Explicating Trust-building Factors Impacting the Use of e-government Services

Abstract

This study investigates the users’ perception of trust-building factors influencing the use of e-government services and information, by integrating constructs identified in the technology acceptance model (TAM) with information systems (IS) success and trust models. Data was collected using a questionnaire targeted towards users of e-government services in Kuwait. The partial least squares structural equation modeling method was used to analyze 717 valid questionnaire responses. The results indicate that information quality and design (IQD) and perceived ease of use (PEU) influence individuals’ trust in e-government (TEG), thereby affecting their behavioral intentions (BI). Furthermore, the results indicate an average level of the users’ satisfaction and significant differences in how gender and nationality are associated with the overall satisfaction of e-government services users. The proposed framework contributes to extending models by integrating IQD (a modified construct of the IS model) and PEU (a construct of the TAM) as trust-related factors that provide better insights into the driving forces of BI and should be considered when designing and developing e-government services. Additionally, the study provides a deeper understanding of the challenges that could hinder the use of e-government systems.

Keywords

e-government services technology acceptance model information systems success model trust in e-government information quality and design Kuwait

The coronavirus global pandemic has compelled many governments to pay particular attention to digital transformation and make changes to business processes for improving the system and delivering efficient and effective services. Accordingly, many organizations worldwide are managing their operations using innovative information and communications technology (ICT) solutions to ensure process continuity. E-government solutions have been increasingly adopted to maintain social distancing and control virus transmission (Mensah et al., 2022). The pandemic has shown that governments can be agile, adaptive, and efficient in managing emergencies when business processes are rapidly and spontaneously redesigned (Gabryelczyk, 2020; Janssen & van der Voort, 2020; Mizrahi et al., 2021). The changes in processes are reflected in the quality and quantity of tasks performed by employees (Gabryelczyk, 2020) and have also impacted the services offered to the public. In particular, IT-based solutions have been implemented to offer electronic information and services; these solutions include websites, social media networks, and mobile applications (Mensah et al., 2022).

The adoption of the e-government services has been affected by numerous factors identified in various models. For example, ElKheshin and Saleeb (2020) found perceived usefulness (PU) and perceived ease of use (PEU) of the technology acceptance model (TAM) by Davis (1989), affected individuals’ behavioral intention (BI). Other factors were found by Almaiah and Nasereddin (2020) including performance expectancy, effort expectancy, and facilitating conditions of the unified theory of acceptance and use of technology model (UTAUT) by Venkatesh et al. (2003). Xie et al. (2017) also found subjective norms and perceived behavioral control of the theory of planned behavior (TPB) by Ajzen (1991) affecting the BI in adopting e-government services. Researchers have also identified other factors that positively influence the BI of using e-government services. These include trust (Al Mansoori et al., 2018; AlAwadhi, 2021; Almaiah & Nasereddin, 2020) and website quality (Almaiah & Nasereddin, 2020; Okunola & Rowley, 2019). User satisfaction has also been the main focus (Bournaris, 2020) in attaining interaction and service adoption (Al-Kaseasbeh et al., 2019).

E-government strategies rely heavily on trust as a key component to increase recommendations from users to potential users. Several governments have experienced difficulties in providing efficient, responsive, and effective services, which negatively impacted users’ trust. Trust is a complex concept that underpins numerous relationships in e-government. Adopting electronic services will remain a challenge until individuals trust the government’s portals, processes, information, and other components (Alzahrani et al., 2017). In addition, trust is a factor that strongly relates to and affects attitudes toward e-government adoption (Xie et al., 2017). Papadopoulou et al. (2010) suggested considering trust in designing and deploying an e-government system, as it is considered an integral part of e-government.

Moving toward an information-based society and promoting inclusive and sustainable economic growth, Kuwait initiated an e-government project in the year 2000. Kuwaiti government departments have greatly invested in building an ICT infrastructure capable of supporting e-government projects to improve government performance, enhance the provision of government services, enable easy access to government information, and promote transparency (AlAwadhi & Morris, 2009). In addition, the project has experienced a substantial transformation and provided services to various stakeholders through a universally accessible portal (Kuwait Government Online, 2021). The portal is designed to meet international technical standards and ensure the highest usability, functionality, and security rates. It continuously provides government services, data, and information, in both Arabic and English.

During the COVID-19 pandemic, the government of Kuwait imposed restrictions that prompted ministries to provide services online, not only to curb the rapid transmission of the coronavirus but also to prevent the suspension of government services (Kuwait News Agency, 2020). Therefore, the Kuwaiti public was obligated to access government services online via ICT tools.

The United Nations e-Government Survey in 2020 (United Nations, 2020) reported that Kuwait is one of the Middle Eastern countries that developed the 2035 Vision. The vision aims to enhance digital transformation initiatives (including e-government) to pursue sustainable development. Among the 193 countries, the UN survey that measures e-government performance ranked Kuwait 46th, compared with 63rd in the year 2012, indicating a substantial development in Kuwait since 2012. However, despite Kuwait’s highly developed telecommunications infrastructure in the year 2022, its rank has dropped to 61st, indicating a decrease in the E-Government Development Index scores. In addition, the e-participation index shows a decline in Kuwait’s rank which dropped from 18th in 2020 to 67th in 2022 (United Nations, 2022). This has raised concerns regarding the success of e-government through user experience, trust, and adoption of effective and efficient e-government services. Other concerns related to the challenges that have deterred individuals from using these services.

Several researchers have explored Kuwait’s e-government from both the supply side (Alenezi et al., 2017) and the demand side (Aladwani, 2013; AlHussainan et al., 2022). However, more rigorous studies are still required to provide insights and understandings of the factors that increase the adoption of e-government services from the demand-side perspective. Moreover, the challenges that could negatively influence the use and effectiveness of e-government systems need to be identified and addressed.

Therefore, this study aims to investigate the users’ perception of factors influencing trust that impact the adoption of e-government services and information by integrating factors identified in the TAM, IS, and trust models. It also aims to identify the challenges that could prevent individuals from using e-government services. The objectives of this study are as follows:

1. Identifying the antecedents of trust factors that influence individual BI to use e-government services.

2. Exploring the demographic factors that influence user satisfaction with e-government services.

3. Determining the barriers that affect trust and impede the use of e-government services.

This study, hence, contributes to the body of knowledge regarding the adoption of e-government services. Additionally, it serves as a guideline for decision makers to develop and apply effective strategies that improve the provision of e-government information and services.

Literature Review

In this section, the literature pertaining trust in e-government (TEG) and its relation to other factors is reviewed. The key challenges that prevent or hinder individuals who are using or expected to use e-government services are also discussed.

Trust in e-government

Trust in e-government was investigated by several researchers, who found that it is constituted by trust in technology (TT) and trust in government (TG). For example, Belanche et al. (2014) empirically investigated the continued usage of e-services and found that trust in public e-services relies on the trust in public administration and TT. Alzahrani et al. (2017) critically reviewed the literature and confirmed that TEG is comprised of both TT and TG. Additionally, Li and Xue (2021) explored the factors influencing post-use of TEG. The results showed the critical role of TEG use, which was found to be influenced by TT, TG, service quality (SQ), and IQ. Capistrano (2020) employed a conceptual framework developed using the dimensions of the information system (IS) success model and trust models. The findings revealed that TT and IQ were significant drivers toward building TEG.

