RESEARCH ARTICLES

 

Factors influencing Generation Y Students' University Website Usage Intentions: A Case of Selected South African Universities

 

 

M Van Deventer^I; H Lues^II,*

^INorth-West University, Management Sciences, Faculty of Economic and Management Sciences. Marko.VanDeventer@nwu.ac.za
^IINorth-West University, Management Sciences, Faculty of Economic and Management Sciences. Heleneze.Lues@nwu.ac.za

 

 

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ABSTRACT

The sustainability and survival of universities in the highly competitive local and global markets are increasingly dependent on the effectiveness of a website. This is because university websites serve as an important marketing tool and are considered a primary source of information to all stakeholders, particularly prospective and current students. The number of Generation Y students registering at higher education institutions increases annually. It is therefore essential to understand the factors that influence these students' university website usage intention. As such, the aim of this study was to investigate the influence of perceived trust, satisfaction and attitude on intention to use university websites amongst South African Generation Y students. Self-administered questionnaires were used to survey a convenience sample of 319 Generation Y students registered at the campuses of two Gauteng-based higher education institutions in South Africa. The statistical techniques used to analyse the data included descriptive statistics, Pearson's product-moment correlation analysis, reliability measures and structural equation modelling. The results of the study suggest that the participants' perceived satisfaction with university websites has a significant positive influence on their perceived trust in university websites, which, in turn, has a significant positive influence on their attitude towards university websites. Subsequently, attitude towards university websites has a significant positive influence on Generation Y students' university website usage intention. Understanding the factors that positively influence the sampled participants' university website usage intention can assist universities in gearing their online marketing strategies more successfully towards this market segment, and in doing so, increase their website penetration rate and student numbers.
JEL CLASSIFICATION: M15, M30, M37, M39

Key phrases: Attitudes; Generation Y; satisfaction; trust and University websites

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1. INTRODUCTION

The internet revolutionised the way in which organisations and individuals interact on both a national and international scale. It is for this reason that an online presence, through the development of a website, is essential for the survival of any organisation, including universities, especially in the global market place (Mentes & Turan 2012:61). Not only does a website enable an organisation to increase its market presence, it also provides a gateway for reaching larger audiences as well as to tap into global markets (Ganiyu, Mishra, Elijah & Gana 2017:27). In addition, websites assist with shaping the image of the organisation, improve its operational efficiency and are a timely and cost efficient platform to communicate with relevant stakeholders (Mentes & Turan 2012:61). For most universities, websites serve as a primary source for sharing university-related information (Buang, Majid, Wahab, Tohid, Abdullah, Adrutdin, Yacob & Zahid 2016:19), including information regarding the curriculums offered as well as other services, such as online registrations and learning facilities (El-Halees & Abu-Zaid 2017:14). Tucciarone (2009:30) highlights that students' use the information on university websites to evaluate institutions prior to selecting an institution.

The current university student cohort forms part of the Generation Y market segment, which includes individuals who were born between 1986 and 2005 (Bevan-Dye & Meyer 2018:69; Markert 2004:21). Generation Y individuals are described as confident, independent and well educated (Broadbridge, Maxwell & Ogden 2007:526). Given that this generation grew up in the digital age, technology has always played an essential role in the lives of these individuals. It is therefore not surprising that Generation Y spends a significant amount of time on the internet to shop, interact on social networking sites, stay updated on the latest news and trends and entertain themselves. From a marketing perspective, this generation is resistant to traditional marketing tactics and dislike being actively sold to, which poses an immense challenge to marketers who target this generation, as they are forced to rethink their ways of marketing to these consumers and have to publish authentic content (Howells 2016). Generation Y individuals are also accustomed to online research to assist with their purchase decision-making behaviour (Valentine & Powers 2013:83).

The theory of reasoned action (TRA) that was developed by Fishbein and Ajzen (1975) hypothesises that behavioural intention predicts an individual's behaviour. Behavioural intention refers to an individual's intention to perform an action (Fishbein & Ajzen 1975:12). Because behavioural intention captures the true preferences of an individual and given that an individual's actual behaviour can be influenced by promotions such as discounted deals, Day (1969) suggests measuring behavioural intention rather than behaviour. For the purpose of this study, behavioural intention refers to users' commitment to use university websites (Kim & Peterson 2017:46).

