The roles of student trust, identity and commitment in the relationship between university reputation and behavioral intention

Feito et al. (2020), university reputation was impacted by performance, innovation, citizenship, services, governance, and workplace climate. In summary: university reputation has been understood as having prestige within the community, being a well- respected university, and positively influencing the value of a student’s degrees. 2.2.1. Student guidance Plewa et al. (2016) indicated that those who provide student guidance possess the following qualities: they understand student needs, are available for consultation when needed, make interacting with students easy, provide support to help students succeed academically, care about students’ experiences, are good at communicating about issues that concern students, and have useful knowledge of educational systems and procedures. 2.2.2. Social contributions The components of social contributions are whether the university strongly supports the community, has a positive social influence, and 6 helps graduates secure high-quality jobs. 2.2.3. Environment The research of Esangbedo and Bai (2019) added several factors for academic environments: being a space in which learners can mingle with other cultures, university ability to protect students from risk, and acting as a social space dedicated to learning. In general, the components of a good environment are (1) a safe, clean, and pleasant environment for students to learn in, (2) diverse cultural backgrounds, and (3) international renown. 2.2.4. Leadership: the quality of leadership expresses having excellent leaders, prestigious professors, a clear vision for development, the latest technology, and the ability to recognize and exploit market opportunities (C. Chen and Esangbedo, 2018; Fombrun et al. 2000; Esangbedo and Bai, 2019). 2.2.5. Funding Funding is related to the income of parents/sponsors, tuition, and scholarships. In summary, funding is indicative of the cost of living at a university, as well as its finances, scholarships, research grants, and tuition fees. 2.2.6. Research and development R&D can be expressed as a link between industry and the university in the form of key projects, as is evident in academic publications. Finally, research and development affect a university’s technological trends, key national projects, laboratory equipment, and library. 7 2.3. Student trust The study of Liu et al. (2019) indicated that trust is to possess a high level of confidence in partners, to accept that partnership will put an organization’s tendencies in a pivotal position, and to be willing to make essential contributions to the partnership. Finally, in the research of Rather (2018), factors of trust were whether a brand was trusted, whether it was perceived as honest, whether it was perceived as safe, and whether customers relied on it. 2.4. Student Identity University identity refers to learners who feel that they belong to (identify with) the evaluation of a university’s performance (Mitchell et al., 2018). This description demonstrates both a useful element and an awareness of the importance of a university. Learners who feel accepted, and who seem to be at a university where they belong, may have an emotional connection with their university. 2.5. Student commitment Commitment is one of the essential concepts in marketing research and is rooted in the social exchange theory. Rather (2018) and Moorman et al. (1992) defined commitment as “an enduring desire to maintain a valued relationship.” Some researchers have confirmed commitment as the essential determinant of creating and sustaining long-term relations between trading companions (Morgan and Hunt, 1994; Rather, 2018). Based on the literature, the research defined customer commitment as a commercial partner’s willingness to maintain a significant and lasting connection (Morgan and Hunt, 1994; Rather, 2018). 2.6. Behavioral intention 8 The behavioral component consists of managing the behavior of the employee. Given the current demand for economic responsibility and the increased focus on customer choice, universities are considering students and staff as clients. Consequently, to maintain the desired level of service quality, the relationship between administrative staff and academics has become more structured. Thus, the behavior of university administrations frequently resembles that of a business organization (Nuraryo et al., 2018). 