Several studies integrated trust with technology acceptance models and theories following two approaches. The first model approach places trust as an antecedent to other factors that lead to the BI. Samuel et al. (2020) expanded TAM and found that trust significantly influenced the PU, thus leading to BI to use e-government. Similarly, Mensah (2020) established that political trust played two roles in the use of e-government services. It predicted the PEU and intention to use e-government, and also moderated the influence of both PU and PEU on the intention to use e-government services. Wu and Chen (2005) found that trust was more significant in determining users’ attitudes than PU and PEU of online services. In addition, trust was found to be an important antecedent of perceived behavioral control, attitude, and subjective norms, thereby contributing to BI to use online tax platforms. Li and Xue (2021) explored the factors influencing post-use of TEG. They surveyed 1867 e-government users using a conceptual framework that identified several factors. Their results showed the critical role of TEG use, which was found to be influenced by TT, TG, SQ, and IQ.

The second approach identifies trust as a variable that is dependent on several antecedents. Aljazzaf (2019) developed an e-government trust model to identify factors influencing individuals’ TEG. The results showed that the PU, PEU, security, and website quality, perceived quality, social influence, trust in the internet, and TG significantly influence citizens’ TEG. Moreover, TEG strongly influences BIs. AlAwadhi (2023) investigated the role trust plays in the adoption of e-government information and services which leads to individuals’ civic engagement in Kuwait. The relationships between the TT, PU, TEG, and the BI to use e-government and civic engagement were confirmed.

Balaskas et al. (2022) adopted the TAM to investigate TEG as a factor that influenced citizens’ use of e-government services during COVID-19. The results indicated that, during the emergency conditions, the role of TEG factor arose and was influenced by TG and TT, security and privacy, social influence and performance expectancy. Moreover, TEG played a critical role in adopting the current as well as future e-government services.

Information Quality and Trust

Several researchers found that “information quality” (IQ) is associated with the citizens’ trust and necessary to the success of e-government, for example, Li and Xue (2021), Capistrano (2020), Salaün and Flores (2001), and Gefen (1997). Lee and Levy (2014) confirmed that IQ had influence on TEG systems and identified three information quality factors that reflect reliability and positive parameter estimates. However, only the two factors of accessibility and representation significantly contribute to trust. Santa et al. (2019) also found that significant relationships existed between attitudes toward trust, IQ, and the system. Hooda et al. (2023) incorporated e-government trust in the IS success model to explore the use of e-government services. They meta-analyzed 67 studies and found that users’ e-government trust was created by the quality dimensions of the IS success model (information quality, system quality, and SQ). Moreover, user satisfaction had influenced e-government trust. In the same vein, Kanaan et al. (2023) found positive and significant influences of quality factors (information quality, system quality, and SQ), perceived security and perceived privacy on TEG. Also, there was a significant association between TEG and intention to use e-government.

During the COVID-19 pandemic, AlHussainan et al. (2022) identified factors that influenced the quality of e-government services in Kuwait. Their results showed that a functional e-government portal enabled citizens to interact online and conduct business transactions effectively. Content reliability and information availability were identified as important factors affecting SQ. It was also found that COVID-19 moderately influenced the correlation between reliability, trust, and citizens’ support with e-government SQ. Conversely, when Alawneh et al. (2013) explored citizens’ perceptions of the e-Government portal in Jordan, they found that security, privacy, and trust had no significant influence. However, accessibility, awareness, and quality of public services were found to have a significant positive influence on citizens’ e-satisfaction levels.

Alkraiji and Ameen (2022) surveyed university students to investigate the effects of SQ, TG, TEG, and citizen satisfaction on loyalty to e-government services, represented in a unified system for university admission. Their findings showed that TG and SQ had strong effects on student loyalty, which can help foster a sense of commitment to e-government services. Similarly, Noori (2022) found a significant relationship between e-SQ, user satisfaction and loyalty in accessing e-government services and information. Alsarraf et al. (2022) found a positive relationship between SQ and satisfaction, thus finding a positive relationship with TG.

Challenges of E-government Adoption

Researchers have identified the challenges encountering the progress of e-government since its implementation; for example, Al Nagi and Hamdan (2009); Dwivedi et al. (2012); Zhao et al. (2012), and Meiyanti et al. (2018). The challenges are related to various issues such as IT infrastructure, management, financial, digital divide, laws and legislation, and human resources. Such challenges would negatively act as barriers that reflect on individuals’ behavioral intentions to use e-services. Sharma et al. (2021) identified 15 key challenges which were hierarchically represented. They found “lack of digital literacy” as a base to other challenges. At the next level came the challenges related to “lack of awareness,” “longer travel time and transaction cost”, which might prevent users from realizing the benefits gained from the e-services. The next level included challenges related to infrastructure such as “lack of infrastructure,” “problem of dormancy,” “lack of interoperability,” and “technology and networking challenges.” Improper infrastructure would lead to inefficient services, which could cause users to look into other tools. Other challenges such as “resistance to change” and “privacy and security issues” were mainly related to “lack of trust.” Therefore, the enhancement of trust would overcome all other challenges. Arief et al. (2021) also identified the barriers of e-government services distributed in three main domains. The technological domain included security and privacy, IT infrastructure, and features of the user interface. The institutional domain included change resistance, financial issues, laws and regulations, and administrative conflicts. The people domain included cultural issues, digital divide, and lack of skillful human resources. Such challenges would affect the progress of the e-government stages, which consequently affected citizens’ adoption.

Revyakin and da Rocha (2021) explored the level of e-government use. They found that although internet penetration was high, the use of public e-services was low. The low use was attributed to various factors, such as lack of skills, low trust in services, unavailability of devices, and inadequate appropriate experience. Similarly, Maharaj and Munyoka (2019) deduced that privacy, security, trust, and risk influenced the utilization of e-government systems. Specifically, there was an inverse relationship between users’ trust and perceived risk. Once trust levels increase, perceived risk in using e-government systems decreases.

Research Model and Hypotheses

Several models and procedures have been adopted in e-government research to identify factors influencing the usage of e-government information and services (Al-Khatib & Lee, 2013). Heeks and Bailur (2007) stated that the use of models in empirical research enhances knowledge-building and academic legitimacy. Therefore, this study proposes a model that integrates the constructs of the IS and trust models with the TAM to provide insights into the use of e-government services. The proposed model incorporates independent variables that may influence the dependent variable, which is the BI to use e-government services, focusing on the TEG factors. All the relationships between the variables adopted from the models are discussed in the following sections.

Information Quality and Design

As e-government users deal with information provided by government agencies, IQ is considered an important factor in evaluating the success of IS (Lee & Levy, 2014). Information quality, which is one of the core constructs of the IS model, measures semantic success, which is concerned with “accuracy, timeliness, completeness, relevance, and consistency” (DeLone & McLean, 2003). It has been operationally defined as “information that is good, useful, current, and accurate” (Lee & Levy, 2014 p. 79). Prior research, such as that by Capistrano (2020), revealed a significant association between IQ and TEG. In particular, dependability, completeness, and representational information quality factors have been found to affect citizens’ TEG systems (Lee & Levy, 2014). For our study, IQ was considered valuable as it measures the availability, accuracy, completeness, and currency of information, thereby positively affecting TEG. Further, the overall system design was added to the IQ factor to provide a comprehensive overview of the organization of the e-government system, which should be easy to use. Therefore, the following hypotheses are proposed:

H1:

Information quality and design (IQD) positively affects PEU.

H2:

Information quality and design positively affects TEG.

