A study on factors affecting job satisfaction in the IT industry

Abstract

Although there are several definitions of job satisfaction or employee satisfaction, we may generally define them as a person's level of contentment with their job. Because they leave the company less frequently and stay longer, content employees help the business grow. Additionally, a positive work atmosphere attracts talent and boosts productivity by encouraging job satisfaction. The information technology (IT) industry has gained traction on the global scale and has taken centre stage in both our society and the world as a whole. The booming Indian economy has contributed to the ability of the IT industry to remain competitive in the international market. This study aimed to evaluate the degree of job satisfaction among IT professionals and identify the factors affecting that satisfaction. To highlight the factors affecting positive job satisfaction among IT industry employees, we included variables such as rewards and recognition, working conditions, fairness, job security, relationships with coworkers and employee satisfaction. After the data were cleaned, 100 responses were collected. The data were analysed using SPSS statistical software, and the findings showed that the job satisfaction of IT employees is strongly correlated with a number of factors connected to the workplace.

Full text

Multidiscip. Sci. J. (2024) 6:e2024223
Accepted: May 4, 2024
RESEARCH ARTICLE
Published Online: May 10, 2024
https://doi.org/10.31893/multiscience.2024223
A study on factors affecting job satisfaction in the IT
industry
Panangati Madana Mohana | A. Vasumathia
aVellore Institute of Technology, Vellore, India.
1. Introduction
An essential component of organisational processes is people management. This resulted from the realisation that an
organisation's human resources and the organisation itself are the same. The typical employees of a well-managed corporate
organisation are typically viewed as the main source of productivity increases. "Job satisfaction is a pleasurable or positive
emotional state coming from the appraisal of one's employment or job experience," claims E.A. Locke. "Job satisfaction will be
defined as the degree of overall good affect or (feelings) that individuals have toward their jobs," write Fieldman and Arnold.
Any confluence of psychological, physiological, and environmental elements that prompts someone to frankly state, "I am
content with my job," is what Hoppock called job satisfaction (Hoppock, 1935). That is, a set of criteria that contribute to job
satisfaction is presented. Although they are related, motivation and job satisfaction are not the same. For continual progress,
IT organisations regularly evaluate and assess job satisfaction as a key aspect. Employee involvement and corporate culture
are two of the variables that could affect job happiness. When workers are happy in their jobs and feel appreciated for their
efforts, they are said to be in a state of job satisfaction. Employee retention is positively impacted by pay scale, objectives,
employee recognition, awards, and organisational mission. Six main factors determine whether an employee stays or leaves a
firm. Rewards in money, job qualities, professional advancement, recognition, personnel administration, and work-life balance
The relationship between employee performance and satisfaction has drawn more attention than ever since the turn
of the 20th century. It is acknowledged that they are interconnected, notwithstanding Bateman and Organ's (1983) claim that
satisfaction and performance do not necessarily follow one another in a linear functional relationship. Scientists and managers
believe that lowering job dissatisfaction will improve employee performance and lower attrition (Lawler and Porter, 1967).
(Hackman and Oldman, 1980). Furthermore, Steijn (2004) even makes the case in which contented workers are more creative
and productive. Therefore, a number of works have investigated potential employee satisfaction motivational strategies,
including job rotation (Scott, 1966), reduced workday length, rising salaries, job participation (Herzberg, 1968), and
autonomous work groups (Gulowsen, 1972). Herzberg (1968) went on to point out that none succeeded in their goals since
the elements influencing employment attitudes were not taken into account. Researchers have discovered that proper
motivation is necessary for achieving job satisfaction, but only when a wide range of factors are considered. Previous research
has shown that demographic factors (age, sex, education, etc.) affect job satisfaction (Lawler and Porter, 1967). The necessary
task qualities were created by Turner and Lawrence (1965) and were predicted to have a favourable relationship with employee
happiness and attendance. According to Hackman and Lawler (1971), some aspects of a job, including variety, task identity,
autonomy, and feedback, might affect employees' attitudes and behaviour at work. Meyer (1991) established a link between
commitment to one's work and job satisfaction, claiming that individuals who are devoted to their responsibilities will be
satisfied and satisfied by affective orientation, involvement, and identification with a particular organisation. Other particular
Abstract Although there are several definitions of job satisfaction or employee satisfaction, we may generally define them
as a person's level of contentment with their job. Because they leave the company less frequently and stay longer, content
employees help the business grow. Additionally, a positive work atmosphere attracts talent and boosts productivity by
encouraging job satisfaction. The information technology (IT) industry has gained traction on the global scale and has taken
centre stage in both our society and the world as a whole. The booming Indian economy has contributed to the ability of
the IT industry to remain competitive in the international market. This study aimed to evaluate the degree of job
satisfaction among IT professionals and identify the factors affecting that satisfaction. To highlight the factors affecting
positive job satisfaction among IT industry employees, we included variables such as rewards and recognition,
working conditions, fairness, job security, relationships with coworkers and employee satisfaction. After the data were
cleaned, 100 responses were collected. The data were analysed using SPSS statistical software, and the findings showed
that the job satisfaction of IT employees is strongly correlated with a number of factors connected to the workplace.
Keywords: employee satisfaction, work environment, rewards, employee support, fairness

