Keywords

Workload, Job Stress, Job Satisfaction.

Introduction

In today’s fast-paced world, human lifestyle is faced with increased complexity and serious challenges in comparison to the lifestyle of previous generations who were stress less. Nowadays, people are constantly dealing with stress arising from their job or workplace. However, work is one of the essential aspects of one’s work behavior and life and job stress cannot simply be dealt by eliminating the source of stress, as it can further leads to other hazards. Therefore, it is important to understand that stress not always cause negative effects rather it can also influence individuals in a constructive manner (Chienwattanasook & Jermsittiparsert, 2019; Kerdpitak & Jermsittiparsert, 2020).

Stress can be of many types, such as, technical stress, managerial stress, mental stress and burnout stress, etc. It may arise in every kind of job. Job stress refers to the pressures and demands arising from organizations toward their employees (Stimec & Grima, 2019). Firms often cause significant impact on the health of their employees (Kanayo, 2017) and may influence individuals in several ways. However, positive stress brings motivation among workers to improve their productivity and performance for better career. On the contrary, unmanageable stress may cause negative impact on employees, leading to physiological, psychological and social disorders.

Kanayo (2017) study found empirical evidence that job stress may possibly causes physical disorders, such as, heartburn, heart disease, asthma, high blood pressure, insomnia, persistent fatigue and cancer. Besides, it can also cause damage to psychological health of employees, such as, dissatisfaction, depression, and lack of concentration.

Stress is generally divided into two main types, first is the eustress, which is defined as the constructive or valid stress that is likely to enhance employees’ personal productivity (Kairiša & Lapina, 2019), like it improves performance and work quality. It thus indicates eustress as a good stress while the second type of stress is distress, which is also known as a bad stress, since it may negatively influence the individuals. Distress refers to ‘a persistent stress that brings about physiological strain on the individuals. Distress can be in the form of being fired at work, filing for divorce, and major illness.

Stress at work may bring serious consequences for the employees. It is interesting to study this topic since the cases of burnout; mental disorder and depression among workers have been rapidly increasing among employees. Ranavolo et al. (2017) supported the argument of National Institute of Occupational Safety and Health’s (NIOSH) chairman, who mentioned that the rate of job stress among employees is growing due to mental health issues and depression and have introduced a policy in the name of “Mental health care policy” to address job stress at workplace. Every organization must address and manage two main issues, namely employees’ job satisfaction and stress among employees. At first, they seem to be unrelated to one another, however, the in-depth analysis of these matters show that one usually tends to influence the other one and may bring positive outcomes both for the organization and the employees, only if they are managed properly (Haque et al., 2018).

Job satisfaction can be a possible cause of stress. Several theories proposed during 1920-1950 have supported the idea that employee’s work is affected by level of satisfaction towards his or her job. Such as, Haque et al. (2018) assumed that cause-and-effect relationship exists between employees’ productivity and satisfaction. He further pointed out that nowadays, organizations are majorly concerned to achieve stable and high productivity, therefore organizations are required to manage job satisfaction of their employees, since job satisfaction is assumed to have a direct impact on employee’s mental health. Furthermore, employees with greater satisfaction towards their job are likely to provide healthy and positive outcomes to the organization. Haque et al. (2018) reported that factors which may influence employee’s job satisfaction also provide meaningful and necessary information to the managers for taking wiser interventions and decisions to increase job satisfaction of their employees. It has been proved by several prior studies that employee retention and employee satisfaction have been the actual concerns for the organizations.

Meanwhile, job stress is considered as a consequence of job satisfaction. According to Tufail & Sultan (2019), working environment can also be a cause of job stress. It can be in the form of role conflict, workload, or the interruptions. Furthermore, a few researchers have attempted to investigate the effects of job stress on employee’s low performance, which is assumed as the most affected area as compared to psychological strain (Lee et al., 2017). Job stress occurs in every profession and even teachers cannot refrain themselves from stress. At all levels, an educator are considered as a main constituent of the education system, even at the university level (Özdemir et al., 2019). A teacher’s responsibilities, roles and duties play a crucial role in achieving national educational goals, and these goals include 1) educator’s aims to educate life of a nation; 2) it strives for enhancing human quality, such as mastery of the art, science, and technology and moral quality, and quality of faith. Thus, in order to achieve strategic positions, roles and functions, universities require professional lecturers, which is one of the essential components in offering students with help to enable them to become innovative, competitive and intelligent human beings having good morals.