Given the increase in the number of student enrolments at higher education institutions in South Africa (Department of Higher Education and Training 2018:9), and university websites being the primary source of information that assist with decision-making regarding universities of choice (Buang et al. 2016:19), it is essential to determine the factors that influence Generation Y students' intention to use university websites. Previously published studies have proven that consumers' behavioural intentions are influenced by attitude (Van der Heijden 2003), which is influenced by consumer trust (Limbu, Wolf & Lunsford 2012) and ultimately satisfaction (Flavian, Guinaliu & Gurrea 2006). The purpose of the study is to determine the influence of satisfaction, trust and attitude on South African Generation Y students' intention to use university websites.

 

2. REVIEW OF THE LITERATURE

2.1 Satisfaction

According to Berbegal-Mirabent, Mas-Machuca and Marimon (2016:90) as well as Zeithaml, Bitner and Gremler (2009:104), satisfaction refers to a customers' evaluation of whether an organisation, product or service met the needs or expectations of a customer. The degree of satisfaction depends on the difference between the consumers' expectations and the actual results that are obtained (Alnaser & Almsafir 2014:3; Lake 2009:39). With each new interaction with an organisation, consumers gain new information and experiences, which influence their level of satisfaction (Casaló, Flavián & Guinalíu 2010:359). For potential customers who do not have any experience with an organisation, overall customer satisfaction cannot be expected (Kim, Xu & Koh 2004:400). Literature suggests that satisfied customers have higher usage and purchase intentions. In addition, satisfied customers are more likely to recommend an organisation, product or service to others (Ghane, Fathian & Gholamian 2011:2), and have a higher level of trust in an organisation (Fang, Chiu & Wang 2011:494). This is because satisfaction with an organisation boosts consumers' confidence that the organisation will continuously meet future obligations (Kim, Ferrin & Rao 2009:242), which creates the belief that the organisation is trustworthy (Doong, Wang & Shih 2008:146). As such, satisfaction directly influences consumers' trust in an organisation (Ghane et al. 2011:5).

Flavian et al. (2006:8) explains that the higher the satisfaction with the organisation, product or service is, the greater the trust in the organisation will be. This relationship has been validated by various studies, including those by Kim et al. (2004:408), who found that satisfaction plays a significant role in generating trust amongst repeat customers. In addition, in their study, Ghane et al. (2011:5) discovered that customer satisfaction has a positive influence on consumer trust within an e-banking context. Liang and Chen (2009:981), who focused on online financial services in Taiwan, found the same results. With reference to online clothing stores, Chou, Chen & Lin (2015:553) reported that females' satisfaction with an online seller influences their trust in that seller.

Loureiro and Amorim (2017:90) discovered that Generation Y consumers' satisfaction with the information received from a fashion review helps to generate trust in fashion websites. Flavian et al. (2006:8) reported that greater website user satisfaction positively influences the trust in that website. In accordance with the results of these studies, the following hypothesis was developed:

H1: Generation Y students' perceived satisfaction with university websites has a significant positive influence on their perceived trust in university websites.

2.2 Trust

Trust can be defined as a parties' (trustor) willingness to be vulnerable to another parties' (trustee) actions, while expecting that the trustee will perform a specific action regardless of the trustors' ability to control or monitor the trustee (Mayer, Davis & Schoorman 1995:712). Trust is formed when the trustee behaves in accordance with the trustors' expectations (Lake 2009:36). Pavlou and Fygenson (2006:123) explain that trust gives the trustor confidence that the trustee will fulfil what is expected as well as behave capably, ethically and fairly.

According to Palvia (2009:213), trust is essential in any situation where uncertainty, risk or interdependence exists. This is because trust mitigates risk or allows consumers to overcome uncertainty and, as a result, influences their behavioural intentions (McKnight, Choudhury & Kacmar 2002:313). Web-based organisations and their customers seldom have direct contact, and therefore customers depend on the information provided on an organisations' website to determine if and to what extent the organisation can be trusted (O'Cass & Carlson 2012:30). Trust plays an important role when consumers gather information from websites, especially since the consumers will assess the reliability, credibility and accuracy of the information (Choudhury & Karahanna 2008:184).

