2.1 Technology acceptance model (TAM)
Technology acceptance model (TAM) was proposed initially by Davis (1985) to understand behavior in technology adoption. This model was extended by other scholars (Lee et al., 2014; Shen & Chuang, 2010), for example, and became a popular model for studying the elements that influence users' acceptance of technology (Marangunić & Granić, 2015). TAM's goal is to show what motivates individuals to reject or accept a new information technology. TAM allows us to understand the connections between system characteristics (external variables), perceived usefulness (PU), perceived ease of use (PEU), attitude toward technology (ATT), and actual use behavior. TAM incorporates two basic elements as significant drivers that influence users' views of new technology acceptance, namely PU and PEU (Davis, 1989; Khalil et al., 2010).
The current study adopted the original TAM, which has been used by previous studies (Bélanger & Carter, 2008; Khan et al., 2021; McKnight et al., 2002; Trong, 2016) as a theoretical background (Fig. 1) and extended the model with two additional factors consisting of structural assurance (SA), and government regulation (GR) as external variables affecting PEU, according to Davis (1985)
2.2 External variables
Based from TAM shown in Fig. 1, it can be seen that PU and PEU are affected by external stimuli (external factors) to predict attitude toward using a new technology system and drive intention and actual usage of technology. A review of external variables identified in previous studies by Castiblanco Jimenez et al. (2021) shows anxiety, experience, facilitating conditions, innovativeness, self-efficacy, system quality, and social norm as affecting TAM applications. Other studies have also identified trust (Khan et al., 2021), perceived security (Al-Sharafi et al., 2016; Khan et al., 2021; Normalini & Ramayah, 2017), structural assurance (Khan et al., 2021), and government regulations (Zhu et al., 2004) as external variables in TAM applications.
The current research extends the original TAM based on integrating TAM factors and other external variables, in which structural assurance and government regulation are determined as two external factors added to the original TAM which have an effect on PEU. Structural assurance, which enhances trust in the institution, and government regulations are deemed as context-specific.
Structural assurance
Structure assurance refers to the belief that legal and technological structures and policies are developed and executed for technology to achieve a successful outcome on e-government-related services (McKnight et al., 2002). Wang et al. (2010) posit that citizens' strong confidence in e-communications’ security is critical to the success of e-government. Technology trust is linked to institution-based trust. There are uncertainties and hazards involved with online channels due to the intrinsic structure of the Internet infrastructure. Institutional frameworks, such as legal and technological safeguards, can provide the perceived safety of the Internet environment, referred to as structural assurance.
A previous study by McKnight et al. (2002) indicates that structural assurance, as a fundamental component of institution-based trust, means the technological and legal warranty that individual consumers perceive. Based from previous studies (Kim et al., 2009; Kim et al., 2004), a good structural assurance can aid in reducing ambiguity and assuring the safety perception of e-government web sites, thereby increasing citizen trust in e-government. Additionally, prior studies also explored how structural assurance affects trust (Al-Sharafi et al., 2016; Khan et al., 2021). According to Al-Sharafi et al. (2016), to establish citizens' trust in an online world, security problems must be addressed as security mechanisms provide citizens with a sense of security. Moreover, citizens' trust and willingness to rely on e-service providers is enhanced by a sense of security (Salo & Karjaluoto, 2007). Citizens' trust in internet services might be increased if they believe their information is safe from system hacking, malware, or viruses, and they must feel that their information will not be accessed or modified by unauthorized parties during social media interactions with government agencies (Mayeh et al., 2013).