2.2. The research model and hypotheses 2.8.1. Factors affecting university reputation “Hypothesis 1 (H1): Social Contributions (SCN) have a positive impact on University Reputation (UR).” “Hypothesis 2 (H2): Leadership (LE) has a positive impact on University Reputation (RE).” “Hypothesis 3 (H3): Environment (EN) has a positive impact on University Reputation (UR).” “Hypothesis 4 (H4): Funding (FU) has a positive impact on University Reputation (UR).” “Hypothesis 5 (H5): Research and Development (RD) have a positive impact on University Reputation (UR).” “Hypothesis 6 (H6): Students Guidance (SG) has a positive impact on University Reputation (UR).” 2.8.2. The roles of student trust, student identity, and student commitment “Hypothesis 7 (H7): There is a positive impact between University Reputation (UR) and Student Commitment (SC).” “Hypothesis 8 (H8): There is a positive impact between University 9 Reputation (UR) and Student Trust (ST).” “Hypothesis 9 (H9): There is a positive impact between Student Trust (ST) and Student commitment (SC).” “Hypothesis 10 (H10): There is a positive impact between Student Identity (SI) and Student Commitment (SC).” “Hypothesis 11 (H11): There is a positive impact between Student Identity (SI) and Behavioral Intention (BI).” “Hypothesis 12 (H12): There is a positive impact between Student commitment (SC) and Behavioral Intention (BI)” Based on the literature review, a model with twelve hypotheses is designed to investigate the research problems and develop the hypotheses. Figure 2.9—the dissertation model—presents the recommended model for this research into students’ intentions when it comes to their choice of master’s programs in Vietnam. Figure 2.9. The theoretical model (Source: Author) CHAPTER 3. METHODOLOGY 3.1. Introduction 10 In a dissertation such as this one, where a large number of research hypotheses require investigation, the appropriate methodology would typically be quantitative analysis. However, the concepts in the model are new in Vietnam, and consequently, they must be evaluated and designed to suit conditions specific to Vietnam. Hence, qualitative research would also be an appropriate methodology. Given the above, a mixed method, in which qualitative research adjusts the scale and quantitative research tests the hypotheses, is the most suitable research strategy for this study. This chapter aims to introduce the research methods and the approaches employed to examine university reputation and behavioral intention in Vietnamese higher education: specifically, the roles of student trust, student identity, and student commitment in student choices of master’s program. This chapter provides some general information about the system researched, the research approach, and measurement, sampling, data collection, and data analysis procedures. To best achieve the dissertation’s aim, Chapter 3 is divided as follows: - An overview of the research process; - The scale design for research concepts tested by the research model; - The design of a questionnaire for the research program and a survey to assess the scale. 3.2. The research process The research process included the following activities: (1) literature review, (2) group discussion (in-depth interviews and seminars), (3) consultations with experts, (4) establishing a scale. 3.3. Sample and data collection 11 Quantitative research was conducted the sample consisted of 1,538 individuals who had graduated from Vietnamese universities, 737 (47.9%) were men and 801 (52.1%) were women. 3.4. PLS-SEM This study aims to explore the relationship between university reputation and behavioral intention. With the help of the survey’s seven-point Likert scale (higher numbers indicate greater agreement), we verify our model with two official datasets for the relationship between UR and BI in Vietnamese higher education in Vietnam. Our dataset had eleven factors: six independent factors, four intermediate factors, and one dependent factor. There were 1,538 individuals and 49 items captured in the data. Adanco software was used as the data processing and statistical analysis software. The scale's reliability and validity were checked by Cronbach's alpha ( ), average variance extracted ( ), and composite reliability (Pc). SEM was utilized to examine the model's hypotheses (Hair et al., 2017; Hair Jr. et al., 2016; Henseler et al., 2016; Latan and Noonan, 2017; Sarstedt et al., 2019). A Cronbach’s alpha coefficient higher than 0.6 would guarantee the scale's reliability (Nunnally and Bernstein, 1994). Pc is better than 0.6 and must be greater than 0.5. PLS-SEM was used on the theoretical framework. This method can manipulate many independent factors, even when multicollinearity exists. PLS can be performed as a regression model, predicting one or more dependent factors from a set of one or more independent factors, or it can be completed as a path model. PLS can connect the set of independent factors to multiple dependent  vc  vc  12 factors (Hair et al., 2017; Hair Jr. et al., 2016; Henseler et al., 2016; Latan and Noonan, 2017; Sarstedt et al., 2019). CHAPTER 4. RESULTS 4.1. Introduction Chapter 4 describes and investigates the data used in this dissertation, beginning with internal consistency and convergent validity. The next sections display the empirical results of testing the hypotheses developed in Chapter 3, including the results of the direct regressions and the mediated path regressions that are treated by Adanco software. The practical results are arranged in order from the first hypothesis to the twelfth. Lastly, the test results of variables and hypotheses are listed. Not only is the data described, but each important dissertation is also explored. 