1 This paper is a pre-accepted version of: Schlesinger, W., Cervera, A., & Wymer, W. (2021). The influence of university brand image, satisfaction, and university identification on alumni WOM intentions. Journal of Marketing for Higher Education, available at https://doi.org/10.1080/08841241.2021.1874588 The influence of university brand image, satisfaction, and university identification on alumni WOM intentions ABSTRACT This study investigates the influence of university brand image, satisfaction, and alumni’s university identification on positive word-of-mouth (WOM) intentions. The model is tested using data collected from a sample of 1000 university alumni, an important and under- researched stakeholder group. A contribution is provided by enhancing our understanding of key under-researched relationships. University brand image was found to be a key driver of alumni positive WOM intentions, due to its direct and indirect influences. The study also identified the mediating roles of alumni’s university identification and satisfaction. The influence of university brand image on alumi WOM is partially accounted for through its influence on alumni satisfaction and alumni’s university identification. Keywords: brand image, university image, word-of-mouth, university identification, satisfaction, alumni. Introduction In a higher education context in an internationally competitive environment (Pyvis & Chapman, 2005), higher education (HE) development relies upon redefining and paying greater attention to building relationships with stakeholders (Drezner, 2018). Given the importance of stakeholder relationship management, it is surprising that relatively little research has focused on student stakeholders, and even less research on alumni stakeholders (Toledo & Luque, 2020). Barnard and Rensleigh (2008, p.433) noted that “the establishment and nurturing of mutually beneficial relations between a university and its alumni as a primary stakeholder group should be a top priority for any HE institution that wants to prosper and grow in a fast- changing and highly competitive market.” It is reasonable to believe that alumni who feel an attachment or identification with their university are more likely to volunteer or donate to support their alma mater. Furthermore, committed alumni may act as their university’s advocates and ambassadors by providing positive word-of-mouth (WOM) comments and referrals (Helgesen & Nesset, 2007; Pedro, da Costa & Nobre, 2020). A good deal of research in HE marketing has been performed on marketing communications (Foroudi et al., 2020; Yousaf, Mishra & Bashir, 2020). Much of this prior rearch has focused on the influence of university-disseminated communications on student choice. Although student choice is an important outcome variable, WOM is also another important outcome variable. Prior research has found that WOM is an important influencer of university brand attitudes (Casidy & Wymer, 2015). Some researchers highlight the crucial role of WOM in evaluating HE institutions’ marketing effectiveness (Herold, Tarkiainen & Sundquist, 2016; Wilkins & Huisman, 2015). Consequently, an earlier review of the HE literature finds a need for more research on antecedents of WOM communications, identifying an important gap in the HE marketing 2 literature (Herold et al., 2016; Hemsley-Brown & Oplatka, 2006). Our study aims to help fill this research gap by examining several antecedents of alumni’s positive WOM. We examine the influence of alumni’s identification with their university on WOM. Prior consumer behavior research has found that customers are more likely to engage in supportive behaviors when they identify with an organization (Ahearne, Bhattacharya, & Gruen, 2005; Bhattacharya & Sen, 2003; Hong & Yang, 2009). The influence of individuals’ identification with their university is a potentially important construct which has been examined in a small number of studies using currently enrolled university students (Heffernan, Wilkins & Mohsin, 2018; Wilkins, Kratochvil, & Balakrishnan, 2016). We examine this construct’s influence on university alumni, another important stakeholder group. Another potential antecedent of alumni WOM is university brand image. There is a gap in the literature on the relationship between brand image and WOM (Ahemd & Spinelly, 2012, Popp & Woratschek, 2017). The relationship between the brand images of public institutions like universities and important outcome variables has been an under-research area (Wæraas & Solbakk, 2009; Watkins & Gonzenbach, 2013; Aghaz, Hashemi & Sharifi, 2015; Lafuente, Zorrilla & Forcada, 2018; Foroudi et al., 2020). Hence, our examination of the influence of university brand image on alumni WOM represents a another contribution of this study. Our study helps fill literature gaps and contributes to under-researched areas by examining the relationships among university brand image, alumni satisfaction, alumni university identification and positive WOM. Our findings enrich our understanding of the influence of a university's brand image on a loyalty behavior like WOM as well as our understanding the influence of satisfaction and identification on the relationship between brand image and WOM. 3 In the next section we will identify and define our focal constructs and present a set of hypothesized relationships. A model of the focal constructs’ inter-relationships is presented. Then, an empirical research study is reported to test our hypothesized relationships. Finally, we conclude with a discussion of our research findings, their managerial implications, and future areas of productive research inquiry. Literature Review MacKenzie (2003) admonishes researchers to clearly define the constructs they are investigating. He argues that a failure to define focal constructs is a major cause of poor quality research. Therefore, we will begin this section by defining our focal constructs. Then we will present a conceptual model, which we will later test in an empirical study. University Brand Image Organizational image is important because it allows members of an organization to compare their own perceptions of the organization with the assessments of external stakeholders (Dutton, Dukerich & Harquail, 1994). Conceptualizing image is a complex issue that has been accompanied with confusion because some scholars and practitioners interchangeably use the term to refer to organizational identity and to the organization’s reputation (Gotsi & Wilson, 2001). However, the differences between them cannot be ignored (Dutton et al., 1994; Aghaz et al., 2015). In this research, following the definitions developed by Aghaz et al., (2015), and Dutton et al., (1994), organizational image is conceptualized as a construct that is distinct from organizational reputation. A university’s brand image refers to how the university is comprehended by members of a target (stakeholder) group based on information group members have received about the university and their experiences with the university (Wymer, 2013). University image has 4 been shown to influence students’ supportive behavioural intentions (Sung and Yang, 2008), loyalty and student satisfaction (Casidy & Wymer, 