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factors for job satisfaction listed by Ting (1997) include lack of promotion opportunities, task clarity, skill use, and task
significance when combined with organisational commitment and relationships with supervisors and coworkers.
Ritu Narang and Alka Dwivedi (2010) conducted research to create a scale that gauges knowledge workers' job
satisfaction. Data from 511 knowledge workers were gathered, and a 30-item scale with a Cronbach’s alpha of 0.93 and
subscale reliability ranging from 0.93 to 0.54 was analysed. The tools that were validated included organisational support,
aggressive competition, repressive management practices, fair and transparent management, supervision, and guidance. The
relative relevance of several aspects has been demonstrated via regression analysis. According to a survey of 210 workers in
the education, banking, and telecommunication sectors in the city of Quetta, Pakistan, Abdul Raziq (2015) discovered a
correlation between job satisfaction and a positive working environment and that higher levels of job satisfaction can be
attained by creating a positive working environment.
The aim of the current paper is to identify the key factors that affect employee satisfaction in the IT industry. Employee
responses to their occupations are recorded on rating scales, which is the most popular method of measurement. On a scale
of 1 to 5, where 1 is "not at all satisfied" and 5 is "highly satisfied," respondents were asked to rate their level of satisfaction.
1.1. Job Satisfaction in the IT Industry
The current business world is dynamic and undergoing ongoing development. Having current knowledge that is also
helpful is the best way to fend off these elements. The personnel are what makes an organisation strong and effective.
Businesses may obtain the data they require to boost employee engagement, retention, and productivity by measuring
employee satisfaction in key areas. HR policy is a key component of improving job satisfaction. The core elements of an
organisation's entire retention strategy, such as fair salary, meaningful benefits, and the capacity to balance work and life,
must be addressed. Organisations must not only develop a variety of benefit policies that inspire and maintain an often highly
varied workforce but also continuously hone these mixed policies based on employee job satisfaction (Human Resource, 2012).
Some elements of job satisfaction are constant and universal. According to both employees and HR specialists, compensation
and benefits are significant factors in employee work satisfaction. Research has revealed that there are other, more significant
aspects that affect job satisfaction, such as interactions with immediate superiors, management appreciation of workers'
efforts, and interaction between staff members and senior management. These aspects more closely relate to the corporate
culture and working environment.
1.2. Employee Job Satisfaction and Rewards
Employee satisfaction is a critical determinant of organizational success, particularly in competitive sectors like
information technology (IT). Rewards, including both monetary and non-monetary incentives, play a pivotal role in shaping
employees' perceptions of their job roles, contributions, and overall job satisfaction. In conclusion, the hypothesis proposes
that specific rewards can significantly influence employee satisfaction within the IT industry. Thus, the following hypothesis is
proposed.
Hypothesis 1: Rewards improved employee job satisfaction in IT industry.
1.3. Employee Job Satisfaction and Fairness
Perceptions of fairness, encompassing distributive fairness (fairness in outcomes), procedural fairness (fairness in
processes), and interactional fairness (fairness in interpersonal treatment), play a crucial role in shaping employees' overall
satisfaction and engagement levels. Employees who perceive fairness in the allocation of rewards, fair processes in decision-
making, and respectful treatment from supervisors and colleagues report higher levels of job satisfaction in IT industry. Thus,
the following hypothesis is proposed.
Hypothesis 2: Fairness affects employee job satisfaction in IT industry.
1.4. Employee Job Satisfaction and Job Security
Job security, defined as the perceived assurance of ongoing employment and career stability within an organization,
plays a significant role in shaping employees' satisfaction, commitment, and engagement levels. Employees who perceive
higher levels of job security, including stable employment conditions, clear career advancement opportunities, and
organizational support during uncertain times, report higher levels of job satisfaction in IT industry. Thus, the following
hypothesis is proposed.
Hypothesis 3: Employee job satisfaction is affected by job security in IT industry.
1.5. Employee Job Satisfaction and Relationship between coworkers

