“South African Generation Y students’ behavioral intentions to use university websites”

University websites are increasingly crucial in meeting the evolving digital demands of students. To effectively manage university websites, it is necessary to first determine students’ behavioral usage intentions of university websites and the factors that influence their intentions, which forms the purpose of this study. Data were collected at a single point in time and described the characteristics of the sample. This study, involving 319 Generation Y students registered at two South African university campuses (one traditional and one university of technology campus), utilizes structural equation modeling to explore the predictive relationships among information quality, system quality, playfulness, ease of use, trust, attitude, satisfaction, and behavioral intentions related to university website use. The study underscores the pivotal role of the univer-sity’s website in shaping student satisfaction, with information quality standing out as a significant positive influence. Additionally, playfulness significantly impacts both satisfaction and overall attitudes toward university websites. The system quality of the university website is also noteworthy, showing a statistically significant positive effect on ease of use and fostering trust among students. Furthermore, satisfaction is anticipated by ease of use, creating a cascade effect where satisfaction predicts trust and trust predicts attitudes. Ultimately, students’ attitudes emerge as a critical predictor for their behavioral intentions to use university websites. The model exhibits acceptable fit indices, demonstrating substantial explanatory power (SRMR = 0.1, RMSEA = 0.06, IFI = 0.94, TLI = 0.93, CFI = 0.94). These findings offer insights for university management and web designers to enhance online platforms, fostering student satisfaction, trust, and usage.


INTRODUCTION
Websites, as a means of establishing an online presence, have become essential for the survival and competitiveness of businesses, including universities (Mentes & Turan, 2012).That is because a website is a costefficient and timely platform to increase a business's market presence and broaden its reach beyond national borders (Ganiyu et al., 2017).As such, a high-quality and efficient website remains one of the universities' strategic priorities (Al-Debei, 2014), especially since it is a primary source of university-related information (Buang et al., 2016).University websites are a valuable and effective tool to convey information to several stakeholders, such as faculty and administrative staff, students, prospective students, and external stakeholders.Because of their flexibility, university websites are used as an avenue to distribute course-related information, information on the services offered, links to the library and support services, and serve as a platform for student queries, applications, and registration, among others (Saichaie & Morphew, 2014).For most prospective students, the university website is the first encounter that they have with the university (Schneider & Bruton, 2004) and a means to evaluate and compare different universities (Anctil, 2008) prior to selecting a university.Since the Covid-19 pandemic, universities have become more reliant on their websites and other online platforms (Bekele, 2021), which stimulated various technological advancements in education and, as a result, shifted the needs and expectations of students (EiffelCorp, 2022).Therefore, it is vital that universities cautiously plan and manage the functionality of their sites and the content displayed on their sites to meet the needs of their target market, namely students (Schneider & Bruton, 2004).