2015; Heffernan et al., 2018). Nguyen et al. (2016) suggest that a strong HE brand signals the university's ability to fulfill student needs, engenders trust in its capacity to deliver the required services, and helps potential students make favorable academic and course decisions. Empirical studies (Ildamaria & Andrz, 2019; Pinar, Girard & Basfirinci, 2020; Foroudi et al., 2020; Hashim, Yasin & Ya´kob, 2020) suggest that, if effective, a successful HE branding strategy could improve university services, as well as attract and retain students. Despite the importance a favorable brand image has for higher education institutions, few studies have examined the perceptions of university alumni of their universities’ brand image (Schlesinger, Cervera & Pérez-Cabañero, 2017; Del Castillo, Blanco-González & González-Vázquez, 2019). University Satisfaction University satisfaction refers to alumni’s summary affective response to their university (Casidy & Wymer, 2015). This conceptualization of satisfaction is adapted to our study’s context (Giese & Cote, 2000). Satisfaction has been considered a focal construct in long-term relationships (Frasquet, Calderón & Cervera, 2012). The construct can also find appropriate application in higher education (Hartman & Schmidt, 1995; Borraz-Mora, Hernández & Melguizo, 2019). Most previous research measuring satisfaction in higher education collect data from current students and examines students’ satisfaction with their current university experience. This approach differs from the recommendations of Westbrook and Oliver (1991) who argue that satisfaction is a state that should be assessed after consumption of the service experience. 5 In this way, and according to Toledo & Luque (2020), we consider students´ satisfaction as a posteriori evaluative judgment of their entire university experience. In this regard, the definition of satisfaction proposed by Elliott and Healy (2001) and Toledo & Luque (2020) is adopted. It views alumni´ satisfaction as an attitude that results from the evaluation of prior experiences with their former university. Alumni´s University Identification The concept of organizational identification is derived from social identity theory (Stryker & Burke 2000), in which individuals integrate the organization’s image into their self-concepts. According to Bhattacharya and Sen (2003), the relationship between the company and its customers is explained by social identity theory (SIT) developed by Tajfel and Turner (1979). Social identity is the way individuals identify themselves with their perceptions of the social group with which they feel a belonging or identification. It serves as a base through which customers define themselves, identify with the company, and build a solid customer– company relationship according to the attractiveness of the offered social identity and the extent to which it satisfies one or more major self-definitional needs (Bhattacharya and Sen, 2003). The concept of social identity is well established and has been used to explain behavior in the fields of organizational behavior (Mael & Ashforth, 1992), group membership (Bhattacharya, Rao, & Glynn, 1995), and consumer brand loyalty (Homburg, Wieseke & Hoyer, 2009). Organizational identification is a specific form of social identification in which individuals define themselves in terms of their memberships of particular organizations (Mael & Ashforth, 1992; Marin & Ruiz, 2013). Alumni university identification refers to the degree to which alumni self-images are derived from their association with their alma mater (Mael & Ashforth, 1992; Hefferman et 6 al., 2018). Alumni identification with a prestigous university can be ego enhancing. Heffernan et al. (2018) provide empirical evidence that students can identify with two transnational HE partner institutions simultaneously; they also found that student-university identification was a significant predictor of student satisfaction, loyalty, and extra-role behaviours. Bhattacharya and Sen (2003) conceptualize student-university identification as the degree to which students perceive themselves and the university as sharing the same defining attributes and values, in an attempt to satisfy one or more personal definition needs. Through this identification, students are somewhat psychologically attached or bonded with their universities. Arnett, German, and Hunt (2003) found that those with more salient alumni- identities are more likely to be donors to their alma maters. Abdelmaaboud, Polo and Mahrous (2020) offer relevant insights into the research on identification with the university. Their results confirmed the significant influence of satisfaction on the identification with the university and on the supportive behaviors towards it. Hence, it is reasonable to believe that the level to which individuals identify with their universities influences their attitudes, intentions, and behaviors. Positive Word-of-Mouth (WOM) Intentions Positive WOM intentions refer to the extent to which alumni anticipate making positive comments about their alma mater (Casidy & Wymer, 2015). WOM is an influential source of interpersonal communication but is scarcely studied in the HE marketing field (Casidy & Wymer, 2015; Lee Ng & Bogomolova., 2020). The works of Heffernan et al., (2018) and Lee et al. (2020) call for additional research on WOM processes in higher education. This study uses positive WOM intentions (or simply WOM, for brevity) as an important HE marketing outcome. Behavioural intentions are strongly associated with 7 behaviours (Heffernan et al., 2018: Lee et al., 2020). Our use of WOM is consistent with the stream of research on influences of WOM (Brown, et al., 2005; Lu & Seock, 2008; Casidy & Wymer, 2015). In the literature, behavioral intentions have generally been examined within the scope of WOM or re-visiting intentions (Brown et al., 2005; Bujisic, Hutchinson & Parsa, 2014; Dedeoglu, et al., 2018). Given its importance to organizations, it is surprising to find relatively little prior research directed at understanding antecedents of WOM in higher education marketing (Gallarza et al., 2019; Heffernan et al., 2018; Lee et al., 2020). Hypotheses Development Now that the focal constructs have been identified and defined, it is appropriate to describe a conceptual model that will depict the predicted relationships among these constructs. The conceptual model to be tested in this study is presented in Figure 1. Figure 1 here. Referring to Figure 1, and starting with Hypothesis 1, we depict the university brand image as an antecedent of positive WOM intentions. Admirable or esteemed organizations are more likely to confer socio-psychological rewards to their members than less prestigious organizations (Sung & Yang, 2008). Self-concept research (Kunda, 1999) finds that people need self-enhancement and the maintenance of positive self-views that result in greater self- esteem. One way in which individuals can meet their self-esteem needs is by associating with prestigious brands or organizations (Casidy & Wymer, 2016). When members of a prestigious organization derive esteem rewards from their association with the organization, it is reasonable to