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Article

Key Determinants of Job Satisfaction among University Lecturers

by
Long Kim
1,
Pimlapas Pongsakornrungsilp
2,*,
Siwarit Pongsakornrungsilp
1,
Ngachonpam Horam
3 and
Vikas Kumar
4,5
1
Center of Excellence for Tourism Business Management and Creative Economy, Department of Digital Marketing, School of Management, Walailak University, Nakhonsithammarat 80161, Thailand
2
Center of Excellence for Tourism Business and Creative Economy, Department of Tourism and Prochef, School of Management, Walailak University, Nakhonsithammarat 80161, Thailand
3
Faculty of Humanities and Social Sciences, Songkhla Rajabhat University, Songkhla 90000, Thailand
4
Faculty of Business, Law and Social Sciences, Birmingham City University, Birmingham B4 7XG, UK
5
Department of Management Studies, Graphic Era Deemed to be University, Dehradun 248002, India
*
Author to whom correspondence should be addressed.
Soc. Sci. 2023, 12(3), 153; https://doi.org/10.3390/socsci12030153
Submission received: 23 January 2023 / Revised: 24 February 2023 / Accepted: 25 February 2023 / Published: 6 March 2023
(This article belongs to the Section Work, Employment and the Labor Market)
Browse Figures
Review Reports Versions Notes

Abstract

:
Creating job satisfaction for employees can help organizations maintain their employees and save more on costs from searching for new ones. Therefore, a primary goal of this research was to investigate how work–family conflict, workload, and job stress influenced university lecturers’ work satisfaction. To accomplish the current aim, researchers invited 450 respondents who were holding positions as lecturers at any university in Thailand. Next, a structural equation model was employed to analyze 387 valid data points. In gender statistics, 45.2% were male respondents while 54.8% were female respondents. Moreover, gender obtained mean scores (1.54) with standard deviation scores (0.49). Based on age statistics, most of the respondents who joined this research were between 20 and 30 years old (41.3%) followed by 31–41 years (24.5%), 41–50 years (19.9%), and above 50 years (14.2%). Meanwhile, mean scores were 2.07 with standard deviation 1.09. According to results of this research, increasing work–family conflict and workload caused lecturers to receive more stress from their work. Moreover, the lecturers found themselves happy once certain degrees of stress and work–family conflict, except workload, diminished. Meanwhile, stress among university lecturers significantly mediated their workloads and work satisfaction. This result highlights a side effect of a certain amount of workload influencing lecturers’ stress levels, which in turn increased the significant role of job stress in further influencing lecturers’ work satisfaction.

1. Introduction

Satisfaction among individuals indicates a positive impact on their working behaviors (Janib et al. 2021). In particular, job satisfaction can affect employees’ work motivation and work productivities (Tentama et al. 2019). At the same time, organizations can save a lot of money from job advertisements and other training programs (Lee et al. 2020) because happy employees normally continue staying with the same organizations (Gurková et al. 2013). Therefore, ensuring high job satisfaction among employees is important to all organizations.
Meanwhile, 310 universities including colleges and academic institutions around Thailand have offered more job opportunities for many scholars (Muangmee et al. 2021). Despite these job opportunities at the university level in Thailand, job satisfaction among university lecturers has not been widely reported yet. Kim et al. (2005) reveal that job satisfaction demonstrates a great influence on a worker’s decision to continue working with their organization. Obviously, many organizations face high turnover once they are unable to make their employees happy with the current jobs (Lee et al. 2020). Consequently, organizations’ productivities can be severely affected while their budget of searching for new and professional employees will be highly spent. Based on the above circumstances, it is obvious that if universities can offer job satisfaction to their employees, especially lecturers, they can receive continuous support and work productivity from their employees. Therefore, investigating job satisfaction among university lecturers is very important and can help all related universities to further understand factors influencing lecturers’ working attitudes, particularly their work satisfaction toward their organizations, which in turn can help human resource management to develop an appropriate working policy to promote a comfortable and healthy working environment for their workers.
So far, many organizations have tried to find new ways to maintain their employee satisfaction at a maximum level so that those employees can continue working for their organizations. In the education service context, Janib et al. (2021) suggest good management of workload to employees. The workload should be well prepared and remain focused on individuals’ primary tasks with the specific number of hours which they are working per day. Hence, it can reduce some unnecessary workload for their employees and make them feel less exhausted. On the other hand, Dodanwala and Shrestha (2021) who studied worker behavior in the construction service industry recommend lowering work–family conflict. A role of human resource management is to rearrange work schedules and daily responsibilities to let employees complete their work within the required hours of the day. This can allow them to have a specific gap of time to reunite with their family so that they can be happy and return to work on the following days. In contrast to the above authors, Ramlawati et al. (2021) who are from the bank industry recommend managing their employees’ job stress. Maintaining low levels of job stress in employees can make them feel less pressure, which in turn creates a favorable desire to work for their organizations.
Obviously, workers in previous contexts have similar characteristics with the workers in the higher education context as lecturers are also working for organizations to provide services to their customers, mainly students. However, the workers’ perspectives toward their job satisfaction between higher education context and those contexts are not the same because workers in different contexts show different working attitudes and behaviors toward their workplaces (Abun et al. 2021). Therefore, although those studies have individually concerned the influence of work–family conflict, job stress, and workload on job satisfaction in their contexts, the impacts of these factors on job satisfaction in higher education have remained scarcely investigated. As a consequence, the existing literature lacks information to explain how these factors influence job satisfaction among university lecturers. In this regard, as this research tries to uncover job satisfaction among the university lecturers in order to judge the overall working attitudes and behaviors in the university context, it is necessary to extend a theoretical model of job satisfaction among university lecturers by including the above factors into the model and aiming to investigate (1) how workload and work–family conflict influence job stress among university lecturers and (2) how workload, work–family conflict, and job stress influence job satisfaction among university lecturers.