4.2. Internal consistency and convergent validity In this study’s model, convergent validity was examined through or Cronbach’s alpha. and were the measures of reliability, as Cronbach’s alpha often undervalues scale reliability (Hair et al., 2017; Hair Jr. et al., 2016; Latan and Noonan, 2017; Sarstedt et al., 2019). Nevertheless, according to Hair et al. (Hair et al., 2017; Hair Jr et al., 2016), Cronbach’s alpha and Pc values should be higher than 0.60, and the index should be higher than 0.50 for the validation of construct reliability. The result of construct reliability and validity are shown in Table 4.1, below. Table 4.1. Internal consistency and convergent validity c  c  vc  vc  13 Factor Cronbach's Alpha rho_A Pc Decision SCN 0.8002 0.8291 0.8576 0.5494 Accepted EN 0.7472 0.7939 0.8246 0.4905 Accepted LE 0.8030 0.8151 0.8641 0.5615 Accepted FU 0.6908 0.7618 0.7833 0.4389 Accepted RD 0.7780 0.8389 0.8408 0.5204 Accepted SG 0.7400 0.7676 0.8193 0.4789 Accepted ST 0.8788 0.8899 0.9167 0.7337 Accepted SI 0.6630 0.7205 0.7945 0.4961 Accepted SC 0.8552 0.9299 0.8913 0.6270 Accepted BI 0.8100 0.8183 0.8870 0.7236 Accepted UR 0.5941 0.7239 0.7790 0.5558 Accepted , , and Source: Calculated by the author These results demonstrate that the model is internally logical. To investigate whether these factor indicators demonstrate converging validity, Cronbach’s alpha was calculated. In Table 4.1, it can be seen that all of the factors are reliable (>0.60), and > 0.5 (Wong, 2013). Factors such as EN, FU, and SG had < 0.5, but the values of and Cronbach’s alpha were good, so EN, FU, and SG were accepted. 4.3. Collinearity issue To assess collinearity issues with the inner model, the latent variable scores can be used Variance Inflation Factor (VIF), a VIF of 5 or lower is needed to avoid the collinearity problem (Hair et al., 2017). 4.4. The fitness of the structural model vc   2 2 1 1 i x xk k                    2 1 2 2 1 1 + 1 ii c i ii i                  2 1 2 2 1 1 + 1 ii vc i ii i                vc  vc  c  14 Based on the above review of literature and methodology, this model with twelve hypotheses is established to analyze the research problems and refine the hypotheses in Figure 4.1. 15 Figure 4.1. Model Testing and Analysis 16 Source: Calculated by the author PLS-SEM results in Table 4.5 indicate that the model fits with the analyzed data (Wong, 2013). Behavioral Intention was modified by SI and SC by about 36.8%. Six factors affected UR by about 51.5%. Table 4.5. Measurement of PLS-SEM SRMR 0.0697 Factor R Square R Square Adjusted d_ULS 6.204 BI 0.0871 0.0865 d_G1 2.164 SC 0.0227 0.0220 d_G2 1.734 SI 0.0288 0.0275 Chi- Square 14,104.711 ST 0.3875 0.3867 NFI 0.622 UR 0.5154 0.5135 Source: Calculated by the author PLS-SEM outcomes indicated that the model was fit with data analysis (Hengky Latan and Richard Noonan, 2017; Henseler et al., 2016) in Table 4.5. 4.5. Stability of parameter estimates Table 4.6. Path coefficients Hypotheses Beta SE T-value P Findings EN  UR (H3) 0.089 0.024 3.700 0.005 Supported FU  UR (H4) 0.150 0.028 5.361 0.000 Supported LE  UR (H2) 0.265 0.027 9.830 0.000 Supported RD  UR (H5) 0.104 0.022 4.714 0.000 Supported SC  BI (H11) 0.597 0.017 35.135 0.000 Supported SCN  UR (H1) 0.237 0.025 9.464 0.000 Supported 17 SG  UR (H6) 0.138 0.024 5.733 0.000 Supported SI  BI (H12) 0.107 0.021 5.110 0.000 Supported SC  SI (H10) 0.151 0.026 5.788 0.000 Supported ST  SC (H9) 0.075 0.015 4.980 0.000 Supported UR  SC (H7) 0.132 0.021 6.281 0.000 Supported UR  ST (H8) 0.295 0.025 11.808 0.000 Supported Source: Calculated by the author In the PLS-SEM investigation, the factors correlated with UR and BI through ST, SI, and SC (p < 0.05). The most significant determinant of UR was Leadership, which had a Beta equal to 0.265. The most significant determinant of BI was Student Commitment, the Beta of which equaled 0.597. 