Perceived Ease of Use

In the TAM, PEU was found to predict PU, both of which affect attitude. Perceived ease of use has been defined as “the degree to which a person believes that using a particular system would be free of mental effort” (Davis, 1989, p. 320). ElKheshin and Saleeb (2020) found that PEU affects PU and attitude, thus positively affecting the e-government adoption process. Additionally, TEG has been found to directly predict ease of using e-government systems. Similarly, Wu and Chen (2005) found that trust influences PEU and PU. In the current context, as the public in Kuwait is required to use government services online and access the required information through various government websites and applications during the COVID-19 pandemic, PU has become less important to include in the model, whereas the perceived ease of using e-government services and locating information has become important to explore. Moreover, the PEU is likely to have a positive influence on users’ TEG. Therefore, the following hypothesis is proposed:

H3:

Perceived ease of use positively affects TEG.

Trust in e-government

Individuals use e-government services because they trust the government and technology. Trust in e-government, which comprises both TG and TT (Bélanger & Carter, 2008; Papadopoulou et al., 2010), has been defined as “the willingness of the trustor to rely on a trustee to do what is promised in a given context, irrespective of the ability to monitor or control the trustee, and even though negative consequences may occur” (Aljazzaf et al., 2010, p. 168). Alkraiji and Ameen (2022) found that higher levels of TEG positively impact citizens’ satisfaction, thereby developing loyalty to e-government services. Although some research has considered trust as an antecedent of other factors, such as attitude, perceived behavioral control, and subjective norm (Xie et al., 2017), in the proposed model, trust is considered a factor that influences individuals’ BI to use e-government services. Belanche et al. (2014) found that trust in e-services helped users maintain their intentions to use e-services. Aljazzaf (2019) also found a strong relationship between TEG and BI to use it. In summary, the following hypothesis is proposed:

H4:

Trust in e-government positively affects individuals’ BI to use e-government services.

Moreover, to investigate whether there are any indirect relationships between the identified factors, the following hypotheses are developed:

H5:

Trust in e-government mediates the relationship between IQD and BI.

H6:

Trust in e-government mediates the relationship between PEU and BI.

H7:

Perceived ease of use mediates the relationship between IQD and TEG.

H8:

The relationship between IQD and BI is mediated by PEU and TEG.

Research Methodology

This study used the quantitative research design. Data was obtained using a questionnaire that targeted the public in Kuwait who were users of e-government services. The questionnaire was developed to include three main sections. The first section was formed to obtain demographic information. The second section included questions on the use of e-government services, and those who used the services were able to proceed to the constructs section. However, those who did not use e-services were asked to report the reasons for their nonuse. The last section included items on constructs identified in the research model regarding IQD, PEU, TEG, and BI. In addition, two questions on users’ overall satisfaction of e-government services were added. The items of the constructs, measured on a five-point Likert scale ranging from (1) strongly disagree to (5) strongly agree, were adopted from previous studies and modified to reflect the context of the study; see Table 1. Furthermore, the questionnaire included open-ended questions regarding the challenges that users may encounter when using e-services, in addition to suggestions that would improve e-government. The questions were developed in English and were back-translated, as recommended by Brislin (1970), into Arabic to allow the questions to reach a wider audience. A panel of five experts, including faculty members and statisticians, reviewed the questionnaire for its structure, word usage, and scale appropriateness. In addition, based on the experts’ comments and suggestions, the questionnaire was modified. Prior to distribution, the questionnaire was tested using a pilot sample of 50 participants to ensure content validity and reliability. Furthermore, necessary analyses, changes, and corrections were made accordingly.

Table 1.

Research Constructs.

Construct	Abbreviation	Items	Source	Items
Information quality and design	IQD	4	Lee and Levy (2014); DeLone and McLean (2003); Capistrano (2020); ElKheshin and Saleeb (2020)	(IQD1) The general designs of e-government websites and applications are aesthetically pleasing.
				(IQD2) There are variety and comprehensiveness of the services available.
				(IQD3) The information available on the websites and applications is adequate and accurate.
				(IQD4) Information is constantly updated on websites and applications.
Perceived ease of use	PEU	4	Davis (1989)	(PEU1) The response of government agencies to inquiries about e-services is quick and effective.
				(PEU2 It is easy to access information available on government websites and applications.
				(PEU3) The transactions are completed quickly and efficiently.
				(PEU4) The instructions and educational aids available on the websites contribute to the development of my skills to use electronic services.
Trust in e-government	TEG	4	Alkraiji and Ameen (2022); Belanche et al. (2014); Twizeyimana and Andersson (2019)	(TEG1) Electronic applications contribute to increase confidence in government services.
				(TEG2) Government services have become more secure and confidential to use.
				(TEG3) I notice an increase in transparency in the work of the government sector in terms of following up and completing government transactions and providing the necessary information.
				(TEG4) The government provides electronic services to enable individuals to participate and achieve transparency.
Behavioral intention	(BI)	3	Shyu and Huang (2011); Xie et al. (2017)	(BI1) I will contribute to spreading the e-government links among friends and family.
				(BI2) The integration between government agencies has contributed to increase my desire to use e-government.
				(BI3) The interaction of citizens with the government has improved through their use of government websites and applications.

Owing to the low cost, time efficiency, increased frankness and rate of responses, as well as improved efficiency of data collection, an online questionnaire was selected to be distributed to the target sample (Huffman, 2006). In addition, it is easier to distribute online questionnaires to as many participants as possible. The study targeted individuals residing in the six governorates in Kuwait who were eligible to use e-government services. Therefore, a stratified random sample was employed in the study to ensure that various population compositions in the six governorates were covered. The researchers shared the questionnaire link, generated by SurveyMonkey, through e-mail and social media platforms, with acquaintances who were asked to fill in the questionnaire and forward the link to other individuals to expand reach to the largest number of e-government users possible. The researchers followed up the number of completed questionnaires in each governorate. They then communicated with acquaintances in governorates in which the responses were too few in order to encourage more participation. The questionnaire made it clear that each participant’s contribution was voluntary and that their information would remain anonymous and confidential. The link was available for 2 months and 1004 responses were received, 717 of which were completed by e-government users and analyzed. Prior to performing inferential analysis, the content validity of each construct in the proposed model was examined. Cronbach’s alpha was used to measure the reliability, whereas the discriminant validity was measured using the Fornell and Larcker (1981) criterion (Ali et al., 2018; Hair, Hult, Ringle, Sarstedt, et al., 2017). Furthermore, partial least squares structural equation modeling, a multivariate data analysis, was employed to examine the relationships between multiple sets of variables (Hair, Hult, Ringle, & Sarstedt, 2017). IBM SPSS statistics version 28.0 and SmartPLS version 3.3.9 were used to analyze the collected data.

Findings

Table 2 presents the demographic characteristics of the respondents. Approximately 55% of the respondents were female and 45% were male. Most were from the age group of 36–45 (n = 194, 27%), followed by 46–55 (177, 25%). More than half of the respondents had a bachelor’s degree (56%), and the majority were Kuwaitis (89%). The distribution of the respondents per governorate revealed that 27% of them were from Hawalli and 26% from the Al-Asimah, whereas more than half of them were employed in the government sector (57%).

Table 2.

Respondents’ Demographic Information (N = 717).