LITERATURE REVIEW
The current student population forms part of the Generation Y cohort, commonly called Millennials (Severt et al., 2013), who comprise individuals born between 1986 and 2005 (Bibby et al., 2019).Being brought up in the digital era made these individuals the first generation to access various multimedia platforms, devices, and technologies (Schlitzkus et al., 2010).Therefore, they are comfortable with the advancement of technology and are known to be tech-savvy and acquainted with various digital devices (Soyez & Gurtner, 2016) and platforms, including the Internet (Bilgihan, 2016).Consequently, the internet and technology have become an integral part of Generation Y individuals' lives and a key source of information for their purchase decision-making.
Given the rising number of Generation Y students enrolled at HEIs in South Africa and the role of online platforms such as websites in these students' daily activities and decision-making, coupled with the role of websites in universities' success and growth, it is paramount to understand South African Generation Y students' intentions to use university websites and the factors that influence their usage intentions.
The term behavioral intention, as outlined by Fishbein and Ajzen (1975), pertains to an individual's inclination or plan to engage in a particular action.In their theory of reasoned action (TRA), individuals' behavioral intention predicts their actual behavior.Since individuals' actual behavior is susceptible to factors such as sales promotions and behavioral intention, it therefore portrays their true preferences.Day (1969) recommends that an individual's behavioral intention should be measured rather than their behavior.Several international research studies within the context of digital platforms examined the influence of behavioral intention as well as the antecedents thereof.
Attitude pertains to an individual's favorable or unfavorable impression of a concept (Hoyer et al., 2013).Within the context of a website, Chen and Wells (1999, p. 28) describe an individual's attitude as a "predisposition to respond favorably or unfavorably to web content in natural exposure situations."An individual's attitude could transform based on life experiences (Himansu, 2009) and the influences of external factors (Hanna & Wozniak, 2001).Under the theory of reasoned action, an individual's attitude toward an object forms the basis of their intention to engage in a particular behavior toward that object (Fishbein & Ajzen, 1975).This means that if an individual has a positive attitude toward a website, the individual is more likely to engage with the website (Limbu et al., 2012).Various digital-related studies have verified the relationship between attitude and usage intention.A study on web-based educational tools reported that students' attitudes toward using those tools affected their intention to continue to use those tools (Yaakop et al., 2020).Another factor that could have a direct or indirect influence on university website usage intentions is trust, which can be described as a person's readiness to be susceptible to another entity's actions (Mayer et al., 1995).Therefore, trust requires the individual to rely on the entity's character or capability.Trust plays a vital role in digital media and technologies, particularly when risk or uncertainty is involved (Shin, 2019).With web-based organizations, an individual has no direct control over the service provider's actions (Muda et al., 2016) and has no or minimal direct contact with the service provider.Consequently, the individual relies on website information to determine the organization's trustworthiness (O'Cass & Carlson, 2012).Trust is formed when the organization's behavior matches the individual's expectations.Within the context of websites, trust will be formed if the information on a website is perceived by a user as reliable, accurate, and credible (Choudhury & Karahanna, 2008).Consequently, higher trust in a website, online service, or digital media requires less effort from users to validate the legitimacy of the information or details of the service (Shin, 2019).As such, trust in a website will result in positive perceptions about the organization and its actions, leading to a positive attitude toward the organization.The influence of trust on attitude has been verified in several studies.It was reported that customers' trust in websites (Limbu et al., 2012) and mobile retail apps (Kaushik et al., 2020) influence their attitude toward that website or app.In a study on blockchain, Shin (2019) found that trust plays a significant role in users' attitudes toward blockchain.Consistent with these findings, this study suggests that Generation Y students' trust in university websites influences their attitudes toward these websites.It is also believed that satisfaction with university websites could influence trust in the website.
Satisfaction represents an individual's judgment on whether a product, service, or organization met their expectations (Berbegal-Mirabent et al., 2016).This judgment is derived from discrepancies between an individual's expectations and the results.The more aligned the actual results and expectations, the higher the level of satisfaction (Alnaser & Almsafir, 2014).With each interaction an individual has with a product, service, or organization, new experiences and information are gained, which influences the individual's degree of satisfaction with the organization (Casaló et al., 2010).Satisfied individuals have higher intentions to purchase or use products or services and are more likely to make recommendations to other individuals (Ghane et al., 2011).In addition, the literature revealed that satisfied individuals have a higher level of trust in an organization (Fang et al., 2011) since individuals' satisfaction gives confidence that the organization will meet their obligations in the future (Kim et al., 2009), thereby depicting that the organization is trustworthy.Therefore, satisfaction has a direct influence on consumers' trust in an organization (Ghane et al., 2011).As a result, higher satisfaction with a product, service, or organization will lead to greater trust in the organization (Flavián et al., 2006).In terms of mobile banking, Febrian et al.
(2021) discovered a direct relationship between users' satisfaction and their trust in mobile banking.Similar findings were reported by Ramadania et al. (2021), who found that users' satisfaction with an online academic service influences their trust in that online academic service.In keeping with these results, this study postulates that Generation Y students' perceived satisfaction with university websites affects their trust in these websites.In addition, ease of use of university websites could influence satisfaction with university websites.
