (2012). Impact of Online Flow Experience on Personality Variables, Subjective Happiness and Satisfaction with Life. Journal of Humanities and Social Science, 5(1), 37-43.
Patwary, M., Uddin, L., Miah, A., & Sarker, M. (2013). Occupational stress and addiction: Possible neurobiological elucidation of medical waste related individuals. Journal of Hospital Administration, 2(2), 71-88.
Pienaar, J., & Rothmann, S. (2006). Occupational Stress in the South African Police Service. SA Journal of Industrial Psychology, 32(3), 72-78.
Ployhart, R. (2006). Staffing in the 21st century: New challenges and strategic opportunities. Journal of Management, 32(3), 868-879.
Rehman, H. (2008). Occupational Stress and a Functional Area of an Organisation, International Review of Business Research Papers, 4(4), 163-173.
Reis, S., & Judd, C. (2014). Handbook of Research Methods in Social and Personality Psychology. New York: Cambridge University Press.
Rosenow, D. (2005). Stress, Burnout and Self-Esteem among Educators. Journal of Border Educational Research, 4(1), 87-92.
Rotter, B. (1966). Generalised expectancies for internal versus external control of reinforcement. Psychological Monographs, 80(1), 1-28.
Ryan, R., & Deci, E. (2000). Intrinsic and Extrinsic Motivations: Classic Definitions and New Directions. Contemporary Educational Psychology, 25(2), 54–67.
Sa, M. (2007). Applied statistics: Using SPSS, Statistica, MATLAB, and R. Berlin: Springer.
Shallal, M. (2011). Job satisfaction among women in the United Arab Emirates. Journal of International Women’s Studies, 12(3), 114-134.
Shikieri, A., & Musa, H. (2012). Factors associated with occupational stress and their effects on organisational performance in a Sudanese University. Creative Education, 3(1), 134-144.
Serratore, N. (2015). Teaching towards self-regulation: The impact of stress, self-efficacy, and motivation. Accounting and Logistics, 4(1), 5-11.
Siddique, U., & Farooqi, Y. (2014). Investigating the Relationship between Occupational Stress, Motivation and Job Satisfaction among University Teachers. International Journal of Academic Research in Progressive Education and Development, 3(4), 36-46.
Sliskovic, A., Sersic, M., & Buric, I. (2011). Work locus of control as a mediator of the relationship between sources and consequences of occupational stress among university teachers. Review of Psychology, 18(2), 109-118.
Touré-Tillery, M., & Fishbach, A. (2011). The course of motivation. Journal of Consumer Psychology, 20(3), 1-10.
Trevino, K., & Nelson, A. (2011). Managing business ethics: Straight talk about how to do it right. New York: John Wiley.
Uma, K., & Manikandan, K. (2013). Influence of Locus of Control, Self-Esteem, and Sex on Academic Stress among Adolescents. Guru Journal of Behavioral and Social Sciences, 1(4), 186-193.
Vaezi, S., & Fallah, N. (2011). The Relationship between Self-efficacy and Stress among Iranian EFL Teachers. Journal of Language Teaching and Research, 2(5), 1168-1174.
Vegchel, N., Jonge, J., & Landsbergis, P. (2005). Occupational stress in (inter)action: the interplay between job demands and job resources. Journal of Organisational Behavior, 26(2), 535–560.
Weinberg, S. L., & Abramowitz, S. K. (2008). Statistics using SPSS: An integrative approach. Cambridge: Cambridge University Press.
Woodhouse, R. (2003). Statistical regression line-fitting in the oil & gas industry: A descriptive guide with Microsoft Excel examples. Tulsa, Okla: PennWell Corp.
Woodside, A. (2010). Case study research: Theory, methods, and practice. London: Emerald Publishing Group.
Wooten, R., Fakunmoju, B., Kim, H., & LeFevre, A. L. (2010). Job-related tension index: Revised. Web.