Additionally, the study by Khan et al. (2021) reveals that government organizations broadcast their information, services, as well as other activities online and therefore there is a need for structural assurance to encourage individuals to participate in such services. In this way, the public is more likely to trust social media for e-government services if it can sense that structural assurances can protect its rights. According to Venkatesh and Bala (2008), system characteristics and structure can assist individuals to generate favorable (or unfavorable) judgments of a system's utility or ease of use. Thus, it is hypothesized that:
H1: SA has a positive effect on PEU
Government regulation
Government regulation refers to the legal environment, including government policies, laws, and regulations that are binding and that any organization and individual must comply (Trong, 2016). In the information technology context, government regulations refer to the provisions offered by government authorities to reassure the integration of organizations (Zhu et al., 2006). According to Yimam and Fernandez (2016) and Mohammed et al. (2016), government regulations are sets of policies governing the use of sensitive data with the goal of providing security and privacy through various criterial such as integrity, accountability, availability, and confidentiality. From these definitions, we define it in this study as a legal system that protects users of e-government systems to access and find information of interest to them and encourages citizens to use official government information systems.
According to (Hien, 2017), in Vietnam, 100% of the government agencies have website/portal where online public services are provided, though at low level (i.e. downloading forms) but are continuously expanding. Some of its legal documents related to e-government development are Law on E-transaction (2005), Law on Information Technology (2006), Law on Cyber Information Security (2015), Law on Access to Information (2016), Government’s Decree No 102/2009 on investment management of IT applications and Guidance circulars, and Government’s Decree No 43/2011 on providing information and online public services on the portal/website of government agencies. Existing regulations is critical in new technology adoption (Lian et al., 2014). The study by Hart and Saunders (1997) reveals that legal environment is one of the most important variables influencing user behavior in innovation and the deployment of new technology. By establishing clear and stringent service or product quality norms and requirements, this contributes to protect the product or service users (Qu, 2007). The study by Ali and Osmanaj (2020) shows that government regulations plays a key role in decision making for adopting any new technology. Several prior studies (Ayudya & Wibowo, 2018; Faletehan, 2020; Rahmatika & Fajar, 2019) prove that government regulations enhances e-money usage for payment transactions. Citizens can easily use public e-government services if the government has good regulations and managerial support (Sebetci, 2015). Thus, it is hypothesized that:
H2: GR has a positive effect on PEU
2.3 TAM Factors in the current research
Perceived ease of use
Davis (1989, p. 320) has defined ‘perceived ease of use’ as the “degree to which a person believes that using the system will be free of effort”. It is a critical component for technology adoption and usage (Ozturk et al., 2016), such as when it is easy to comprehend or use (Jen & Hung, 2010). It relates to the evaluation of users on their effort during the progression of using a technology (Venkatesh & Davis, 2000). Hence, this study defines PEU as the public’s perception of how easy it is to find information from and use e-government services.
Previous studies determine that PEU has a positive effect on attitude toward technology (Davis, 1989; Salo & Karjaluoto, 2007; Sebetci, 2015; N. M. Suki & Ramayah, 2010; Taipale, 2013; Venkatesh et al., 2003). The study by Okumus and Bilgihan (2014) has shown the positive influence of PEU in usage intentions of smartphone applications. When people feel that a new system is easy to learn and use, it will be easy for them to adopt the system (Kim et al., 2010; Park et al., 2016). Moreover, PEU drives convenience (Yoon & Kim, 2007), which explains why consumers utilize online shopping (Ozturk et al., 2016). It also enhances loyalty of the users when technology seems easy to use and functional (Lee et al., 2015).
Also, the effect of external variables, such as structural assurance and government regulations, on attitude towards technology is mediated by PEU. According to Rogers (2010), perceived ease of use denotes the degree in which any change is perceived as easy to operate, understand, or learn or it may also represent the degree in which an individual perceived a new service or product as better than its substitutes. If the users of e-government services perceived e-government system as less complex and that structural assurance are perceived to be helpful, then there is a greater chance for the system to be accepted and be widely-used as the system will be perceived as convenient, easy to use, and free of mental or physical effort. Thus, it is hypothesized that:
H3: PEU has a positive effect on ATT
H4: PEU mediates the relationship between SA and ATT
H5: PEU mediates the relationship between GR and ATT
Attitudes toward technology
Attitude toward technology (ATT) is known as the degree of user's interest in a particular system and this directly affects intention and behavior to use that system (Davis et al., 1989). According to Modahl (1999), the use of technology is a polarizing influence in which people will either like the technology or not. Attitude, as defined by Eagly and Chaiken (1993), is the psychological tendency conveyed when evaluating something with some element of approval or disapproval. According to Ajzen and Fishbein (1980), it refers to the degree as to how much a person favors or disfavors something. In this study, it refers to positive attitude toward using e-government system to search for general information.