Ease of use describes the degree to which a user understands the structure of a website, how it functions, its content, and its interface (Casaló et al., 2008).In addition, it refers to the time and physical and mental effort required from a user to find the relevant information (Davis, 1989).Perceived ease of use is a key determinant of users' acceptance of information technology or systems (Davis, 1989).If a system is perceived to be straightforward, simple, and effortless, it is more likely that a user will form a favorable attitude toward the system (Renny et al., 2013).In addition, a system that is easy to use will likely result in higher user satisfaction.When considering ease of use within a university website context, it includes effortless website interaction and quick downloading of webpages.Several previously published studies across different contexts have reported a correlation between ease of use and user satisfaction.Chong (2021) reported that the ease of use of mobile short video applications directly influences users' satisfaction with the application.Similarly, Alkhateeb and Abdalla (2021) focused on students' satisfaction with university learning management systems.They found that the perceived ease of use of the system directly influences students' satisfaction with the system.Accordingly, this study theorizes that Generation Y students' perception of the ease of use of university websites directly impacts their perceived satisfaction with these websites.System quality could also impact perceptions of ease of use of university websites.
System quality refers to a website's overall performance (Gorla et al., 2010) concerning its ability to capture, process, store, and retrieve information (Al-Debei et al., 2013).From the user's point of view, the system quality of a website becomes apparent through its interface and the ease with which users can navigate it.It includes appearance features such as colors, text fonts, graphics, layout (Aladwani & Palvia, 2002), and website security (Ahn et al., 2007).Regarding university websites, the system quality is assessed based on the website's functionalities that are controllable by the student.Universities must cater to Generation Y students regarding system functionalities and aesthetics since they grew up with technology and have certain expectations regarding websites.By ensuring that a website has adequate link structures and interfaces and navigates seamlessly, the website will be more user-friendly and, ultimately, enhance users' experience and trust (Kuan et al., 2008).Based on the literature, system quality positively influences the ease of use of information systems (Zhou, 2011) and users' trust in information systems (Van Deventer et al., 2017).Zhou and Zhang (2009) reported that system quality positively influenced the respondents' trust in e-commerce websites.Van Deventer et al. (2017) reported similar findings that perceived system quality directly and positively influences customers' trust in mobile banking.Consistent with these results, this study hypothesizes that university website system quality influences Generation Y students' perception of the ease of use of these websites and the trust Generation Y students have in these websites.Like system quality, information quality could also directly or indirectly impact university website usage intentions.
Information quality represents individuals' subjective evaluations and judgments regarding the quality of information displayed online (Yang et al., 2005).A website's information quality is vital to its success since it is often a deciding factor when selecting from several service providers or products (Kuan et al., 2008).As such, good quality information on the website will likely attract new customers and assist in retaining existing customers.Therefore, businesses must take caution when deciding on the information to be displayed on their website (Rahimnia & Hassanzadeh, 2013).Detail, timeliness, accuracy, and reliability are critical factors in information quality (Ahn et al., 2007).These factors significantly impact the overall quality and effectiveness of the information provided.Detail refers to the level of comprehensiveness or completeness of the information provided.Accuracy pertains to the degree of correctness or precision of the information.Timeliness indicates how recent or up-to-date the information is, reflecting its relevance within a specific timeframe.Reliability relates to whether the information is consistent and dependable (Yang et al., 2005).Within the context of university websites, high information quality would signify that the information related to the academic calendar, faculty details, and publications is comprehensive, accurate, up-to-date, and reliable (Al-Debei, 2014), as well as the modules, courses, and other teaching and learning content is relevant, up-todate and accurate.The literature indicates that information quality predicts customer satisfaction.A study conducted by Dirgantari et al. ( 2020) on e-commerce customer satisfaction reported that information quality significantly influences satisfaction.Similarly, investigating users' satisfaction with online learning systems, Nuryanti et al.
(2021) found that information quality significantly contributed to users' satisfaction with the learning system.Based on the results of these studies, this study posits that the information quality of university websites directly impacts the perceived satisfaction of Generation Y students.
Another critical factor to consider in predicting university website usage intentions is playfulness.Playfulness can broadly be described as the level of enjoyment experienced by a user (Padilla-Meléndez et al., 2013).Moon and Kim (2001) explain that perceived playfulness is captured in three variables, namely concentration, curiosity, and enjoyment.Concentration refers to the de-gree to which a user is focused on an interaction.In contrast, curiosity refers to the inquisitiveness of the user, and enjoyment denotes the level of fun that the user experiences during the interaction.Playfulness results from a user's interaction with a situation and, therefore, is described by Serenko and Turel (2007) as a personal, irrational, and spontaneous activity.When an individual experiences a pleasant feeling during an interaction, this feeling will create a sense of playfulness and likely result in a positive attitude toward the interaction.Within a website context, users' perceived playfulness of a website will depend on their experience with the website, where a positive experience will likely lead to a favorable attitude toward the website.The correlations between playfulness and satisfaction, as well as attitude, have been confirmed in various studies.For example, it was reported that playfulness positively influences users' satisfaction with an e-book application (Liu et al., 2021).Moreover, it was found that playfulness influences students' attitudes toward participating in online education (Wang et al., 2021) and their attitudes toward brain-computer interface games (Wang et al., 2023).In keeping with these findings, university website playfulness may predict Generation Y students' perception of satisfaction with these websites and influence the attitudes Generation Y students display toward these websites.