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The quality of relationships with co-workers, characterized by teamwork, mutual support, effective communication, and
positive collaboration, plays a vital role in shaping employees' satisfaction, engagement, and overall well-being. Employees
who experience strong teamwork, effective communication channels, supportive collaboration with colleagues, and a sense of
camaraderie report higher levels of job satisfaction and job engagement. Thus, the following hypothesis is proposed.
Hypothesis 4: Relationship between coworkers affects employee job satisfaction in IT industry.
1.6. Employee Job Satisfaction and Working conditions
Working conditions, including aspects such as workload, workspace comfort, autonomy in job tasks, flexibility, and
perceived job security, play a crucial role in employees' satisfaction. Employees who experience manageable workloads,
conducive physical environments, autonomy in job tasks, opportunities for work-life balance, and a sense of job security report
higher levels of job satisfaction. Thus, the following hypothesis is proposed.
Hypothesis 5: Working conditions have an impact on employee job satisfaction in IT industry.
1.7. Conceptual Framework
Figure 1 Framework model.
2. Materials and Methods
This study used a descriptive research design as its method of inquiry. One hundred employees from IT companies in
Karnataka were surveyed as part of the study using convenience sampling. For the purpose of this investigation, the
investigators acquired the primary data. Data was gathered by the researchers from individuals employed as regular workers
within the Information Technology sector. The respondents voluntarily provided their responses through an online platform
utilizing a questionnaire hosted on Google Docs. Convenience sampling, a non-probabilistic approach, was employed to gather
data from individuals willing and able to participate in the study. Primary data will be collected through the use of
semistructured questionnaires. Twenty responses were evaluated and pilot tested with the goal of increasing the validity and
reliability of the collected data to test and improve the questionnaire's validity. For the data analysis, the researcher used
quantitative methods. Statisticians used inferential methods and descriptive analysis.
2.1. Analysis
PLS-SEM, or partial least square path modelling, is used to analyse the study and has recently been validated in the
literature (Hubona & Ray., 2016). The second generation of the multivariate approach to analysis has the same characteristics
as the first generation (Wold, 1982). It is based on the regression approach, which investigates the relationship between a large
number of independent variables and one or more dependent variables (Janadri & Wei.). In path model analysis, PLS-SEM is
recognised as the gold standard (Hair et al., 2014). Since PLS-SEM enables researchers to identify pathways among variables
Employee
Satisfaction

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and investigate the existing links between them, it is advised that PLS-SEM be used to create a statistical model (Wende &
Well., 2012).
2.2. Structural equation model (SEM)
To determine how the endogenous constructs interact with one another via linear regression, a structural model is used.
Regression using PLS was used to test the hypotheses. A regression-based technique called PLS regression examines the linear
correlations between a number of independent factors and one or more dependent variables (s). It differs from conventional
regression and is founded on preestablished networks of correlations between constructs and between constructs and their
measures.
2.3. Factor Loading
The factor loadings depict how important each item is to each construct in relation to the others. One may determine
how much of the observed variance can be attributed to validity coefficients, also known as factor loadings, by multiplying the
observed variable score by the factor loading (Lomax, 2016). The factor loadings demonstrate the validity of the items
employed in this inquiry. A critical component to consider is the level of factor loading. When a factor has great convergent
validity, the latent constructs converge toward a common point. Standardised loading estimates, which are recommended,
should be at least 0.50 and preferably 0.70. (Hair, 2014).
As previously indicated, standardised loading calculations should be at least 0.50 and, ideally, at least 0.70. (Hair, 2017).
The fact that all of the variables in Table 1 have specified factor loadings greater than 0.7, demonstrating that the loadings of
the variables are genuine, highlights the significant connection between latent variables and absolute variables.
Table 1 Factor loading.
Emp Sat
Fairness
Job Security
Relationship
Rewards
Working condition
ES1
0.818
ES2
0.833
ES3
0.853
ES4
0.767
Fairness1
0.774
Fairness2
0.799
Fairness3
0.863
Fairness4
0.508
JS1
0.844
JS2
0.803
JS3
0.751
JS4
0.537
Relationship1
0.653
Relationship2
0.816
Relationship3
0.890
Relationship4
0.737
Rewards1
0.840
Rewards2
0.671
Rewards3
0.707
Rewards4
0.852
WC1
0.850
WC2
0.838
WC3
0.840
WC4
0.805
2.4. Assessment of Construct Reliability
The reliability of the study's constructs was assessed. Consistency captures the essence of dependability. Reliability is
used to assess the internal consistency of the constructs. According to Mark, a measuring device's reliability is determined by
how stable and constant it is (1996). The foundation of reliability is repetition. When used frequently, will a tool yield the same
results? Cronbach’s alpha (CA) and composite dependability are the two most frequently used methods for assessing construct
reliability (CR). Factor loadings are used to calculate the composite reliability. This statistic shows how consistently the
questions used to evaluate the latent idea were answered. The method currently most frequently used to assess an
instrument's dependability is Cronbach's alpha. Recently, critics of Cronbach's alpha, a reliability metric, have raised the
concern that it might not always be enough (Cronbach, 2004). Consequently, Cronbach’s alpha and composite reliability
statistics are becoming more frequently used in research.

