INTRODUCTION:

As the world evolves, the technological, productive, and service-oriented transformations among organizations, companies, and industrial units have become increasingly complex. In today’s global landscape, harmonizing traditional thinking with modern strategies is essential to overcome crises and pave the way for sustainable development.

Among the critical challenges to progress is the absence of knowledge and effective human resources. Therefore, human capital is considered the most valuable and strategic asset of any institution.

Organisational growth, motivation, and even failure are significantly influenced by human resources. Achieving organizational goals without competent employees is virtually impossible. According to Taghipour, Azarian, Machiyani, and Fard (2020), employee job satisfaction is a crucial factor that organizations must prioritize. The success and growth of an institution are largely determined by the extent to which employees are satisfied with the organizational culture and their professional roles (Amin, 2015).

Job satisfaction is a broad and significant topic that has attracted considerable global research interest. Organizations worldwide are striving to enhance job satisfaction through various tools, methods, and strategies, recognizing its central role in organizational development. Through job satisfaction, institutions—whether governmental, industrial, or private—can effectively achieve their strategic goals and objectives. Job satisfaction encompasses both psychological and physical fulfillment related to one’s profession, work environment, entitlements, and accomplishments. Pandey (2021) defines job satisfaction as the degree to which an employee holds a positive emotional and evaluative perception of their work. Employees with higher levels of satisfaction demonstrate greater engagement, enthusiasm, and organizational commitment (Boon, Keong, and Ooi Wen Yue, 2010).

Job satisfaction influences various dimensions of an organization, including employee productivity, loyalty, and attendance. It is shaped by numerous internal and external factors. As the global community progresses, nations are often classified into industrial and non-industrial categories. The development of advanced countries is closely linked to the quality of life across different sectors. As a result, organizations focus on Total Quality Management (TQM) as a critical strategy for quality improvement.

RESEARCH PROBLEM:

Although Total Quality Management tools are known to influence job satisfaction, no study has yet been conducted in the context of Helmand University to explore this relationship. Therefore, this research aims to fill this gap by examining the specific TQM tools that significantly impact job satisfaction among the staff and faculty at Helmand University.

SIGNIFICANCE OF THE STUDY:

This research is of great importance in evaluating and enhancing job satisfaction among administrative staff and faculty members through the application of Total Quality Management (TQM) tools. It provides valuable insights into the degree of satisfaction among employees, enabling the university to make informed decisions to improve staff and faculty engagement.

For Helmand University, the findings of this study can offer practical and academic guidance to inform human resource strategies. More specifically, the research identifies and analyzes key factors that influence job satisfaction—distinguishing between those that have strong, moderate, or weak associations with TQM tools. Ultimately, By offering evidence-based suggestions based on the operational context of the university, the study seeks to improve employee satisfaction.

RESEARCH OBJECTIVES:

1. To evaluate how TQM tools affect job satisfaction.

2. To determine the correlation between TQM tools and job satisfaction.

3. To identify the specific TQM factors that exhibit the strongest relationship with job satisfaction.

RESEARCH QUESTIONS:

1. Do tools for Total Quality Management significantly impact job satisfaction?

2. Is there a relationship between TQM tools and job satisfaction?

3. Which TQM factor has the strongest correlation with job satisfaction?

REVIEW OF LITERATURE:

Abdulrahman and Mansor (2023) conducted a research entitled “The Effect of TQM Practices on Job Satisfaction in Higher Education Institutes: A Systematic Literature Review from the Last Two Decades,” examining the influence of TQM practices on job satisfaction inside higher education institutions. The study, based on survey data from university workers, determined that Education and Training, Top Management Commitment, Organisational Culture, and Customer Focus positively influenced job satisfaction.

In the same way, Najwa (2012) did a research called "A Study on the Total Quality Management (TQM) Practices and Its Association with Job Satisfaction among Workers in Malaysia's Electronics Market." The study gathered information from 100 individuals employed in the electronics industry. Regression study indicated that Top Management Commitment, Training, and Teamwork positively influenced job satisfaction.

Aminuddin et al. (2022) conducted a research entitled “The Effects of Total Quality Management Practices on Employees’ Job Satisfaction,” which sought to investigate the impact of TQM instruments on job satisfaction. The study examined five hypotheses and determined that all were positively correlated with work satisfaction. Top Management Commitment had the largest association, showing how important it is to make TQM tools a priority in organisational growth.A study titled “Examining the Relationship Between Soft TQM Aspects and Employee Job Satisfaction in ISO 9001 Certified Sudanese Oil Companies” by Ahmed et al. investigated the influence of TQM tools on employee satisfaction. The results showed that employee job satisfaction was significantly and favourably impacted by Total Quality Management tools.