Literature Review

Job Stress

Job stress is defined by Foy et al. (2019) as “a conflict between employee capabilities and job demands, which consequently leads to harmful emotional and physical responses”. Numerous prior studies have reported different levels of job stress, its causes and effects based on the factors which affect job stress, such as, working environment. Additionally, job stress may also cause mediating effects on the certain human aspects. Mediating effect refers to “an intervening variable which intermediates between the independent and dependent constructs” (Hair et al., 2016).

Besides, job stress may also affect satisfaction as a moderating variable (Lukango, 2017). High levels of stress may have adverse effects on the psychological well-being, physical health and work performance of the employees. In view of Karem et al. (2019), stress refers to “an emotional reaction against external effects and may negatively influence health of employees”. The effects of stress are often intangible and may take place in the form of frequent headaches, fatigue, low productivity and weight loss or weight gain. Prior studies (Kong & Jolly, 2019; Lukango, 2017) have shown that job stress often brings about job dissatisfaction.

Nonetheless, job stressors are not only linked with mental health but also cause physical ill-health, which occurs, may be because of workplace frustration. Such as, the university lecturers are generally required to actively learn new skills and implement these new learned skills to improve their teaching skills and also resolve social issues (Gloria & Oluwadara, 2016). Thus, in an attempt to achieve multiple tasks, lecturers may sometimes find themselves frustrated due to stressful work situation.

Researchers consider stress as a threat to a sound physical and mental health. According to a report, stress signs, such as, conflict or tension can easily be identified in individuals as well as organizations (Jayanthi et al., 2018). There are several characteristics of stress which can be observed in various ways. As a matter of fact, conflict and stress may cause massive damages, therefore, every year, firms have been spending considerable amount of money to deal with issues arising from job stress (Jayanthi et al., 2018), which seems to be quite costly for the organizations.

Workload

Workload refers to ‘the number of tasks an individual must carry out, and thus acts as one of the important stressor’ (Goldschmied & Spitznagel, 2020). It can be further divided into two types; firstly, when too many tasks are assigned to the employees; secondly, when employees feel incapable to manage that certain task due to perceived lack of abilities, knowledge and skills to accomplish that task. However, work is not harmful in itself, but workload may lead to massive issues. In addition, effects of workload may also occur in the form of higher propensity to quit, lower commitment, psychological health, exhaustion and higher tension. Tufail & Sultan (2019) suggest work environment as one of the job stressors. For instance, it may occur as role ambiguity, or work load, which are capable of affecting the well-being of individuals at their job place. Virgolino et al. (2017) supported this argument and described the term workload as “a confusion, or difficulty in completing tasks, cognitive overload and rapid decision-making which serve as the contributory factors in causing job stress”.

Time Pressure: Meanwhile, time pressure is also assumed to have a direct relationship with amount of time within which employees are required to complete a certain task (Goldschmied & Spitznagel, 2020), which is likely to increase the perceived level of stress. In this regard, several psychology and stress and auditing related studies have reported that time pressure significantly affects the task performance.

In a study, the top management healthcare workers were found to be more susceptible to higher stress levels than the general workforce (Richter et al., 2018). Thus, time pressure acts as one of the important factors which cause health care workers to face higher stress levels. Scholars have argued that time pressure often occurs when there is insufficient time available for the employees to complete certain tasks (Mangalaselvi, 2017; McVicar, 2016). Another study suggested time pressure as a factor responsible for long working hours and increasingly competitive work environment. In addition, time pressure may directly influence the strain producing factor and in turn it will trigger several other workplace factors. Thus, time pressure determines the level to which employees are exposed to workplace stressors. Moreover, long working hours also expose workers to other job stressors.