believe they are motivated to engage in positive WOM (Ahmed & Spinelli, 2012). It is also reasonable to believe that comments to others that are favorable affirm the organization’s positive brand image, maintaining the 8 derived esteem rewards. Research that actually examines the influence of brand image on WOM is needed to add to our knowledge of this relationship (Ahmed & Spinelli, 2012; Pedro et al., 2020; Yousaf et al., 2020). Hence, the following hypothesis is presented. H1: University brand image has a positive influence on positive WOM intentions. It is reasonable to believe that university satisfaction will have a mediating effect on the influence of university brand image on WOM. University brand image influences alumni satisfaction with the university and, in turn, satisfaction influences WOM intentions. Brakus, Schmitt, and Zarantonello (2009) found that brand experience was an antecedent to satisfaction. Hence, to some degree, the brand image evokes a halo effect on student affect and behaviors. However, this halo effect is mediated by students’ satisfaction with their university experience. Because alumni are more likely to derive esteem-enhancement rewards as a university’s prestige increases, there is a positive bias operating on alumni perceptions of their alma mater. This argument is supported by prior research on prestigious brands (Casidy & Wymer, 2016). For example; Baek, Kim, and Yu (2010) found that brand prestige has a positive influence on perceived quality (a mediator) and purchase intention (a consequent). In HE, prior research has found that high-status universities experience very low student withdrawal rates (Select Committee on Education and Employment, 2001). The low dropout rates for prestigious universities implies higher university satisfaction rates (Guilbault, 2018). Several studies support a link between student satisfaction and WOM (Arif, Ylyas & Hameed, 2013; Ledden & Kalafatis, 2010; Lee et al., 2020). Santini, et al., (2017) and Schlesinger et al. (2017) provided a review of the literature on satisfaction in the educational context to gain a better understanding of its antecedents and outcomes. Their 9 results demonstrate that satisfaction and consequent behaviors are significantly influenced by the educational context. We predict that university brand image influences WOM, and that this influence is mediated by university satisfaction. Even though the association between brand image, satisfaction and customers’ identification with an organization has yet to be empirically tested, the findings from Mael and Ashforth’s (1992), Hong and Yang (2009), Pedro et al., (2020) and Bhattacharya et al. (1995) may be applied to predict this association. Therefore, we present our next hypothesis: H2: The influence of university brand image on positive WOM intentions is mediated by university satisfaction. Research relating to social and organization identity theories has found that the strongest individual-organization relationships occur when individuals identify with an organization that satisfies one or more of their self-definitional needs (Su, et al., 2016). In an educational context, Mael and Ashforth’s (1992) study on alumni university identification has found that alumni satisfaction with the institution is positively associated with organizational identification. Wilkins et al. (2016) and Abdelmaaboud et al. (2020) found that student identification with a university was related to both student commitment to study, student trust, and student satisfaction. However, discrepancy exists between these studies in the directionality of the relationship between satisfaction and identification. While some studies present satisfaction as an antecedent to identification (Arnett et al., 2003; Mael and Ashforth´s, 1992; Myers et al.,2016; Schlesinger et al., 2017), others present identification to satisfaction (Abdelmaaboud et al., 2020, Popp & Woratschek, 2017, Wilkins et al., 2016). This study proposes that students who are satisfied with their university are more likely to develop higher levels of identification with their institution. Based on the previous discussion, we hypothesize that: 10 H3: University satisfaction has a positive influence on alumni’s identification with their universities. According to social identity theory, consumers are willing to identify with companies with a positive image, which can facilitate their self-definition process and satisfy the need for self-distinctiveness and self-enhancement (Bhattacharya & Sen, 2003; Keh & Xie, 2009). Ahearne et al. (2005) found that a company’s image influences customer–company identification. They found that customers who identified with a company were likely to behave in ways that were beneficial to the company. Other research has found that customers who identified with companies were more likely to be loyal, manifested by positive WOM behaviors (Bhattacharya & Sen, 2003; Kim, Han & Park, 2001). Fombrun and Van Riel (2003) reported that the more customers identify with a company, the more likely they are to engage in supportive behaviors for the company, even acting as ambassadors for it. Bhattacharya and Sen (2003) and Popp and Woratschek (2017) also emphasized positive WOM as one of the key behavioral outcomes of customer–company identification. With respect to our HE context; Balaji, Roy, and Sadeque (2016); Schlesinger, Cervera, and Iniesta (2015); and Lee et al. (2020) found that students who have a strong university brand identification are more likely to spread positive messages about their universities. Given this prior research, it is reasonable to believe that university brand image will influence alumni’s university identification which will, in turn, influence WOM. Hence, we predict that alumni’s university identification will have a mediating effect on university brand image’s influence on WOM intentions. Thus, our next hypothesis: 11 H4: The influence of university brand image on positive WOM intentions is mediated by alumni’s university identification. To test the hypotheses derived from the conceptual model presented in Figure 1, we conducted a study that we report in the following section. Research Methods Measures Existing validated scales were used to measure our focal constructs. They were measured using an 11-point Likert scale (0 = completely disagree to 10 = completely agree). To test our research hypotheses, a two-step confirmatory modeling procedure using SEM was employed. In both steps, the procedure was based on a covariance structure approach using EQS 6.2 and SPSS 26.0. Our measurement scales are presented in Table 1. University brand image was measured through 4 items, adapted for our context from a scale by Nguyen and Le Blanc (2001). For alumni’s university identification, the scale we used was proposed by Mael and Ashforth (1992) applied to the university context and replicated by Caboni and Eiseman (2003) in the educational sector. The scale used to measure satisfaction has been used in the university context with appropriate reliability measures by Palacio, Díaz and Pérez (2002) and Helgensen and Nesset (2007). Lastly, prior research has operationalized WOM as intentions (Brown et al., 