MATERIALS AND METHODS:

Research Design:

This study adopts a descriptive and correlational research design, and employs a quantitative research method to analyze data related to job satisfaction. A cross-sectional approach is used, meaning data were collected from participants at a single point in time. The reason for selecting this design is the feasibility of accessing data from the defined population—faculty members and administrative staff of Helmand University—within a specific time frame without requiring follow-up.

Research Approach:

The study follows a deductive approach. Based on existing theories, hypotheses were formulated and a research plan was designed accordingly. In view of this plan, the hypotheses were then put to the test in order to investigate the connections between job satisfaction and TQM tools.

Study Area and Population:

The study was conducted at Helmand University, a public higher education institution located in Helmand province, Afghanistan. The university provides academic services through six faculties and 19 departments, and currently employs 137 faculty and administrative staff members. Additionally, the university has an active student body of approximately 2,000 students.

Sample Size and Sampling Technique:

The study utilized total population sampling, meaning data were collected from all 137 employees. This was feasible due to accessibility and the manageable size of the population. In academic research, confidence levels of 90%, 95%, and 99% (corresponding to significance levels of 0.10, 0.05, and 0.01) are commonly accepted. This implies that researchers are willing to accept a 1% or 5% margin of error in their conclusions (Khadim et al., 2023).

Data Sources and Collection Method:

Primary data were used in this research, gathered by distributing a structured questionnaire to Helmand University's faculty and administrative staff. A 5-point Likert Scale was employed, with response options ranging from: 1- strongly dissatisfied, 2- dissatisfied, 3- neutral, 4- satisfied, 5- strongly satisfied.

These responses helped quantify participant perceptions regarding the influence of TQM tools on their job satisfaction.

Hypotheses:

The following hypotheses were tested:

· H11: Leadership and Top Management Commitment have a significant positive effect on job satisfaction.

· H12: Job satisfaction is significantly improved by education and training.

· H13: Job satisfaction is significantly improved by customer focus.

· H14: Job satisfaction is significantly improved by organisational culture.

· H15: Teamwork has a significant positive effect on job satisfaction.

Theoretical Model:

The impact of different Total Quality Management (TQM) tools on employee job satisfaction is investigated in this study using an econometric model. Job satisfaction (JS) is the dependent variable in this model, and the five variables listed below are considered independent variables: 1-Commitment to Leadership and Top Management (TM), 2-Education and Training (ET), 3-Customer Focus (CF), 4-Organizational culture (OC), 5-Teamwork (TW)

The model is expressed as follows: JS=β0+β1⋅TM+β2⋅ET+β3⋅CF+β4⋅OC+β5⋅TW+𝜀

Where:

· β0β_0β0 is the constant (intercept),

· β1β_1β1 to β5β_5β5 are the coefficients of the independent variables,

· 𝜀𝜀𝜀 is the error term.

Data Analysis:

To analyze the data, the study uses Statistical Package for the Social Sciences (SPSS) Version 27.0. The following statistical techniques are applied:

· Descriptive Statistics: To list and explain the fundamental characteristics of the data.

· Correlation Analysis: To ascertain the direction and strength of relationships between variables,

· Regression Analysis: To evaluate the effect of TQM tools on job satisfaction and test hypotheses.

These analyses allow the researcher to derive insights about how TQM factors influence employee satisfaction within the university context.

Reliability and Validity Testing:

The study involves latent variables—constructs that are not directly measurable. To evaluate them, a measurement scale was developed. This scale consists of a group of items (questions), each measuring a specific aspect of the variable.

Cronbach's Alpha was used to evaluate each scale's reliability in order to guarantee internal consistency. When a scale's items consistently measure the same underlying construct, it has a high Cronbach's Alpha value.

Regression Analysis:

Regression analysis is used to examine how changes in one or more independent variables (TQM tools) influence variations in the dependent variable (job satisfaction). Specifically, this analysis allows for:

1. Measuring impact: How each TQM factor affects job satisfaction.

2. Predictive modeling: Using one variable to predict changes in another.

In this study, regression analysis helps assess how significantly each of the TQM components influences job satisfaction among staff and faculty at Helmand University.