Interruptions: According to Gupta et al. (2016), interruptions are the interferences which usually arise while performing certain tasks. In most professions, workflow interruptions arise every now and then (Maniya, 2018). Interruptions refer as “the secondary tasks which appear during the primary tasks, such as, requests for assistance”. Previous research findings suggest that negative relationship exists between satisfaction and occurrence of interruptions. Moreover, positive relationship was reported between performance and experience of irritation and forgetting of intentions. A study asserts interruption as “common workplace phenomena (Lee, 2017b) and an unwanted intrusion that cause disruptions in employees work”, since it require workers to relocate the total time needed to accomplish the required tasks. From the HR perspective, there exists an association between interruptions and stress, which causes relocation of employees’ time by using cognitive and self-regulatory resources.

Interruption effects occur in the form of physical complaints, anxiety and emotional exhaustion. In Lee (2017b) study, they found organizational factors and interruptions as the main job stress factors. For instance, phone calls, jokes from peers, social networking, emails, and phone calls, etc. Thus, if employees perceive them negatively then they would likely to cause stress among them. (Basheer et al., 2019; Lee, 2017b) supported this and stated that phone calls, colleagues at workplace and e-mails are the common cases of interruption and commonly occur when it is essential for the employees to continuously and quickly share the required information and improve employee performance.

Job Satisfaction

Several definitions have been proposed by scholars to interpret job satisfaction. Job satisfaction is an essential contributor to enhance employees’ competitiveness and organizational performance (Hafeez et al., 2018). In another definition, job satisfaction refers as ‘the perception of employees towards their job’ (Danendra & Rahyuda, 2019). According to Jiang et al. (2019), job satisfaction is a fusion of environmental and psychological factors. However, job satisfaction among academicians is related to the well-being, commitment and their level of motivation towards their job. This is mainly because of the fact they are the important part of human capital resource which accounts for greatest cost. Thus, improving the level of job satisfaction among academicians may reduce costs that are associated with high stress among academicians, such as, illness or absenteeism (Robinson et al., 2019).

The empirical evidence from prior studies has indicated that certain job aspects bring satisfaction to the academicians, for instance, teaching work. However, job dissatisfaction occurs when some elements affect the employees’ job performance, including salary, working conditions and interpersonal relations. Skaalvik & Skaalvik (2016) study has reported teaching efficacy and job stress as the contributors in job satisfaction.

It has been found in a study that job satisfaction among academic staff affects their motivation, performance, their morale as well as performance of their students. A study Fayzhall et al. (2020) reported that observing work pattern is assumed to be helpful in distinguishing the academic staff or teachers who are planning to quit this profession and those who wants to retain their job. However, the perceptions, reactions and attitudes of academicians’ exhibit their intentions. Another study about primary teachers also claim stress and job satisfaction as related (Carson et al., 2016).

Hypothesis

Goldschmied & Spitznagel (2020) defined workload as “a pressure associated with certain tasks that an individual is expected to perform”. Numerous researchers have studied and reported various effects arising from high workload. For instance, a meta-analysis had been conducted using 295 prior researches and the result revealed a strong relationship of workload with depersonalization, higher tension job stress, propensity to quit, psychological health, lower commitment towards firm, and exhaustion (Lee, 2017a).

Moreover, Goldschmied & Spitznagel (2020) study also found a direct relationship between time pressure and the required amount of time within which the employees are expected to finish their assigned tasks. However, if time pressure exceeds from a certain point, then it may negatively influence employees’ performance and ultimately result in job stress (Maniya, 2018). Due to a great deal of workplace interruptions, time pressure also acts as a factor to add on to the job stress (Maniya, 2018). In other research, the researchers failed to establish any direct relationship between job stress and time pressure, even when individuals were assumed to be capable of controlling their tasks on their own.

Gupta et al. (2016) define interruptions as “an interference which generally appears while performing certain assigned tasks”. Addas & Pinsonneault (2018) expound that frequent interruptions usually lead to stress and time delay in tasks completion. Simply put, no direct association exists among interruption and job stress, if the required task is not accomplished in the required time. Thus, a certain task can potentially affect workers’ job stress level.