4.6. Discussion From the researches of Esangbedo and Bai (2019), Chen and Esangbedo (2018), and Plewa et al. (2016), this research proves six factors influence the university reputation such as contributions, environments, leadership, funding, R&D, and student guidance through H1 to H6. From the researches of Keh and Xie (2009), Rather (2018), Liu et al. (2019), and Nuraryo et al. (2018), this research prove the roles of student trust, student identity, and student commitment in mediating university reputation and student behavioral intention through H7 to H12 in the framework of Vietnam education. 18 CHAPTER 5. CONCLUSIONS, DISCUSSION, AND MANAGERIAL IMPLICATIONS 5.1. Conclusions The main purpose of the dissertation was to develop and test a model of the relationship between university reputation and behavioral intention in higher education that was based on signal theory and the theory of planned behavior (TPB). According to the TBP described by Fishbein and Ajzen (1977) and Quintal et al. (2010), emotional and psychological reputation, as affability and ability, serves specific functions for individuals since it is nearer to how the general public ordinarily thinks while assessing a university. Reputation has become essential for higher education institutes, and universities have been working hard to improve their reputations. As the higher education market had become more accessible, state schools that previously operated within comfortable national systems must now compete for resources. Creating and maintaining a sustainable reputation in higher education is significant, but it does guarantee inclusive and equitable education or study opportunities for all. Signal theory supports hypotheses H1, H2, H3, H4, H5, and H6. This dissertation investigated the factors that influence UR, and it built and tested a model to explain the relationship between UR and BI in Vietnamese universities. UR was explored as a multidimensional construct. The influence of new dimensions—from ST to SC—was discovered alongside that of BI. This dissertation confirmed the reliability and validity of measurement scales, and it verified the relationship between constructs in the proposed research model (the factors that directly and indirectly 19 influenced university reputation and behavioral intention). The paper built, expanded, and measured elements of the roles of student trust (ST), student identity (SI), and student commitment (SC) in mediating the relationship between university reputation (UR) and behavioral intention (BI). The dissertation found evidence supporting the impact of these factors on both UR and BI. The final goal of the paper was to examine the moderating roles of student trust (ST), student identity (SI), and student commitment (SC) on relationships. These roles act as a bridge to connect university reputation (UR) and behavioral intention (BI). The theory of planned behavior was used to explain hypotheses H7, H8, H9, H10, H11, and H12 in the research model. A mixed research method (qualitative and quantitative) was used for this paper. Qualitative research was conducted on four groups. The authors collected 61 comments, conducted group discussions with four groups (61 individuals in total), and performed in-depth interviews with nine economic, educational, and management specialists to validate the explored categories. Expert research helped adjust the measurement scales to match the research context. These components have been the basis for the development of measurement scales for quantitative research. Before the quantitative study was conducted, the expert research was performed immediately after the exploratory study to evaluate the ambiguity, redundancy, content validity, and face validity of the scales. The results of the expert research were scales used in quantitative research. Quantitative research was conducted with a sample of 1,538 respondents. The purpose of the quantitative research was to confirm the reliability and validity of measurement scales and verify the relationship between constructs in the proposed research model. 20 5.2. Key Contributions The dissertation determined the factors affecting university reputation and the roles of student trust, student identity, and student commitment to the basis of testing studies, the relationship between university reputation, and behavioral intentions. With the link between university reputation and behavioral intention, it also developed the model in Vietnamese higher education the researches of Esangbedo and Bai (2019), Chen and Esangbedo (2018), Plewa et al. (2016) Keh and Xie (2009), Rather (2018), Liu et al. (2019), and Nuraryo et al. (2018). This dissertation has aimed to improve our thoughtful of university reputation and its relationships in the framework of Vietnamese higher education. I joined Chen and Esangbedo (2018) and others (e.g., Keh and Xie, (2009), Rather (2018), Nuraryo et al. (2018), and Harahap et al (2018) in conflict for the necessity to realize reputation as a continuous rebuilding and student trust, student identity, and