2006). WOM intentions were measured using behavioral-intention items, adapted to our study’s context, from Söderlund (2006) and Henning-Thurau et al. (2001). Table 1 here. 12 Questionnaire Development As the data were to be collected from alumni of two Spanish universities, and since all scales were originally written in English, we used translation and back-translation to ensure the equivalence of the Spanish version (Brislin 1980). Next, we carried out two pilot applications of the survey with 70 university graduates to verify that the questions were clear, to solve some drawbacks of the translation to Spanish and to check the time required to answer the questionnaire. Data collection was made through Computer Assisted Telephone Interviewing (CATI). Sample In the quantitative study, the target population consisted of alumni from two Spanish public universities. In order to be able to generalize these results, the study sample consisted of graduate students at two Spanish public universities belonging to the European Higher Education Area. This area arises as a result of the European convergence process (Bologna Declaration, 1999; European Commision, 2003). At the time of data collection, respondents had completed their university studies within the last three years. This condition ensured that they were able to offer a personal assessment as alumni while remembering their own university experiences as students and avoiding some potential biases derived from circumstances associated with a specific academic course. The universities provided the contact information of their alumni. The selection of sample units used simple random sampling with a 5 percent margin of error and a confidence levels of 95 percent (p = q = 0.5). The final sample consisted of 500 alumni from each university (N = 1000) in all areas of study (i.e., formal and applied sciences, health sciences, 13 social sciences, and humanities). The characteristics of our sample are presented in Table 2. The sample obtained represents the population under study. Table 2 here. Data Analysis In order to ensure comparability of universities chosen, an analysis of variance (ANOVA) was performed and revealed no statistically significant differences in the mean responses between university samples for any of the variables in this study. The descriptive statistics are presented in Table 3. Referring to Table 3, it appears that alumni were quite satisfied with their universities, with a mean of 7.6 out of 10. Alumni also gave favorable assessments of other variables such as university brand image (mean 7.2 out of 10) and positive WOM intentions (mean 7.7 out of 10). Compared to the means of other constructs, alumni’s university identification is moderately low (mean 4.3/10). Table 3 here. The data were analyzed using structural equation modelling (SEM) with EQS 6.1. software, following the two-stage method recommended by Anderson and Gerbing (1988). First, the measurement model was evaluated. Then, the structural model was evaluated which, in effect, tested the hypotheses presented previously. Measurement Model Evaluation To check psychometric properties of the measurement model, we carried out confirmatory factor analysis. Table 3 shows the high internal consistency of the constructs. Reliability 14 evaluation using Cronbach’s Alpha coefficients, Bagozzi and Yi’s (1988) recommended composite reliabilities (all values are higher than 0.8), and Fornell and Larcker’s (1981) average variance extracted index (higher than 0.7 for the three measures) yielded good results. The overall fit indices provide support for the fit of the proposed structural model (S- B 2 (115) = 1030.713 p< .000; BBNFI= 0.879; BBNNFI= 0.910; IFI= 0.921; CFI= 0.921; RMSEA= 0.068). All items load positively on their designated factors, and their estimates were positive and significant. The results of the confirmatory factor analysis are also reported in Table 3. For convergent and discriminant validity, the model was re-estimated following Bagozzi and Yi (1981). Evidence for discriminant validity of the measures was provided for a pair of factors (image with WOM) that have a high positive correlation. The S-B 2 value of the baseline measurement model was compared to that value for a measurement model constraining their correlation to equal one (Fornell & Larcker, 1981); the 2-difference test was significant between identification and WOM. The global support of this test suggests that the measurement model achieves discriminant validity. Findings The Structural Model Evaluation The hypotheses predict that satisfaction and alumni’s university identification mediate the relationship between university brand image and WOM intentions. The classical mediation test of Baron and Kenny (1986) is probably the most popular test for checking if a third variable exerts a mediation effect on the influence of an independent variable on a dependent one. Although Baron and Kenny’s test is very simple and intuitive, it has an important shortcoming: it involves regression equations and, thus, manifest variables have to be used instead of latent variables measured through indicators (Holbert & Stephenson, 2003). As 15 Baron and Kenny (1986) recognize, like any regression, their basic approach makes no particular allowance for measurement error, which is simply subsumed into the overall error term. Because of this shortcoming and consistent with the approach adopted in our research, we have used Structural Equation Modelling (SEM) to assess the classical mediation test of Baron and Kenny (1986), following the recommendations by Iacobucci, Saldanha and Deng (2007) and Sánchez-García and Currás-Pérez (2011). The procedure proposed by Baron and Kenny (1986) does not allow simultaneous testing of the effect of more than one mediational variable or the effect of one mediational variable on more than one dependent variable. The three models have been estimated using SEM (EQS 6.1), providing the standardized  of the three proposed relationships, on the dependent variable (WOM intentions), and reporting the standardized  of the direct relationship and the R2 of the dependent variable. Finally, the direct effect models have been compared with their respective simple mediation models, providing the effect size (ƒ 2) of the R2 variation (Cohen, 1988; levels around 0.02 denote weak effect size; higher than 0.15 denote a moderate effect size and 0.35 strong effect size) and if ‘full’, ‘partial’ or ‘no’ mediation exists). The results of the structural model evaluation confirm the importance of our model’s inter-construct relationships. The results of these estimations are shown in Table 4. Mediation test results confirm a partial mediation effect in all mediation models that have been estimated. Table 4 here. H1 predicted that university brand image influenced WOM intentions. The effect between university brand image and WOM resulted in a significant (p < 0.01) standardized coefficient of 0.51. A standardized path coefficient greater than 0.50 is considered evidence 16 of a strong effect (Ellis 2010; Galán, Galera & Wymer, 2013). Hence, H1 is supported and the influence of university brand image on WOM is a strong effect. According