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The Table 2 shows that the composite reliability for all variables and constructs lies in the range of 0.8 to 0.9. We are
nearing validity determination. The average variance that constructs and their measures share should be greater than the
variance that other constructs share, according to AVE (Couchman & Fulop., 2006).
Table 2 Construct Reliability.
Cronbach's Alpha
rho_A
Composite Reliability
Average Variance Extracted (AVE)
Job Security
0.723
0.774
0.828
0.552
Fairness
0.740
0.794
0.831
0.561
Rewards
0.780
0.836
0.854
0.596
Relationship with Coworkers
0.788
0.858
0.859
0.607
Emp Sat
0.836
0.836
0.890
0.607
Working Condition
0.858
0.885
0.901
0.694
2.5. Fornell & Larcker Representing Divergent Validity
According to (Larcker, 1981), the discriminant validity of a concept is demonstrated when its square root of the AVE
exceeds the correlation between that particular construct and all other latent constructs.
Table 3 Fornell and Larcker.
Emp Sat
Fairness
Job Security
Relationship with
Coworkers
Rewards
Working
Condition
Emp Sat
0.818
Fairness
0.528
0.749
Job Security
0.539
0.631
0.743
Relationship with
Coworkers
0.21
0.298
0.375
0.779
Rewards
0.706
0.389
0.394
0.174
0.772
Working Condition
0.161
0.371
0.309
0.645
0.184
0.833
2.6. Heterotrait-Monotrait (HTMT)
The HTMT results, which revealed that all values were significantly different from 1, and the HTMT correlation ratio in
Table 4, which reveals that all values fall below the cut-off of .90, both demonstrated that the reflective constructs exhibited
discriminant validity.
Table 4 Heterotrait-Monotrait (HTMT).
Emp Sat
Fairness
Job Security
Relationship with
Coworkers
Rewards
Working
Condition
Emp Sat
Fairness
0.626
Job Security
0.677
0.795
Relationship with
Coworkers
0.24
0.363
0.479
Rewards
0.79
0.433
0.51
0.254
Working Condition
0.174
0.406
0.383
0.809
0.222
3. Results and Discussion
To determine the importance of the path coefficients, 500 subsamples were taken as part of the bootstrapping
technique. Figure 2 and Table 5 display the dependent and independent variables' values for the hypothesised path coefficient
and the T statistics for every item and concept.
H1, the original hypothesis, proposed that rewards improved IT employees' job satisfaction. The association between
rewards and job satisfaction was supported by the study's findings. The P value (0.001) was lower than the alpha value. H1 is
therefore accepted. This result is in line with earlier research findings of Siregar et al., (2023).
Fairness affects the job satisfaction of IT employees, according to the second hypothesis, H2. The results show that this
factor significantly and favourably influences job satisfaction, this findings aligns with findings of seung (2022). The alpha value
was greater than the P value (0.023). H2 is widely accepted. The third hypothesis, H3, was "Employee Job Satisfaction Is
Affected by Job Security." According to the results, this component positively affects job satisfaction. The alpha value is greater
than the P value (0.021). H3 is therefore accepted, this results inline with the research findings of khalid and sahibzada (2023).