2. Literature Review

2.1. Thoery of Planned Behavior (TPB)

In the study of human behavior, the theory of planned behavior (TPB) which is extended from the theory of reasonable action (TRA) has been developed to explain how volitional individual decisions are (Ajzen 1985). Most individual behavior can be predictable because his or her choice is created based on logical reasoning (Ajzen and Fishbein 1972). In fact, people’s decisions are made based on their evaluation of available alternatives. Based on behavioral analysis, the TPB outlines two factors that influence individual behavior, namely, subjective norms and attitude (Ajzen and Fishbein 1972). Subjective norms are an outcome of people’s normative beliefs. Attitude, on the other hand, is derived from people’s beliefs that their specific performed actions can provide them beneficial results. As these factors continue their influences on individual behavior, a certain degree of actual behavior can be predicted. According to the above evidence, this theory can be suitable to explain an attitude of job satisfaction which can significantly predict individuals’ actual working behavior in an organization, particular in a university context.

2.2. Job Satisfaction

Job satisfaction refers to a worker’s positive emotion toward his or her current work which is derived after evaluating their current job (Pratama et al. 2021). In particular, job satisfaction can happen when employees’ work outcomes surpass their expectations (Mahmood et al. 2021). In the theory of planned behavior (TPB), Ajzen (2020) explains that an actual behavior is a result of a person’s behavioral intention which develops from interacting with his or her behavioral attitudes, perceived behavioral control, and subjective norms. The TPB concept also emphasizes that an individual’s work satisfaction is a part of his or her emotion and attitude to work which influences overall working productivities and determines a certain extent of relationship between a worker and a firm (Ren et al. 2022). According to this theoretical point of view, job satisfaction is highlighted as the main factor influencing individuals’ working productivities and their relationships with the firms. Therefore, job satisfaction is an important variable to which all related institutions have to pay more attention and conduct a proper investigation on.
In a higher education context, job satisfaction has also been used to measure overall working attitudes (Alonderience and Majauskaite 2016). The current measurement highlights job satisfaction as a valid factor to predict individuals’ work commitment and work productivities for universities. Meanwhile, job satisfaction has also displayed a great influence on employees’ working behavior which results in continuing the current work or leaving their workplaces (Annisa and Supriyanto 2021). Therefore, many organizations or institutions always evaluate their employees’ satisfaction, including higher education institutions (Alonderience and Majauskaite 2016; Park and Kim 2021). However, there can be several dimensions that need to be assessed (e.g., salary, recognitions, relationship between workers and supervisors, etc.) (Ramlawati et al. 2021). One of these dimensions may influence job satisfaction; however, there can be different factors or a combination of these factors to decide the full potential of individuals’ job satisfaction. Likewise, workload (Janib et al. 2021), job stress (Ramlawati et al. 2021), and work–family conflict (Dodanwala and Shrestha 2021) have been identified as the main predictors of job satisfaction in previous contextual studies. However, as job satisfaction is complicated to assess, all related organizations have to put more effort into further investigating how the main factors influence employee satisfaction. In this regard, understanding how the main factors influence lecturers’ work satisfaction can increase awareness of lecturers’ working attitudes which can be helpful for human resource managers to develop an effective policy to promote a friendly and a healthy working environment for their workers in the university context.
Based on scholars’ perspectives from different contexts, they individually highlighted workload (Janib et al. 2021), work–family conflict (Dodanwala and Shrestha 2021), and job stress (Ramlawati et al. 2021) as the main predictors of job satisfaction. Unlike other industries, a number of workloads in universities indicate amount of time spent in certain activities such as teaching tasks, conducting research, facilitating curricular activities, and involving other meetings (Janib et al. 2021). It has been revealed that providing a certain number of responsibilities to workers can potentially change the degree of laziness in their workers (Inegbedion et al. 2020). However, individual employees become uncomfortable once the level of workload surpasses the standard level of workload (Inegbedion et al. 2020; Kokoroko and Sanda 2019). Consequently, a high number of tasks becomes a negative pressure for the workers and makes them feel exhausted at the end of the day (Miller 2019). Therefore, it can significantly damage individuals’ joy and desire to work for their organizations.
Regarding job stress, stress has been identified as a psychological illness which causes a person to have low motivation to continue doing his or her work (Dodi et al. 2021). Job stress is derived from various factors such as work pressures, low work–life balance, high frustration, and so on (Kokoroko and Sanda 2019; Bell et al. 2012; Keenan and Newton 1984). These indicators are seen to be significant determinants of job stress among employees. Furthermore, high job stress can further develop into a condition which negatively influences employee emotions, thought processes, and thinking processes (Dodi et al. 2021). Overall, if the current job stress condition continues, job satisfaction among workers will be diminished.
Last but not least, work–family conflict reveals a certain number of activities which individuals have to further engage in with their organizations (Hong et al. 2021). This further engagement can cause a serious interference to the personal lives of workers. This situation can make it more difficult for employees to participate in their families’ activities (Lambert et al. 2017). There are three main forms of work–family conflict which cause such interferences to an individual’s family life, namely time-based work–family conflict, strain-based work–family conflict, and behavior-based work–family conflict (Dodanwala and Shrestha 2021). Time-based work–family conflict happens once workers spend more time on work which causes low availability to join the family time (Greenhaus and Beutell 1985). This situation creates such a dynamic work environment which causes additional pressures to workers to complete additional workload with an unspecific length of time to complete the tasks (Turner et al. 2008). On the other hand, strain-based work–family conflict happens when high strain from the work domain directly affects workers’ ability to address their family domain’s demands and expectations (Greenhaus and Beutell 1985). Employees have to extend their working hours which leads to high physical tiredness for employees (Lingard and Francis 2004). In contrast, behavior-based work–family conflict happens when the work domain’s behavior adversely affects workers’ behavior in the family domain (Greenhaus and Beutell 1985). This situation indicates aggressiveness and objectivity in work to achieve project successes; however, it also causes emotional exhaustion in workers (Zheng and Wu 2018). Consequently, their emotional exhaustion can negatively influence their family time. To sum up, if one of these forms changes, conflict between work and family can happen and influence their working attitudes and behaviors.
Despite the above claims, the impacts of these factors on job satisfaction in the higher education context remain unclear as workers who are from different workplaces show different working attitudes and behaviors (Kim et al. 2022a). Consequently, the information on how the above factors influence individuals’ work satisfaction in higher education context has been little explained in the existing literature. Hence, this research aims to contribute more knowledge to the existing literature by integrating job stress, workload, and work–family conflict into a job satisfaction theoretical model and testing the relationships among these variables.