to the results of our mediation tests (Table 4 and Figure 2) the effect of university image on WOM is partially mediated by satisfaction (H2) and identification (H4). H3 is also confirmed, supporting the hypothesis that satisfaction is an antecedent of alumni’s university identification. Figure 2 here. Discussion Our results offer relevant insights into the the body of knowledge on alumni-university relationships (Mael & Ashorth, 1992; Toledo & Luque, 2020) and specifically in emerging research on identification with the university (Abdelmaaboud et al., 2020; Wilkins et al., 2016) as well as alumni and WOM (Casidy et al., 2015; Pedro et al., 2020). This study suggests that a social identification perspective can integrate with a social identity theory approach to enhance alumni supportive behaviors. This study demonstrates this by developing and testing a broader model that integrates identification with other variables - satisfaction and university image- as antecedents of alumni’s loyalty intentions as WOM. The results also show that identification, satisfaction, and university brand image are key factors in influencing alumni WOM intentions. Overcoming previous inconsistent considerations of the relationship between identification and satisfaction (Abdelmaaboud et al., 2020; Popp & Woratschek, 2017), this study provides new results in line with previous findings that confirmed the significant influence of alumni satisfaction on identification (Arnett et al., 2003; Mael and Ashforth´s, 1992; Myers et al.,2016; Schlesinger et al., 2017). Moreover, our comprehensive integration 17 of university image, identification, and satisfaction into a framework of influencers of WOM intentions extends previous findings from Abdelmaaboud et al. (2020) and Popp and Woratschek (2017). In these studies, the authors assume that satisfaction mediates the effect of identification on loyalty. They pointed out that the effect of identification on loyalty does not necessarily have to be mediated by satisfaction, but could also be a direct effect. By considering this additional direct link in our conceptual model, we demonstrate the fundamental role of identification for alumni-university relationships and positive WOM intentions. Finally, the results of the tested conceptual model that includes alumnis’ brand image perception of their university as well as alumni’ identification (attachment) to the university may provide more understanding about antecedents of alumni outcomes. Limitations and Future Research All studies have limitations and ours is no exception. One of the limitations of this research is the fact that the sample (although quite large) is from two Spanish universities. Although most prior studies are performed in one or two universities (Wardley, Bélanger & Valorie, 2013; Toledo & Luque, 2020), incorporating more universities would improve the study’s generalizability across institutions and regions. Another limitation relates to the scale items included in the independent variable (university brand image) used in the study. The inclusion of a multidimensional approach would have provided more information. Furthermore, the consideration of additional moderating variables (i.e., satisfaction, gender, current employment/unemployment status) may be an interesting option for future research. Also, additional relationships can be proposed (e.g., students’ satisfaction influencing directly perceived university brand image, brand image influencing directly alumni’s university identification). These relationships 18 could be an opportunity to test competing models. The extent to which our findings are generalizable will be clarified through replications and extensions of this study in future research. The university experience is primarily a service-related phenomena resulting from a process of co-creation with many participants. Planning that process can exert a positive influence on important outcomes like WOM. Future studies can investigate other variables affecting university satisfaction and alumni’s university identification as commitment, trust or shared values, for example. Other stakeholders should be considered in order to test the relationships analyzed. Finally, future research is needed to examine the influence of our focal constructs on other desired loyalty alumni outcomes such as volunteering and donating to the alma mater. Conclusions Despite the growing importance of WOM to institutions, only a few studies have examined the factors that influence stakeholders’ positive WOM intentions. Our findings enhance our understanding of university brand image’s influence on alumni positive WOM intentions. In HE, contradictory and scarce results are provided about the relationship between brand image and WOM. Herold et al. (2016) provide evidence that brand attitudes are formed mainly through cognitive information. In this research, we found that university brand image was a key driver of alumni positive WOM intentions (H1). Additionally, the study has identified the mediating role of alumni university identification on the influence of university brand image on positive WOM intentions. Admittedly, alumni university identification had only a relatively moderate influence on alumni positive WOM intentions. The findings also show that satisfaction significantly influences university identification (H3). It is relevant to note that the influence of university 19 brand image on WOM intentions was partially mediated by university satisfaction and alumni’s university identification (accepting H2 and H4). This study investigated perceptions of universities in the minds of graduates through the lens of a developed model based on the prior literature. Hence, this study helped to fill relevant research gaps in the literature. The main contribution of this paper arises from the development of a model including university brand image, satisfaction, alumni’s university identification and their influence on positive WOM . We believe that the originality of the findings can clearly contribute to research in higher education marketing. This work illustrates innovative theoretical paths, which will facilitate a better understanding of how branding strategies can be applied to HEIs. These conclusions show the important consequences for a university in developing a favorable brand image. Practical Implications Results obtained provide substantive managerial implications. The importance of WOM communication is based on the idea that people consider personal sources of information to be more trustworthy than other sources (Murray, 1991) and university brand image has been found to be a key influencer of positive WOM intentions. University managers should increasingly view their respective university brand images as an important facet of their long- term marketing strategy. A prestigious university brand has a strong influence on alumni satisfaction, alumni university identification, and alumni positive WOM intentions. It appears that university brand image is a strong driver of important outcomes and, thus, university managers should strive to enhance it. Another implication of this research is derived from the relevance of alumni