Demographics	Number of Respondents	Percentage (%)
Gender
Male	322	44.9
Female	395	55.1
Age
Less than 25	73	10.2
25–35	157	21.9
36–45	194	27.1
46–55	177	24.7
More than 55	116	16.2
Education
Intermediate and less	7	1.0
High school	50	7.0
Diploma	119	16.6
Bachelor’s degree	401	55.9
Post-graduate	140	19.5
Nationality
Kuwaiti	640	89.3
Other nationalities	77	10.7
Governorate
Al-Asimah	185	25.8
Hawalli	190	26.5
Farwaniya	64	8.9
Mubarak Al-Kabeer	125	17.4
Ahmadi	79	11.0
Jahra	74	10.3
Occupation
Student	69	9.6
Employee—government sector	409	57.0
Employee—private sector	75	10.5
Retired	122	17.0
Business owner	21	2.9
Housewife	14	2.0
Unemployed	7	1.0

Test of the Measurement Model

Cronbach’s alpha was used to measure the reliability of each measurement scale. Generally, data are considered reliable if the Cronbach’s alpha value is >.7 (Hair, Hult, Ringle, Sarstedt, 2017). As presented in Table 3, the Cronbach’s alpha values for IQD, PEU, TEG, and BI ranged from .721 to .865. Moreover, the overall Cronbach’s alpha coefficient was .932, indicating high reliability and consistency across the questionnaire.

Table 3.

Factor Loadings, Variance, Validity, and Reliability.

Factor	Indicator	Factor Loading	AVE	Cronbach’s Alpha	CR	R-Square
IQD	IQD1	.881	.715	.865	.909
	IQD2	.889
	IQD3	.877
	IQD4	.725
PEU	PEU1	.819	.626	.799	.87	.698
	PEU2	.805
	PEU3	.811
	PEU4	.726
TEG	TEG1	.796	.644	.816	.879	.502
	TEG2	.809
	TEG3	.810
	TEG4	.795
BI	BI1	.857	.64	.721	.842	.568
	BI2	.765
	BI3	.775

Factor loading, average variance extracted (AVE), composite reliability (CR), and overall reliability (Cronbach’s alpha = .932).

To ensure the convergent and discriminant validity of the model, a confirmatory factor analysis was performed to examine the factor loadings and determine if any items had weak loadings for their corresponding factors. According to Henseler et al. (2009) and Sanchez (2013), a strong factor-loading value should be greater than .70; otherwise, it is identified as weak. Table 3 also indicates that all items were related to their corresponding factors and were significant (p < .01), with factor loadings higher than .70. Similarly, the average variance extracted (AVE) for each construct was calculated to measure the internal consistency. Sanchez (2013) and Chin (2010) suggest that the cut-off value of AVE should be ≥.50. All constructs had AVE ≥.50 (IQD = .715; PEU = .626; TEG = .644; BI = .640). The composite reliability for each construct was higher than .8 (IQD = .909; PEU = .870; TEG = .879; BI = .842).

Furthermore, the Fornell–Larcker criterion was used to measure the discriminant validity of the constructs. According to this criterion, the requirement of discriminant validity should be fulfilled if the square root of each construct AVE is greater than its correlation with other constructs (Fornell & Larcker, 1981). It can be seen from Table 4 that the Fornell–Larcker criterion was satisfied.

Table 4.

Discriminant Validity of Constructs: Fornell–Larcker Criterion.

	BI	IQD	PEU	TEG
BI	.80
IQD	.502	.846
PEU	.582	.835	.791
TEG	.754	.634	.703	.802

Structural Equation Model and Hypotheses Testing

Structural equation model was employed to test the direct and indirect relationships between constructs. Table 5 presents the path coefficients for each path between the constructs. These findings support all the hypotheses. The IQD significantly predicted PEU (β = .84, t-value = 67.41, p < .001) and TEG (β = .16, t-value = 2.61, p = .009); one-unit increase in the IQD increases the expected value of the PEU and TEG by .84 and .16 units, respectively. Hence, PEU (β = .57, t-value = 10.28, p < .001) significantly predicted TEG. In addition, a one-unit increase in PEU increases the expected value of TEG by .57 units, whereas a one-unit increase in TEG increases the expected BI by .75 units. Hence, TEG (β = .75, t-value = 38.38, p < .001) significantly predicted BI.

Table 5.

Path Coefficients and Hypotheses Testing (Direct and Indirect Effects).

Path and hypothesis		Path Coefficient	t-Values	ρ-Values	Remark
Direct effects	H1: IQD → PEU	.835	67.407	<.001	Supported
	H2: IQD → TEG	.156	2.608	.009	Supported
	H3: PEU → TEG	.573	10.276	<.001	Supported
	H4: TEG → BI	.754	38.381	<.001	Supported
Indirect effects	H5: IQD -> TEG -> BI	.118	2.62	.009	Supported
	H6: PEU -> TEG -> BI	.432	9.363	<.001	Supported
	H7: IQD -> PEU -> TEG	.478	9.797	<.001	Supported
	H8: IQD -> PEU -> TEG -> BI	.361	8.897	<.001	Supported

With regard to the indirect effects, the analysis showed that the mediation effect of TEG was significant for IQD and BI (B = .12, t = 2.62, p = .009) and for PEU and BI (B = .43, t = 9.36, p < .001). The mediation effect of PEU was also significant for IQD and TEG (B = .48, t = 9.80, p < .001). In addition, the combined mediation effect of PEU and TEG was significant for IQD and BI (B = .36, t = 8.90, p < .001); see Figure 1.

Figure 1.

The measurement model.

Respondents were requested to rate their overall satisfaction with the e-government services on a scale from 1 to 5. The results revealed that more than half of the respondents (64%) were generally satisfied. Moreover, it was necessary to identify any association between respondents’ overall satisfaction and their demographic characteristics. The results of a two-sample t-test in Table 6 indicate that only gender (p = .005) and nationality (p = .026) were significantly associated with overall satisfaction. No significant association was observed among education level, age, and satisfaction level.

Table 6.

Overall Satisfaction Based on the Demographics.

	Group	Mean	SD	SE	t or z Statistics	p-value
Gender	Male	3.087	1.016	.057	−3.425^a	<.001
Gender	Female	3.339	.951	.048	−3.425^a	<.001
Nationality	Kuwaitis	3.191	.986	.039	−2.771^a	.006
Nationality	Other nationalities	3.519	.968	.112	−2.771^a	.006

^aTwo independent sample t-test.

Barriers Impeding E-government Usage

The 76 respondents who reported not using online services were asked to provide the reasons for not using the services. Of them, 22 (39.3%) did not acquire knowledge about government websites and applications, 15 (26.8%) respondents thought that they lacked the technological skills that would enable them to use e-services, 13 (23.2%) found difficulty in accessing them, 9 (16%) were skeptical about the security and confidentiality of the system, and 4 (7.1%) were distrustful of electronic payments. Furthermore, nine of the respondents reported other reasons relating to technical issues, distrust in the government to acknowledge e-services, and being unnecessary for some people.

Challenges of Using e-Government Services

Respondents were asked to provide details of the challenges they encountered while using government websites and applications. The reported challenges were related to lack of technical support (58%), incomplete transactions which belong to different organizations (47.7%), inefficient services (37.7%), and insufficient information about the services (34.9%). Moreover, other challenges reported by the respondents were related to complicated websites and applications due to lack of training (19.5%), lack of feeling that the transactions are secure and information are confidential (13.1%), and lack of TT to pay online (10.4%).

Suggestions for E-government Improvement

The respondents were asked to state any suggestions that would contribute to improvements in e-government services. A total of 237 participants reported suggestions related to the following themes.

