The impact of key aspects of service quality on student satisfaction and subsequently influence positive word of mouth behavior among students at the university of economics and law

This research aimed to explore The impact of key aspects of service quality on student satisfaction and subsequently influence positive word-of-mouth behavior among students at the Unive

INTRODUCTION

Rationale

University autonomy refers to the ability to make independent decisions without external constraints (Maggetti, 2014) In Vietnam, there is a strong push to establish public service delivery units in the education sector to improve educational outcomes This includes promoting self-financing units by granting them authority and accountability over their finances, personnel, and operations (Hương, 2017) Data from Hương (2022) indicates that 109 public educational institutions will adopt financial autonomy by 2022, achieving a 23.9% rate, surpassing the 10% target set by the 6th Plenary of the 12th Central Committee This reflects significant progress toward greater efficiency and institutional autonomy in Vietnam's education system, marking a shift from a focus on public interest to treating higher education as a public service business, in line with Vietnam's commitment to the General Agreement on Trade and Services (GATS) (Tiến, 2007).

The University of Economics and Law, part of Ho Chi Minh City National University, serves as a leading institution for high-quality undergraduate and postgraduate education It plays a crucial role in Vietnam's higher education system by addressing the country's socioeconomic development needs and aligning with global trends Currently, the university boasts an enrollment of approximately 6,500 full-time students.

29 majors and programmes, including 4 university-level programmes with overseas affiliations In the period 2020 - 2024, the school's enrollment reached 2100 - 2600 students, exceeding the target by 10% - 30% each year (Phúc, 2024)

Recent enrollment results at the school have been promising; however, in the highly competitive landscape of economic training institutions nationwide, maintaining both quantity and quality is crucial This focus is essential for the school to enhance its training quality and effectively implement University Autonomy as sanctioned by the Ministry of Education and Training.

In 2021, implementing an effective marketing strategy to attract learners is essential, particularly by leveraging the positive referral intentions of current students This approach serves as a powerful and persuasive channel for enrollment promotion, providing valuable information to prospective students interested in the school.

The University of Economics and Law, operating as a financially independent entity since January 1, 2021, has implemented various measures to enhance its operations in accordance with service industry standards and state legislation Educational administrators must recognize their role within the service sector and their responsibility to fulfill student expectations (Elliott & Shin, 2002) Research by Van et al (2021) highlights that improving student satisfaction requires assessing educational service quality across four key dimensions: accessibility to educational services, the quality of educational settings and facilities, and the effectiveness of educational delivery By understanding student expectations and perspectives on these service quality elements, educational institutions can better cater to their needs.

Students are the primary beneficiaries of university services and should be regarded as the core customers of higher education institutions Recognizing students as invaluable resources, universities must focus their marketing strategies on building lasting relationships with them At the University of Economics and Law, students are empowered to choose a university that aligns with their individual needs and expectations.

The expansion of private universities in Vietnam, driven by international integration, aims to meet the growing demand for education and develop skilled professionals, leading to heightened competition in the education sector (Vân, 2023) In this competitive landscape, maintaining high-quality educational services is essential for Economics - Law institutions to gain a competitive advantage While competition may focus on research and academic innovation, the importance of service quality and educational standards remains paramount By recognizing universities as service industries, institutions are encouraged to prioritize the delivery of exceptional educational services and enhance student satisfaction to secure their competitive position.

(2002) universities can enhance their standing and reputation by adjusting their practices to better meet the requirements of their students through the consideration of student satisfaction

Research shows that student satisfaction significantly impacts behavioral intentions, including positive word-of-mouth (WOM) behavior For instance, Giantari (2021) found that during the COVID-19 pandemic in Indonesia, student satisfaction served as a crucial link between perceived value and WOM Additionally, Mulyana (2015) emphasizes that higher education institutions can foster favorable WOM by focusing on enhancing their institutional image and prioritizing student contentment.

Colleges should focus on delivering high-quality services to boost student satisfaction, which is essential for ongoing development By analyzing student satisfaction data, institutions can swiftly implement improvements to enhance educational quality, ultimately transforming students into advocates for the university and fostering a positive institutional reputation.

This research investigates how essential elements of service quality affect student satisfaction at the University of Economics and Law, ultimately leading to increased positive word-of-mouth behavior among students.

Overview of the Research Status of the Topic

Numerous studies have investigated the relationship between word-of-mouth (WOM) and consumer satisfaction, with findings suggesting that WOM often results from customer contentment Research by Shi (2016) reveals that customers who receive services that surpass their expectations are more likely to feel satisfied and share positive WOM about the service provider On the other hand, dissatisfied customers are more inclined to express negative WOM.

Cheng and Tam’s 1997 study highlights that service quality in educational activities encompasses the inputs, procedures, and outcomes aimed at meeting the expectations of students In higher education, stakeholders are categorized into providers, such as schools and institutions, and consumers, namely students who utilize these services Educational service providers have a fundamental responsibility to create value for students throughout their academic journey Service quality significantly influences student satisfaction, serving as a competitive advantage for institutions seeking contributions When universities deliver superior products and services, students are more likely to express satisfaction and recommend the institution to others, thereby providing strong evidence for prospective students considering higher education The factors influencing student satisfaction and their intention to recommend institutions have attracted considerable scholarly interest globally.

The SERVQUAL model posits that customer service evaluation hinges on the disparity between perceived and expected service quality Numerous studies have applied this model across diverse sectors, such as entertainment (Trang, 2003) and banking (Mehta, 2020), revealing that service quality differs significantly among various industries and markets.

Various studies have compared service quality measurement models, revealing that flexible approaches can differ across educational institutions Consistent with Haves's (1992) research, key factors influencing educational service quality include administrative services, libraries, practical tools, training programs, and teaching methods To effectively address student needs, institutions must understand their perceptions and expectations regarding these quality determinants.

Research Objective

The thesis pursues the subsequent objectives:

- Determine which factors contribute to educational service quality

- Determine what elements of service quality affect student satisfaction and, by extension, how likely students are to recommend their organization to others

To enhance the effectiveness of the University of Economics and Law's operations, it is essential for the administration to consider implementing policy changes based on the analysis provided These changes should not only address current challenges but also pave the way for future research opportunities, fostering an environment of continuous improvement and academic excellence By prioritizing strategic adjustments, the university can optimize its resources and better serve its student body.

Research question

- What factors contribute significantly to the quality of educational services at the University of Economics and Law?

The elements of service quality significantly affect student satisfaction at the University, with higher satisfaction levels leading to an increased likelihood of students recommending the institution to others Factors such as responsiveness, reliability, and assurance play crucial roles in shaping students' perceptions of their educational experience Consequently, enhancing these service quality elements can not only improve student satisfaction but also foster positive word-of-mouth referrals, ultimately benefiting the University’s reputation and enrollment.

To enhance the overall effectiveness of the University of Economics and Law, it is essential to analyze the factors impacting educational service quality and recommend potential policy changes By focusing on improving faculty training, integrating advanced technology in teaching methods, and fostering a supportive learning environment, the institution can significantly elevate its educational standards Additionally, implementing regular feedback mechanisms from students and staff will help identify areas for continuous improvement, ensuring that the university remains responsive to the needs of its community and maintains a competitive edge in the educational landscape.

Research subjects

Research object: Identify the factors influencing the satisfaction of undergraduate students at the University of Economics and Law and explore the consequential impact on their Word-of-Mouth Behavior

Survey object: Undergraduate students enrolled in years 1 through 4, currently undergoing academic studies at the University of Economics and Law.

Research Scope

Research space: The study conducted at the University of Economics and Law

Research period: from January 2024 to March 2024.

Research methods

This research was conducted in two stages: a preliminary study and a formal study

The author conducted independent research, compiling relevant resources from both local and international scientific studies on the topic This process involved developing a foundational research framework and appropriate measurement tools Additionally, the author sought guidance from experts in consumer behavior to refine the measurement scale as necessary.

A quantitative survey was conducted at the University of Economics and Law to gather feedback from students The collected data was analyzed using SPSS, employing exploratory factor analysis (EFA) and Cronbach's Alpha coefficient to assess the validity and reliability of the scale Subsequently, regression analysis was performed on the theoretical model to determine the impact of various factors on customer satisfaction and its relationship with word-of-mouth (WOM).