2.3. Workload and Job Stress

Workload refers to the number of job responsibilities and other activities which employees are required to do with a given amount of time (Janib et al. 2021). In the context of academic staff, workload particularly refers to the number of duties that a lecturer has to handle such as teaching, conducting research, facilitating curricular activities, and joining meetings (Hosain 2016). The workload can change an individual’s laziness into being active and productive for the firm; however, it may create psychological illness to him or her if the workload surpasses the standard (Inegbedion et al. 2020).
Based on conceptual comparisons, workloads reveal pressures which require a person to conduct more tasks for his or her organization (Lea et al. 2012) whereas stress highlights a person’s mental discomfort which results from receiving pressures from his or her organization (Pahi et al. 2016). The two main concepts seem to show a common view. According to perceptions of workload balance, many people seem to show a negative feeling after they are required to complete more tasks with different deadlines (Inegbedion et al. 2020). Likewise, Kokoroko and Sanda (2019) have added that when workloads are increased, people start having more responsibilities which lead to high anxiety. As a result, it ultimately creates job stress in everyone. According to the above explanations, there is a positive relationship between workload and job stress. In the police department, Sadiq (2020) found that high workloads increase job stress. In the hospital context, Kokoroko and Sanda (2019) reveal that workload positively influences job stress. The current relationship can be hypothesized below:
H1:
Workload has a positive relationship with lecturers’ job stress.

2.4. Workload and Job Satisfaction

In comparison, workloads cause emotional pressures on workers (Janib et al. 2021) while satisfaction reveals an individual’s positive feeling toward their current jobs (Hong et al. 2021). These two concepts have displayed different positions. Based on pharmacists’ perspectives, more tasks require more physical and psychological effort to carry out; thus, it creates an unfavorable desire in the workers who in turn no longer enjoy their work (Lea et al. 2012). In addition, Basson and Rothmann (2018) revealed that high workloads cause more pressures and discomfort to the workers, who in turn feel dissatisfied with their organizations. These arguments reveal that workload and job satisfaction have a negative relationship. In the education context, Janib et al. (2021) found that high workload reduces employees’ job satisfaction. In the health care context, Holland et al. (2019) emphasized that workload negatively influences nurses’ job satisfaction. The current relationship can be hypothesized below:
H2:
Workload has a negative relationship with lecturers’ job satisfaction.