university identification. The descriptive analysis (see Table 3) shows that alumni university identification has a relatively lower mean than the other variables. The proposed model and 20 its supported relationships have important managerial implications. Managers of HEIs can take advantage of identifying the drivers that enhance identification and satisfaction. It will help them make informed decisions and direct their efforts toward the factors that most influence the desired marketing outcomes. Universities would benefit from articulating and communicating their identities clearly, coherently, and in a persuasive manner (Bhattacharya & Sen, 2003). In particular, strategies that develop sustained and meaningful interactions between alumni and their institutions might lead to stronger identification and satisfaction (Wilkins & Huisman, 2013). Accordingly, a strategic plan of communication appears to be a key marketing tool to help build a stronger university brand image and to achieve higher levels of identification. Acknowledgements The present paper has been elaborated in the context of the R+D National Plan SEJ2007- 68105-C02-01 and 02/ECON of the Spanish Ministry of Education and Science. Disclosure statement No potential conflict of interest was reported by the authors Manuscript (including references, tables & graphics) : 7.637 words References Abdelmaaboud, A.; Polo, A. & Mahrous, A. (2020). The influence of student-university identification on student’s advocacy intentions: the role of student satisfaction and student trust, Journal of Marketing for Higher Education, DOI:10.1080/08841241.2020.1768613 21 Aghaz, A.; Hashemi, A. & Sharifi, M. (2015). Factors contributing to university image: the postgraduate students’ points of view, Journal of Marketing for Higher Education, 25(1), 104-126 Ahearne, M; Bhattacharya, C. & Gruen, T. (2005). Antecedents and Consequences of Customer–Company Identification: Expanding the Role of Relationship Marketing, Journal of Applied Psychology, 90, 574–585. Ahmed, I. & Spinelli, G. (2012). Effects of brand love, personality and image on word of mouth. Journal of Fashion Marketing and Management; 16, (4), 386-398. Alcaide-Pulido, P.; Alves, H. & Gutiérrez-Villar, B. (2017). Development of a model to analyze HEI image: a case based on a private and a public university, Journal of Marketing for Higher Education, 27(2), 162-187. Anderson, J. & Gerbing (1988). Structural equation modeling in practice: a review and recommended two-step approach, Psychological Bulletin, 103(3), 411-423. Arif, S., Ilyas, M., & Hameed, A. (2013). Student satisfaction and impact of leadership in private universities. TQM Journal, 25(4), 399-416. Arnett, D. B., German, S. D., & Hunt, S. D. (2003). The identity salience model of relationship marketing success: The case of nonprofit marketing, Journal of Marketing, 67(2), 89–105 Baek, T., Kim, J. & Yu, J. (2010). The differential roles of brand credibility and brand prestige in consumer brand choice, Marketing and Psychology, 27(7), 662-678. Bagozzi, R. & Yi, Y. (1988). On the Evaluation of Structural of Equation Models, Journal of the Academy of Marketing Science, 16 (1), 74-94. Balaji, M., Roy, S. K., & Sadeque, S. (2016). Antecedents and consequences of university brand identification. Journal of Business Research, 69(8), 3023–3032. 22 Barnard, Z., & Rensleigh, C. (2008). Investigating online community portals for enhanced alumni networking. The Electronic Library, 26(4), 433-445. Baron, R, and Kenny, D. (1986). The moderator-mediator variable distinction in social psychological research: conceptual, strategic and statistical considerations, Journal of Personality and Social Psychology, 51, 1173-1182. Bhattacharya, C. & Sen, S. (2003). Consumer-Company Identification: A Framework for Understaning Consumers' Relationships with Companies, Journal of Marketing, 67(2), 76-88. Bhattacharya, C., Rao, H. & Glynn, M. (1995). Understanding the bond of identification: An investigation of its correlates among art museum members. Journal of Marketing, 59(4), 46–57. Bologna Declaration (1999). Towards the European Higher European Area. Conference of Ministers responsible for Higher Education in 29 European countries (June), Bologna, Italy. Borraz-Mora, J., Hernandez-Ortega, B. & Melguizo-Garde, M. (2019). The influence of generic-academic competences on satisfaction and loyalty: the view of two key actors in higher education, Journal of Higher Education Policy and Management, DOI: 10.1080/1360080X.2019.1689802 Brakus, J., Schmitt, B., & Zarantonello, L. (2009). Brand experience: What is it? How is it measured? Does it affect loyalty? Journal of Marketing, 73(5), 52-68. Brislin, R. (1980). Translation and content analysis of oral and written material. In H. C. Triandis & J. W. Berry (Eds.), Handbook of cross-cultural psychology, 398–444. Brown, T., Barry, T., Dacin, P. & Gunst, R. (2005). Spreading the word: Investigating antecedents of consumers' positive WOM intentions and behaviors in a retailing context, Journal of the Academy of Marketing Science, 33(2), 123-138. 23 Brown, T., Dacin, P., Pratt, M. & Whetton, D. (2006). Identity, intended image, construed image and reputation: An interdisciplinary framework and suggested terminology. Journal of the Academy of Marketing Science, 34(2), 99-106 Bujisic, M., Hutchinson, J. & Parsa, H. (2014). The effects of restaurant quality attributes on customer behavioral intentions, Int. J. Contem. Hospitality Management. 26 (8), 1270– 1291 Caboni, T. & Eiseman, (2003). Organizational Identification and the Voluntary Support of Higher Education, Annual Meeting Study of Higher Education, Oregon, Portland, November 12-16. Casidy, R. & Wymer, W. (2015). The impact of brand strength on satisfaction, loyalty and WOM: An empirical examination in the higher education sector, Journal of Brand Management, 22(2), 117-135. Casidy, R. & Wymer, W. (2016). Linking prestige perception with consumption experience, loyalty, and WOM, Marketing Intelligence & Planning, 34(4), 540-558. Cohen, J. (1988), Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Erlbaum. Dedeoglu, B.; Bilgihan, A., Haobin, B.; Buonincontri, P. & Okumus, F. (2018). The impact of servicescape on hedonic value and behavioral intentions: The importance of previous experience, International Journal of Hospitality Management 72, 10–20. Del-Castillo-Feito, C., Blanco-González, A., & González-Vázquez, E. (2019). The relationship between image and reputation in the Spanish public university. European Research on Management and Business Economics, 25(2), 87-92. Drezner, N. (2018). Alumni Engagement in Higher Education: A Matter of Marketing and Leveraging Social Identities, in Competition in Higher Education Branding and Marketing, Palgrave Mac Millan Ed, Papadimitriou, 247. 