Pavlou and Fygenson (2006:123) explain that trust will create positive expectations that the information on a website is credible, which, in turn, will create favourable perceptions about the organisation and the outcomes of its actions, which will translate into a positive attitude towards the organisation. Consequently, when an organisation has trustworthy characteristics, it is likely that it will positively influence consumers' attitudes towards the organisation (Teo & Liu 2007:33; Zhu, Chih, O'Neal & Chen 2011:12). The relationship between trust and attitude has been confirmed in various studies. For example, it was found that consumers' trust in a website positively influences their attitude towards the website (Limbu et al. 2012:144; Palvia 2009:216; Zhu et al. 2011:12). Correspondingly, Pavlou and Fygenson (2006:131) reported that if consumers trust that a web vendor will provide credible information, it will positively influence their attitudes towards using that web vendor to obtain information. In line with the findings of these studies, the following hypothesis was formulated:

H2: Generation Y students' perceived trust in university websites has a significant positive influence on their attitude towards university websites.

2.3 Attitude

Attitude is described as an individual's favourable or unfavourable assessment of a concept or object (Hoyer, MacInnis & Pieters 2013:128). Joubert, Erdis, Brijball Parumasur and Cant (2013:80) add that attitude refers to a person's learned tendency to behave positively or negatively towards an object. In terms of websites, attitude towards a website would represent a users' tendency to respond favourably or unfavourably to that website (Martínez-López, Luna & Martínez 2005:316). As part of the theory of reasoned action, it is argued that consumers' attitudes significantly influence their behavioural intention. This is because an individual forms an attitude about a specific object based on their beliefs, which consequently serves as a basis for forming an intention to behave in a particular way towards that object (Fishbein & Ajzen 1975:59). Within the context of websites, this would mean that a consumer with a positive attitude towards a website is more likely to visit the website, whereas a consumer with a negative attitude might be less willing to visit the website (Limbu et al. 2012:141).

A number of studies on online shopping amongst online users (Ahn, Ryu & Han 2007:272), and students in the USA (Limbu et al. 2012:144; Palvia 2009:216) and Taiwan (Wu, Lee, Fu CS & Wang 2013:796) found that consumers' attitudes toward online retailers' websites positively influence their behavioural intention to use or purchase from those retailers. Similarly, the Nadeem, Andreinib, Saloa and Laukkanen (2015:438) study on Italian Generation Y consumers' online shopping through Facebook, in particular, also discovered that consumers' attitudes towards an online retailer positively influence their intention to be loyal to that retailer. In addition, Van der Heijdens' (2003:546) study on a Dutch generic portal found that the intention to use a website is significantly influenced by the users' attitude. Consistent with the results of these studies, this study proposes the following hypothesis:

H3: Generation Y students' attitude towards university websites has a significant positive influence on their university website usage intention.

 

3. RESEARCH METHODOLOGY

3.1 Sampling Method and Data Collection

For this study, the target population was defined as male and female Generation Y students aged between 18 and 24 years, registered at South African public higher education institutions (HEIs). In South Africa, there are 26 registered South African public HEIs. The studies' sampling frame comprised these 26 public HEIs. Judgement sampling was then used to select two Gauteng-based HEI campuses, namely one traditional university campus and one university of technology campus. Fieldworkers distributed 400 questionnaires to a convenience sample of students who voluntarily agreed to partake in the study using the mall-intercept survey method.

3.2 Research Instrument

To collect the required data, a self-administered survey questionnaire was employed. The questionnaire consisted of two sections. In the first section, demographic data was requested. The second section contained scales from studies that were previously published and measured the constructs of trust in university websites, satisfaction with university websites, attitude towards and intention to use university websites.

Trust in university websites was measured using seven items, whereas satisfaction with university websites was measured using three items, both construct items harvested from Flavian et al. (2006). Attitude towards university websites (Ahn et al. 2007; Van der Heijden 2003) as well as behavioural intention to use university websites (Ahn et al. 2007) was measured using three items each. To record the responses to the scaled items, a six-point Likert-type scale that ranged from strongly disagree (1) to strongly agree (6) was used.

3.3 Data Analysis

Two statistical packages were used to analyse the data of this study, namely the IBM Statistical Package for Social Sciences (SPSS) and Analysis of Moment Structures (AMOS), Versions 25 for Windows. A number of statistical measures were employed to analyse the data, including descriptive statistics, Pearson's product-moment correlation analysis, reliability measures and structural equation modelling using the maximum likelihood method.