Comprehensive Integrated System

Several respondents stated that they needed a complete system that included all e-services. One commented, “The government should provide a complete electronic system to conduct all government services, transactions, and payments that accommodate citizens’ needs.” Others highlighted the importance of having an integrated system to perform all government services, transactions, and payments that accommodate citizens’ needs, particularly the needs of older adults, persons with disabilities, and those lacking technological skills. They reported that this would improve the efficiency of e-services, eliminate unnecessary applications, eradicate bureaucracy, and bring Kuwait to the world’s stage. Another respondent said, “Connecting all ministries of the state to each other for ease of dealing and exchanging information.” Other respondents suggested the “Electronic messaging system” to be fully implemented in government institutions.

User Help Features

A number of respondents reported that technical support was required to investigate and solve the electronic failure of services owing to high traffic in the domain. Some respondents required e-services to necessarily include user help features, such as live chats and answering questions efficiently, whereas others referred to availability of competent employees capable of resolving any issue effectively. One commented, “Technical issues must be attended to in a timely manner.”

Safe and Secure Services

A few respondents reported the importance of a safe and secure web portal for e-service access. One respondent stated, “We do not feel safe, as most government departments are not run by government departments themselves but rather by private utilitarian companies; neither they nor their privacy procedures are trusted.”

Easy-to-Use Services

Several respondents emphasized the importance of having a system that is easy to use to enable them to easily navigate through services and access information. Some respondents suggested using the services uniformly, and others thought that facilitating electronic platforms and offering more simplified alternatives would help those unfamiliar with technology, particularly older adults. One respondent commented, “The design of the services is complicated, and it is not easy to use it.”

New e-services

Several respondents suggested that all services should be available online, whereas others requested services that they deemed important. The suggested services included car registration renewal, marriage licenses, health services and records, housing, school registration, visa issuing and renewal, education services and records, business permits, driving license issuing and renewal, social security services, passport renewal, and mail services.

Discussion

The analysis of the results supports all suggested hypotheses and indicates that individuals’ TEG is influenced by IQD and PEU. As such, TEG affects BI. IQD influences both PEU and TEG. Moreover, the results indicate the mediating effect of TEG on IQD, and BI, as well as on PEU and BI. The PEU mediates the effect of IQD and TEG. Furthermore, PEU mediates the effects of IQD, TEG and BI. Hence, the proposed model provides insights into how the use of e-government can be further improved.

The construct of IQD consists of the availability, accuracy, completeness, and currency of information as well as aesthetically pleasing design. This is strongly related to PEU and TEG, thereby indicating that the better the overall design of the government portal, the easier the use of e-government services. Content availability allows users to navigate the system and retrieve relevant information effortlessly. Therefore, designers must consider users’ information needs when designing e-government systems. In addition, rich and relevant information should be presented and organized clearly and systematically. Links and navigation, as well as improved attractiveness of layout and design, are important features for users, thereby increasing their trust. This was confirmed based on the fact that some individuals reported a lack of knowledge regarding government websites and applications and the complexity of e-services hindered them from using e-government services. This agrees with the findings of previous studies (e.g., Capistrano, 2020; Lee & Levy, 2014; Santa et al., 2019), which established that IQ contributes to TEG. However, such findings contradict those in Mensah et al. (2021) who found that although TEG predicted BI to use e-government services, IQ did not have any significant effect on TG.

In this study, PEU was significantly related to TEG, thus confirming Aljazzaf’s (2019) finding that PEU is among the factors that significantly influence individuals’ TEG. This implies that users prefer trusting systems that are convenient according to their lifestyle. Hence, usage of e-government websites or applications should not require much effort by the users. However, according to Badir and Andjarwati (2020), the use of technology only requires minimal effort and is expected to facilitate users’ activities effeciently. It is related to user confidence in the system, which should be learnable, flexible, and easy to search and understand.

One important finding concerns BI to use e-government services. TEG was found to influence users’ BI directly, whereas both constructs of IQD and PEU influenced BI indirectly and through the mediating effect of TEG. These findings are logical because users intend to use e-government services once they trust them. Furthermore, user trust is determined by easy-to-use and user-friendly systems as well as attractive and well-organized designs that include comprehensive, relevant, and accurate information. These results are in line with the results of AlAwadhi (2023), AlHussainan et al. (2022), and Liu and Zhou (2010).

The results also indicate an average level of user satisfaction. This is in line with Noori (2022) who found a significant relationship between e-SQ, user satisfaction and loyalty to e-government services. Interestingly, gender was significantly associated with the respondents’ overall satisfaction. This could be attributed to the fact that personal relationships and face-to-face contact, particularly in collectivist societies, such as Kuwait, are important and add value to customers (AlAwadhi & Morris, 2009). Therefore, men prefer conducting government services through personal relationships to avoid uncertainty, whereas women prefer online services that help them perform transactions independently and equally. Moreover, nationality was significantly associated with user satisfaction, thus indicating that residents were more satisfied than citizens. Most residents in Kuwait, who constitute the workforce in the public and private sectors, are drawn to work in the country to earn money; thus, they are expected to follow the rules and laws that help them avoid incurring fines or being penalized. Conducting online services, particularly during the pandemic, was one of the instructions issued by the government that should be followed and not violated. All in all, governments should reinforce a customer-focused approach to deliver better services, meet different needs and experiences, and manage individuals’ demands effectively, which would thus help increase citizens’ trust and satisfaction.

Several challenges regarding the use of e-government services have been reported. The majority of respondents were unable to proceed with transactions because of impediments associated with challenges such as lack of technical support, incomplete transactions, inefficient services, insufficient information about the services, and lack of information literacy skills. This is consistent with Sharma et al. (2021) and Arief et al. (2021). Undeniably, the challenges are relevant to the IQD and PEU of services, which impact TEG and BI. Thus, as suggested by the respondents, governments must design one safe and secure comprehensive integrated system that is easy to use and navigate and includes all services and relevant information. In addition, these services should be simple and uniform to accommodate the diverse needs of individuals. Specifically, social challenges represented by age, gender, education, language, and other factors should be addressed to rebuild individual trust and achieve social inclusion, as indicated by AlAwadhi (2019). Additionally, ICT resources and facilities should be provided in community centers, public libraries, and other public places to help less-advantaged people benefit from such resources, as recommended by AlAwadhi and Morris (2009).

The e-government system is also expected to be safe, secure and provide efficient technical support to rectify electronic service failures. This is stated by Abbas et al. (2021) who found a significant relationship between the measures of e-government development and public service sustainability. Also, they found that once corruption control measures and enhanced cybersecurity initiatives were applied, the quality of public service sustainability improved. In a further study, Abbas et al. (2022) found that secure cybersecurity measures have played a critical role in promoting e-government and the use of ICT throughout Asia. Such measures have also enhanced and supported government services and sustainable development. Therefore, policy measures and distinct e-government features are critically necessary to be enforced in the use of e-government websites and applications in order to ensure the privacy and safety of individuals’ information, as suggested by Abbas, Xu, and Sun (2021) and Sharma et al. (2021).

Furthermore, user help features, such as live chats and answering question forms, in addition to competent employees, are necessary to effectively resolve issues. Hence, this can improve the efficiency of electronic services and eliminate unnecessary applications, which can consequently assist in responding to citizens, rebuilding their trust, and increasing their satisfaction and BI to use e-government services.