2.5. Work–Family Conflict and Job Stress

Work–family conflict (WFC) is conceptualized as a form of correlated-role conflict where the role of work interferes a person’s family time (Hong et al. 2021). Based on the conservation of resources theory of Hobfoll (1989) and the boundary theory of Ashforth et al. (2000), once a certain task requires more time and effort, a worker has to reallocate his or her resources to complete that task. However, this may cause an imbalance of time with his or her family; thus, it creates a conflict between work and family.
In comparison, WFC indicates a person’s frustration and negative attitude (Batur and Nart 2014) while stress highlights a negative perception and feeling toward a person’s job (Sadiq 2020). The above concepts have demonstrated a common direction. In a work–relationship perspective, once a person cannot control their time between work and family, he or she seems to have high emotional tension with the current work (Armstrong et al. 2015). Mansour and Mohanna (2018) revealed that high WFC creates a discomfort zone where work interferes and pressures employees to remain working rather than leaving to meet their families. This situation causes employees to physically and emotionally feel exhausted with the current job position. In the above theoretical explanations, work–family conflict is likely to show a positive effect on job stress. In the correctional institution context, Vickovic and Morrow (2020) highlighted that high WFC causes more stress to employees. The current relationship can be hypothesized below:
H3:
Work–family conflict has a positive relationship with lecturers’ job stress.

2.6. Work–Family Conflict and Job Satisfaction

Strong work–family conflict creates a negative impact on a person’s working attitude in the workplace (An et al. 2020) whereas high employee satisfaction has a positive influence on a person’s working attitude at his or her workplace (Karatepe and Uludag 2008). These variables’ concepts reveal different directions. In an innovative worker’s behavior, having high conflicting roles between work and family may cause psychological pressure to a worker; thus, he or she may no longer feel happy with the current job (Choi et al. 2018). In workplace flexibility perspectives, a sign of discomfort among workers appears when their works require more time to complete while they are expecting to leave their offices to meet their families (Rhee et al. 2020). These arguments express work–family conflict as a negative antecedent of job satisfaction. In the construction context, Dodanwala and Shrestha (2021) mentioned that workers who possess high work–family conflict are not happy with their jobs. In the high school education context, Hong et al. (2021) revealed that the degree of job satisfaction can diminish once teachers have high work–family conflict. The current relationship can be hypothesized below:
H4:
Work–family conflict has a negative relationship with lecturers’ job satisfaction.

2.7. Job Stress and Job Satisfaction

Job stress refers to a negative psychological state which a person possesses as a side effect from his or her work (Tongchaiprasit and Ariyabuddhiphongs 2016). A conservative theory mentions that psychological stress of each person can happen based on three main environments, namely (1) a depletion of an individual’s resources, (2) a low return from an individual’s investment, and (3) a threat of losing so many resources (Hobfoll 1989).
Based on conceptual comparisons, stress shows a negative effect on individuals’ behavior in the workplace (Sadiq 2020). In contrast, the central concept of satisfaction positively changes workers’ attitudes in the workplace (Karatepe and Uludag 2008). Based on these arguments, stress and satisfaction show opposite views. In the satisfaction concept of the telecommunication context, when a person feels stressed with his or her work, he or she feels less enjoyment with the current work (Hayajneh et al. 2021). In working life balance perspectives in the middle of the COVID-19 pandemic, having high stress can develop into a certain degree of psychological illness which further affects a person’s mood (Dodi et al. 2021). These explanations have shown that job stress possibly has a negative influence on workers’ satisfaction. In a work-from-home context, Dodi et al. (2021) revealed that high job satisfaction is a result of maintaining a low degree of individuals’ stress. The current relationship can be hypothesized below:
H5:
Job stress has a negative relationship with lecturers’ job satisfaction.

2.8. Theoretical Model Construct

Based on the above proposed hypotheses, a theoretical model construct of job satisfaction is developed in Figure 1. Based on the Figure 1, the model begins with direct impacts of workload and work-family conflict on job stress and job satisfaction. Last but not least, workload, work-family conflict and job stress directly influence job satisfaction.

3. Research Methods

3.1. Sample of Research

To be qualified respondents of this study, respondents must have been working as a lecturer at any university around Thailand. In this study, researchers invited 450 lecturers to fill in self-administered questionnaires. Moreover, the researchers developed a Google survey form to conveniently survey respondents’ perspectives, especially those who were working in different provinces of Thailand.