 

4. RESULTS

A total of 400 questionnaires were distributed. Of the 400 questionnaires, 319 questionnaires were subject to further analysis as these questionnaires met the target population specifications. As such, this study achieved a response rate of approximately 80 percent. Consistent with the specified target population, the sample included each of the seven age categories. The sample comprised fewer male participants than female participants, and consisted of more first-year students. In terms of ethnicity, the majority of the sampled participants were black, followed by white participants. The high number of black participants in the study may be attributed to the high percentage of black individuals (84 percent) who make up the Generation Y cohort (Statistics South Africa 2018:2). In addition, the sample consisted of participants from eight of South Africa's nine provinces and each of the countries' 11 official language groups. In Table 1, a description of the sample is given.

The descriptive statistics, which included the means and standard deviations, were computed for each of the constructs. The Cronbach alpha values were calculated for each construct to evaluate its internal-consistency reliability. This was followed by the construction of a correlation matrix of Pearsons' product-moment correlation coefficients to determine the relationships between the constructs. The descriptive statistics, internal consistency reliability and correlation coefficients are outlined in Table 2.

As indicated in Table 2, Cronbachs' alpha values exceeding the recommended level of 0.60 (Malhotra 2010:319) were calculated for each of the four latent factors, thereby providing evidence of internal-consistency reliability of the scales. Means above 3.5 were recorded on each of the latent factors, which, given the six-point Likert-type scale used, suggests that those South African Generation Y students that participated in the study trust and are satisfied with their university website, have a positive attitude towards their university website, and intend to browse their university website.

In terms of the relationships between the constructs, there were statistically significant positive associations (p<0.01) between each of the pairs of latent factors, thereby implying the nomological validity of the measurement theory. The strongest relationship occurred between the latent factors of trust and satisfaction (r = 0.81) and, given that this coefficient was below the suggested level of 0.90, there were no obvious multicollinearity issues (Hair, Black, Babin & Anderson 2010:710). In addition, there were no subtle forms of multicollinearity given that the collinearity diagnostics revealed tolerance values above the 0.10 cut-off level, ranging from 0.282 to 0.483 and an average variance inflation factor (VIF) of 2.88, which was below the cut-off of 10 (Pallant 2010:164). Given the nomological validity of the measurement theory, as well as a lack of any evidence of multicollinearity issues, it was possible to propose a measurement model.

A four-factor measurement model was specified for confirmatory factor analysis that included trust (seven indicators), satisfaction (three indicators), attitude (three indicators) and behavioural intention (three indicators). For model identification purposes, the first loading on each of the four latent factors was fixed at 1.0, which resulted in 136 distinct sample moments and 38 distinct parameters to be estimated, equalling 98 degrees of freedom (df) based on an over-identified model, as well as a chi-square value of 309.71 with a probability level equal to 0.001.

Problematic estimates, such as standardised factor loadings above 1.0 or below -1.0, as well as negative error variances, also referred to as Heywood cases, were examined in the model (Hair et al. 2010:706). In addition, the composite reliability (CR), average variance extracted (AVE) and the square-root of the AVE (VAVE) were calculated to assess the composite reliability and construct validity, as tabled in Table 3.

As indicated in Table 3, none of the estimates were problematic. Moreover, the association between each observed variable and its latent factor is statistically significant (p<0.001). There is evidence of composite reliability given that all the CR values exceed the recommended 0.70 level. The standardised loading estimates and AVE values are above 0.50, thereby suggesting convergent validity. The square-root of the AVE values surpasses the correlation coefficients associated with each respective latent factor, thereby indicating discriminant validity (Hair et al. 2010:709). These two forms of validity, together with the nomological validity established in Table 2, suggest construct validity (Malhotra 2010:321).

To assess model fit, several statistical measures were used, namely the goodness of fit index (GFI), incremental fit index (IFI), comparative fit index (CFI), Tucker-Lewis index (TLI), the standardised root mean residual (SRMR), the root mean square of approximation (RMSEA), and the chi-square statistic. Good model fit is indicated through a non-significant chi-square value, GFI, IFI, CFI and TLI values larger than 0.9, as well as a small SRMR value and an RMSEA value of 0.08 or less (Malhotra 2010:732-733). Despite a significant chi-square value of 309.71 with 98 degrees of freedom (df), the measurement model returned acceptable fit indices of SRMR=0.06, RMSEA=0.08, GFI=0.90, IFI=0.93, TLI=0.92 and CFI=0.93.