Structure of the research

The following is an outline of the five sections that make up the thesis:

Chapter 3: Research methods and models

In the first chapter, the author justifies the choice of subject matter by focusing on the University of Economics and Law, where the research aims to identify and analyze the factors influencing word-of-mouth (WOM) behavior and student satisfaction levels The study also explores future opportunities within this field and proposes practical strategies to enhance customer satisfaction efficiency.

The structure of the article is built according to: (1) Introduction to the research problem;

(2) Overview of the research situation; (3) Research methods; (4) Results and evaluation;

LITERATURE REVIEW

Some related concepts

According to Kotler and Armstrong (2014), a service is an intangible offering that one party provides to another, often without the need for physical products Quality, as defined by Feigenbaum (1945), refers to a customer's evaluation of a product or service based on personal interactions, measured against their own expectations These expectations, which can be both implicit and explicit, conscious or intuitive, are inherently subjective and continually evolve in a highly competitive market.

Service quality remains a complex and debated concept, with various interpretations among researchers Cronin and Taylor (1992) define it as the customer's subjective perception of service quality, independent of their expectations, which can create confusion and complicate differentiation Conversely, Berry, Parasuraman, and Zeithaml (1988) describe service quality as the disparity between customer expectations and their evaluations of service outcomes Despite the lack of a universally accepted definition, a common theme emerges: service quality is fundamentally about the difference between customer expectations and their experiences Ultimately, the assessment of service quality should prioritize the customer's perspective.

In the academic realm, "Quality of education and training" encompasses the inputs, processes, and outcomes of the educational system, designed to effectively meet the needs of both internal and external stakeholders This approach aims to fulfill established expectations and enhance the capabilities of learners (Cheng, 1997).

The Expectation-Confirmation theory plays a crucial role in understanding customer satisfaction during the post-consumption stage of the consumer decision-making process, particularly in higher education (Đức, 2023) This theory highlights two key processes that influence satisfaction: the initial expectations of service before enrollment and the perceptions formed after experiencing the services Prospective students set expectations regarding the quality of service they anticipate from an institution, and their satisfaction is confirmed if the actual service exceeds these expectations Conversely, if the institution's performance falls short, students experience negative confirmation, leading to dissatisfaction This dissatisfaction can result in complaints and adverse behaviors that harm the institution's brand Conversely, positive experiences foster loyalty and encourage students to recommend the institution to others Thus, customer satisfaction emerges as a vital asset for organizations aiming to enhance service quality, retain customers, and improve competitiveness, as illustrated by the satisfaction of students at the University of Economics and Law.

According to Oliver's Expectation-Confirmation Theory, customer satisfaction is defined through the comparison of pre-purchase expectations and post-consumption perceptions of quality (Vichiengior, 2019) This differential assessment, referred to as "the customer’s fulfillment response" (Hernon, 2010), occurs when consumers evaluate a product or service against their personal criteria, ultimately resulting in either satisfaction or dissatisfaction (Zeithaml, Bitner, & Gremler).

Customer satisfaction is defined as the extent to which a product or service fulfills a client's needs and desires (2010) According to Kotler and Keller (2012), it reflects how well a customer's experience aligns with their expectations following a purchase.

In this context, "expectations" denote the buyer's desires and goals shaped by their individual requirements, past experiences, and influences from advertisements and recommendations from friends and family.

Customer satisfaction is defined as the extent to which a product or service meets customer expectations It involves evaluating expectations through a confirmation and disconfirmation process, which can be categorized into three levels At the intermediate level, customer satisfaction is confirmed when perceived performance aligns with expectations The lowest level occurs when expectations are disconfirmed, indicating that the product or service fell short Conversely, the highest level of satisfaction is achieved when expectations are affirmed, meaning the performance exceeded what was anticipated (Peter, Ellen, & Robert, 2015).

Customer satisfaction can be defined as the evaluation made by customers based on their past interactions with a service provider, which they use to predict future experiences (Crosby, Evans, & Cowles, 1990).

Customer satisfaction is both a key goal and an essential marketing strategy that companies should continuously pursue, as highlighted by Kotler and Keller (2012) Research by Al-Msallam (2015) indicates that satisfied customers are more inclined to make repeat purchases, thereby influencing future buying decisions Furthermore, high levels of consumer satisfaction enhance the ability to generate positive word-of-mouth referrals, which can significantly impact brand perception and reach among potential customers.

As far as the area of education is concerned, (Tough, 1982) defined that student satisfaction refers to the views or attitudes that students have about learning motivation

Student satisfaction is reflected in positive attitudes towards learning and contentment with the educational experience Conversely, dissatisfaction is indicated by negative or submissive behaviors According to Thảo (2007), student satisfaction is defined as a subjective evaluation of the quality of services provided by educational institutions, shaped by individual experiences Thus, the emotions and attitudes students display during learning activities can be seen as indicators of their overall satisfaction with their educational journey.

According to the study, student satisfaction encompasses all positive and negative responses students have towards their institution regarding the educational services provided to meet their needs When students are pleased with the services offered by a university, they are more inclined to develop favorable attitudes towards the institution and share their experiences with others This definition of satisfaction, while adapted for this study, is rooted in previous research and emphasizes the importance of understanding satisfaction not merely as a process.

Casi and Wymer (2015) highlight that satisfaction and dissatisfaction should be viewed as distinct dimensions rather than opposing ends of a continuum Consequently, satisfaction can be effectively measured using a unipolar scale, reflecting its unique nature as an attitude consequence.

Word-of-mouth (WOM) significantly influences customer attitudes and behaviors, highlighting its importance in gauging customer satisfaction (Nam, 2020; Reichheld, 2003) Companies must recognize that consumer feedback transcends product usage, as positive WOM can attract a substantial number of new customers, representing a crucial value for businesses to leverage (Kumar, 2007).

Word of mouth (WOM) is the process by which individuals share their evaluations of products or services through interpersonal communication (Dichter, 1996; Richins, 1984) It has long been recognized by researchers as a significant influence on customer perceptions and behaviors WOM can carry positive, negative, or neutral messages (Richins, 1984; Tybout, 1981), and is estimated to be nine times more effective than other advertising mediums in turning negative or neutral sentiments into positive ones (Day, 1971) In marketing, WOM directly impacts a company's sales and overall profitability, as customers often seek out recommendations and reviews before making purchases (Thompson, 1995) Therefore, a key strategy for business growth is to harness positive WOM while mitigating the effects of negative feedback.

Literature review

2.2.1.1 Five service quality gaps model

Figure 2 1 Five service quality gaps model

Service quality, as defined by Parasuraman, Zeithaml, and Berry in 1985, refers to the gap between consumer expectations for a company's intended service and the actual experience they encounter after using that service.

- Gap 1: The discrepancy between the expectations of the client and the company's attempts to meet those expectations

- Gap 2: The discrepancy between an organization's quality standards and its attempts to meet the standards of service quality set by its clients

- Gap 3: Discrepancy between the design specifications and the delivered quality of the service

- Gap 4: The discrepancy between the quality of services provided and the level of quality that the company has assured clients of

- Gap 5: The discrepancy between the level of service received and what was expected

To achieve customer satisfaction in service quality, businesses must address the critical fifth gap This gap is essential for improving service quality, as it highlights the need for organizations to minimize deficiencies within their operational framework.

2.2.1.2 The SERVQUAL model for service quality management

Figure 2 2 The SERVQUAL model for service quality management

The SERVQUAL model quantifies service perception through five key factors: Reliability, which emphasizes the importance of consistent and timely service; Responsiveness, highlighting the staff's commitment to providing exceptional customer support; Service Capacity, showcasing professionalism and a welcoming attitude during client interactions; Empathy, reflecting genuine concern for individual customers and their unique needs; and Assurance, ensuring customers feel secure and confident in the service provided.

Tangible elements are reflected in the appearance of service personnel and the tools used in service delivery, while student satisfaction serves as the dependent variable in this model.

A study by Ngamkamollert and Ruangkanjanases (2015) aimed to identify the factors influencing international students' satisfaction with university programs in Thailand Using a five-point Likert scale, a satisfaction questionnaire was distributed to 271 international students The results indicated that overall satisfaction was positively affected by four key factors: education quality, financial and economic suitability, office personnel, and school reputation However, the four-factor multiple regression model accounted for only 51.3% of the variance in overall satisfaction, highlighting the need to expand the analytical model to include additional factors for improved predictive accuracy.