3.2. Measurements

Each variable contained measurements which were adopted from previous studies. For example, researchers borrowed measurements of workload from Sadiq (2020) (e.g., “I think I need more effort to finish my work.”). Next, researchers borrowed measurements of work–family conflict from Vickovic and Morrow (2020) (e.g., “My job keeps me away from my family too much.”). Then, researchers borrowed measurements of job stress from Chen et al. (2011) (e.g., “I think I can’t handle this job anymore.”). Finally, researchers borrowed measurements of job satisfaction from Matzler and Renzl (2006) (e.g., “Overall, I am quite satisfied with this job responsibilities.”).
At the same time, the measurements of each variable were rated by respondents using a 5-point Likert scale (1 = strongly disagree, 2 = disagree, 3 = neutral, 4 = agree, and 5 = strongly agree). This rating technique contained a neutral scale (3) which displayed a clear cut between negative and positive scales in the survey (Kim and Jindabot 2022); therefore, it was easy to let the respondents rate their opinions. Furthermore, Kim et al. (2021) agreed that this rating procedure was suitable for collecting information from the respondents because it saved more time and effort for the respondents to complete the surveys. All of the measurements and the Likert scale are reported in Table 1.

3.3. Pilot Test, Data Collection, and Data Validity

Before starting the data collection for this research, researchers submitted a research proposal and survey tool to consult with the Internal Review Board (IRB). In this step, all respondents’ personal information was kept confidential. In particular, their identities such as names, salary, signatures, and workplaces were not highly required. At the same time, respondents were given the right to join the survey or refuse to participate in the survey processes. In this case, their decisions to join or not fill out the survey were highly respected by researchers. Moreover, even though they already volunteered to participate in the survey, they could stop filling out the survey at any time if they felt uncomfortable with the survey. Hence, these practices could highly protect the participants and prevent any possible risk from happening to respondents’ current careers and their relationships with their workplaces. Once the above conditions were implemented, researchers could continue their investigation with the respondents.
In pilot testing procedures, researchers developed self-administered questionnaires and conducted a pre-test with 40 lecturers to check content reliability using Cronbach’s Alpha scores (scores > 0.7) (Kim and Jindabot 2022). Based on the results in Table 2, the content of each variable was reliable because all scores passed the thresholds. Therefore, the researchers could finally conduct a full scale of data collection around Thailand.
In data collection processes, the researchers first searched for respondents’ profiles in the universities’ websites. At the same time, researchers used a snowball sampling method to collect data. In this technique, researchers could continue contacting more respondents to join the survey processes because after respondents filled in the survey, researchers could ask them for their recommendations for other qualified respondents (Kim et al. 2022a). Next, when they found qualified respondents, researchers immediately sent emails to those respondents and asked for their consent to fill out the survey. Furthermore, the researchers also promised to keep their information secret. Then, the researchers sent Google survey links to their emails when they volunteered to fill out the survey form. Finally, all of the data were fully collected with a 100% response rate.
Regarding data validity, the researchers checked the collected data and eliminated outliers using a statistical software. Mahalanobis scores were applied to detect any data which contained the possibility scores below 0.001, indicating outliers (Grande 2015). As a result, there were only 387 valid data points which were used in data analysis.

4. Research Results

4.1. Basic Respondents’ Information Results

Basic respondents’ information results such as gender and age are reported in Table 3. Regarding gender, researchers found that 54.8% were female respondents while 45.2% were male respondents. Furthermore, statistics of gender displayed a mean score of 1.54 with a standard deviation score of 0.49. These statistical results indicate that there was a similar average proportion of participant numbers between male and female respondents in this research.
Regarding age, researchers found that most of the respondents who joined the survey were mainly 20–30 years old (41.3%), followed by 31–40 years old (24.5%), 41–50 years old (19.9%), and above 50 years old (14.2%). In addition, the age of the respondents obtained a mean score of 2.07 with a standard deviation score of 1.09, indicating an average age of respondents of 31–40 years old.

4.2. Model Measurement and Data Analysis

A structural equation model (SEM) was employed to analyze the data of this study. However, before starting data analysis, model fitness, model measurement, convergent and discriminant validity, and multi-collinearity statistics were reported. First, the SEM model fitness was evaluated through confirmatory factor analysis to modify the model so that good fitness indicators could obtain acceptable scores (Kim et al. 2021). In Table 4, the current model fortunately passed the thresholds without making further modification due to all indicators obtained acceptable scores.
Next, the model measurement was evaluated using loading factors and content reliability in Table 5. First, all loading factors were kept for analysis because they had scores higher than 0.6. Second, content reliability was checked using Cronbach’s Alpha and composite reliability (CR) scores (scores > 0.7) (Kim and Jindabot 2022; Sang 2022). In Table 5, all of variables consisted of content reliability. At the same time, the convergent validity was checked by using average variance extracted (AVE) (scores > 0.5) following the suggestion of (Kim et al. 2022b). As shown in Table 5, the convergent validity existed in this study due to all variables obtaining AVE scores higher than 0.5.
Finally, researchers assessed the discriminant validity by comparing scores of AVEs and interrelation coefficient scores of variables. If the scores of AVEs were higher than the scores of interrelation coefficient scores of variables, it indicated discriminant validity (Kim et al. 2022b). In Table 6, the scores of AVEs were bigger than the scores of interrelation coefficient scores of variables showing the discriminant validity of this study. Meanwhile, researchers also checked for multi-collinearity among independent variables to ensure no conflicting regression outcomes between independent variables using collinearity statistics of tolerance and variances inflation factors (VIF) (tolerance scores > 0.10 and VIF < 10) (Ringim et al. 2012). According to Table 6, the tolerance and the VIF scores were above the thresholds showing no sign of multi-collinearity.