In another study, a negative correlation was reported between job satisfaction and workload (Guarnaccia et al., 2018). On the contrary, workload is one of the significant job satisfaction factors, especially in context to job satisfaction among academicians. Furthermore, an inconsistent relationship was found by Sun & Xia (2018) between job satisfaction and workload, which has occurred maybe because of situational circumstances or different socio-economic factors.

More importantly, there exists a significant relationship among job satisfaction level and time pressure. Adi et al. (2020) argued that it is the increasing job demands which put time pressure upon the individuals at their workplace. Meanwhile, some scholars Lee (2017b) hold an opinion that job satisfaction and interruptions share a positive relationship, whereas, others Maniya (2018) believe that no correlation exists between interruption and job satisfaction. Majority of the researchers who studied the job satisfaction and interruption relationship have reported that a positive relationship exists between the two.

The academic staff in universities has been experiencing increased job expectations, which have given rise to job stress and low job satisfaction levels among the staff. For instance, a direct relationship was reported among job satisfaction and job stress (Abualoush et al., 2018), while in another study, Haque et al. (2018) found negative effects of job stress, such as, low levels of job satisfaction.

Therefore, job satisfaction serves as an important measure to explain employees’ feelings or perceptions towards their jobs. In addition, job satisfaction is an essential variable to predict work behavior, like employee turnover, absenteeism, or organizational citizenship (Danendra & Rahyuda, 2019). Thus, high stress levels may have negative effects on the psychological well-being, physical health and work performance of individuals. Karem et al. (2019) also defined stress as ‘the emotional or mental response against external influences, which can affect the psychological and physical health of individuals. In Safadi et al. (2019) study, they found a mediating role of job stress on job satisfaction.

H1 Time pressure has significant impact on the job satisfaction.

H2 Interruptions has significant impact on the job satisfaction.

H3 Time pressure has significant impact on the job stress.

H4 Interruptions has significant impact on the job stress.

H5 Job stress has significant impact on the job satisfaction.

H6 Job stress mediates the relationship between the time pressure and job satisfaction.

H7 Job stress mediates the relationship between the interruptions and job satisfaction.

Research Methodology

The survey-based data collected from the university employees was then analyzed after data sorting. In addition, the percentages and frequency tables were also generated. The Statistical Package for Social Sciences (SPSS) was used by the researcher for interpretation of the collected responses. SPSS refers to a data analysis and data management program which is basically designed to perform data analysis, such as, descriptive analysis, which includes, frequencies, lists, plots and charts; and the multivariate statistical methods and inferential statistics (Akter et al., 2017). These analyses allow researcher to interpret the results and can further make recommendations, accordingly. A partial least square structural equation modelling (PLS-SEM) was adopted in this research. PLS-SEM is a statistical data analysis tool that has been extensively used by social science researchers for more than a century (Hair et al., 2016). This technique was used in this research for understanding the complex relationships involved in this study. For this purpose, it is also essential to adopt multivariate data analysis methods. The researcher received 247 questionnaires from the data collection process, representing a response rate of 98.02%. From a total of 247 questionnaires, 97 were male (39.35) and 150 were female (60.7%). The findings indicate female domination over males. The study respondents who were selected for data collection belong to different age groups. Majority of the respondents i.e. 103 respondents fall in 25-35 age group, 90 from 36-45 years of age bracket, 46 were from age group above 45years, and only 8 respondents were below the age of 25 years. In terms of educational background, 78.5 percent (194) of the respondents hold a Masters’ degree, while 15.8% (39) hold a PhD degree and 5.7% (14) hold a bachelor’s degree.

Research Results

The current study has used SPSS-22 to screen the collected data and performance of statistical analysis to answer the research questions. This study has used both statistical techniques (inferential and descriptive). We have broken down a seven point Likert scale further into five different categories, so we have classified the mean values by following the study of Hair et al. (2016) according to which if the mean values lies between (1.00-2.20)very low, if mean values lies between (2.21-3.40) low, if the mean values lies between (3.41-4.60) moderate, and they lie between (4.61-5.80) high, and if they lies between (5.81-7.00) indicates the very high. For the research hypothesis, reliability, and validities we have assessed the measurement and structural model for this we have used Smart PLS 3.1.2 software.