A study titled "Empirical Study on Factors of Student Satisfaction in Higher Education" (Guo, 2016) highlights teaching quality as a crucial factor for the sustainable growth of colleges and universities The research aimed to identify the variables affecting university student satisfaction, utilizing surveys and interviews with students at a Chinese university The findings reveal that student satisfaction is positively influenced by three key factors: the quality of teachers, the training program, and other related elements.

The study highlights that the most critical elements influencing student satisfaction in higher education are the teaching materials, teaching apparatus, and the instructors' attitudes However, it also notes that while these factors play a significant role, there are additional influences on student satisfaction that remain unexplored and warrant further research.

Figure 2 3 The research model proposed by (Guo, 2016)

A study by Sumartias (2017) titled "Student Satisfaction, University Brand Image, and Its Impact on Word of Mouth Communication" explores the influence of university student satisfaction and brand image on word-of-mouth (WOM) activities, mediated by student loyalty Utilizing a questionnaire distributed to 350 students at private universities in North Jakarta, the research achieved a response rate of 336 participants and employed Structural Equation Modeling (SEM) to analyze the relationships between variables Findings reveal that both student satisfaction and university brand image significantly affect WOM communication through their impact on student loyalty However, the study did not address the factors influencing student satisfaction and brand image, suggesting opportunities for further research to improve the university's brand image, enhance student satisfaction, and foster positive WOM activities.

Figure 2 4 The research model proposed by (Sumartias, 2017)

The study by Tandilashvili (2019) investigates the factors influencing student satisfaction at a Georgian state university, utilizing the HEdPERF scale to assess service quality in higher education Data from 793 students across various disciplines were analyzed through exploratory factor analysis and multiple regression to evaluate eight research hypotheses These hypotheses examined the impact of factors such as the reputation of study programs, perceived quality of academic services, non-academic services, university environment and location, as well as demographic variables like gender and age group Additionally, the study explored the influence of learning experiences on student satisfaction and the effect of satisfaction on student loyalty.

Administrative factors significantly influenced student satisfaction, followed closely by the quality of teaching staff A positive correlation was observed between the curriculum and student satisfaction levels Despite the high overall satisfaction reported, students expressed reluctance to recommend the university or demonstrate loyalty unless they were particularly pleased with service quality However, the study faced limitations, including a sample predominantly composed of female respondents (86%) and a majority of students lacking experience at multiple universities (78%) Future research should aim to incorporate a broader range of cultural and demographic diversity among its variables.

A study by Giao (2021) explored the relationship between word-of-mouth (WOM) and student satisfaction at English language centers in urban Ho Chi Minh City Utilizing a questionnaire with 200 participants, the research assessed students' satisfaction levels and the impact of WOM on these perceptions Various statistical methods were employed, including the AMOS program, linear structural equation modeling (SEM), Cronbach's Alpha for reliability, exploratory factor analysis (EFA), confirmatory factor analysis (CFA), and Raymon's scale.

The study from 2006 indicates that emotional commitment significantly influences word-of-mouth praise and behaviors among students It highlights that satisfaction is more strongly affected by the quality of functional services than by technical services Additionally, satisfaction positively impacts both emotional and high-sacrifice commitment, which helps the foreign language center build a strong reputation and promotes positive word-of-mouth among students However, the research found no direct link between Service Quality and Technical Service Quality on student satisfaction, nor did it establish a correlation with increased word-of-mouth activities among peers.

Figure 2 5 The research model proposed by (Giao, 2021)

A study titled "Factors Influencing the Intention to Recommend the University of Economics, Hue University" by Hương N T (2023) aimed to identify the variables affecting students' intentions to recommend the institution Using Structural Equation Modeling (SEM) on a survey of 623 third- and fourth-year students, the research revealed four key factors that enhance student satisfaction: facilities, training activities, trust, and instructors' assurance Additionally, student satisfaction was found to significantly influence their intention to recommend the university The findings suggest that institutions can leverage positive word-of-mouth and implement strategies to boost student satisfaction to enhance their reputation.

Figure 2 6 The research model proposed by (Hương N T., 2023)

The author identifies that understanding the factors affecting student satisfaction and its relationship with word-of-mouth promotion has important implications for universities This knowledge enables institutions to adjust their educational and training programs effectively, ultimately helping to attract more students.

Table 2 1 Comprehensive synthesis table of related studies

Order Research Title Author(s) Independence variables

1 Factors influencing foreign students' satisfaction toward international program in Thai universities

Staff support, (4) Image & Prestige of the university

271 Quantitative study, using a questionnaire to assess levels of satisfaction using a Likert scale with five points

Image & Prestige of the university all have an impact on student satisfaction

2 Empirical study on factors of student satisfaction in higher education

Guo, K (1)Hardware facilities, (2)Teacher quality, (3)Curriculum construction

Augmenting the research to further explore the influence of student satisfaction on the engagement of word-of- mouth activities among students

University brand image and its impact on word of mouth

(1) Student Loyalty, (2) Word-of- mouth

Through this study, an improved examination of the elements that communication influence

WOM behavior among students was carried out

4 Factors influencing student satisfaction in higher education

Service Quality, (2)Technical Service Quality

793 Quantitative study using the regression analysis approach

Assessing higher education service quality with the use of HEdPERF

Administrative factors, faculty quality, and training program have a strong impact on student satisfaction

However, satisfaction does not have a significant impact on loyalty or word-of- mouth activity

5 Quan hệ giữa sự hài lòng và truyền miệng tại các trung tâm Anh ngữ ở TP HCM

(1) Functional service quality, (2) Technical service quality

(a) Emotional commitment, and (b) Sacrificial commitment

200 CFA, AMOS program, Linear Structural

Functional service quality and technical service quality impact satisfaction

Satisfaction impacts word- of-mouth through two mediating variables: emotional commitment and sacrificial commitment

6 Các yếu tố ảnh hưởng đến ý định giới thiệu trường Đại học Kinh tế, Đại Học Huế

(1) Tangible facilities (2) Educatinal activities, (3) Reliability, (4) Lecturers, and (5) Assurance impact satisfaction

Tangible facilities; Educatinal activities; Reliability; Lecturers; Assurance impact satisfaction impact satisfaction

Satisfaction is a factor increasing the intention to recommend (word-of- mouth)

Through a synthesis of reference materials, the author draws out some important common points below, which will be the basis for developing the research model:

- Regarding the dependent variable, focus on satisfaction and word-of-mouth in the field of education Studies mostly focus on the university level of research

- In terms of analysis techniques: Previous studies have mainly used structural equation modeling (SEM) techniques, and some studies have used regression analysis

The research methods utilized in this study include both qualitative and quantitative approaches, with a primary focus on quantitative methods through sampling predominantly at universities Most of the research was conducted at a single university, although notable exceptions include Sumartias (2017), which examined data from three universities, and Giao (2021), which was carried out at an English center.

Research hypothesis

include additional variables into the study framework to guarantee a significant amount of impact and provide highly relevant suggestions

2.3.1 The relationship between Administrative & Staff support and Student

Prioritizing high-quality administrative services in universities is essential for several reasons The first point of contact for students is often through admissions and registration services, making superior service crucial for creating a positive impression of the institution Additionally, university administrative departments, such as the registration office, finance department, and library, typically operate using models similar to those of community organizations or government agencies.

Research by Vũ and Tâm (2020) indicates that students report greater satisfaction when office and support staff exhibit a positive, knowledgeable, and professional attitude, which helps in effectively addressing their needs Additionally, Tandilashvili (2019) highlights that the competence of administrative personnel plays a crucial role in enhancing student happiness within non-academic services.

The author hypothesizes that the responsiveness and conduct of office personnel significantly enhance student satisfaction with the quality of services provided by the institution To explore this argument, a hypothesis is proposed for further examination.

H1: Administrative & Staff support positively influences student satisfaction

2.3.2 The relationship between Lecturer and Student Satisfaction

Lecturers play a dual role in education by both teaching students and engaging in research, highlighting their responsibility for maintaining high instructional quality (Bentley, 2013) University administrators must ensure that instructors have the appropriate qualifications and expertise to fulfill their roles effectively Research indicates that students respect instructors who demonstrate qualities such as helpfulness, concern, expertise, enthusiasm, and genuine interest (Davison, 2009) Additionally, stakeholders, including parents and government entities, are increasingly prioritizing the quality of education delivered by faculty.