student commitment as mediating university reputation and student behavioral intention. Specifically, I stress that the reconstruction of reputation rests upon those organizational features that an organization and its stakeholders consider essential. The current study, therefore, contributes to the extant research that considers reputation as continuously (re)constructed in discursive practices. This systematic method has allowable me to identify university reputations as impacted by six factors. Implications for domestic manager The theoretical framework of behavioral intention also suggests significant management implications for Vietnamese universities. The globalization of education offers opportunities to select master’s 21 programs in Vietnam. This implies that managers should enhance their universities’ reputations in the target education market. Domestic universities can also recognize this is an opportunity for the Vietnamese educational market to find a place in the hearts of students, as well as a chance for Vietnamese students to use Vietnamese educational markets. This statement follows from the evidence of the roles of student trust, student identity, and student commitment in mediating the relationship between university reputation and behavioral intention: confirming the roles of these factors simultaneously shows that Vietnamese students think of and react to domestic universities. They are willing to support domestic universities in the educational market; they are also interested in the existence of the competitive pressure that domestic universities must face as the country opens the door to a more integrated global economy. Managers of universities in Vietnam should closely attend their reputational development. Implications for university managers Research results show a series of links starting at university reputation (UR), passing through student trust, student identity, and student commitment, and ending at the behavioral intentions of students enrolling in courses. In light of these links, universities should follow the below recommendations and promote the listed factors. University Reputation (UR) was significant to universities. It acted as a competitive advantage, satisfying and engaging society's expectations, and was sufficient for maintenance throughout the whole university. Research results indicate that Social Contributions, Leadership, Environment, Funding, R&D aspects, and Student Guidance are essential factors for determining a university's reputation, and they have a strong influence on the reputation of organizations. As a result of data 22 analysis, six hypotheses were accepted. Six components contributed significantly to the university's reputation in order of importance: (1) Leadership, (2) Social Contributions, (3) Funding, (4) Student Guidance, (5) R&D aspects, and (6) Environment. The Leadership aspect greatly attracted students. This aspect played an important role in affecting university reputation. Universities should have excellent leadership, employ prestigious professors, have a clear vision of development, use the latest technology, and recognize and exploit market opportunities to help students develop this ability in the future. The second was Social Contributions. This factor affected university reputation, so the universities should strongly support the community, have positive social influences, help graduates to obtain better jobs, equip student workplaces well, and positively influence the value of students’ degrees to direct them to the good things in their life. Funding also affected university reputation, so universities should offer a reasonable cost of living, reduce financial worries for students, give scholarships to students, offer grants for research conducted by students, and maintain competitive tuition fees. The fourth factor was Student Guidance. To take advantage of this, universities should understand student needs, consult with students when they need it, make student–university interactions easy, respect student freedom and privacy, and be available for consultation and vocational guidance. The fifth was Research and Development. To promote this factor, universities should follow technological trends in conveying knowledge, take part in key national projects, be innovative in their publications, be in good working condition and properly maintained, and keep the library provided with up-to-date books and sources. 23 The last factor was the Environment. To promote this factor, universities should create a safe, clean, and pleasant environment for students to learn in, foster cultural diversity, establish international renown, create visually appealing physical facilities, and maintain up- to-date university equipment. Furthermore, university