Table 1: Profile of Respondents:

category	Sub-category	frequency	Percentage%
Gender	Male female	107 0	100 0.0
Age group	18-28 29-39 40-50 Above 50	31 55 16 5	28.97 55.40 14.95 4.67
Educational level	High school Bachelor Master PhD	0 64 41 2	0.0 59.81 38.31 1.86
Work experience	Under 5 year 5 years and above	39 68	36.44 63.66
Organization type	public	107	100.0

Findings and Results Respondents’ Profile:

In the above table Out of the 110 questionnaires distributed to the lecturers and administrative staff of Helmand University, 107 were accurately completed and collected by the researchers. However, 3 questionnaires were not properly filled out. The response rate was 97.27%.

The profile of the respondent includes the following attributes: gender, age, education, work experience, and organisation type.

Table 2. Skewness and Kurtosis Values for Data Normality Test:

Variables	Skewness		kurtosis
Variables	statistics	Standard error	statistics	Standard error
Top management	-.428	.234	-.908	.463
Education training	.303	.234	-.569	.463
Customer focus	-.493	.234	-.276	.463
Organization culture	-.442	.234	-.276	.463
Team work	-.511	.234	-.519	.463
Job satisfaction	-.582	.234	-.509	.463

Normality Test of the Data Using Kurtosis and Skewness:

Kurtosis represents the relative peakedness of the distribution, whereas the Skewness test shows how far the data deviates from the mean. The skewness and kurtosis values for a normal distribution should be roughly within ±3 and ±5, respectively (Khadim et al., 2023).

Correlation Matrix: To examine the relationships and interconnections among the variables, the results of the Correlation Matrix test are presented in the table-3 below.

Reliability Test Results:

The reliability test measures the internal consistency among the variables in a research study. It is an important indicator that focuses on the accuracy and credibility of the research findings. Through this test, the degree to which a particular study produces consistent results can be determined.

The reliability of 17 questions spanning 6 variables was evaluated in this study using Cronbach's Alpha. Cronbach's Alpha has a range of 0 to 1, with a value nearer 1 denoting greater internal consistency (Khadim et al., 2023).

A high degree of reliability was indicated by the study's overall Cronbach's Alpha value of 0.837. (Table-4).

Table 4: Statistical Test Values for Examining the Reliability of the Study:

Variables	No. of items	Cronbach’s Alpha if items deleted
Top management	2	0.765
Education training	3	0.719
Customer focus	3	0.731
Organizational culture	3	0.728
Team work	3	0.709
Job satisfction	3	0.736

Results of Regression Analysis:

summary model
model	R	R-square	Adjusted R square	Std error of the Estimate
1	0.605^a	0.366	0.335	0.65339
a. Constant predictors include TW, TM, CF, ET, and OC.

After the Coefficient of Correlation, the Coefficient of Determination is used as a strong indicator to show the strength of the relationship between variables.

Co-efficient
Model	Unstandardized coefficient		standardized coefficient	T	Sig. (p value)
Model	B	Std. Error	Beta	T	Sig. (p value)
(Constant)	1.033	0.507	--	2.039	.044
Top management	0.227	0.106	0.190	2.140	.035
Education training	0.327	0.130	0.243	2.518	.013
Customer focus	0.258	0.084	0.304	3.089	.003
Organizational Culture	-0.303	0.106	-0.285	-2.848	.005
Team work	0.290	0.098	0.284	2.968	.004
Dependent variable: job satisfaction

Hypotheses Testing

First Hypothesis: With a beta coefficient of 0.227 and a significance level of 0.035, the regression analysis's findings show that top management commitment significantly and favourably affects job satisfaction. Therefore, the researcher rejects the null hypothesis and accepts the alternative hypothesis, concluding that top management commitment has a significant and positive effect on job satisfaction.

Second Hypothesis: The regression analysis results show that education and training have a significant and positive influence on job satisfaction, with a Beta value of 0.327 and a significance level of 0.013. therefore, the null hypothesis is rejected, and the alternative hypothesis is accepted, confirming that education and training positively and significantly affect job satisfaction.

Third Hypothesis: According to the regression analysis, customer focus also has a significant and favourable effect on job satisfaction, with a significance level of 0.003 and a beta coefficient of 0.258. Consequently, the alternative hypothesis is accepted and the null hypothesis is rejected, suggesting that job satisfaction is positively and statistically significantly impacted by customer focus.

Fourth Hypothesis: The regression analysis indicates that organisational culture has a significant negative impact on job satisfaction, with a beta coefficient of -0.303 and a significance level of 0.005. As a result, the alternative hypothesis, which posits that organisational culture adversely and significantly affects job satisfaction, is accepted, while the null hypothesis is rejected.