Enhancing student satisfaction involves instructors building positive relationships with students, assigning relevant coursework, delivering high-quality lectures, focusing on course objectives, incorporating diverse in-class activities, ensuring fair grading practices, offering constructive feedback, being punctual, and presenting clear and informed lectures (Gee, 2018).

Teaching behavior significantly affects instructors' effectiveness, resulting in increased student satisfaction with lectures (HHDNP, 2020) Long (2014) highlights that lecturers' subject competence is the most crucial factor influencing student happiness Additionally, Khanh (2021) emphasizes that the teaching staff plays a pivotal role in determining student satisfaction.

The author suggests that students' satisfaction with their university faculty is likely to rise when instructors actively engage with them both during and after class, imparting valuable knowledge and support This leads to the hypothesis that enhanced faculty-student interaction positively influences overall student satisfaction.

H2: The lecturers have a positive impact on student satisfaction

2.3.3 The relationship between the educational program and student satisfaction

To guarantee a high-quality education for university students, the design of educational programs plays a vital role It is essential to create subjects and instructional materials that meet the needs of both the profession and society.

A study by Tram in 2018 highlights that students gain insights into program structure and content when selecting a major The primary factor influencing their choice is the quality of training facilities offered by academic institutions When these facilities meet expectations, students experience greater satisfaction with both the school and their chosen field of study, aligning with findings from Yawson's research.

(2011), Aziz (2012), and Alqurashi (2019), it has been noted that the training programme has an impact on student satisfaction with the university's services

Research indicates that student satisfaction with educational programs improves when the curriculum aligns with students' goals and supports their learning objectives This leads to the hypothesis that enhancing program alignment can significantly boost overall student satisfaction.

H3: The educational program has a positive impact on student satisfaction

2.3.4 The relationship between brand image and student satisfaction

Effective branding serves as an unambiguous signifier of the caliber and dependability of an academic institution to both present and potential students (Thomson,

Student loyalty plays a crucial role in enhancing a university's reputation through positive recommendations and referrals (Helgesen, 2007) In the context of integration in Vietnam, academic institutions utilize their identities to strengthen their competitive advantage, attracting prospective students and retaining alumni from advanced training programs A study indicates that brand reputation, brand engagement, and overall satisfaction significantly influence student loyalty (Hiên, 2021).

A study by Rofingatun (2021) reveals that service value is significantly impacted by both service quality and reputation, which in turn affects student satisfaction The research suggests that a strong university reputation fosters greater student confidence, ultimately enhancing their overall satisfaction with the services provided.

H4: The brand image positively influences student satisfaction

2.3.5 The relationship between Tangible facilities and student satisfaction

University facilities play a vital role in enhancing students' learning experiences, as highlighted by Hoang (2006) These facilities encompass a variety of essential spaces, including lecture halls, exam rooms, auditoriums, libraries, technology resources, and faculty offices (Farahmandian, 2013).

Educational institutions should prioritize accessibility and hygiene to meet student expectations, as this leads to increased satisfaction and comfort on campus When students are pleased with the facilities, they are more likely to recommend the school to prospective students Therefore, improving campus facilities not only enhances student experiences but also strengthens the university's reputation (Dora, 2017).

Effective management of educational facilities is essential for providing faculty and staff with the necessary infrastructure that supports university operations (Kọrnọ, 2013) Moreover, the quality of university facilities plays a crucial role in influencing students' choices when selecting higher education institutions (Price).

The proposed research model

This study offers an in-depth review of existing research on how factors such as teaching staff, facilities, school reputation, administrative support, and training programs influence student satisfaction The analysis reveals that these elements significantly impact student satisfaction and subsequently affect their word-of-mouth activities Additionally, the author presents a proposed research model based on six hypotheses drawn from earlier research frameworks.

In Chapter 2, the author presents key theoretical concepts essential for understanding student satisfaction and positive word-of-mouth (WOM) activities, including Service Quality, Expectation-Confirmation Theory, Satisfaction, and WOM Intention The chapter also reviews relevant domestic and international research, highlighting gaps that inform the development of the author's research model This model comprises seven variables: five independent variables—Administrative and Staff Support, Lecturer Quality, Brand Image, Facilities, and Academic Programme—and two dependent variables: Student Satisfaction and Positive Word-of-Mouth Activities The proposed research model will guide future data collection and analysis to effectively address the research questions.

RESEARCH DESIGN

Research Process

The research was conducted in two key stages: preliminary and formal research Initially, the author explored relevant theories and literature on the topic, both domestically and internationally, to identify the research problem Following this, a questionnaire was developed based on previous studies and tested with experts and experienced individuals The formal research utilized quantitative methods, involving data collection and reliability testing through statistical analysis The outcomes of this quantitative phase informed the creation of a scale and survey form for broader data collection in subsequent research.

This study was carried out in five key stages to guarantee scientific validity, with each phase focused on maintaining objectivity and enhancing the generalizability of the findings The specific steps of the research process will be detailed in the subsequent section.

Research method

Convert the sample's demographics (gender, age, monthly income, education level, marital status, and years of experience) into a frequency table for statistical analysis

The reliability of scales can be evaluated through Exploratory Factor Analysis (EFA) and the Cronbach's Alpha reliability coefficient Cronbach's Alpha serves as a statistical measure of the internal consistency among scale items Researchers can utilize this method to reduce extraneous factors and exclude unsuitable variables in their studies, following the guidelines established by Nunnally and Bernstein.

In 1994, the author established criteria for selecting variables by eliminating those with an item-total correlation value below 0.3 Additionally, a scale must achieve a Cronbach Alpha reliability coefficient of 0.6 or higher to be considered for inclusion.

The selection of an appropriate minimum Cronbach's Alpha (α) coefficient is crucial for evaluating the reliability of a scale, with many researchers agreeing that α values from 0.8 to 1 signify a high-quality measurement Values between 0.7 and 0.8 are deemed acceptable, while some experts, like Hair (2006), argue that α values of 0.6 and above can be utilized, especially when the concept being measured is new.

The selection of the minimum α coefficient is influenced by factors such as research type, the number of scale questions, and the scale's intended application (Hair et al., 2006) In this study, feedback from supervising lecturers indicated that an α value of 0.6 or higher is considered acceptable for practical use.

Exploratory Factor Analysis (EFA) is a statistical technique used to condense and summarize data after assessing the reliability of the scale through Cronbach’s Alpha coefficient and eliminating unreliable variables (Lê Thị Bích Nga, 2016) This method is essential for identifying sets of variables relevant to the research problem and exploring relationships among those variables Researchers typically consider multiple criteria when performing exploratory factor analysis.

To ensure the effectiveness of Exploratory Factor Analysis (EFA), the Kaiser-Meyer-Olkin (KMO) coefficient must exceed 0.5, while Bartlett's significance should be 0.05 or lower KMO serves as a crucial metric for evaluating the suitability of EFA, with values ranging from 0.5 to 1 indicating varying levels of adequacy for factor analysis According to Kaiser (1974) and Tho (2021), KMO values of 0.90 and above are considered excellent, 0.80 to 0.89 as good, 0.70 to 0.79 as fair, 0.60 to 0.69 as acceptable, 0.50 to 0.59 as poor, and anything below 0.50 as unacceptable.

In exploratory factor analysis (EFA), it is essential for the factor loading coefficient to be at least 0.5, as emphasized by Hair et al (2006) This threshold is vital for establishing the practical significance of the analysis While factor loadings above 0.3 indicate a minimum level of relevance, those above 0.4 are deemed important, with values of 0.5 or greater representing practical significance.

Thirdly, the scale is considered acceptable if the total extracted variance is equal to or greater than 50%, and the eigenvalue coefficient exceeds 1 (Gerbing and Anderson,

Fourthly, a factor loading coefficient difference of ≥ 0.5 for an observed variable across factors is necessary to guarantee distinctiveness between the factors (Kline, 2015)

After conducting Exploratory Factor Analysis (EFA), only scales with an acceptable factor structure will be selected for further evaluation using Confirmatory Factor Analysis (CFA) and Structural Equation Modeling (SEM) This process highlights the significance of the scale's internal structure, the intercorrelation among derived concepts, and the uniqueness of the extracted factors.

To accurately represent the underlying structure of the data, this study will employ the Principal Axis Factoring (PAF) method with Promax rotation Gerbing and Anderson (1988) recommend PAF with Promax rotation over the Principal Components method with Varimax rotation, as it effectively captures complex interrelationships between factors This approach is especially pertinent for multidimensional scales, where the independence of factors cannot be assumed.