While previous research has been conducted to determine individuals' behavioral intention to use various digital platforms, limited research is available on students' behavioral intention to use university websites. Moreover, what factors drive their intention to use university websites is unclear.
This study seeks to provide insight into the perceived value of university websites and guidance concerning the factors that universities should invest their time, effort, and resources in to increase the usage of their websites.
Therefore, the objective of this paper is to assess how information quality, playfulness, system quality, ease of use, satisfaction, trust, and attitude toward university websites impact the intention of Generation Y students to utilize these websites.
As per the literature and in a university website context, the following hypotheses are formulated: H1: Information quality positively influences satisfaction.
H4: System quality positively influences ease of use.
H5: System quality positively influences trust.
H6: Ease of use positively influences satisfaction.

METHOD
The study aimed to target students from the Generation Y age group (between 18 and 24 years old) enrolled in two South African institutions of higher education (HEIs).The paper used judgment sampling to select two campuses (a traditional university campus and a university of technology campus) in Gauteng from the 26 HEIs available.
To gather data, 200 questionnaires were distributed at each HEI using the mall-intercept survey method to a convenience sample of voluntarily participating students.
The study used a two-section self-administered questionnaire to collect data from the sample.The first section gathered the demographic information of the participants, while the second section employed adapted scales from prior studies to assess the factors of information quality (

RESULTS
Four hundred self-administered questionnaires were handed out, and 319 of them met the study's population specifications and were considered complete for data analysis.Therefore, the study achieved a response rate of around 80%.The sample mainly consisted of individuals who were 20 and 18 years old, in that order.Furthermore, the sample had more women than men participating, with the majority African.First-year students constituted the majority of study participants based on the study year.Table 1 presents a breakdown of the sample's demographics.
The statistics used to describe the data, measure internal consistency, and assess relationships between factors were computed for each latent factor.These included Cronbach's alpha values for internal consistency and Pearson's product-moment correlation coefficients for relationships.The results for the summary statistics and correlations can be found in Table 2.
The mean (X ̄) value of each latent factor was 3.5 or above, indicating that South African Generation Y students participating in the study view the quality of their university websites and the information provided as good, as determined by the six-point Likert scale.Additionally, the students find their university websites enjoyable and user-friendly and exhibit trust, positive attitudes, and satisfaction toward their university websites.They also intend to continue using their university websites.Each latent factor's internal consistency reliability is supported by Cronbach's alpha (α) values above the advised level of 0.70 (Malhotra, 2020).
Significant positive correlations (p ≤ 0.01) were observed between all latent factor pairs, indicating nomological validity (Malhotra, 2020).The strongest association was observed between sat- isfaction and trust latent factors, with an r-value of 0.74.Additionally, none of the correlation coefficients exceeded the recommended threshold of 0.90, indicating no apparent issues of multicollinearity (Pallant, 2020).Consequently, a measurement model was proposed.
Confirmatory factor analysis utilized the eight-factor measurement model.To evaluate the construct validity and composite reliability of the measurement model, composite reliability (CR), average variance extracted (AVE), and heterotrait-monotrait (HTMT) values were computed.The estimates for standardized loading, error variance, CR, AVE, and HTMT values are reported in Table 3.
Table 3 reveals no problematic estimates.All latent factors displayed a CR value greater than 0.70, which indicates composite reliability (Malhotra, 2020).Additionally, there is evidence of convergent validity since all AVEs and standardized loadings surpassed the 0.50 cut-off level (Hair et al., 2014).Each factor pair's HTMT values were below the 0.90 threshold, indicating discriminant validity, as suggested by Henseler et al. (2015).According to Malhotra (2020), the construct validity of the measures was supported by the convergent and discriminant validity, as well as the nomological validity confirmed in Table 2.
Various statistical measures were employed to evaluate the adequacy of the model fit.An acceptable model fit is indicated by an incremental fit index (IFI), Tucker-Lewis index (TLI), and comparative fit index (CFI) value exceeding 0.9, a root mean square of approximation (RMSEA) value of 0.08 or less (Malhotra, 2020), and a standardized root mean residual (SRMR) value below 0.1 (Hair et al., 2014).All the measurement model fit indices indicate a suitable fit.
After confirming the satisfactory reliability, validity, and fit of the measurement model, a structural model was tested.The objective of the proposed structural model is to examine the predictive relationship between the factors.Playfulness is also found to influence both student satisfaction with university websites and their attitudes toward them.The quality of the university website's system has a statistically significant and positive impact on the university website's ease of use and students' trust in university websites.The students' satisfaction with university websites is significantly predicted by ease of use.Satisfaction, in turn, predicts trust in university websites, and trust subsequently predicts students' attitudes toward university websites.Ultimately, students' attitudes predict their behavioral intention to use university websites.Therefore, all hypotheses are supported.According to the coeffi-cients for squared multiple correlation (SMC), the model explains a substantial proportion of variance in each factor, ranging from 45% for ease of use to 80% for attitude and 63% for behavioral intention.Figure 1

