The earliest theory to clarify the prediction of individuals’ behavioral intentions is called TRA [10]. According to the theory of reasoned action, an individual’s attitude (beliefs and emotions) towards something motivates their behavior. Additionally, an individual’s behaviors are driven by social influence, often known as subjective norms; pressure from influential people is a common concern that can make people change the way they think and act [11]. Regarding the adoption of technology, ref. [12] highlights the fact that individuals are comfortable in forming opinions that are impacted by family members and friends. Nonetheless, TRA skeptics have long argued that individual choice must be acknowledged before any meaningful change in behavior can occur [13]. As a direct result of this, the theory of reasoned action (TRA) was revised to become the theory of planned behavior (TPB) [14].

According to TPB, which merges TRA with perceived behavior control, a person’s actions are influenced by how much willpower, personality, and passion they believe they have [15]. Previous research has found that the theory of planned behavior falls short in explaining human behavior, because other elements, such as fear, mood, and past experiences, are thought to be more important in elucidating motives [16]. The theory of planned behavior takes normative impacts into concern but ignores environmental, emotional, or financial aspects that might have an impact on actual behavior [17,18]. Although the theory of planned behavior places importance on perceived behavioral control, it says nothing about real behavioral control [9]. The research has formed this idea and produced more branching theories [14]. In addition, the research has shown that there is a deficit in the existing literature about the usefulness of the theory of planned behavior in relation to people’s behaviors towards technologies. This was discovered by the researchers of [19].

Researchers have created a technology acceptance model to fill the gap between the theory of reasoned action and the theory of planned behavior in understanding people’s behavior towards technology [16]. The objective of the technology acceptance model (TAM) is to provide explanations of the elements that influence customer adoption that can be applied to a variety of advancements and improvements [13]. Perceived usefulness, which indicates the feeling that using a technology would boost one’s performance, and perceived ease of use, which declares that one believes that utilizing the technology will be free of effort, are the two beliefs that, according to TAM, shape attitudes towards technology usage [16]. The technology acceptance model’s limitations have been mentioned as a subject of contention. The technology acceptance model ignores the effects of human variances and contextual influences on how successfully a technology is embraced [20,21]. Moreover, previous studies on the technology acceptance model have concentrated on reasoning, information, and rationality rather than emotions (understanding through feelings and attitudes). According to recent studies, placing a strong emphasis on understanding may be acceptable for forced and constrained consumer technology acceptance. This is not a good explanation, because customers can decide whether to embrace new technology based on their feelings and beliefs [22]. To understand more about how customers adopt technology, the research has revised and improved the TAM because of its lack of clarity [9,23,24]. The research still believes that amendments to the technology acceptance model (TAM) can only partially account for technological adoption [9]. Ref. [24] states that intrinsic motivation, such as enjoyment, has a large effect on how people accept technology when combined with the technology acceptance model. Ref. [25] states that emotions play a large role in how people use technology, and that both hedonic and utilitarian incentives can affect how people use technology. In order to understand consumers’ technological behaviors, further research has included emotional responses in the technology acceptance model, bridging some of the gaps and overcoming some of the challenges [22].

According to the research, customers evaluate various mental readiness indicators and emotions before using a technology; these emotions might include contentment, courage, and self-assurance as well as resentment, doubt, and worry [13]. A technology readiness index theory was developed by [26] to demonstrate the dichotomy of feelings that users have when thinking about utilizing new technologies (either positive or negative technology-related attitudes). How likely a person is to use a new technology depends on these ideas. The four facets forming these beliefs are: optimism, inventiveness, discomfort, and insecurity. Optimism is the idea that technology boosts workplace productivity; innovativeness is the belief that consumers plan to utilize a new technology; discomfort is the belief that technology is confusing because it is challenging to control; and insecurity indicates mistrust and suspicion towards technology’s ability to function as intended [27]. The technology readiness index fills a further gap in the technology adoption paradigm by displaying individual mental attributes as forerunners of the cognitive components [27]. According to [28], consumers build positive values as a result of the dimensions of optimism and inventiveness, whereas consumers develop negative values as a result of the dimensions of discomfort and insecurity. According to [13], customers might quickly decide to embrace or decline a technology based on their personal beliefs; this can be used to explain m-government adoption in Egypt.