The study reports a thorough understanding of the factors that facilitate the acceptance and use of e-government services and information. The use of a robust model that integrates factors from TAM, IS and trust models constitutes a significant theoretical advancement in the field, providing a useful framework for officials and policymakers involved in planning and implementing e-government initiatives. Specifically, PEU and IQD are identified as trust-related factors that influence the users’ TEG, thereby influencing the users’ BI toward e-government adoption and usage. Another theoretical contribution of this study is the identification and validation of the IQD construct as a trust-building factor that influences user acceptance and use of e-government services. Moreover, the IQD construct could help in the design and development of e-government platforms and applications, leading to more efficient e-services and improved citizen satisfaction.

Conclusion

This study provides insights into users’ perceptions of the trust construct in the adoption of e-government services and information by developing theoretical rationales that explain the interactions between the constructs identified in the TAM, IS, and trust models. Previous research has explored the interactions of trust with constructs of various models, such as the TAM, IS, TPB, and unified theory of acceptance and use of technology, to identify the effect of trust on the core constructs of the models. However, this study identified IQD (a modified construct from the IS model) and PEU (a construct from the TAM) as trust-building constructs that should be considered when designing and developing e-government services. As users search for information that involves government transactions or performance on e-government websites or applications, information quality is deemed critical for meeting such needs. Hence, the quality and design of the available information should be easy to use to ensure improved trust and increased uptake of e-government services.

Therefore, this study’s framework contributes to extending models by integrating IQD and PEU with trust to provide better insights into the driving forces of BI. Additionally, it provides a deeper understanding of the challenges that could negatively affect the use of e-government systems. When designing and developing e-government services, governments should consider IQD and PEU as trust-building constructs that motivate individuals to adopt and continue using e-government services. Further, to ensure that people can reap the benefits of e-government, necessary support capable of overcoming the challenges encountered by users must be provided. In addition, governments should develop awareness campaigns to educate people about the services and information provided by e-government. Social challenges should be addressed to overcome any differences that might be found among different ages, gender, educational level, languages, and other factors. This would assist in rebuilding individual trust and achieve social inclusion. Challenges related to the lack of information literacy skills are interrelated with the notion of the “digital divide” to reveal the inequality between those with access to ICTs and those without. Therefore, efforts should be devoted to equipping those who do not have necessary information literacy skills by making knowledge, resources, and ICT facilities available to help minimize the “digital divide” and increase individuals’ access to government services and information. Furthermore, community centers, public libraries, and other public places are expected to have a greater role in providing ICT resources and facilities to help less-advantaged people benefit from such resources.

This study limited its investigation to user perceptions of the trust factor in the adoption of e-government services and information; however, exploring government employees’ opinions can provide a thorough and comprehensive overview on how e-government is trusted and adopted. Research is, therefore, required to complement the results of this study. Future research should also focus on other factors identified in models of technology acceptance. More research is necessary to compare findings of studies of regional and cross-countries.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Author Biographies

Suha AlAwadhi is an Associate Professor of information studies at Kuwait University, Kuwait. She received her PhD in Information Science from Loughborough University, United Kingdom in 2007. Her main research interests focus on e-government, technology acceptance, usability and evaluation of information systems, social media, social inclusion and knowledge sharing. Dr AlAwadhi has written and published articles on a variety of professional topics in regional and international journals and delivered international conference presentations, posters and workshops.

Husain Alansari is currently a professor of information studies at Kuwait University. He received his master’s degree from University of Wisconsin – Milwaukee 1983 and his PhD in information studies from the School of Information Studies at Florida State University, Tallahassee – Florida in 1992. His publications have appeared in leading library and information science journals such as Journal of Librarianship and Information Science, Library Management, The Electronic Library, Libri, Technical Services Quarterly, and other scholarly journals. His current research interests include e-government, soft skills for information professionals, and digital information use. During his career, Husain Alansari occupied positions including President of Kuwait University (2015-2020), Director of Kuwait National Library, Assistant Dean for Academic Affairs of College of Social Sciences, and Library Director at Kuwait University.

Ahmad R. Alsaber received a B.Sc. (Mathematics) and a M.Sc. (Statistics) from Kuwait University in 2002 and 2007, respectively; and a Ph.D. from University of Strathclyde, in 2022, when he started his faculty career at American University of Kuwait (AUK), College of Business and Economics. He was assigned as an assistant director of Research and Grants Office (ORG), AUK in 2021. His specialty is related to data-science, artificial intelligence and multivariate time-series analysis with focus on random forest, neural network and missing imputation analysis. In his research, he targets materials with environmental, rheumatology studies, time series of diabetics, and multivariate time series analysis between the effect of environmental aspects toward public health applications.

References

Abbas

H. S. M.

Qaisar

Z. H.

Ali

Alturise

Alkhalifah

(2022). Impact of cybersecurity measures on improving institutional governance and digitalization for sustainable healthcare. https://doi.org/10.4018/IJEGR.2021040102, 17(11), Article e0274550. https://doi.org/10.1371/journal.pone.0274550

Abbas

H. S. M.

Qaisar

Z. H.

Sun

(2021). Nexus of E-government, cybersecurity and corruption on public service (PSS) sustainability in Asian economies using fixed-effect and random forest algorithm. Online Information Review, 46(4), 754–770. https://doi.org/10.1108/OIR-02-2021-0069

Abbas

H. S. M.

Sun

(2021). Role of COVIDsafe app and control measures in Australia in combating COVID-19 pandemic. Transforming Government: People, Process and Policy, 15(4), 708–719. https://doi.org/10.1108/TG-01-2021-0004

Ajzen

(1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211. https://doi.org/10.1016/0749-5978(91)90020-T

Aladwani

A. M.

(2013). A contingency model of citizens’ attitudes toward e–government use. Electronic Government, an International Journal, 10(1), 68–85. https://doi.org/10.1504/EG.2013.051276

AlAwadhi

(2019). A proposed model of trust factors for E-government adoption and civic engagement. In 52nd Hawaii International Conference on System Sciences, Grand Wailea, HI, United States, 8–11 January 2019. https://doi.org/10.24251/HICSS.2019.381

AlAwadhi

(2021). Trust factors affecting the adoption of E-government for civic engagement. In Scholl

H. J.

Gil-Garcia

J. R.

Janssen

Kalampokis

Lindgren

Rodríguez Bolívar

M. P.

(Eds.), Electronic Government. EGOV 2021. Lecture notes in computer science (vol. 12850, pp. 229–244). Springer. https://doi.org/10.1007/978-3-030-84789-0_17

AlAwadhi

(2023). Trust as a leveraging factor for civic engagement. Electronic Government, an International Journal, 19(3), 356–375. https://doi.org/10.1504/EG.2023.10042953

AlAwadhi

Morris

(2009). Factors influencing the adoption of e-government services. Journal of Software, 4(6), 584–590. https://doi.org/10.4304/jsw.4.6.584-590

10.

Alawneh

Al-Refai

Batiha

(2013). Measuring user satisfaction from e-Government services: Lessons from Jordan. Government Information Quarterly, 30(3), 277–288. https://doi.org/10.1016/j.giq.2013.03.001

11.

Alenezi

Tarhini

Masa’deh

Alalwan

Al-Qirim

(2017). Factors affecting the adoption of e-government in Kuwait: A qualitative study. Electronic Journal of e-Government, 15(2), 84–102.

12.

AlHussainan

O. N.

AlFayyadh

M. A.

Al-Saber

Alkandari

A. M.

(2022). The factors of E-government service quality in Kuwait during the coronavirus disease 2019 pandemic. International Journal of Electronic Government Research, 18(1), Article 17. https://doi.org/10.4018/IJEGR.311417

13.