DISCUSSION
The study identified information and system quality, playfulness, ease of use, trust, attitude, and satisfaction with university websites as predictors of students' intention to use these websites.These findings are consistent with the findings of previous studies.For example, the influence of information quality on customer satisfaction was confirmed in an e-commerce study (Dirgantari et al., (2020), while playfulness was also found to have an influence on customer satisfaction (Liu et al., 2021) and attitude (Wang et al., 2021).In another study, system quality was found to be a predictor of ease of use (Zhou, 2011)  Additionally, the study revealed that these factors could be reliably used to create a structural model that accurately predicts students' behavioral intention to use university websites.
Based on the study's findings, university management can implement various strategies to positive-ly influence students' behavioral intention to use university websites.Universities are encouraged to improve the quality of information on university websites by ensuring that the information available is accurate, relevant, and up-to-date to increase students' trust and satisfaction with the website.Universities must enhance the playfulness of the website by adding interactive elements or gamification features.In doing so, universities can make the experience more enjoyable and engaging for students, which may increase their intention to use the website.Moreover, university management must keep system quality and ease of use in mind to ensure that university websites have a user-friendly interface and technical infrastructure that will warrant easy navigation and quick access to information.In addition, universities should foster trust through transparency and security measures.University websites should be transparent about their privacy policies and security measures to reassure students about the safety of their personal information.Lastly, university management should attempt to promote positive attitudes toward the website.University administrators and faculty members can actively promote university website use and emphasize its benefits, such as easier access to course materials, online registration, and academic resources.

CONCLUSION
This study aimed to identify the factors that predict the behavioral intention of Generation Y university students to use university websites.The results showed that several factors, including information and system quality, playfulness, ease of use, trust, attitude, and satisfaction with university websites, significantly influenced students' intention to use these websites.By identifying the predictors of students' behavioral intention to use university websites, universities can formulate effective strategies to enhance the website's quality, usability, and usefulness, increasing student satisfaction.By doing so, universities can recover the costs associated with website development and maintenance and increase the number of users and the website's value.This highlights the importance of understanding the factors that influence students' intention to use university websites to ensure a positive online learning experience for students and a good return on investment for universities.

Furthermore,
Huang and Chueh (2022) studied the intention to use mobile apps in a membership application.Lin et al. (2020) conducted a study on the adoption of the Nike+ run club app.Nyagadza et al. (2022) examined the intention to use chatbots in e-banking customer service.They all have reported similar results.In keeping with these findings, this study proposes that Generation Y students' attitudes toward university websites influence their usage intention.
depicts the structural model.The goodness of fit of the structural model was assessed based on various model fit indices.Although the model's chi-square statistic was significant [528.46 (df = 236, p < 0.001)], it demonstrated acceptable model fit, as evidenced by the following indices: SRMR = 0.1, RMSEA = 0.06, IFI = 0.94, TLI = 0.93, and CFI = 0.94.

Table 3 .
Measurement model statistics

Table 4 .
Path analysis