By following the study of Hair et al. (2016), to estimate the path coefficients and loadings, we have used Smart PLS-3 multiple regression and variation of correlation analysis. In general, we use PLS-3 for the estimation of average variance extracted AVE and to bootstrap data set. According to the study of Naala et al. (2017) for complexed model we may employee PLS-3 since there are 4 second order constructs in the present study so, for this study PLS-3 is an ideal to use. In the meantime, the items are of formative and reflective nature so here the use of this software is important in this study as the other software’s may not handle it properly (Hair et al., 2017). In addition to this the measurement errors can be considered by this software so; it is more appropriate for the present study. The statistical analysis of model was also performed by this study for checking the relations among the variables of the study (Hair et al., 2017). Therefore, we have used PLS to estimate the variables and for the confirmation of relations among the variables included in this study. Moreover, we also use this to check the significance of performance matrix analysis (Tables 1-3 & Figure 1).

Table 1 Cross Loadings
	INT	JBST	JST	TP
INT1	0.918	0.854	0.638	0.83
INT2	0.873	0.772	0.55	0.766
INT3	0.929	0.833	0.654	0.806
INT4	0.906	0.821	0.607	0.81
INT5	0.926	0.843	0.659	0.806
JBST1	0.796	0.868	0.65	0.77
JBST2	0.766	0.818	0.602	0.783
JBST3	0.797	0.895	0.686	0.804
JBST4	0.815	0.905	0.69	0.831
JBST5	0.852	0.855	0.603	0.797
JBST7	0.571	0.73	0.857	0.638
JS1	0.599	0.716	0.883	0.626
JS2	0.53	0.64	0.823	0.581
JS3	0.572	0.681	0.875	0.575
JS4	0.531	0.662	0.844	0.55
JS6	0.669	0.744	0.916	0.657
JS7	0.636	0.762	0.909	0.618
JS8	0.667	0.755	0.917	0.653
TP2	0.764	0.803	0.624	0.894
TP3	0.799	0.824	0.59	0.905
TP4	0.752	0.794	0.611	0.884
TP5	0.834	0.861	0.684	0.925
?TP1	0.824	0.819	0.603	0.894

Table 2 Reliability
	Cronbach's Alpha	rho_A	CR	(AVE)
INT	0.948	0.95	0.96	0.829
JBST	0.92	0.921	0.938	0.718
JST	0.952	0.955	0.961	0.777
TP	0.942	0.942	0.955	0.811

Table 3 Validity
	INT	JBST	JST	TP
INT	0.891
JBST	0.806	0.847
JST	0.684	0.806	0.882
TP	0.883	0.711	0.692	0.901

For the determination of construct validity that is (convergent and discriminant validity) and items reliability we have performed the Confirmatory factor analysis (CFA) subsequently in the estimation of MM. Moreover, we have also calculated the average variance extracted (AVE) and composite reliability (CR) for present study. The value of CR must be higher than 0.70, whereas the values of AVE must be higher than 0.50 (Hair et al., 2017; Henseler et al., 2016).

For the Cronbach alpha Ramayah et al. (2018) has suggested the value that is 0.70. The convergent validity will be achieved if the loadings of outer model exceed 1.96 at alpha value 0.05. After the achievement of validity and reliability of MM, the structural model was estimated in next step.

So, though the observation of condition index of independent variables, VIF value and tolerance value we have performed the multicolinearity test where the independent variables were indicate the tolerance, the extent of variance which was not explained by independent variables, were included in structural model.

The variance inflating factor was represented by VIF which is known as the level at which the change in independent variable increase due to the correlations among independent variables, however in formative models the critical levels of collinearity were observed by a conditional index (CI) (Akter et al., 2017; Hair et al., 2016; Mikalef & Pateli, 2017). The VIF value will be greater or equal to 5 when tolerance level is less or equal to 0.2, however if the value of CI is greater than 30 it indicates that there is an existence of multicolinearity in the study. We can see in below Table 4 …all tolerance values are higher than 0.2, whereas the VIF values are less than 5, and the value of CI is less than 30. Which is an indication of multicolinearity issue in the present study (Figure 2).