Based on this measurement model, a structural model was subsequently tested in accordance with the literature, whereby it was hypothesised that satisfaction with university websites (F2) has a direct positive influence on trust in university websites (F1), which, in turn, has a direct positive influence on attitude towards university websites (F3). Attitude towards university websites was then hypothesised to have a direct positive influence on behavioural intention to use university websites (F4). The estimated standardised and unstandardised regression coefficients for the model are presented in Table 4.

As indicated in Table 4, all paths tested were positively and statistically significant (p<0.001). Satisfaction with university websites has a statistically significant positive influence on trust in university websites (β=0.66, p<0.001), which, in turn, is a statistically significant predictor of attitude towards university websites (β=1.08, p<0.001). As per the literature, attitude towards university websites has a statistically significant positive influence on behavioural intention to use university websites (β=0.69, p<0.001). With regard to the squared multiple correlation coefficients (SMCs), the model explains 71 percent of the variance in trust in university websites, 69 percent of the variance in attitude towards university websites and 57 percent of the variance in behavioural intention to use university websites. Figure 1 illustrates the structural model with the standardised regression estimates and SMCs.

In terms of model fit, while the chi-square statistic [(311.46 (df=101, p<0.001)] remained significant, the model produced acceptable fit indices of SRMR=0.05, RMSEA=0.08, GFI=0.90, IFI=0.93, TLI=0.92 and CFI=0.93.

 

5. DISCUSSION

The aim of this study was to investigate the influence of perceived satisfaction, trust and attitude on South African Generation Y students' behavioural intention to use university websites. Confirmatory factor analysis established that the proposed model is a four-factor structure consisting of satisfaction with university websites, trust in university websites, attitude towards university websites and behavioural intention to use university websites. The measurement model exhibited acceptable fit to the model as well as internal-consistency reliability, composite reliability and construct validity, thereby making the model suitable for path analysis.

In accordance with the literature and previously published findings, the results of the path analysis suggest that Generation Y students' perceived satisfaction with university websites positively influences their perceived trust in university websites. In turn, the findings of the study suggest that trust in university websites positively influences their attitude towards university websites, and that their attitude towards university websites positively influences their behavioural intention to use university websites.

 

6. RECOMMENDATIONS

Given the ever-increasing number of online users, high costs involved in developing and maintaining a website as well as the high competition amongst South African universities for increased student numbers, it is important that universities should develop and devise its online strategies more carefully to improve the usability of its website, establish healthy communication between the university and its stakeholders, as well as achieve a higher level of user satisfaction. A higher level of user satisfaction is more likely to be achieved when the university fulfils the expectations of its users and satisfies their constantly changing demands. To this end, it is advised that universities should conduct a detailed analysis of the users' online needs and should ask for continuous feedback.

Online surveys or a site intercept survey on the universities' website could be used in this regard, whereby users are asked about what it is they want and expect from a university website. In addition, automated diagnostic tools could be used to detect any internal problems with the website. The focus should be on simplifying the website to ensure that it is user-friendly in terms of navigation and layout. In doing so, universities could strengthen users' trust in its websites as well as positively influence users' attitude towards the functionality of its websites.

 

7. LIMITATIONS

Although this study has limitations, these limitations present avenues for future research. This study was limited to two HEI campuses located in Gauteng. This study used a single cross-sectional research design. HEIs in different locations could improve the representativeness of the target population, and could therefore be a valuable consideration for future research. In addition, a longitudinal research design is advised.

 

8. CONCLUSION

The model empirically tested in this study concluded that Generation Y students' perceived satisfaction with university websites has a statistically significant positive influence on their perceived trust in university websites, which, in turn, has a positive influence on their attitude towards university websites. Generation Y students' attitude towards university websites was then found to have a direct positive influence on their behavioural intention to use university websites. Understanding the factors that positively influence Generation Y students' university website usage intention can assist universities in gearing their online marketing strategies more successfully towards this market segment, and, in doing so, increase their website penetration rate and student numbers.

 

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