The extraction process will persist until the eigenvalues for each factor are at least 1, ensuring that the factors captured explain a substantial portion of the data's variance (Hayton, 2002) Unlike the Principal Components method with Varimax rotation, Principal Axis Factoring (PAF) with Promax rotation provides a more detailed representation of the data by accommodating possible correlations among the extracted factors.

3.2.3 Validating the scale using confirmatory factor analysis (CFA)

Confirmatory Factor Analysis (CFA) is a statistical technique used in Structural Equation Modeling (SEM) to assess the extent to which observed variables accurately represent underlying factors This method is applied after Exploratory Factor Analysis (EFA) and is particularly useful when researchers have existing knowledge about the latent structure, including hypothesized relationships between observed variables and underlying factors based on theoretical or practical insights.

Evaluating the reliability of measurement scales involves several key methods: the composite reliability coefficient by Joreskog (1971), the total extracted variance by Fornell and Larcker (1981), and the Cronbach’s Alpha reliability coefficient According to Hair (1998), the extracted variance for each concept must exceed 0.5, indicating reliability and reflecting the shared variability among observed variables derived from latent variables Schumacker and Lomax (2010) highlight the importance of assessing the reliability of observed variables in Confirmatory Factor Analysis (CFA), where Cronbach’s Alpha is a widely used metric for measuring internal consistency in respondents' answers (Thọ, 2011).

Unidimensionality occurs when a set of observed variables can be effectively represented by a single dimension According to Steenkamp & Trijp (1991), the suitability of the model with market data is essential for assessing whether these observed variables achieve unidimensionality However, this condition may be compromised if there are correlations among the errors of the observed variables.

(3) Convergent validity: According to Gerbing and Anderson (1988), a scale achieves convergent validity when the standardized loadings of its items are all high (>0.5) and statistically significant (P < 0.05)

To establish discriminant validity in our model, we will evaluate the distinctiveness of the measured concepts by comparing a saturated model, where all concepts are allowed to correlate freely, to our proposed theoretical model By analyzing the correlation coefficients from the saturated model, we can identify whether these coefficients are statistically different from 1 If they are significantly different, it confirms that the concepts are distinct, demonstrating that our scales effectively capture unique aspects rather than overlapping constructs (Anderson J C., 1988).

Nomological validity refers to the effectiveness of a measuring methodology in evaluating specific problems, as identified by Anderson and Gerbing (1988) A theoretical model is employed to assess the values of these relationships, and a measuring model is considered excellent when it meets all established criteria However, it is uncommon for a measuring model to fulfill every requirement, and, for instance, a measurement model may still be utilized even if the scale does not achieve unidimensionality (Thọ, 2011).

Scale Development

The study identifies five key independent variables influencing student satisfaction and word-of-mouth activity at the University of Economics and Law: (1) Administrative and staff support, (2) Lecturers, (3) Educational programs, (4) Brand image, and (5) Tangible facilities By utilizing a 5-level Likert scale, the research aims to measure and analyze the factors that impact college students' satisfaction with the quality of services provided by the institution.

I Administrative and Staff support (OF) Sources

Members of the administrative and support personnel always have a positive attitude while interacting with students

(Trâm Đ T., Các yếu tố tác động đến truyền miệng của sinh viên trong ngữ cảnh giáo dục cao đẳng ở Việt Nam, 2015)

The administrative and staff support team is reliable since they consistently complete their tasks when they say they would

When interacting with students, administrative and staff support personnel always use polite and respectful language

Administrative and staff support often shows care and endeavours to solve student difficulties when they confront academic or administrative challenges

OF5 Administrative and staff support personnel have extensive understanding of the system/procedures

OF6 Administrative and staff support personnel ensure that academic records are precise and easily accessible

LEC1 Lecturers' expert knowledge fulfils students' informational demands

LEC2 The lecturers' methods for education are straightforward and simple to comprehend

LEC3 Lecturers have the ability to capitalise on the proactive and positive attitudes of learners

The instructors commit additional time beyond usual hours to provide support to students in their academic pursuits

LEC5 Lecturers prioritise developing a professional mindset among college students

LEC6 The development of students' capacities for independent learning is the top priority of lecturers

Information on graduation requirements, final exam policies, and test policies relevant to certain courses are either given to students or conveyed to them

PRO2 The course requirements and learning outcomes for your chosen major are clearly noticeable to students

PRO3 The amount of knowledge in both foundational and specialized subjects is reasonable

PRO4 The courses and lectures are regularly revised to reflect current events

PRO5 The information provided is adequate to serve as a basis for further courses or self-learning by the learner

PRO6 Curriculum designed to foster students' ability to independently learn and do thorough research

TANG1 The classroom is completely furnished with practical and useful educational tools

TANG2 The university's classrooms are spacious pleasant, and have good ventilation

The number of students in a class are reasonable , which allows students can concentrate effectively during lectures

TANG4 The library meets the reading and borrowing requirements of students in an efficient manner

Students' information search requirements are efficiently served in the computer room located within the library

TANG6 The space for independent study and relaxation at the university is abundant and conveniently accessible

BI1 I have always had a good impression of this university

BI2 In my opinion, this university has a good image in the minds of consumers

BI3 I believe that the university has a better image than its competitors BI4 In general, I have a positive image from this University

SS1 My decision to choose it were correct

SS2 Has satisfied my expectations

SS3 In general, I am satisfied

WOM1 If somebody ask me surely, I'll recommended my university

(Kwun, 2013) WOM2 If the opportunity arose, I would make positive comments to family and friends WOM3 I would encourage others to study at this university

Sampling

Utilizing a combination of a direct survey and a Google form, the questionnaire is distributed directly to the respondents in accordance with the convenience non-probability sampling method

Structural Equation Modeling (SEM) is utilized in research, with minimum sample size recommendations influenced by the model's complexity and key characteristics of the measurement model, as highlighted by Hair Jr (2017).

For models comprising five concepts or fewer, each defined by at least three measured variables and exhibiting high communalities of 0.60 or greater, a minimum sample size of 100 participants is essential.

Models with no underidentified constructs, a minimum of seven concepts, and a minimum value of communalities of 0.50 are required, with a minimum sample size of

A minimum sample size of 300 is required for models that contain seven or fewer concepts, have low communalities (0.45), and have no underdetermined concepts (less than 3)

For models with a greater number of concepts, some low communalities values, and approximately three measured variables per concept, a minimum sample size of 500 is required

In accordance with (Green, 1991) regression formula, the bare minimum sample size for regression analysis is 98 samples (N = 50 + 8*number of independent variables included).

As per (Comrey, 1973) findings, the bare minimum sample size is 170 samples, or

N = 5 times the number of observed variables (34).

In light of this, the author suggests a survey sample size ranging from 200 to 300 samples, based on the minimum sample size requirement of 170 samples.

Chapter 3 covers the research process, including the development of the scale, the implementation of quantitative studies, the sampling method used, and the techniques employed for data analysis and processing

For the subsequent quantitative research, a convenience sampling method using a non-probability approach was chosen, with a minimum sample size of 264 deemed appropriate

The data collected will be analyzed using IBM SPSS Statistics, which involves several key procedures: describing the sample, assessing the reliability of the scales, conducting exploratory factor analysis, testing the proposed model, performing regression analysis, conducting hypothesis testing, and finally, verifying any necessary assumptions.

RESULTS AND EVALUATION

Descriptive Statistics

(Source: Results obtained from the analysis using SPSS software)

The gender distribution of the survey participants showed a female majority, with 62.1% of respondents identifying as female, compared to 37.9% who identified as male

In terms of academic year, K20 had 39 respondents (14.8%), K21 had 91 respondents (34.5%), K22 had 81 respondents (30.7%), and K23 had 53 respondents (20.1%)

Faculty analyses revealed significant variations in student participation rates across different programs Business Administration led with the highest involvement at 32.2%, followed by Accounting and Auditing at 26.5% and International Economics at 22.3% Information Systems recorded a participation rate of 15.2%, while the "Others" category had the lowest at just 3.8%.

Applying Cronbach's Alpha to the Observed Variables for assessing Scale

When evaluating the reliability of a questionnaire, if the removal of an observed variable leads to a higher Cronbach's Alpha If Item Deleted than the original value, the author may consider keeping that variable To ensure the questionnaire's reliability, items that meet the standard of a Cronbach's Alpha of 0.6 or higher and a Corrected Item–Total Correlation above 0.3 are retained, while those failing to meet these criteria, specifically with a Corrected Item–Total Correlation below 0.3, may be eliminated The final results of the Cronbach's Alpha test are summarized as follows.