The UTAUT was developed by the authors of [9]. This theory states that performance expectancy, effort expectancy, facilitating conditions, and social influence all have a significant impact on predicting behavioral intentions to use a technology. This is a unified model that combines past theories related to technology acceptance [9]. Ref. [29] tried to clarify the UTAUT model’s elements, in which the authors examine the connection between students’ opinions regarding computerized placement exams and their desire to utilize e-placement tests. The study examines four factors that affect students’ attitudes: performance expectations, effort expectations, social influence, and enabling circumstances. College students in Taiwan were given legitimate survey questionnaires to complete in order to gather information. Out of the four main components, performance expectation, effort expectancy, and social influence were revealed to have a significantly favorable impact on attitude. Additionally, ref. [30] examined the connection between behavioral intention and the UTAUT model (performance expectancy, effort expectancy, social influence, and facilitating conditions), employing attitude as a mediator. Structural equation modeling was used to examine the data, which was collected from 169 university students in Saudi Arabia via an online survey. Only attitude, it was discovered, affected behavioral intention. Expectations of performance, expectations of effort, social influence, and enabling environment all had an impact on attitude.

The authors of [31] tried to assess academics’ acceptance of electronic media using the qualitative analysis software NVivo and came up with the result that e-learning platforms are not extensively utilized by academicians. Another study [32] attempted to assess teachers’ perceptions using the qualitative analysis tool Nvivo. The authors used qualitative methods to investigate the perspectives of 12 higher education teachers who had used Google Classroom for at least one semester and found that Google Classroom is merely a document management tool with no significant impact on teaching methodology. Ref. [33] examined university staff acceptance of Moodle and the perceptions of nine faculty staff members with the interview method and came up with the results that performance expectancy, effort expectancy, social influence, and facilitating conditions had a significant and direct effect on behavioral intention.

As part of the technology acceptance model (TAM) framework, attitude is often defined as someone’s positive or negative feelings towards the execution of a target behavior (e.g., using technology) [16]. Meanwhile, behavioral intention is defined as the intention of a customer to approve of and utilize a particular tool in the future [9,15]. Ref. [34] also sought to examine how behavioral intent to embrace technology affected expectations for effort, performance, social influence, and enabling circumstances. Data were collected from 192 aid professionals who had participated in various crises. Behavioral intention to use technology was positively influenced by performance anticipation, effort expectancy, social influence, and enabling situations, according to the findings.

Additionally, ref. [35] intended to look at how social influence, performance expectations, and effort expectations influence behavior when it comes to using social networking apps (Facebook, WhatsApp, WeChat, Twitter, Instagram, YouTube, Snapchat, and others). The data collected from the surveys conducted among users of social networking apps included responses from 384 valid participants. These participants were students from six different colleges in Malaysia. The results showed that behavioral intention toward social networking applications was impacted favorably by performance expectation, effort expectancy, and social influence.

Openness and transparency are seen as phenomena that provide important knowledge and relevant information about citizens’ expectations [36,37]. Currently, openness and transparency are advancing as public interactions with the government increase and conflicts decrease [38]. Openness and transparency in government refer to the evaluations and comprehension of as well as the significance placed upon public service to implement ongoing enhancements and produce outcomes [39].

Good governance must adhere to the principles of openness and transparency in order to successfully regulate and manage public resources [40]. As a result, active public engagement in decision making, community compliance, and a rise in public trust in government are all influenced by openness and transparency in the supply of government information [40,41]. In times of national and international emergencies, the public is expected to receive information that is open, transparent, and free from political manipulation and distortion. That is, information and communication intended for the general public should be truthful, open, and free from political content [42].