We argue that a positive attitude towards e-government system would drive its usage by the general public. The positive relationship between ATT and use behavior of technology system have been established in several previous studies (Davis, 1989; Salo & Karjaluoto, 2007; Sebetci, 2015; N. M. Suki & Ramayah, 2010; Taipale, 2013; Venkatesh et al., 2003) in different contexts. Orgaz et al. (2018) prove that user’s attitude toward technology influences their perception about the use of technology. Therefore, we hypothesize that:
H6: ATT has a positive effect on looking up general information from official government information system (e-government use).
2.4 Demographic factors as mediators
In the current study, demographic factors comprise income and education level of participants. Education levels were measured at 7 levels, from 1- elementary graduate to 7-doctorate while income was measured by six corresponding levels, from 1-under 3 million VND to 6-above 15 million VND.
Previous research has shown that some demographic factors influence the effects of different independent variables and e-government use in research models (Mpinganjira, 2015; Nam, 2014; Silcock, 2001). Specifically, Nam (2014) indicates that demographic factors influence e-government use as well as user’s adoption in looking up information from the government information system. Additionally, the primary motivation for using e-government services is to meet an actual need, rather than satisfaction, habit, or utility, and therefore the user's capacity is also an essential factor (Kamal, 2020). Besides, people's abilities and competences in using technology differ by age and education level, while family circumstances are linked to a variety of service demands (Carter, 2008; Carter & Bélanger, 2005; Horst et al., 2007; van Dijk et al., 2007).
Moreover, education is demonstrated to be the most important predictor of e-government service use and attitudes; with increasing levels of education, adoption rates increase and attitudes improve (van Dijk et al., 2007). The amount of knowledge one has about how to use a new technology is related to the decision to embrace it, and complicated technologies, such as e government, necessitate greater understanding (ElKheshin & Saleeb, 2020). Early adopters of new technology had a higher educational level, which may reflect their ability to grasp "how-to" knowledge faster than people with less education (E.Rogers, 1995).
Additionally, education is frequently mentioned as a factor that influences people's attitudes and behaviors. (Wang et al., 2021). ATT increases with education level (Matikiti et al., 2018) while e-government use rises with income level or family condition (Jyoti & Yogesh, 2005; Taipale, 2013). In addition, in a study on exploring difference in technology-use based on social-economic situation, Yardi and Bruckman (2012) find that in comparison to low-income families, high-income households own and use more technology. High-income households, in particular, are more likely to use the Internet on a daily basis and to own numerous Internet-enabled devices. They also have a greater number of mobile devices. Employee studies suggest that the higher the socio-economic status, the higher the rate of acceptance of e-government (Jyoti & Yogesh, 2005; Nguyen et al., 2020). According to Jyoti and Yogesh (2005), Reddick (2005) and Bélanger and Carter (2009), the higher one's income, the more likely one is to use public e-services and perform online transactions with the government. Therefore, the following hypotheses are proposed:
H7: The effect of PEU on ATT increases with education
H8: The effect of ATT on looking up information from the e-government information system (e-government use) increases with income.
Figure 2 summarizes the conceptual model of the study on the basis of Technology Acceptance Model and extending it to e-government usage for general information in the Vietnam context. External variables (SA and GR) are also proposed as drivers of PEU, which then drives a positive ATT.