4.3. Results of Structural Equation Model

The main critical results of this research were reported in Figure 2 and Table 7. According to empirical results of this research, job stress was significantly influenced by work–family conflict and workload with β = 0.56, p < 0.001 and β = 0.42, p < 0.001, respectively, which accepted hypothesis 3 and 1. Finally, job satisfaction was significantly influenced by work–family conflict and job stress with β = −0.56, p < 0.001 and β = −0.41, p < 0.001, respectively, which accepted hypothesis 4 and 5. In contrast, job satisfaction was not significantly influenced by workload with β = −0.02, p > 0.05, which rejected hypothesis 2.
Regarding mediation testing in this study, relationships among variables (Workload-- > Job Stress-- > Job Satisfaction) indicated that a direct impact of workload on job satisfaction was insignificant (β = −0.02, p > 0.05), while its indirect impact on job satisfaction was significant (β = −0.25, p < 0.001). Thus, job stress which stayed between workload and job satisfaction was identified as a full mediator between workload and job satisfaction.
To sum up, a hypotheses summary is provided in Table 7 following the above relationship results. We accepted four hypotheses, and rejected hypothesis 2.

5. Discussion, Implications, and Limitations of Research

5.1. Research Discussion

5.1.1. Discussions of the Effects on Job Stress

Regarding relationships with job stress, work–family conflict showed a positive relationship with job stress. This found that conflicting time management resources between work and family caused a negative impact on lecturers’ attitudes at workplaces. Meanwhile, those lectures seemed to be frustrated if their work continued interfering with their social lives (e.g., family meeting and other celebrations). As these pressures continued, their psychological well-being would be negatively affected (Zábrodská et al. 2018). Similarly, An et al. (2020) who studied worker behavior in the fishery industry also found that most of the workers had tension with their work after they could not meet their families since everyday tasks required more time and effort to complete. Based on these empirical results, high work–family conflict simply caused high job stress among those lecturers who had a tough time completing their work before returning home. Second, workload showed a positive relationship with job stress. Workers normally had to manage their time to finish their workloads. In case of high workload, the workers were required to have more time and effort to complete their tasks for their organizations (Inegbedion et al. 2020). However, we found that it turned out to be more pressures on lecturers’ emotional and physical exhaustions. Likewise, Sadiq (2020) supported that high workloads increased tension among workers. Once the workloads increased beyond the normal tasks, those lecturers possibly felt pressured and anxious. Based on this scenario, lecturers who received more tasks above their normal tasks (e.g., teaching and doing research) may have psychologically suffered from high workloads in their universities. Thus, as the number of academic tasks surpassed the standard number, stress absolutely increased.

5.1.2. Discussions of the Effects on Job Satisfaction

Regarding relationships with job satisfaction, work–family conflict showed a negative relationship with job satisfaction. An imbalance of managing time for work and family caused an unsatisfactory experience for the workers. In a study in the construction context, Dodanwala and Shrestha (2021) found that a degree of their joy in doing the work for organizations was reduced as their relationships with their family seemed to be cut off from their lives. Similarly, we also found that lecturers may have found it unfavorable to do the current work. Consequently, high job dissatisfaction appeared among lecturers. The current results implied that lecturers who faced high work–family conflict simply had low job satisfaction. They felt unhappy with their work because the current work isolated them from their families. Second, job stress negatively influenced job satisfaction. High stress possibly caused psychological illness to many workers. This possibly led to more negative attitudes among workers toward their current duty at the workplace (Hayajneh et al. 2021; Ramlawati et al. 2021). In this regard, this research found that university lecturers also raised their concern over their job stress level. This situation underscored some extent of the issues related to their psychological healthiness and attitudes toward the current jobs at the universities. Thus, it was unavoidable that their high stress level could definitely reverse their satisfaction toward the current job position at the universities. In contrast, workload was not demonstrated as a significant predictor to job satisfaction. Its insignificant relationship with job satisfaction happened due to job stress being a full mediator between workload and job satisfaction. This phenomenon caused workload to have an indirect impact on job satisfaction. Unlike workers in previous studies such as those of Holland et al. (2019) and Janib et al. (2021), workload did not cause an immediate job dissatisfaction among university lecturers. In fact, the current findings outlined the potential impact of job stress on lecturers’ satisfaction through a major involvement of academic workload. Thus, we could logically assume that when lecturers received a higher workload than usual, they began having more stress in their current positions which in turn caused them feel unhappy with their job at the final stage.