Table 4 2 Factor results from the Cronbach's Alpha test

Scale Mean if Item Deleted

Scale Variance if Item Deleted

Cronbach's Alpha if Item Deleted

(Source: Results obtained from the analysis using SPSS software)

The scale validation data indicated that all components achieved Cronbach's Alpha values exceeding 0.6, with corrected item-total correlation coefficients above 0.3 Therefore, it can be concluded that the scales are reliable and suitable for further analysis using Exploratory Factor Analysis (EFA).

Exploratory Factor Analysis (EFA)

The first-order Exploratory Factor Analysis (EFA)

Table 4 3 KMO Test Results KMO and Bartlett's Test

Kaiser-Meyer-Olkin Measure of Sampling Adequacy 0,822

(Source: Results obtained from the analysis using SPSS software)

The factor analysis results show that the KMO index is 0.822 > 0.5, indicates strong sampling adequacy for factor analysis

The results of Bartlett’s test indicate a significance level of 0.000, which is less than the 0.05 threshold, leading to the rejection of the null hypothesis (H0) that suggests the observed variables are uncorrelated in the population This outcome rejects the hypothesis that the correlation matrix of the variables is an identity matrix, confirming that the variables are indeed correlated and fulfilling the necessary conditions for conducting factor analysis.

Table 4 4 Eigenvalues and Variance Extracted

Initial Eigenvalues Extraction Sums of Squared

(Source: Results obtained from the analysis using SPSS software)

Perform a factor analysis utilising the Principal Components matrix and applying Promax rotation Based on the findings, the 34 observed variables have been categorised into 7 factors

The cumulative variance extracted is 56.183%, exceeding the 50% threshold and meeting the necessary criteria This indicates that the seven identified factors collectively explain 56.183% of the data variation Additionally, all factors exhibit high eigenvalues, with the seventh factor showing an eigenvalue of 1.083.

(Source: Results obtained from the analysis using SPSS software)

All observations indicate that the factor loading is greater than 0.5, with the exception of variable PRO4 This results in the variable PRO4 being eliminated

The second-order Exploratory Factor Analysis (EFA) (eliminate PRO4)

Table 4 6 KMO and Bartlett's Test

Kaiser-Meyer-Olkin Measure of Sampling Adequacy 0,829

Bartlett's Test of Sphericity Approx Chi-Square 4425,560 df 528

(Source: Results obtained from the analysis using SPSS software)

Kaiser-Meyer-Olkin Measure of Sampling Adequacy (KMO) value = 0,829

The results of factor analysis show that the KMO index is 0,871 > 0,5, which proves that the data used for factor analysis is completely appropriate

Barlett's test results with significance level Sig = 0.000 < 0.05, so the variables are correlated with each other and meet the conditions for factor analysis

Eigenvalue = 1,056 Extraction Sums of Squared Loadings (Cumulative %) = 56,694%

(Source: Results obtained from the analysis using SPSS software)

The factor loading coefficients in the Rotated Component Matrix table above are all greater than 0.5, thereby ensuring statistical significance and preventing the elimination of any variables

The Eigenvalue = 1,056 > 1 signifies the proportion of variation accounted for by each factor, then the extracted factor provides the most comprehensive synthesis of information

Extraction Sums of Squared Loadings (Cumulative %) = 56,694% > 50% This indicates that the 7 independent factors account for 56.694% of the variance in the research model.

Confirm Factor Analysis (CFA)

Table 4 8 Composite Reliability (CR) & Average Variance Extracted (AVE)

(Source: Results obtained from the analysis using Excel software)

The CFA analysis results, as shown in Table 4.8, confirm the reliability and effectiveness of the measurement scales, with both Composite Reliability (CR) and Average Variance Extracted (AVE) exceeding 0.5 Additionally, the AVE surpasses the Maximum Shared Variance (MSV), indicating strong discriminant validity This ensures that the scales consistently measure their intended constructs while maintaining distinctiveness, capturing unique aspects not shared with other constructs in the model Overall, this convergence and discriminant validity provide a robust foundation for further analysis.

SS TANG OF LEC PRO BI WOM

(Source: Results obtained from the analysis using Excel software)

Analyzing the square root of Average Variance Extracted (AVE) for each variable reveals that it consistently exceeds the total correlations with all other variables in the model, indicating that these variables each capture unique information.

Each variable in the model addresses a unique aspect of the underlying construct, rather than merely being variations of a single theme This distinctiveness enhances the model's overall validity, indicating that the variables accurately measure their intended concepts without merely overlapping with one another.

(Source: Results obtained from the analysis using AMOS software)

The evaluation of the Confirmatory Factor Analysis (CFA) model indicates a strong fit between the hypothesized model and the observed data, supported by various goodness-of-fit indices The Chi-square value normalized by degrees of freedom is 1.716, significantly lower than the recommended threshold of 3 Additionally, the Tucker-Lewis Index (TLI) and Comparative Fit Index (CFI) are both above 0.9, with TLI at 0.911 and CFI at 0.921, suggesting a good model fit The Goodness-of-Fit Index (GFI) is 0.861, further confirming this assessment Moreover, the Root Mean Square Error of Approximation (RMSEA) is 0.052, well below the acceptable limit of 0.08 Together, these indices demonstrate that the observed variables effectively represent the underlying latent constructs, indicating a high degree of convergence with the hypothesized model.

(Source: Results obtained from the analysis using AMOS software)

The convergent validity of the scale is reinforced by the standardized weights, all exceeding 0.5, which indicates a strong relationship between each item and the underlying construct Furthermore, with all p-values below 0.05, the results are statistically significant, suggesting that the observed relationships are not due to random chance Collectively, these findings affirm that the scale's items are both relevant and statistically significant in measuring the intended construct, thereby enhancing the overall validity of the scale.

Testing the research model and the hypotheses

This research employed a comprehensive multi-step methodology to enhance the reliability of its findings It began with Exploratory Factor Analysis (EFA) to identify underlying factors within the data that correspond to the proposed constructs, which set the stage for the subsequent Confirmatory Factor Analysis (CFA) The CFA evaluated the fit of a predetermined model that illustrated the relationships between items and factors To ensure internal consistency of the scales, Cronbach's Alpha was utilized, confirming that items within each scale accurately measure the same construct Finally, Structural Equation Modeling (SEM) was implemented to test the hypothesized relationships among the constructs identified earlier This thorough approach—combining exploration, confirmation, and hypothesis testing—bolsters confidence in the study's results.

(Source: Results obtained from the analysis using AMOS software)

The Structural Equation Modeling (SEM) analysis, as shown in Figure 4.2, demonstrates strong model suitability for the market, supported by favorable fit indices The Chi-square value normalized by degrees of freedom is 1.727, significantly below the recommended threshold of 3 Additionally, the TLI and CFI values exceed 0.9 (TLI = 0.910, CFI = 0.918), indicating a good model fit, while the GFI of 0.858 further reinforces this conclusion Moreover, the RMSEA of 0.053 is well under the accepted cut-off of 0.08 Together, these indices provide compelling evidence that the model accurately represents the market dynamics being studied.

Table 4 11 Summary of coefficients of the SEM

(Source: Results obtained from the analysis using AMOS software)

A recent analysis revealed that independent factors such as TANG, OF, LEC, PRO, and BI significantly enhance student satisfaction, with p-values below 0.05 indicating statistical significance These positive relationships confirm the beneficial impact of these variables, which collectively explain 53.7% of the variation in student satisfaction.

Student Satisfaction (SS) plays a crucial role in determining the likelihood of students recommending the program to others, known as WOM intent This relationship is statistically significant, as indicated by a p-value below 0.05, confirming the positive impact of student satisfaction on word-of-mouth recommendations.

Increased student satisfaction significantly enhances the likelihood of students recommending their school, with research indicating that it accounts for 35.4% of the variation in word-of-mouth intent This underscores the crucial role that student satisfaction plays in fostering positive recommendations.