24 Dutton, J. E., Dukerich, J. M., & Harquail, C. V. (1994). Organizational image and member identification. Administrative Science Quarterly, 39 (34), 239−263. Elliott, K. & Healy. M. (2001). Key Factors Influencing Student Satisfaction Related to Recruitment and Retention. Journal of Marketing for Higher Education, 104, 1-11. Ellis, P. D. (2010). The essential guide to effect sizes: Statistical power, meta-analysis, and the interpretation of research results. London: Cambridge University Press. European Commission (2003). The role of the universities in the Europe of knowledge, Brussels 〈 https://eur- lex.europa.eu/LexUriServ/LexUriServ.do?uri=COM:2003:0058:FIN:en:pdf 〉. (July, 24, 2020) Fombrun, C. & Van Riel, C. (2003). Fame & fortune: How successful companies build winning reputations. Upper Saddle River, NJ: Prentice Hall. Fornell, C. & Larcker, D. (1981). Evaluating structural equation models with unobservable variables and measurement error, Journal of Marketing Research, 18(1), 39-50. Foroudi, P.; Nazarian, A.; Ziyadin, S.; Kitchen, P.; Hafeez, K.; Priporas, C. & Pantano, E. (2020). Co-creating brand image and reputation through stakeholder’s socialnetwork, Journal of Business Research, 114, 42-59. Frasquet, M.; Calderón, H. & Cervera, A. (2012). University–industry collaboration from a relationship marketing perspective: an empirical analysis in a Spanish University, Higher Education, 64, 85-98. Galán, M.; Galera, C. & Wymer, W. (2013). Attitudes towards cause-related marketing: determinants of satisfaction and loyalty, International review on public and nonprofit marketing, 10(3), 253-269. 25 Gallarza, M.; Fayos, T.; Arteaga, F.; Servera, D. & Floristán, E. (2020). Different levels of loyalty towards the higher education service: evidence from a small university in Spain, International Journal of Management in Education, 14(1), 36 - 48 Giese, J. & Cote, J. (2000). Defining consumer satisfaction, Academy of Marketing Science Review, 1(1), 1-24. Gotsi, M. & Wilson, A. (2001). Corporate reputation: seeking a definition. Corporate Communications, 6(1), 24-30. Guilbault, M. (2018). Students as customers in higher education: The (controversial) debate needs to end. Journal of Retailing and Consumer Services, 40, 295-298. Hartman, D. & Schmidt, S. (1995). Understanding student/alumni satisfaction for a consumers´ perspective, Research in Higher Education, 362(1), 197-217. Hashim, S.; Yasin, N. & Ya’kob, S. (2020). What constitutes student–university brand relationship? Malaysian students’ perspective, Journal of Marketing for Higher Education, DOI: 10.1080/08841241.2020.1713278 Heffernan, T.; Wilkins, S.; Mohsin, M. (2018). Transnational higher education: The importance of institutional reputation, trust and student-university identification in international partnerships, International Journal of Educational Management, 32(2), 227-240. Helgesen, A. & Nesset, E. (2007). Images, satisfaction and antecedents: Drivers of student loyalty? A case study of a norwegian university college. Corporate Reputation Review, 10(1), 38-59. Hemsley-Brown, J., & Oplatka, I. (2006). Universities in a competitive global marketplace: A systematic review of the literature on higher education marketing. International Journal of public sector management, 19(4), 316-338. 26 Henning-Thurau, T., Langer & M.; Hansen, U. (2001). Modelling and managing student loyalty: an approach based on the concept of relationship quality, Journal of Service Research, 3(1), 331-344. Herold, K.; Tarkiainen, A. & Sundqvist, S. (2016). How the source of word-of-mouth influences information processing in the formation of brand attitudes, Journal of Marketing for Higher Education, 26(1), 64-85 Holbert, R. & Stephenson, M. (2003). The importance of analyzing indirect effects in media effects research: testing for mediation in structural equation modeling, Journal of Broadcasting & Electronic Media, 47, 553-569. Hong, S. & Yang, S. (2009). Effects of Reputation, Relational Satisfaction, and Customer– Company Identification on Positive Word-of- Mouth Intentions, Journal of Public Relations Research, 21(4), 381-403. Homburg, C., Wieseke, J. & Hoyer, W. D. (2009). Social Identity and the Service-Profit Chain. Journal of Marketing, 73(2), 38–54. Iacobucci, D., Saldanha, N. & Deng, X. (2007). A mediation on mediation: evidence that structural equations models perform better than regressions, Journal of Consumer Psychology, 17, 139-153. Ildamaria, P. & Andraz, J. (2019). Alumni Commitment in Higher Education Institutions: Determinants and Empirical Evidence, Journal of Nonprofit & Public Sector Marketing, DOI: 10.1080/10495142.2019.1656138 Keh, H. & Xie, Y. (2009). Corporate reputation and customer behavioral intentions: The roles of trust, identification and commitment, Industrial Marketing Management, 38(7), 732- 742. 27 Kim, C., Han, D. & Park, S. (2001). The effect of brand personality and brand identification on brand loyalty: Applying the theory of social identification, Japanese Psychological Research, 43 (4), 195-206. Kunda, Z. (1999). Social cognition: Making sense of people. MIT press. Lee, D., Ng, P. & Bogomolova, S. (2020): The impact of university brand identification and eWOM behaviour on students’ psychological well-being: a multigroup analysis among active and passive social media users, Journal of Marketing Management, 36:3-4, 384- 403. Ledden, L., & Kalafatis, S. (2010). The impact of time on perceptions of educational value. International Journal of Public Sector Management, 23(2), 141–157. Lafuente-Ruiz-de-Sabando, A., Zorrilla, P. & Forcada, J. (2018). A review of higher education image and reputation literature: Knowledge gaps and a research agenda, European Research on Management and Business Economics, 24, 8-16. Lu, Y. & Seock, Y. (2008). The influence of grey consumers’ service quality perception on satisfaction and store loyalty behavior. International Journal of Retail & Distribution Management, 36(11), 901–918. MacKenzie, S. (2003). The Dangers of Poor Construct Conceptualization. Journal of the Academy of Marketing Science 31(3), 323-326. Mael, F. & Ashforth, B. (1992). Alumni and their alma mater: a partial test of the reformulated model of organizational identification, Journal of Organizational Behavior, 13(2), 103-123. Marín, L. & Ruiz, S., (2013). The role of affiliation, attractiveness and personal connection in consumer-company identification, European Journal of Marketing, 47 (3/4), 655 – 673. Murray, K. (1991). A test of services marketing theory: consumer information acquisition activities, Journal of Marketing, 55(1), 10-25. 28 Nguyen, N. & Leblanc, G. (2001). Image and reputation of higher education institutions in students' retention decisions, International Journal of Educational Management, 15(6), 303-311. Nguyen, B.; Yu, X; Melewar, T.; & Hemsley-Brown, J. (2016) Brand ambidexterity and commitment in higher education: an exploratory study, Journal of Business Research, 69(8). 