5.2. Theoretical and Managerial Implications

In light of this research, there are two main contributions to the existing literature. First, this research extends the job satisfaction literature in the context of higher education by investigating how workload, work–family conflict, and job stress affect lecturers’ job satisfaction. Although previous studies have raised the significant impacts of these factors on job satisfaction in different sectors (Janib et al. 2021; Dodanwala and Shrestha 2021; Ramlawati et al. 2021), it remained questionable how these factors explain job satisfaction in the higher education context. Therefore, our current theoretical model provided more knowledge of how the above factors influence working attitudes among employees, particularly job satisfaction among university lecturers. Second, this research increases the awareness of the influences of job stress and work–family conflict on job satisfaction among the university lecturers. Even though previous studies have considered workload as a major concern for job satisfaction (Lea et al. 2012; Janib et al. 2021; Holland et al. 2019), the major plot of work satisfaction among university lecturers is severely affected once their jobs cause more stress and time conflict with their families. These results raise such a concern for their current psychological healthiness if they are unable to control the level of stress and do not have enough time to meet their families.
In managerial implications, job satisfaction among university lecturers can be enhanced through managing job stress and work–family conflict. First, the universities can manage their employees’ stress by encouraging them to focus on the main related tasks and complete those tasks based on daily objectives. For instance, lecturers are encouraged to prioritize the main tasks such teaching, meetings, and doing research while running university campaigns for society should be conducted by other marketing employees and experts. Second, work–family conflicts can be managed by encouraging their staff to leave offices following the leaving time policy. Moreover, the universities should provide an early leave privilege (applying one day for every month) to lecturers who are in a hurry and can apply it to leave offices approximately 30 min earlier. By doing so, the workers can have a relaxing time with their families and recover their energy to work the next day.

5.3. Limitations of Research

In spite of completing the research’s objective, this research’s results had some limitations. For instance, the results mainly focused on employee working behavior in the university context. Thus, they could not be suitable to generalize for employees in other contexts such as hotels, restaurants, or banks, since employees from different contexts demonstrate different working attitudes and behaviors. Therefore, future studies may use these variables to continue investigating job satisfaction in those contexts so that they can come up with new findings and conclusions. Next, the results of this research contained some degree of bias since the respondents filled in the Google form by themselves. The future studies can minimize the level of bias by using face-to-face interviews based on a structural questionnaire so that quality of data control can be better. Finally, the results of this research were based on the national context of Thailand. Future studies can also use these variables to further investigate job satisfaction in other national contexts such as Cambodia, Laos, or Indonesia.

6. Conclusions

This research’s main objective was to investigate university lecturers’ job satisfaction around Thailand. Researchers investigated 450 lecturers who were currently working at different universities of Thailand. After clearing potential outliers, the researchers employed a structural equation model to analyze 387 valid data points. Results of this research highlighted that workers felt stressed once they faced a high workload and work–family conflict. Next, employees remained happy as long as the level of stress and work–family conflict dropped significantly. Finally, the empirical results of this study confirmed job stress as a full mediator between workload and job satisfaction.

Author Contributions

Conceptualization, L.K.; data collection, S.P., P.P., and N.H.; data analysis, V.K.; original draft writing, S.P. and L.K.; manuscript revising, S.P., P.P., and L.K. All authors have read and agreed to the published version of the manuscript.

Funding

This research was supported by Research and Innovation Institute of Excellence, Walailak University under grant number WU66217.

Institutional Review Board Statement

The methods used for the survey in this research fully guaranteed the anonymity of the participants. Therefore, the aforementioned project and informed consent were reviewed and approved by Ethics Committees in Human Research Walailak University, based on the Declaration of Helsinki.

Informed Consent Statement

Informed consent was obtained from all participants involved in this research.

Data Availability Statement

Data are not public available due to high privacy restriction.

Acknowledgments

The authors are grateful to Walailak University and the Center of Excellence for Tourism Business Management and Creative Economy for their supports. We also wish to thank the Institute of Research and Innovation, Walailak University for granting this research project.

Conflicts of Interest

The authors declare no conflict of interest.