The author enhanced the official survey's sample size of 264 to 500 for the Bootstrap analysis, ensuring that the initial sample effectively serves as a "crowd" necessary for obtaining accurate results The findings from the Bootstrap test, utilizing the larger sample size, are as follows:

Parameter SE SE-SE Mean Bias SE-Bias CR

(Source: Results obtained from the analysis using AMOS software)

Note: SE is standard deviation; SE-SE is the standard error of the standard error; Bias is bias; SE-Bias is the standard error of bias

The results in Table 4.12 indicate that the model's estimates are dependable, as any existing bias is minimal and does not significantly affect the outcomes Therefore, the model can be confidently utilized for populations exceeding the initial sample size of 500 individuals.

1 H1: Administrative & Staff support positively influences student satisfaction Accept

2 H2: The lecturers have a positive impact on student satisfaction Accept

3 H3: The educational program has a positive impact on student satisfaction Accept

4 H4: The brand image positively influences student satisfaction Accept

5 H5: Tangible facilities positively impact student satisfaction Accept

6 H6: Student satisfaction has a positive impact on word-of-mouth activities Accept

(Source: Results obtained from the analysis using AMOS software)

Research result discussion

Recent research reveals that Administrative & Staff Support plays a crucial role in enhancing student satisfaction, demonstrating a significant impact with an estimated effect size of 0.371 This finding is consistent with previous studies by Ngamkamollert (2015) and Vu & Tam, underscoring the importance of effective administrative support in educational settings.

Student satisfaction in 2020 is influenced by positive interactions with university office staff, characterized by strong communication skills, timely responses to concerns, and a high degree of professionalism among all personnel.

Research indicates that the Tangible Facilities system significantly affects student satisfaction, with an estimate of 0.276 This finding aligns with studies by Guo (2016) and Huong (2023), highlighting the importance of comfortable learning environments Consequently, the tangible facilities available on university campuses are essential for enhancing students' comfort and overall study experience.

This study reveals that the university's image significantly influences student satisfaction, with an estimate of 0.207 This finding aligns with earlier research by Ngamkamollert (2015) and Rofingatun (2021) A positive institutional image encourages students to adopt a favorable attitude, ultimately leading to increased satisfaction with their university experience.

The educational program significantly influences student satisfaction, with an estimate of 0.173, as supported by research from Huong (2023) and Alqurashi (2019) To enhance employability post-graduation, course content should prioritize equipping students with essential skills and knowledge Students view higher education as a critical pathway to achieving their career objectives and securing future employment opportunities.

Fifthly, the Lecturer is the factor with the least impact on student satisfaction (Estimate = 0.159), a hypothesis supported by the research of Huong (2023) and Gee

(2018) Most participants hold the view that proficiency, teaching methods, and positive interaction are key determinants of student satisfaction

Lastly, satisfaction positively influences students' positive word-of-mouth (Estimate

Satisfied students are likely to promote their university through positive word-of-mouth, as supported by research from Giao (2021) and Huong (2023) To attract more new students, colleges should focus on enhancing the satisfaction of current students and alumni by improving the quality of services provided, thereby boosting their word-of-mouth recommendations.

Chapter 4 conducted analysis and verification using SPSS software The scales and questionnaires in the model are sufficient for implementing quantitative research methods The factors in the proposed model, including Administrative & Staff Support, Lecturer Quality, Brand Image, Facilities, and Academic Program, are accepted to impact Student Satisfaction and thereby stimulate positive word-of-mouth behavior regarding their university The techniques used for data analysis include descriptive statistics of the survey sample, evaluation of the reliability of the Cronbach’s Alpha scale, testing the scale through Confirmatory Factor Analysis (CFA), testing the model through Structural Equation Modeling (SEM), and checking the reliability of estimates in the research model using the Bootstrap method The findings from Chapter 4 will serve as a basis for Chapter

5, which will propose recommendations to help the university enhance student satisfaction with the services provided, thus promoting their positive word-of-mouth behavior.

CONCLUSION AND MANAGEMENT IMPLICATIONS

Research discussions

This research explores the key factors influencing student satisfaction and its impact on positive word-of-mouth (WOM) behavior By emphasizing the importance of student experience, the author has meticulously crafted a research model derived from prior studies, which encompasses 33 variables categorized into seven primary factors.

This study utilizes Structural Equation Modelling (SEM) to analyze the significant impact of various factors on student satisfaction The SEM analysis strongly supports all six research hypotheses, highlighting the importance of administrative and staff support, lecturer effectiveness, university brand image, adequate tangible facilities, and the overall educational program in enhancing student satisfaction.

The study emphasizes the crucial role of student satisfaction in fostering positive word-of-mouth behavior among students It reveals a significant positive correlation between student satisfaction (SS) and the likelihood of engaging in positive word-of-mouth (WOM) activities In essence, when students are satisfied, they are more inclined to recommend their university to others, which can help attract new students.

In a formal research study, the author surveyed 264 valid respondents, specifically targeting students enrolled at the University of Economics and Law Utilizing IBM SPSS Statistics 20 for data analysis, the author identified significant correlations among the variables in the study model based on the survey findings.

Implications

5.2.1 Implications for Administrative & Staff Support

Administrative and Staff Support at universities play a crucial role in managing administrative tasks and assisting students with various issues, such as scheduling, tuition fees, and documentation These staff members are often the primary point of contact for students seeking services, making their effectiveness vital for overall student satisfaction To enhance the impact of Administrative and Staff Support, universities should consider implementing strategies that foster better communication, streamline processes, and provide comprehensive training, ultimately leading to improved student experiences and satisfaction.

To enhance efficiency and reduce costs, universities should streamline administrative processes by eliminating unnecessary steps, allowing students to navigate procedures more swiftly By reviewing existing processes and gathering feedback from both students and administrative staff, institutions can implement continuous improvements Furthermore, investing in automation software for repetitive tasks like student registration, course scheduling, document management, and fee collection is essential for optimizing operations.

Administrative and Staff Support serve as the initial contact for students seeking assistance, making positive interactions crucial for enhancing student satisfaction Universities can foster these interactions by recognizing and rewarding staff who improve student experiences, prioritizing student satisfaction in their mission, and conducting regular performance evaluations Additionally, establishing clear communication channels will enable students to effectively voice their concerns and receive the support they need.

Enhancing student satisfaction necessitates collaboration among various university departments Administrative and staff support must closely coordinate with academic advisors, lecturers, and other key stakeholders to effectively meet student needs.

Enhancing the quality of university faculty is vital for elevating the student educational experience and boosting overall satisfaction To achieve this, universities should implement diverse strategies, including comprehensive training programs, improved instructional methods, and effective communication with students.

Improving teaching quality is essential for universities, which should implement strict minimum requirements for lecturer recruitment to maintain high standards Providing educators with opportunities for professional development, such as obtaining additional certifications and participating in specialized training and workshops focused on teaching methods, is vital Furthermore, encouraging faculty to engage in research and publish scholarly work in their fields can significantly enhance their expertise and effectiveness in the classroom.

Transitioning to online teaching is crucial for universities, which should provide training sessions and resources to support lecturers in adapting from traditional methods This training should cover instructional design, the use of educational technology, and strategies to engage students actively in the online learning environment.

Promoting collaboration and knowledge-sharing among professors is essential for enhancing educational practices Universities can facilitate this by organizing workshops, gatherings, and discussions that allow educators to exchange teaching strategies and insights By cultivating a supportive environment, institutions can inspire teamwork, drive innovation, and motivate educators to refine their instructional methods.

Acknowledgment and accolades serve as a source of motivation Recognising lecturers for their exceptional teaching accomplishments and their positive impact on the educational setting promotes a culture of ongoing enhancement

Implementing robust assessment procedures is essential for enhancing educational quality By integrating student feedback, peer reviews, and self-assessment into the evaluation framework, these assessment activities can provide lecturers with critical insights for ongoing improvement.

These strategies collectively contribute to the continual enhancement of the teaching staff, resulting in a more positive educational experience for students and increased satisfaction levels

To cultivate a strong and positive university’s image, a multi-faceted approach encompassing strategic communication, academic excellence, and commitment to quality is recommended

Revamp the university's branding by updating its logo, color palette, typography, and visual elements for consistency across all communication platforms Leverage digital channels, including social media, email marketing, and SEO, to effectively engage diverse target audiences and enhance the university's reputation By strategically utilizing these platforms, the university can strengthen its brand presence and foster meaningful connections with stakeholders.