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The fourth hypothesis is the relationship between coworkers and job happiness among IT employees, or H4. The findings
indicate that this factor has a negative impact on job satisfaction. The alpha value was greater than the P value (0.655). H4 is
thus rejected, this results inline with the research findings of Herawati et al., (2023).
According to the fifth hypothesis, H5, working-setting conditions have an impact on IT employees' job satisfaction.
According to the findings, this factor has a negative impact on job satisfaction. The P value (0.256) exceeded the alpha value
(0.05). H5 is therefore rejected, this results inline with the research findings of inrisar et al., (2023).
Table 5 Hypothesis, beta values, t statistics, and p values.
Original
Sample (O)
Sample
Mean (M)
Standard
Deviation (STDEV)
T Statistics
(|O/STDEV|)
P Values
Decision
H1: Rewards > Emp Sat
0.547
0.561
0.094
5.802
0.001
Accepted
H2: Fairness > Emp Sat
0.213
0.185
0.094
2.276
0.023
Accepted
H3: Job Security > Emp
Sat
0.208
0.19
0.09
2.313
0.021
Accepted
H4: Relationship with
Co-Worker > Emp Sat
0.051
0.034
0.114
0.447
0.655
Rejected
H5: Working Condition >
Emp Sat
-0.117
-0.081
0.103
1.137
0.256
Rejected
Figure 2 Path coefficients and t-statistics.
4. Conclusions
Because productivity depends on employee satisfaction, it is of utmost importance in a company. By establishing
procedures that will ensure that workers are given challenges and then rewarded for achievement, businesses can contribute
to the development of job satisfaction. To summarise, this study has established the factors that influence employees' job
satisfaction. IT employees in Karnataka were the target of a study to determine the study's objective. The findings showed that
reward benefits and compensation, fairness, and job security improve employees' job satisfaction.
4.1. Theoretical implications

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This investigation validates the correlation between incentives and job content among IT personnel, affirming prior
research discoveries. Furthermore, it offers novel perspectives on elements that influence job contentment, such as equity and
job stability, broadening conceptual comprehension beyond incentives. Nevertheless, the investigation refutes the association
between colleagues and job contentment, as well as the influence of working environment conditions on job contentment,
indicating that conventionally favourable factors may not be applicable in the particular context of IT staff. This emphasises
the necessity of accounting for industry-specific dynamics when examining job contentment. Social Exchange Theory highlights
the mutual relationship between employees and their organization, emphasizing the evaluation of job satisfaction based on
the perceived equilibrium between contributions to the organization (such as skills and effort) and rewards received (such as
salary, recognition, and growth opportunities). Within the realm of the IT industry, considerations may extend to aspects like
fairness in promotions, opportunities for skill enhancement, and conducive work atmospheres.
4.2. Managerial implications
This investigation underscores the significance of efficient incentive systems for information technology staff,
underscoring the necessity for supervisors to formulate incentive frameworks that are in harmony with the preferences and
motivations of employees. It also underscores the importance of equity and job stability in job contentment, highlighting the
need for clear-cut protocols, fair treatment, and opportunities for career progression. Despite the refutation of hypothesis 4,
it is imperative for managers not to disregard the importance of nurturing positive relationships among colleagues since a
helpful and cooperative workplace atmosphere can enhance the overall well-being and job contentment of employees. Finally,
the research proposes that managers should address any adverse aspects of the work environment, such as workload,
workplace safety, and ergonomic issues, to establish a more gratifying work setting for information technology employees.
The study indicates that job satisfaction is substantially impacted by multiple factors. Achieving a healthy work-life balance is
crucial, and managers should give priority to implementing measures such as flexible work hours, telecommuting choices, and
wellness programs to assist employees in attaining this balance. The organization should offer skill development and promotion
opportunities, as well as clearly defined avenues for career progression. Establishing effective communication and feedback
channels is vital, and managers should implement open-door policies and foster an environment that encourages constructive
criticism. Recognition and awards are also crucial, and managers should establish reward systems that highlight employee
efforts and achievements. A positive company culture, characterized by transparency, trust, collaboration, and inclusivity, can
also contribute to increased job satisfaction. Job design and job clarity are also vital, with clear definitions and relevant
activities. High workload and stress levels can severely affect job satisfaction, therefore managers should monitor and handle
these concerns. Building strong interpersonal ties and team bonding can also contribute to increased job satisfaction.
4.3. Limitations & Future Research Direction
Given that all study participants were from the same region of India, it is plausible to conclude that participants from
Karnataka are more familiar with and have more first-hand experience with the idea of job satisfaction than participants from
other regions of the country. The overall job satisfaction of employees in the IT sector may be impacted by other factors that
are specific to certain geographical areas. Although it seems reasonable to conclude that the study's findings contribute to a
significantly deeper understanding of the job satisfaction of employees of Indian IT firms and the underlying factors that affect
their overall satisfaction, more empirical research must be conducted to obtain a more complete picture.
Ethical considerations
Data was gathered by the researchers from individuals employed as regular workers within the Information Technology sector.
The respondents voluntarily provided their responses through an online platform utilizing a questionnaire hosted on Google
Docs.
Conflict of Interest
The authors declare no conflicts of interest.
Funding
This study did not receive any financial support.
References
Aggarwal, P., & Pal, P. (2014). A Review of complexity method for wireless Channel Estimation using a BEM. International Journal for Research in Applied
Science and Engineering Technology, 2(12), 590–593.
Card, D., Mas, A., Moretti, E., & Saez, E. (2012). Inequality at work: The effect of peer salaries on job satisfaction. American Economic Review, 102(6), 2981-
3003.