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Socsci 12 00153 g001 550
Figure 1. A theoretical model of employee satisfaction.
Figure 1. A theoretical model of employee satisfaction.
Socsci 12 00153 g001
Socsci 12 00153 g002 550
Figure 2. Results of SEM.
Figure 2. Results of SEM.
Socsci 12 00153 g002
Table
Table 1. Measurement and Likert scale.
Table 1. Measurement and Likert scale.
SourcesVariablesItemsLikert Scale
Sadiq (2020)WorkloadW1: Normally, I receive extra work to do at my workplace.
W2: I think I need more effort to finish my work.
W3: I think I need more time to finish my work.		5-point Likert Scale
Vickovic and Morrow (2020)Work–family ConflictWFC1: My job keeps me away from my family too much.
WFC2: This job makes me too tired to enjoy my family life.
WFC3: I find that my job has negatively affected my homelife.		5-point Likert Scale
Chen et al. (2011)Job StressJS1: I think I can’t handle this job anymore.
JS2: I think I receive too much pressure from my work.
JS3: I think doing this work negatively affects my mood.		5-point Likert Scale
Matzler and Renzl (2006)Job SatisfactionJSat1: Overall, I am quite satisfied with these job responsibilities.
JSat2: I am happy to work for this institution.
JSat3: I really like the working environment of this job.		5-point Likert Scale
Table
Table 2. Content reliability of pilot test.
Table 2. Content reliability of pilot test.
VariablesCronbach’s Alpha ScoresResults
Workload0.722Passed
Work–Family Conflict0.805Passed
Job Stress0.733Passed
Job Satisfaction0.792Passed
Table
Table 3. Basic respondents’ information results.
Table 3. Basic respondents’ information results.
VariableDescriptionFrequencyPercentageMeanStandard Deviation
Gender1. Male
2. Female
 Total		175
212
387		45.2
54.8
100		1.540.49
Age1. 20–30 years
2. 31–40 years
3. 41–50 years
4. Above 50 years
 Total		160
95
77
55
387		41.3
24.5
19.9
14.2
100		2.071.09
Table
Table 4. Model fit.
Table 4. Model fit.
IndicatorsIndexThresholdsResults
CMIN2/df1.423≤3Good
GFI0.949>0.9Good
NFI0.928>0.9Good
CFI0.993>0.9Good
AGFI0.914>0.8Good
RMSEA0.033<0.08Good
PCLOSE0.802>0.05Good
Table
Table 5. Model measurement and convergent validity.
Table 5. Model measurement and convergent validity.
VariableComponentsLoading FactorsCronbach’s AlphaCRAVE
WorkloadW1: Normally, I receive extra work to do at my workplace.
W2: I think I need more effort to finish my work.
W3: I think I need more time to finish my work.		0.71
0.71
0.70		0.730.790.65
Work–Family ConflictWFC1: My job keeps me away from my family too much.
WFC2: This job makes me too tired to enjoy my family life.
WFC3: I find that my job has negatively affected my homelife.		0.65
0.68
0.68		0.840.750.79
Job StressJS1: I think I can’t handle this job anymore.
JS2: I think I receive too much pressure from my work.
JS3: I think doing this work negatively affects my mood.		0.73
0.66
0.75		0.820.850.88
Job SatisfactionJSat1: Overall, I am quite satisfied with this job responsibilities.
JSat2: I am happy to work for this institution.
JSat3: I really like the working environment of this job.		0.73
0.73
0.71		0.760.940.71
Table
Table 6. Discriminant validity and collinearity diagnostic.
Table 6. Discriminant validity and collinearity diagnostic.
Variable1234Collinearity Scores
ToleranceVIF
Workload0.8810.4480.5290.6410.3154.112
Work–family Conflict 0.8900.6970.5680.3285.043
Job Stress 0.7920.7210.4863.962
Job Satisfaction 0.811--
Note: Bolded numbers indicate rooted square scores of AVE.
Table
Table 7. Critical ratios and hypotheses summary.
Table 7. Critical ratios and hypotheses summary.
Channel A: Regressions and Critical Ratios
Hyp.
No.		Proposed RelationshipsStd. Beta (β)p-ValueSig.
Level		Hyp.
Result
Independent VariableDependent Variable
1WorkloadJob Stress0.420.000 **Sig.Accepted
2WorkloadJob Satisfaction−0.020.208Insig.Rejected
3Work–Family ConflictJob Stress0.560.000 **Sig.Accepted
4Work–Family ConflictJob Satisfaction−0.510.000 **Sig.Accepted
5Job StressJob Satisfaction −0.410.000 **Sig.Accepted
Channel B: Mediation Testing
RelationshipsIndirectDirectMediationResult
Workload-- > Job Stress-- > Job Satisfaction−0.25 **−0.02Full MediationSig.
Note: ** indicates sig. level p < 0.001.
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MDPI and ACS Style

Kim, L.; Pongsakornrungsilp, P.; Pongsakornrungsilp, S.; Horam, N.; Kumar, V. Key Determinants of Job Satisfaction among University Lecturers. Soc. Sci. 2023, 12, 153. https://doi.org/10.3390/socsci12030153

AMA Style

Kim L, Pongsakornrungsilp P, Pongsakornrungsilp S, Horam N, Kumar V. Key Determinants of Job Satisfaction among University Lecturers. Social Sciences. 2023; 12(3):153. https://doi.org/10.3390/socsci12030153

Chicago/Turabian Style

Kim, Long, Pimlapas Pongsakornrungsilp, Siwarit Pongsakornrungsilp, Ngachonpam Horam, and Vikas Kumar. 2023. "Key Determinants of Job Satisfaction among University Lecturers" Social Sciences 12, no. 3: 153. https://doi.org/10.3390/socsci12030153

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