Effectively showcasing a university's accomplishments is crucial for enhancing its credibility and appeal By emphasizing academic programs, faculty expertise, and notable alumni, the institution can strengthen its value proposition Additionally, strategically highlighting university rankings, accreditations, and teaching excellence awards helps build trust and attracts top-tier students.

Collaborating with research organizations, government agencies, and relevant entities offers a valuable opportunity to enhance the university's reputation Engaging in joint research projects and internship programs not only enriches the educational experience but also equips students with access to advanced research, practical skill development, and improved job prospects after graduation.

Ensuring the fulfillment of commitments related to infrastructure development and high-quality training is essential for student satisfaction during the practical implementation phase of the program By consistently delivering on these promises, institutions can build trust among students, resulting in heightened satisfaction and positive word-of-mouth referrals.

Improving university facilities is essential for fostering an environment that supports effective teaching, learning, and research The state of physical infrastructure greatly influences student satisfaction during their academic experience To tackle this issue, universities must consistently invest in the enhancement, renovation, and upkeep of their facilities, focusing on upgrading older structures to guarantee safety and functionality.

Integrating advanced technological tools like multimedia equipment and smart projectors into classrooms boosts student engagement and aligns with contemporary teaching methods Furthermore, investing in the construction and modernization of laboratories and research facilities significantly aids students in their academic and research endeavors.

Research Contribution

Student satisfaction is a key indicator of a university's commitment to quality education and plays a crucial role in long-term success and sustainability High levels of student contentment not only reflect the institution's ability to provide excellent education and services but also encourage students to become advocates, boosting enrollment rates To enhance student happiness, universities should consider revising instructional programs, upgrading facilities, and improving teacher quality This research adds valuable insights to the field of student satisfaction and its impact on positive word-of-mouth in education.

This research builds on existing insights into student satisfaction and positive word-of-mouth (WOM) in education by creating a comprehensive framework that links student perceptions to satisfaction and WOM behavior Conducted in two phases—preliminary and formal—the study evaluates the relevance of these theoretical models in the Vietnamese context The findings indicate that these established frameworks are valuable and applicable within Vietnamese universities.

The research identifies key factors that affect student satisfaction and influence word-of-mouth (WOM) behavior By examining these elements, the author suggests practical strategies for universities to enhance student experiences, ultimately fostering positive WOM among students and creating a framework for ongoing improvement.

Limitation

This study provides valuable insights but recognizes its limitations, particularly in its focus on students from the University of Economics and Law, which may restrict the applicability of the findings to the wider Vietnamese university context To enhance the research, future investigations should consider a broader range of universities to obtain a more diverse and representative sample of Vietnamese students.

To achieve a more comprehensive understanding of student satisfaction, future research should expand its participant pool to include alumni and students involved in dual work-and-study programs, in addition to current students This broader approach will yield a richer insight into the diverse experiences and satisfaction levels of the student body.

The study utilized quantitative data from surveys, which, while valuable, may limit the exploration of unanticipated factors Future research should consider integrating qualitative methods, such as interviews, to gain deeper insights into student experiences Furthermore, enhancing surveys with open-ended questions alongside closed-ended options would enable students to elaborate on their experiences, contributing to a more comprehensive understanding of student satisfaction.

In Chapter 5, the author presents conclusions and evaluations derived from quantitative analysis, comparing findings with prior research and recommending actionable solutions for UEL to enhance value for target customers and support their sustainable development during challenging times Furthermore, this chapter addresses the study's limitations and proposes new avenues for further exploration of its practical implications.

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OFFICIAL SURVEY

The impact of key aspects of service quality on student satisfaction and subsequently influence positive word-of-mouth behavior among students at the University of Economics and Law

Thank you for your interest in my survey I am currently conducting a study named

"The Influence of Key Elements of Service Quality on Student Satisfaction and Subsequent Impact on Positive Word-of-Mouth Behaviour among Students at the University of Economics and Law."

Your feedback is essential for enhancing my research on services and improving student satisfaction, which will ultimately lead to positive recommendations I greatly appreciate your involvement and kindly ask you to complete this survey Rest assured, all collected data will be kept confidential and secure.

Thank you very much for your time and support!

Please indicate your response by marking the appropriate checkbox

Question 1 Are you a student at the University of Economics and Law?

 No => End the survey  Yes=> Continous

Question 2 What is your gender?

Question 3 What is your academic year?

Question 4 What is your major?

Please indicate your level of satisfaction by ticking the appropriate box for the following statements:

(1 - Strongly Disagree, 2 - Disagree, 3 - Neutral, 4 - Agree, 5 - Strongly Agree)

Order Criteria mearsure RATING SCALE

I ADMINISTRATIVE AND STAFF SUPPORT (OF)

Members of the administrative and support personnel always have a positive attitude while interacting with students

The administrative and staff support team is reliable since they consistently complete their tasks when they say they would

When interacting with students, administrative and staff support personnel always use polite and respectful language

4 Administrative and staff support often shows care and endeavours to solve student difficulties when they confront academic or administrative challenges

Administrative and staff support personnel have extensive understanding of the system/procedures

Administrative and staff support personnel ensure that academic records are precise and easily accessible

1 Lecturers' expert knowledge fulfils students' informational demands

The lecturers' methods for education are straightforward and simple to comprehend

Lecturers have the ability to capitalise on the proactive and positive attitudes of learners

The instructors commit additional time beyond usual hours to provide support to students in their academic pursuits

Lecturers prioritise developing a professional mindset among college students

The development of students' capacities for independent learning is the top priority of lecturers

Information on graduation requirements, final exam policies, and test policies relevant to certain courses are either given to students or conveyed to them

The course requirements and learning outcomes for your chosen major are clearly noticeable to students

The amount of knowledge in both foundational and specialized subjects is reasonable

4 The courses and lectures are regularly revised to reflect current events

The information provided is adequate to serve as a basis for further courses or self-learning by the learner

Curriculum designed to foster students' ability to independently learn and do thorough research

The classroom is completely furnished with practical and useful educational tools

2 The university's classrooms are spacious pleasant, and have good ventilation

The number of students in a class are reasonable, which allows students can concentrate effectively during lectures

The library meets the reading and borrowing requirements of students in an efficient manner

Students' information search requirements are efficiently served in the computer room located within the library

The space for independent study and relaxation at the university is abundant and conveniently accessible

1 I have always had a good impression of this university

2 In my opinion, this university has a good image in the minds of consumers

3 I believe that the university has a better image than its competitors

4 In general, I have a positive image from this University

1 My decision to choose it were correct

VII WORD-OF-MOUTH (WOM)

1 If somebody ask me surely, I'll recommended my university

2 If the opportunity arose, I would make positive comments to family and friends

3 I would encourage others to study at this university.

RESULTS DATA ANALYSE

1 Analysis describing survey sample characteristics Gender

Scale Variance if Item Deleted

Cronbach's Alpha if Item Deleted

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Scale Variance if Item Deleted

Cronbach's Alpha if Item Deleted

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Cronbach's Alpha if Item Deleted

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Cronbach's Alpha if Item Deleted

Scale Variance if Item Deleted

Cronbach's Alpha if Item Deleted

Scale Variance if Item Deleted

Cronbach's Alpha if Item Deleted

Kaiser-Meyer-Olkin Measure of Sampling

Factor Initial Eigenvalues Extraction Sums of Squared Loadings Rotation

Extraction Method: Principal Axis Factoring a When factors are correlated, sums of squared loadings cannot be added to obtain a total variance

Extraction Method: Principal Axis Factoring

Rotation Method: Promax with Kaiser Normalization a Rotation converged in 6 iterations

Kaiser-Meyer-Olkin Measure of Sampling

Factor Initial Eigenvalues Extraction Sums of Squared Loadings Rotation

Extraction Method: Principal Axis Factoring a When factors are correlated, sums of squared loadings cannot be added to obtain a total variance

Extraction Method: Principal Axis Factoring

Rotation Method: Promax with Kaiser Normalization a Rotation converged in 6 iterations

CR AVE MSV MaxR(H) SS TANG OF LEC PRO

Regression Weights: (Group number 1 - Default model)

Standardized Regression Weights: (Group number 1 - Default model)

Correlations: (Group number 1 - Default model)

Regression Weights: (Group number 1 - Default model)

Standardized Regression Weights: (Group number 1 - Default model)

Squared Multiple Correlations: (Group number 1 - Default model)

Standardized Regression Weights: (Group number 1 - Default model)

Parameter SE SE-SE Mean Bias SE-Bias