8
Mohan and Vasumathi (2024)
https://www.malque.pub/ojs/index.php/msj
Eedara, V. S., & Korrapati, R. B. (2017). A Review of Research on the Factors Affecting Job Satisfaction in Information Technology (IT) Companies. International
Journal of Engineering and Management Research (IJEMR), 7(1), 232-234.
Gulowsen, J. (1972). A Measure of Work-Group Autonomy. In L. E. Davis & J. C. Taylor (Eds.), Design of Jobs.
Hair Jr, J. F., Matthews, L. M., Matthews, R. L., & Sarstedt, M. (2017). PLS-SEM or CB-SEM: updated guidelines on which method to use. International Journal
of Multivariate Data Analysis, 1(2), 107-123.
Hair Jr, J. F., Sarstedt, M., Hopkins, L., & Kuppelwieser, V. G. (2014). Partial least squares structural equation modeling (PLS-SEM): An emerging tool in business
research. European business review, 26(2), 106-121.
Herawati, H., Setyadi, D., Michael, M., & Hidayati, T. (2023). The effect of workload, supervisor, and coworker supports on job performance through job
satisfaction. International Journal of Finance, Economics and Business, 2(1), 13–33. https://doi.org/10.56225/ijfeb.v2i1.168
Herzberg, F. (1968). One more time: How do you motivate employees (Vol. 65). Boston, MA: Harvard Business Review.
Khalid, K. M., & Sahibzada, A. (2023). The mediating role of job satisfaction at selected public universities in Afghanistan: the effect of job security on turnover
intention. Journal of Management and Business Education, 6(3), 244-256.
Kiruthiga, V., & Magesh, R. (2015). Brunt of employee retention strategies on job satisfaction. International Journal of Management and Commerce
Innovations, 2(2), 394-398.
Lamba, A., Dutta, N., Rela, S., & Singh, S. (2014). A Role of Data Mining Analysis to Identify Suspicious Activity Alert System. International Journal for
Technological Research in Engineering, 2(3).
Malik, I., Abdulahad, S., Saleh, A., & Shabila, N. (2023). Health employees’ perceptions of their working conditions. Asia Pacific Journal of Health
Management, 18(1). https://doi.org/10.24083/apjhm.v18i1.2141
Narang, R., & Dwivedi, A. (2010). Managing the job satisfaction of knowledge workers: an empirical investigation. Asia Pacific Journal of Business and
Management, 1(1), 1-14.
Raziq, A., & Maulabakhsh, R. (2015). Impact of Working Environment on Job Satisfaction. Procedia Economics and Finance, 23, 717-725.
Seung, Haeng, Cho. (2022). A study on the effect of organizational fairness on turnover intention through job satisfaction of resort employees. International
Journal of Tourism and Hospitality Research. https://doi.org/10.21298/ijthr.2022.7.36.7.83
Siregar, Z. M. E., Marihot, M., & Lubis, I. (2023). Does Reward System Effect Employee Job Satisfaction: Evidence from Public Sector. International Journal of
Business, Technology and Organizational Behavior (IJBTOB), 3(1), 51-55.
Sweeney, A. P., Hohenshil, T. H., & Fortune, J. C. (2002). Job satisfaction among employee assistance professionals: A national study. Journal of Employment
Counseling, 39(2), 50-60.
Turner, A. N., & Lawrence, P. R. (1965). Industrial jobs and the worker: An investigation of response to task attributes. Boston, Harvard University.
Questionnaire. Bibliography pp. 169-177.