According to a survey across different EU fields, the application of ICT with social media integration skills might promote openness and transparency in the government sector [43]. IT experts used an e-government survey to conduct a number of ICT-based studies and came to the conclusion that e-government is not only a reality but also a requirement for people to meet their needs in a more open, transparent, and responsible way [44].

Transparency and openness in government services refer to the extent to which government agencies provide accessible and reliable information to the public [45]. These principles are crucial in enhancing trust and accountability, as they allow citizens to hold their governments accountable for their actions and decisions. Furthermore, transparency and openness empower citizens by enabling them to make informed choices and participate actively in the democratic process [46]. Ultimately, these principles foster a more responsive and responsible government that prioritizes the needs and interests of its citizens [45].

Product usage varies depending on consumers’ personal factors. According to the research, each segment of the population holds their own personal preference or attitude towards technology usage [11]. Therefore, when it comes to technology, not all segments of the population hold similar opinions [9,11]. This section investigates the role of demographics in enhancing users’ behavioral intentions. Ref. [47] used attitude towards using technology as a moderator to examine the association between performance expectation, a UTAUT component, and behavioral intention. The results showed that age influenced the association between behavioral intention and performance expectations. Ref. [48] examined the impact of UTAUT variables (performance expectancy, effort expectancy, social influence, and facilitating conditions) on behavioral intention utilizing gender, age, and experience as moderators. The results showed that the association between behavioral intention and performance expectancy, effort expectancy, social influence, and facilitating conditions did not depend on age, gender, or experience as moderators.

Egypt started investing in communication and IT infrastructure in 1985, while it was still undergoing economic transition and development. The Egyptian e-government initiative was formally established in 2001, with the purpose of offering innovative and value-added technology to citizens and companies in order to provide high-quality public services [2]. Egyptians are presently provided with more than 100 transactional services. This extensive range of services in dual languages (English and Arabic) will be supported by the e-government platform’s framework, which will eventually be expanded to include up to 700 services. The e-government has provided quite a restricted number of services through phones and tablets, such as sending SMS voting information [49]. Egypt is currently struggling to overcome a variety of challenges that have prevented it from fully implementing m-government applications. In contrast to other nations across the world, Egypt is still in the early stages of m-government development [50].

Ref. [51] discusses some of the challenges that the Egyptian government is experiencing. Among these difficulties are the lack of an e-signature mechanism, privacy and security issues, e-payment transaction obstacles (credit card penetration is low, and there appears to be a paucity of payment tools for ordinary citizens), delivery mechanism inconvenience and its impacts on the reputation of e-services’ quality, low internet penetration rates, as well as a lack of computer literacy. These concerns have been raised regarding a lack of citizen awareness and engagement; reluctance towards and mistrust of automation; and rigidity towards change.

The Ministry of Communications and Information Technology (MCIT) has begun constructing Digital Egypt as part of Egypt’s digital transformation strategy and in line with Egypt Vision 2030. The goal of Digital Egypt is to turn Egypt into a digital society, and the strategy is comprehensive. “Digital Egypt” rests on many crucial pillars to facilitate this shift towards a digital society and to create a robust digital economy, as shown in Figure 1. Yet, a beginning has been made, for instance, with IDSC and smart electricity services [52].

To deliver public services more quickly and easily, Egypt has been implementing a solid plan and a strong course of action to transition the current community ecosystem and government services into a totally digital and data-driven ecosystem. MCIT aims to create public benefit by making it easier for people to access government services and information and by making it more efficient for the government to operate [52].

The MCIT collaborates with all parts of the government to make digital change happen. This is achieved through two pillars: providing services to people and making the government work better. All public services will be offered online, all over the country, to all citizens. Regardless of where they reside in the country, Egyptians will have access to these services in digital format. Several online payment options for service fees have been established [53].