Ali

Rasoolimanesh

S. M.

Sarstedt

Ringle

C. M.

Ryu

(2018). An assessment of the use of partial least squares structural equation modeling (PLS-SEM) in hospitality research. International Journal of Contemporary Hospitality Management, 30(1), 514–538. https://doi.org/10.1108/IJCHM-10-2016-0568

14.

Aljazzaf

Z. M.

(2019). Evaluating trust in E-government: The case of Kuwait. Proceedings of the 2019 5th International Conference on Computer and Technology Applications, Istanbul, Turkey, 2019, pp. 140–144. https://doi.org/10.1145/3323933.3324073

15.

Aljazzaf

Z. M.

Perry

Capretz

M. A. M.

(2010, September 20–25). Online trust: Definition and principles. In 2010 Fifth International Multi-Conference on Computing in the Global Information Technology, Valencia, Spain, 20–25 September 2010, pp. 163–168. IEEE Publications. https://doi.org/10.1109/ICCGI.2010.17

16.

Al-Kaseasbeh

H. M.

Harada

Saraih

U. N. B.

(2019). E-government services assessment from the perspective of citizens interaction and satisfaction in Jordan: Pilot study. International Journal of Research and Review, 6(12), 50–59.

17.

Al-Khatib

Lee

(2013). E-government systems success and user acceptance in developing countries: The role of perceived support quality. International Journal of eBusiness and eGovernment Studies, 3(2), 69–78. https://doi.org/10.14329/apjis.2019.29.1.1

18.

Alkraiji

Ameen

(2022). The impact of service quality, trust and satisfaction on young citizen loyalty towards government e-services. Information Technology and People, 35(4), 1239–1270. https://doi.org/10.1108/ITP-04-2020-0229

19.

Almaiah

M. A.

Nasereddin

(2020). Factors influencing the adoption of e-government services among Jordanian citizens. Electronic Government an International Journal, 16(3), 236–259. https://doi.org/10.1504/EG.2020.108453

20.

Al Mansoori

K. A.

Sarabdeen

Tchantchane

A. L.

(2018). Investigating Emirati citizens’ adoption of e-government services in Abu Dhabi using modified UTAUT model. Information Technology and People, 31(2), 455–481. https://doi.org/10.1108/ITP-12-2016-0290

21.

Al Nagi

Hamdan

(2009). Computerization and e-government implementation in Jordan: Challenges, obstacles and successes. Government Information Quarterly, 26(4), 577–583. https://doi.org/10.1016/j.giq.2009.04.003

22.

Alsarraf

H. A.

Aljazzaf

Ashkanani

A. M.

(2022). Do you see my effort? An investigation of the relationship between e-government service quality and trust in government. Transforming Government: People, Process and Policy, 17(1), 116–133. https://doi.org/10.1108/TG-05-2022-0066

23.

Alzahrani

Al-Karaghouli

Weerakkody

(2017). Analysing the critical factors influencing trust in e-government adoption from citizens’ perspective: A systematic review and a conceptual framework. International Business Review, 26(1), 164–175. https://doi.org/10.1016/j.ibusrev.2016.06.004

24.

Arief

Wahab

I. H. A.

Muhammad

(2021, May). Barriers and challenges of e-government services: A systematic literature review and meta-analyses. In IOP conference series: Materials science and engineering (vol. 1125, No. 1, p. 012027). IOP Publishing.

25.

Badir

Andjarwati

A. L.

(2020). The effect of E-WOM, ease of use and trust on purchase decisions (study on Tokopedia application users). Journal Minds, 7(1), 39–52. https://doi.org/10.24252/minds.v7i1.13715

26.

Balaskas

Panagiotarou

Rigou

(2022). The influence of trustworthiness and technology acceptance factors on the usage of e-government services during COVID-19: A case study of post COVID-19 Greece. Administrative Sciences, 12(4), 129. https://doi.org/10.3390/admsci12040129

27.

Belanche

Casaló

L. V.

Flavián

Schepers

(2014). Trust transfer in the continued usage of public e-services. Information and Management, 51(6), 627–640. https://doi.org/10.1016/j.im.2014.05.016

28.

Bélanger

Carter

(2008). Trust and risk in e-government adoption. The Journal of Strategic Information Systems, 17(2), 165–176. https://doi.org/10.1016/j.jsis.2007.12.002

29.

Bournaris

(2020). Evaluation of e-government web portals: The case of agricultural e-government services in Greece. Agronomy, 10(7), Article 932. https://doi.org/10.3390/agronomy10070932

30.

Brislin

R. W.

(1970). Back-translation for cross-cultural research. Journal of Cross-Cultural Psychology, 1(3), 185–216. https://doi.org/10.1177/135910457000100301

31.

Capistrano

E. P.

(2020). Determining e-government trust: An information systems success model approach to the Philippines’ government Service Insurance System (GSIS), the Social Security System (SSS), and the Bureau of Internal Revenue (BIR). Philippine Management Review, 27, 57–78.

32.

Chin

W. W.

(2010). How to write up and report PLS analyses. In Esposito Vinzi

Chin

Henseler

Wang

(Eds.), Handbook of partial least squares (pp. 655–690). Springer. https://doi.org/10.1007/978-3-540-32827-8_29

33.

Davis

F. D.

(1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008

34.

DeLone

W. H.

McLean

E. R.

(2003). The DeLone and McLean model of information systems success: A ten-year update. Journal of Management Information Systems, 19(4), 9–30. https://doi.org/10.1080/07421222.2003.11045748

35.

Dwivedi

Y. K.

Weerakkody

Janssen

(2012). Moving towards maturity: Challenges to successful e-government implementation and diffusion. ACM SIGMIS Database: The DATABASE for Advances in Information Systems, 42(4), 11–22. https://doi.org/10.1145/2096140.2096142

36.

ElKheshin

S. A.

Saleeb

(2020). Assessing the adoption of e-government using TAM model: Case of Egypt. International Journal of Managing Information Technology, 12(1), 1–14. https://doi.org/10.5121/ijmit.2020.12101

37.

Fornell

Larcker

D. F.

(1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.1177/002224378101800104

38.

Gabryelczyk

(2020). Has COVID-19 accelerated digital transformation? Initial lessons learned for public administrations. Information Systems Management, 37(4), 303–309. https://doi.org/10.1080/10580530.2020.1820633

39.

Gefen

(1997). Building users’ trust in freeware providers and the effects of this trust on users’ perceptions of usefulness, ease of use and intended use of freeware. [Doctoral Dissertation]. Georgia State University.

40.

Hair

J. F.

Hult

G. T.

Ringle

C. M.

Sarstedt

(2017). A primer on partial least squares structural equation modeling (PLS-SEM). Sage.

41.

Hair

J. F.

Hult

G. T. M.

Ringle

C. M.

Sarstedt

Thiele

K. O.

(2017). Mirror, mirror on the wall: A comparative evaluation of composite-based structural equation modeling methods. Journal of the Academy of Marketing Science, 45(5), 616–632. https://doi.org/10.1007/s11747-017-0517-x

42.

Heeks

Bailur

(2007). Analyzing e-government research: Perspectives, philosophies, theories, methods, and practice. Government Information Quarterly, 24(2), 243–265. https://doi.org/10.1016/j.giq.2006.06.005

43.

Henseler

Ringle

C. M.

Sinkovics

R. R.

(2009). The use of partial least squares path modeling in international marketing. In Sinkovics

R. R.

Ghauri

P. N.

(Eds.), New challenges to international marketing (pp. 277–319). Emerald Group Publishing Limited. https://doi.org/10.1108/S1474-7979(2009)0000020014

44.