3105–3111 Palacio, A.; Díaz, G. & Pérez, P. (2002). The configuration of the university image and its relationship with the satisfaction of students, Journal of Educational Administration, 40, (5), 496-505. Pedro, I., de Costa, J. & Nobre, L. (2020). Understanding Alumni-Alma mater commitment Relationships upstream and downstream. Journal of Marketing for Higher Education, DOI: 10.1080/08841241.2020.1768200 Pinar, M.; Girard, T. & Basfirinci, C. (2020). Examining the relationship between brand equity dimensions and university brand equity, International Journal of Educational Management, DOI 10.1108/IJEM-08-2019-0313. Popp, B., & Woratschek, H. (2017). Consumer–brand identification revisited: An integrative framework of brand identification, customer satisfaction, and price image and their role for brand loyalty and word of mouth. Journal of Brand Management, 24(3), 250–270. Pyvis, D. & Chapman, A. (2005), “Culture shock and the international student ‘offshore’”. Journal of Research in International Education, Vol. 4 No. 1, pp. 23-42. Sánchez-García, I. & Currás-Pérez, R. (2011). Effects of dissatisfaction in tourist services: The role of anger and regret, Tourism Management, 32, 1397-1406. Santini, F.; Ladeira, W.; Hoffmann, C.; Sampaio & Da Silva, G. (2017). Student satisfaction in higher education: a meta-analytic study, Journal of Marketing for Higher Education, 27(1), 1-18 29 Select Committee on Education and Employment. (2001). Higher Education: Student Retention. Sixth Report (London: House of Commons). Schlesinger, W.,Cervera, A. & Pérez-Cabañero, C. (2017). Sticking with Your University: The Importance of Satisfaction, Trust, Image, and Shared Values. Studies in Higher Education, 42 (12), 2178–94. Schlesinger, W., Cervera, A., & Iniesta, M. A. (2015). Key elements in building relationships in the higher education services context. Journal of Promotion Management, 21(4), 475–491. Söderlund, M. (2006). Measuring customer loyalty with multi-item scales: A case for caution. International Journal of Service Industry Management, 171(1), 76-98. Stryker, S., & Burke, P. (2000). The past, present, and future of an identity theory. Social Psychology Quarterly, 284–297. Su, L., Swanson, S.R., Chinchanachokchai, S., Hsu, M.K. & Chen, X. (2016), “Reputation and intentions: the role of satisfaction, identification, and commitment”, Journal of Business Research, 69(9), 3261-3269. Sung, M. & Yang, S. (2008). Toward the Model of University Image: The Influence of Brand Personality, External Prestige and Reputation, Journal of Public Relations Research, 20(4), 357-376. Tajfel, H. & Turner, J. (1979). An integrative theory of intergroup conflict. In W. G. Austin & S. Worchel (Eds.), The social psychology of intergroup relations, 33–47. Toledo, L. & Luque Martínez, T. (2020) How loyal can a graduate ever be? The influence of motivation and employment on student loyalty, Studies in Higher Education, 45(2), 353-374. 30 Wardley, L.; Bélanger, C. & Valorie, L. (2013) Institutional commitment of traditional and non-traditional-aged students: a potential brand measurement?, Journal of Marketing for Higher Education, 23(1), 90-112 Wæraas, A. & Solbakk, M. (2009). Defining the essence of a university: lessons from higher education branding, Higher Education, 57, 449-462. Watkins, B. & Gonzenbach, W. (2013). Assessing university brand personality through logos: An analysis of the use of academics and athletics in university branding, Journal of Marketing for Higher Education, 23, 15–33. Westbrook, R. & Oliver, R. (1991). The Dimensionality of Consumption Emotion Patterns and Consumer Satisfaction. Journal of Consumer Research 18 (1). 84–91 Wilkins, S., & Huisman, J. (2013) The components of student–university identification and their impacts on the behavioural intentions of prospective students, Journal of Higher Education Policy and Management, 35(6), 586-598. Wilkins, S., & Huisman, J. (2015). Factors influencing university image formation among prospective higher education students: The case of international branch campuses. Studies in Higher Education, 40(7), 1256–1272. Wilkins, S., Butt, M., Kratochvil, D. & Balakrishnan, M. (2016). The effects of social identification and organizational identification on student commitment, achievement and satisfaction in higher education, Studies in Higher Education, 41(12), 1-21. Wymer, W. (2013). Deconstructing the brand nomological network. International Review on Public and Nonprofit Marketing, 10(1), 1-12. Yousaf, A., Mishra, A. & Bashir, M. (2020) Brand trust, institutional commitment, and their impact on student loyalty: evidence for higher education in India, Studies in Higher Education, 45(4), 878-891 31 32 Table 1. Measurement scales Variable Items University Brand Image I1 I have always had a good impression of this university Nguyen and Le Blanc (2001) In my opinion, this university has a good image in the minds of I2 consumers I3 I believe that the university has a better image than its competitors I4 In general, I have a positive image from this University Satisfaction S1 My decision to choose it were correct Fornell (1992) S2 Has satisfied my expectations S3 In general I am satisfied Identification ID1 If the university were criticized, it would influence how I thought Mael and Ashforth (1992) about myself. ID2 I am interested about the people think about the university ID3 When I talk about the university normally I say “us” ID4 When the university obtain a success I feel that was mine ID5 When somebody praise the university I feel that they praise me ID6 If a story in the media criticized the university, I would feel embarrassed Positive Word of Mouth WOM1 If somebody ask me surely I´ll recommended my university Söderlund (2006) WOM2 If the opportunity arose I would make positive comments to family Henning-Thurau et al. (2001) and friends WOM3 I would encourage others to study at this university. 33 Table 2. Sample Characteristics Characteristics Amount/% University 1 University 2 Total Gender Male 32.8% 31.6% 34.6% Female 67.2% 68.4% 65.4% Age < 25 years old 8% 8.9% 7.7% 25 – 33 years old 85% 84.3% 84.4% 34 – 41 years old 4% 3.7% 4% 41 years old 3% 2.8% 2.9% University education 5-year degree course 64% 62.2% 54.6% 3-year degree course 36% 37.8% 35.4% Area of study Arts and Humanities 6.6% 6.4% 5.2% Sciences 10.7% 12.2% 7.6% Health Sciences 15.8% 14.8% Social and Legal 15.7% 58.2% 61.2% Sciences 58.9% 7.4% 11.2% Engineering and 8.1% Architecture Employment situation Employed 77.4% 78.6% 78% Unemployed 22.6% 21.4% 22% 34 Table 3. Measurement Model Convergent Reliability validity Factor Item Factor Loading Cronbach’s α CR AVE Mean (Desv.St)* loading average UNIVERSITY BI 1 .767* BRAND IMAGE BI 2 .919* .77 .86 .91 .74 7.2(1.48) BI 3 .871* BI 4 .842* SATISFACTION S1 .890* S2 .953* .92 .84 .97 .91 7.6(1.67) S3 .911* ID1 .762* IDENTIFICATION ID2 .804 * ID3 .780* .85 .93 .97 .69 ID4 .914* 4.3(2.55) ID5 .927* ID6 .867* POSITIVE WOM WOM1 .933* WOM2 .931* 7.7(1.92) WOM3 .982* .924 .90 .98 .89 Goodness of fit indexes S-B 2 (115)=1030.713 BBNFI BBNNFI CFI IFI RMSEA (p=0.000) .879 .910 .921 .921 .068 Note: CR=Composite Reliability; AVE=Average Variance Extracted *For all variables the minimun is 0 and the maximun is 10. 35 Table 4. Hyphoteses Testing Direct model Mediation model satisfaction  R2  ind R2 ƒ2 Mediation University Brand Image  WOM .51* .26 .43** .22* .18 .28 Partial University Brand Image  Satisfaction .30* moderate Satisfaction  WOM .51** Direct model Mediation model identification  R2  ind R2 ƒ2 Mediation University Brand Image  WOM .51* .26 .46** .08* .32 .47 Partial University Brand Image Identification .34** strong Identification  WOM .25*  Satisfaction  Identification 0.31* * p < 0.05; ** p < 0.01.;  ind: indirect effect  are standardized coefficients 36 Figure 1. Conceptual Model 37 Figure 2. Hypotheses Testing 38