Fifth Hypothesis: The regression analysis demonstrates that teamwork exerts a significant and positive effect on job satisfaction, evidenced by a Beta coefficient of 0.290 and a significance value of 0.004. Consequently, the null hypothesis is rejected, and the alternative hypothesis is accepted, thereby validating that teamwork exerts a positive and significant influence on job satisfaction.

DISCUSSION:

The research findings indicate that top management commitment has a significant and positive impact on job satisfaction. These results align with the findings of Kiani (2020), whose study also showed that top management commitment has a significant and positive relationship with satisfactionof job. Similarly, This outcome aligns with the results of Setapa, Halif, Mansor, Zakaria, and Aminuddin (2022), which also confirmed the positive influence of top management commitment on job satisfaction.

The study also reveals that training and education have a significant and positive effect on job satisfaction. These results are in line with the results of Essien Samuel and OlaoluwaJ (2018), whose research likewise confirmed that training and education significantly and positively influence job satisfaction.

Additionally, the results demonstrate that customer focus positively and significantly affects job satisfaction. These outcomes align with the findings of Abbas, Danish, Shoaib, Hashmi, and Mahmood (2014), who also identified a significant positive relationship between customer orientation and job satisfaction. The current results are further supported by Essien Samuel and OlaoluwaJ (2018), as well as by Alsalamah (2023), whose studies confirmed that focusing on customers has a significant and positive impact on job satisfaction.

Conversely, the analysis indicates that organisational culture exerts a substantial negative impact on job satisfaction. This finding is somewhat consistent with Abbas et al. (2014), although their research indicated a positive and significant correlation between organisational culture and job satisfaction. The difference may stem from contextual, institutional, or cultural variations.

The results also show that working together has a big and positive effect on job satisfaction. These results are akin to those of Jain (2010), whose study emphasised a positive and significant correlation between teamwork and job satisfaction.

CONCLUSION:

The aim of this study was to assess the influence of Total Quality Management (TQM) tools on job satisfaction. To accomplish this objective, the researcher gathered data via a questionnaire administered to 110 administrative personnel and lecturers. Based on the demographic analysis of the respondents:

· 100% are male

· 51% are between the ages of 29–39

· 60% held bachelor’s degrees

· 68% had over five years of work experience

· 100% were employed in the public sector

The findings show that the faculty and administrative staff of Helmand University were generally satisfied with the implementation of TQM tools. They expressed the highest level of satisfaction with senior management commitment, while training and education and focus to customer received relatively lower satisfaction scores.

The correlation analysis revealed that four out of the five TQM tools exhibited a positive and significant association with job satisfaction. But there was a strong and negative link between organisational culture and performance.

Furthermore, the regression analysis indicates that the five TQM tools—Teamwork (TW), Organizational Culture (OC), Customer Focus (CF), Education and Training (ET), and Top Management (TM)—account for approximately 36% of the variance in job satisfaction.

RECOMMENDATIONS:

Based on the conclusion of this research, the researcher has made a number of important and necessary recommendations, which are outlined as follows:

· Training and Education: Training and education are among the key tools of Total Quality Management (TQM) that have a significant and good effect on job satisfaction. However, the faculty and administrative staff of Helmand University expressed relatively low satisfaction in this area. Therefore, the university administration should develop new strategic plans, programs, and educational initiatives to improve training and development opportunities.

· Customer Focus: Customer focus is another vital component of TQM that significantly influences job satisfaction. Yet, faculty and administrative staff were not highly satisfied with this aspect either. The administration of Helmand University should ensure the timely delivery of services, academic planning, information, and training programs to students in order to enhance satisfaction and performance.

· Exploring Additional Factors: Since the research findings indicate that TQM tools account for only 36% of the variance in job satisfaction, it is essential to explore other underlying factors that may influence the remaining 64%. Identifying and understanding these additional variables can help improve job satisfaction more effectively.

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Received on 07.08.2025 Revised on 01.09.2025

Accepted on 20.09.2025 Published on 07.11.2025

Available online from November 17, 2025

Asian Journal of Management. 2025;16(4):336-342.

DOI: 10.52711/2321-5763.2025.00052

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. Creative Commons License.

Variables	Senior leadership	Education training	Focus for Customer	Organizational culture	Team work	Job satisfaction
Top management	1.000
Education training	.461	1.000
Customer focus	.109	.542	1.000
Organizational culture	.350	.476	.548	1.000
Team work	.459	.508	.449	.476	1.000
Job satisfaction	.397	.547	.435	.259	.527	1.000