Hooda

Gupta

Jeyaraj

Dwivedi

(2023). Clarifying the role of e-government trust in e-government success models: A meta-analytic structural equation modeling approach. Australasian Journal of Information Systems, 27, 1–22. https://doi.org/10.3127/ajis.v27i0.4079

45.

Huffman

(2006). Online questionnaire software advantages/disadvantages. Master’s Thesis. University of North Carolina at Chapel Hill. https://doi.org/10.17615/xd3g-qh05

46.

Janssen

van der Voort

(2020). Agile and adaptive governance in crisis response: Lessons from the COVID-19 pandemic. International Journal of Information Management, 55, Article 102180. https://doi.org/10.1016/j.ijinfomgt.2020.102180

47.

Kanaan

AL-Hawamleh

Abulfaraj

Al-Kaseasbeh

Alorfi

(2023). The effect of quality, security and privacy factors on trust and intention to use e-government services. International Journal of Data and Network Science, 7(1), 185–198. https://doi.org/10.5267/j.ijdns.2022.11.004

48.

Kuwait Government Online . (2021). About KGO. https://e.gov.kw/sites/kgoenglish/Pages/InfoPages/AboutKGO.aspx

49.

Kuwait News Agency . (2020). Kuwait gov’t to ease coronavirus-related restrictions. KUNA. https://www.kuna.net.kw/ArticleDetails.aspx?id=2900522&language=en

50.

Lee

Levy

(2014). The effect of information quality on trust in e-government systems’ transformation. Transforming Government: People, Process and Policy, 8(1), 76–100. https://doi.org/10.1108/TG-10-2012-0011

51.

Xue

(2021). Analyzing the critical factors influencing post-use trust and its impact on citizens’ continuous-use intention of e-government: Evidence from Chinese municipalities. Sustainability, 13(14), Article 7698. https://doi.org/10.3390/su13147698

52.

Liu

Zhou

(2010, July 16–18). A citizen trust model for e-government. In IEEE International Conference on Software Engineering and Service Sciences, Beijing, China, 16–18 July 2010, pp. 751–754. https://doi.org/10.1109/ICSESS.2010.5552260

53.

Maharaj

M. S.

Munyoka

(2019). Privacy, security, trust, risk and optimism bias in e-government use: The case of two Southern African development community countries. South African Journal of Information Management, 21(1), 1–9. https://doi.org/10.4102/sajim.v21i1.983

54.

Meiyanti

Utomo

Sensuse

D. I.

Wahyuni

(2018, August). e-Government challenges in developing Countries: A literature review. In 2018 6th International conference on cyber and IT service management (CITSM), Parapat, Indonesia, 7–9 August 2018, pp. 1–6. IEEE.

55.

Mensah

I. K.

(2020). The impact of political trust on E-government services adoption. International Journal of Technology Diffusion, 11(4), 27–47. https://doi.org/10.4018/IJTD.2020100102

56.

Mensah

I. K.

Adams

Adjei

J. K.

Mwakapesa

D. S.

(2022). Drivers of e-government adoption amidst COVID-19 pandemic: The information adoption model (IAM) approach. Information Development, 38(4), 494–509. https://doi.org/10.1177/02666669211010872

57.

Mensah

I. K.

Luo

Abu-Shanab

(2021). Citizen use of e-government services websites: A proposed e-government adoption recommendation model (EGARM). International Journal of Electronic Government Research, 17(2), 19–42. https://doi.org/10.4018/IJEGR.2021040102

58.

Mizrahi

Vigoda-Gadot

Cohen

(2021). How well do they manage a crisis? The government’s effectiveness during the Covid-19 pandemic. Public Administration Review, 81(6), 1120–1130. https://doi.org/10.1111/puar.13370

59.

Noori

(2022). The effect of e-service quality on user satisfaction and loyalty in accessing e-government information. International Journal of Data and Network Science, 6(3), 945–952. https://doi.org/10.5267/j.ijdns.2022.2.002

60.

Okunola

O. M.

Rowley

(2019). User experience of e-government: The Nigeria immigration service. Library Hi Tech, 37(3), 355–373. https://doi.org/10.1108/LHT-09-2018-0138

61.

Papadopoulou

Nikolaidou

Martakos

(2010, January 5–8). What is trust in e-government? A proposed typology. In 43rd Hawaii International Conference on System Sciences, Honolulu, HI, 5–8 January 2010, pp. 1–10. https://doi.org/10.1109/HICSS.2010.491

62.

Revyakin

da Rocha

(2021). An empirical investigation of E-government adoption in Russia: Access, rights, trust and citizens’ experience. Public Administration Issues, (5), 137–160. https://doi.org/10.17323/1999-5431-2021-0-5-137-160

63.

Salaün

Flores

(2001). Information quality: Meeting the needs of the consumer. International Journal of Information Management, 21(1), 21–37. https://doi.org/10.1016/S0268-4012(00)00048-7

64.

Samuel

Doctor

Christian

Baradi

(2020). Drivers and barriers to e-government adoption in Indian cities. Journal of Urban Management, 9(4), 408–417. https://doi.org/10.1016/j.jum.2020.05.002

65.

Sanchez

(2013). PLS path modelling with R (p. 383). Trowchez Editions.

66.

Santa

MacDonald

J. B.

Ferrer

(2019). The role of trust in e-Government effectiveness, operational effectiveness and user satisfaction: Lessons from Saudi Arabia in e-G2B. Government Information Quarterly, 36(1), 39–50. https://doi.org/10.1016/j.giq.2018.10.007

67.

Sharma

S. K.

Metri

Dwivedi

Y. K.

Rana

N. P.

(2021). Challenges common service centers (CSCs) face in delivering e-government services in rural India. Government Information Quarterly, 38(2), 101573. https://doi.org/10.1016/j.giq.2021.101573

68.

Shyu

S. H. P.

Huang

J. H.

(2011). Elucidating usage of e-government learning: A perspective of the extended technology acceptance model. Government Information Quarterly, 28(4), 491–502. https://doi.org/10.1016/j.giq.2011.04.002

69.

Twizeyimana

J. D.

Andersson

(2019). The public value of E-Government–A literature review. Government Information Quarterly, 36(2), 167–178. https://doi.org/10.1016/j.giq.2019.01.001

70.

United Nations . (2020). UN E-government Survey (2020) Digital government in the decade of action for sustainable development. https://publicadministration.un.org/egovkb/Portals/egovkb/Documents/

71.

United Nations . (2022). UN E-government Survey (2022) The future of digital government. https://desapublications.un.org/sites/default/files/publications/2022-09/WebversionE-Government2022.pdf

72.

Venkatesh

Morris

M. G.

Davis

G. B.

Davis

F. D.

(2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478. https://doi.org/10.2307/30036540

73.

Chen

J. L.

(2005). An extension of trust and TAM model with TPB in the initial adoption of on-line tax: An empirical study. International Journal of Human-Computer Studies, 62(6), 784–808. https://doi.org/10.1016/j.ijhcs.2005.03.003

74.

Xie

Song

Peng

Shabbir

(2017). Predictors for e-government adoption: Integrating TAM, TPB, trust and perceived risk. The Electronic Library, 35(1), 2–20. https://doi.org/10.1108/EL-08-2015-0141

75.

Zhao

José Scavarda

Waxin

(2012). Key issues and challenges in e-government development. Information Technology & People, 25(4), 395–422. https://doi.org/10.1108/09593841211278794