Table 4 Direct Results
	(O)	(M)	(STDEV)	(|O/STDEV|)	P Values
INT -> JBST	0.461	0.474	0.079	5.82	0
INT -> JST	0.371	0.383	0.066	5.63	0
JBST -> JST	0.806	0.808	0.045	17.792	0
TP -> JBST	0.504	0.49	0.079	6.345	0
TP -> JST	0.406	0.397	0.07	5.775	0

The dependent relationships were reflected by structural model (SM) by creating a connection between hypothetical model and constructs (Hair et al., 2017). The link between the latent variables and relations among the constructs of model were represented well through SM. With the estimation of SM, we have checked the relations of variables and tested the hypothesis as well. We have analyzed the SM for the determination of relevance and significance of structural relations, coefficient of determination, predictive relevance, effect sizes and collinearity issues. To obtain the slandered errors and t-statistics we have carried out the bootstrapping procedure, since for the measurement of PLS estimates accuracy it’s a nonparametric approach. In addition to this it helps the researcher in determination path coefficients significance (Henseler et al., 2016).

All the exogenous or independent variables were represented by Coefficient of determination (R²). The coefficient of determination measures the goodness of fit from obtained items. The range of R-square lies between 0 to 1. It’s the most suitable criteria to measure the predictive relevance of model (Tables 5-7).

Table 5 Mediation
	(O)	(M)	(STDEV)	(|O/STDEV|)	P Values
INT -> JBST -> JST	0.371	0.383	0.066	5.63	0
TP -> JBST -> JST	0.406	0.397	0.07	5.775	0

Table 6 R-Square
	R Square
JBST	0.877
JST	0.649

Table 7 Q-Square
	SSO	SSE	Q² (=1-SSE/SSO)
INT	1085	1085
JBST	1302	491.425	0.623
JST	1519	761.951	0.498
TP	1085	1085

We use the predictive relevance to determine the predictor variables. In SEM this measure assists the observed relevance of reflective constructs. In PLS it’s a supplementary measure to check the goodness of fit (Figure 3).

We have computed the value of Q-square with the accomplishment of blindfolding procedure. The cross-validated redundancy approach was used to check the predictive relevance of construct as structural model, predicted eliminated data and few elements of path model were involved in this approach (Hair et al., 2017).

Discussion and Conclusion

It can be concluded that interruption and time pressure are directly related to job satisfaction. The results obtained from hypothesis testing show that job satisfaction is positively related to interruptions and time pressure, in context to public university’s lecturers in Indonesia. These findings are in line with Medrano & Trógolo (2018) study who found positive relationship between job satisfaction and time pressure. Other studies Lee (2017b) that have been conducted in past also discovered a positive relationship among job satisfaction and interruptions. In every workplace, interruptions commonly occur and may not create any issues if employees are capable of managing their time and work effectively without letting interruption cause negative effects on them (Maniya, 2018). Alternatively, no direct relationship was found between job satisfaction and workloads. For instance, Guarnaccia et al. (2018) have also provided the empirical evidence to prove that job satisfaction and workload are unrelated. Other researchers, like Sun & Xia (2018) also supported this argument, and revealed inconsistent relationship between job satisfaction and workload in their study. However, these inconsistent findings occurred may be because of difference in socio-economic circumstances.

In past, majority of the studies have accepted the potential ability of job stress to reduce job satisfaction level. In Abualoush et al. (2018) study, those victims were identified who experienced job stress and their study reported that they were also experiencing low job satisfaction. Besides, there are several factors which may reduce job stress. For instance, a friendly work environment and a good salary package may improve employees’ attitude towards their job and reduce their stress levels. In view of Yee (2018), a few factors can increase job satisfaction, and also reported age, status, and salary as the factors that were found to improve job satisfaction among academicians.

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